Scipedia: Documents published in 2019

An Event-Driven Multi Agent System for Scalable Traffic Optimization

Scipedia content — Mon, 08 Feb 2021 09:57:18 +0100

Global demand for mobility will grow from 44 trillion to 122 trillion passenger-kilometres by 2050, and freight demand will triple in that time increasing traffic emissions by 60%. With current innovation and policy measures we are ‘on course for a 3.2 \$^{\\circ }\$C temperature rise’, according to the 2019 UN Emissions Gap Report. Nothing short of revolutionary is required to address this emergency. However, there is hope: shared mobility and widespread adoption of autonomous vehicles could cut \$\\mathrm {CO}_2\$ emissions by 73% and congestion by 24% if managed by appropriate policies. This paper presents a vision and a concept for future distributed management systems for complex multi-modal transport networks that exploit Multi Agent Systems (MAS) to support individual actors based on data collected from heterogeneous sources like vehicles, freight items, infrastructures, Global Positioning Systems (GPS); and simulations of the behaviour of the many different actors involved in the transport system. Event driven approaches are envisioned to react and respond to real-time events efficiently. The main objective is to identify the best optimization strategies to reduce traffic emissions and maximize the use of the public infrastructures and shared mobility. Motivations, expected impacts, and challenges are also discussed.

Highly efficient distributed embedded image/video processing in cyber-physical systems

Scipedia content — Mon, 08 Feb 2021 09:56:37 +0100

Cyber-Physical Systems (CPS) are systems that are in feedback with their environment, possibly with humans in the loop. They are often distributed with sensors and actuators, smart, adaptive and predictive and react in real-time. Image- A nd video-processing pipelines are a prime source for environmental information improving the possibilities of active, relevant feedback. In such a context, FitOptiVis aims to provide end-to-end multi-objective optimization for imaging and video pipelines of CPS, with emphasis on energy and performance, leveraging on a reference architecture, supported by low-power, high-performance, smart devices, and by methods and tools for combined design-time and run-time multi-objective optimization within system and environment constraints.

Two new control strategies: For hydrogen fuel saving and extend the life cycle in the hydrogen fuel cell vehicles

Scipedia content — Mon, 08 Feb 2021 09:53:59 +0100

3rd International Hydrogen Technologies Congress (IHTEC) -- MAR 15-18, 2018 -- Alanya Alaaddin Keykubat Univ, TURKEY WOS: 000477092000031 With the acceleration of the development process of hydrogen fuel cell electric vehicles (HFCEV), it has become very important to maximize the energy stored in the vehicle and to use the vehicle with high efficiency. This paper puts forward how to cooperate with a proton exchange membrane fuel cell (PEMFC) as the primary energy source, a lithium-ion battery (LiB) and a supercapacitor (SCAP) as the energy storage technology. Furthermore, this paper examines the effect of two new control strategies developed for HFCEV in different road models on the vehicle fuel economy and life cycle of the system components. Both control strategies applied to the system can be easily applied to the different HFCEVs with minor changes due to the simplicity of their structure and parameters. The simulation results of the study have indicated that the impact of control strategies created in different road conditions on the power of energy sources, the life cycle of system components, system efficiency and fuel economy parameters of HFCEV. (C) 2018 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Investigation of a force-guided assembly strategy for radial mounting of jet engine blades

Scipedia content — Mon, 08 Feb 2021 09:52:49 +0100

Increasing air traffic and growing pressure on costs in aviation MRO, especially for jet engines, demand for an increase of process efficiency. While research concentrates on inspection and repair methods, the potential for automated reassembly is thereby mostly neglected. An approach for automated assembly of compressor and turbine blades is introduced in [1]. Part of this approach is a force-guided assembly, which is performed by an industrial robot. The aim of this force-guidance is to compensate positioning deviations, which can occur at different steps throughout the assembly process. Furthermore, sticking of blades during tangential movement, as a consequence of tilting, needs to be avoided. In this paper the proposed force-guided assembly strategy is investigated concerning its capacity of fulfilling the two claims stated above. Therefore, the hardware setup which is used to conduct the assembly and the process execution are described, as well as sources of positioning deviations are identified. Furthermore, the implementation of the force-control on the specific type of robot controller is described. Applying this force-control multiple experiments with defined positioning deviations are conducted. Furthermore, variations of additional assembly parameters are taken into account. The subsequent evaluation will allow a comparison of deviations, occurring during assembly process and the ability to compensate them. Potential for further optimization is stated in the conclusion.

Wizards of WoZ

Scipedia content — Mon, 08 Feb 2021 09:50:01 +0100

Interactions between autonomous vehicles (AV) and pedestrians remain an ongoing area of research within the AutoUI community and beyond. Given the challenge of conducting studies to understand and prototype these interactions, we propose a combined full-day workshop and tutorial on how to conduct field experiments and controlled experiments using Wizard-of-Oz (WoZ) protocols. We will discuss strengths and weaknesses of these approaches based on practical experiences and describe challenges we have faced. After diving into the intricacies of different experiment designs, we will encourage participants to engage in hands-on exercises that will explore new ways to answer future research questions.

Designing a naturalistic in-car tutor system for the initial use of partially automated cars

Scipedia content — Mon, 08 Feb 2021 09:41:48 +0100

Commercial cars start to include more automated functions it becomes difficult for drivers to understand how and when to use them safely. While general HMI recommendations for partially automated cars have been made, it is unclear how drivers should be supported during the initial use period. Recommendations for a tutor system that guides drivers in their initial use of partially automated cars are necessary. To gain inspiration for such a tutor system, we examined the existing communication loop of driving instructors and their students. Driving instructors and their students were video recorded during regular driving lessons. The tutoring patterns that were found (i.e. situation and student adaptive feedback, student adaptive tasks, body movements for correcting and requesting actions) during the initial qualitative analysis are discussed. Furthermore, we suggest methods how to implement the tutoring patterns in a tutor system to support drivers in the use partially automated cars.

How Visual Cues on Steering Wheel Improve Users’ Trust, Experience, and Acceptance in Automated Vehicles

Scipedia content — Mon, 08 Feb 2021 09:39:47 +0100

With the introduction of ADAS systems and vehicle automation, an interface informing the driver of the automation state is required. This study evaluates the suitability of a visual interface comprising up to 64 LEDs on the steering wheel perimeter; it displays continuous visual feedback about the automation state—including notifications of an unscheduled hand-over due to sudden system failure. Three HMI (Human Machine Interface) designs were evaluated: two versions with visual cues on the steering wheel and one without (baseline). We implemented the designs in a driving simulator and compared the subjective responses of 38 participants to questionnaires measuring user experience, trust, and acceptance. The designs with visual cues improved the participants’ user experience, as well as their trust in, and acceptance of, automated vehicles. Moreover, both designs were well perceived by participants.

The strategy of air cargo operators : about carpet sellers and cargo stars

Scipedia content — Sun, 07 Feb 2021 13:48:52 +0100

cargo was traditionally considered as a by-product of passenger air transport. However, in the last decade a defined strategy for air cargo has gained a key position in the strategies of most combination airlines, contributing largely to the cash and profit levels of these airlines. The global air cargo industry is nowadays a mature industry with over 60 billion USD in direct revenues. The strategic context is, therefore, far beyond the basic entrepreneurial framework in which an emerging and young industry tends to operate. This chapter aims to gain an enhanced insight into the strategies of airlines that transport cargo, either in the bellies of passenger aircraft or in full-freighter aircraft. A Cluster Analysis generates a typology of seven representative clusters of air cargo operators’ strategy models. The typology proposes a spectrum of strategies for air cargo, ranging from the cluster group “Carpet Sellers” up to the “Cargo Stars” cluster. While the former tend to be the small airlines or all-cargo carriers which barely manage to cover their costs with their revenues, the latter are profitable, very large globally operating airlines that focus on both passengers and cargo with passenger and freighter aircraft. Within this spectrum there are five other main strategy groups: the “Basic Cargo Operators,” the “Strong Regionals,” the “Low Cost Low Yielder,” the “Large Passenger Wide-body Operators,” and the “Premium Cargo Operators.” Our findings suggest the existence of superior strategy models that could be defined as “winning strategies” that differ according to airline size.

Managing aircraft mobility in a context of the ATN/IPS network

Scipedia content — Wed, 03 Feb 2021 22:00:05 +0100

International audience; For the sake of Air Traffic Management modernization , civil aviation organizations are currently developing IPS for Aeronautical Safety Services in the new ATN/IPS infrastructure. This includes to define new airborne and ground-based communication systems capable of managing both air traffic services (ATS) and aeronautical operational communications (AOC) safety services. One of the main challenges in this new ATN/IPS network is the IPv6 mobility problem. This paper proposes a solution which takes both advantages of ground based Locator/Identifier Separation Protocol and Proxy Mobile IPv6 to manage all the aircraft mobility scenarios. A dedicated OMNeT++ simulation model is also provided and shows the performances of our solution.

Developing a user typology considering unimodal and intermodal mobility behavior: a cluster analysis approach using survey data

Scipedia content — Wed, 03 Feb 2021 21:59:24 +0100

This paper aims to develop a user typology which enables user-specific analyses in respect of mobility behavior. It addresses the challenge of integrating unimodal and intermodal travel behavior into a user typology to obtain an overview of intermodal users within the context of their overall mobility behavior. The user typology is based on two cluster analyses (agglomerative hierarchical clustering) which use quantitative survey data on unimodal and intermodal mobility behavior obtained for Berlin, Germany. One cluster analysis was performed for unimodal use and one for intermodal mode use to take into account the users’ relatively low use of intermodal modes as well. The analyses resulted in 6 intermodal and 5 unimodal clusters based on users’ mobility behavior. Since in each case every individual is assigned to one intermodal and one unimodal cluster, the resulting intermodal and unimodal clusters were then combined in order to represent the overall mobility behavior of each individual as mobility types. The mobility types are further characterized by information on socio-demographics and mobility resources obtained from the dataset. These enhanced mobility types (EMT) provide a clearer impression of the users’ characteristics and needs. This user typology takes account of the wide range of mobility options available in cities today and the resulting diversity in people’s mobility behavior. To enable us to address the needs of users who combine several modes of transport within one trip, the proposed procedure approaches the challenge of integrating intermodal behavior into user types. The results provide a user typology which combines intermodal and unimodal travel behavior with personal characteristics and enable researchers and practitioners to work on user-specific research questions and planning tasks.

Document type: Article

SIMNORAT - Project Poster

Scipedia content — Wed, 03 Feb 2021 21:59:07 +0100

The SIMNORAT project poster gives a general overview of the project and its activities. Initially developed for the Sea Tech Week in Brest in October 2018, the poster was also displayed at the SIMNORAT Final Conference. The poster is available in English and French. Please note that the website indicated on the poster is no longer online. This document was produced as part of SIMNORAT Project (Grant Agreement N0. EASME/EMFF/2015/1.2.1.3/03/SI2.742089). Competition for maritime space – for renewable energy equipment, aquaculture and other uses – has highlighted the need to manage our waters more coherently. Maritime spatial planning (MSP) works across borders and sectors to ensure human activities at sea take place in an efficient, safe and sustainable way. That is why the European Parliament and the Council have adopted a legislation to create a common framework for maritime spatial planning in Europe. The Directive 2014/89/EU of the European Parliament and of the Council of 23 July 2014 (said Maritime Spatial Planning Directive) establishes a framework in order to reduce conflicts between sectors and create synergies between different activities, to encourage investment – by creating predictability, transparency and clearer rules, to increase cross-border cooperation – between EU countries to develop energy grids, shipping lanes, pipelines, submarine cables and other activities, but also to develop coherent networks of protected areas, and to protect the environment – through early identification of impact and opportunities for multiple use of space. The SIMNORAT project (Supporting Implementation of Maritime Spatial Planning in the Northern European Atlantic) is an EU/DG Mare co-funded cross-border project. It was launched on 1st of January 2017 and involves Portugal, Spain and France, while these countries had just designated their Competent Authorities and transposed the Maritime Spatial Planning (MSP) Directive. SIMNORAT aims to support the implementation of the MSP Directive in the waters of Portugal, Spain and France, as well as to establish cross-border cooperation mechanisms between these Member States, to contribute to the coherence of their marine spatial plans to be established in 2021. The action ran until 31st of January 2019 and was based on a partnership of public bodies of the countries and one international organisation. It was composed of UAVR, CEDEX, IEO, AFB, CEREMA, Shom, and CPMR. Shom acted as coordinator. The objectives of the SIMNORAT project were addressed through a variety of activities and desktop or case studies. They are dedicated to identifying the methodology steps, and explore the challenges and opportunities of the MSP implementation in the Northern European Atlantic, including thus related to transboundary issues (Ecosystem based approach, marine policies, OSPAR Convention, Land Sea Interactions, geographical scale of the plans, data interoperability, tools to support MSP). The project led to a multiplicity of outputs including overviews of MSP relevant information related to the countries and on more focus areas, to a number of interviews and meetings where stakeholder views were collected to feed the reasoning, and to guidelines and good practices to be shared at a national and transnational level with marine stakeholders, scientific as well as planners, administrations and authorities. In addition, SIMNORAT permitted a lot of progression internally in the countries and regarding transboundary cooperation. It led to establish and develop new dialogues and to connect the technical or scientific actors, the stakeholders, the administrations of the countries of a same sea basin, and the administrations within the countries, including the representative of Regions. It allowed to better understand Maritime Spatial Planning mechanisms, to share knowledge and as such reached to build capacities, which is of importance as there is such a need in the Atlantic area compared to more Northern countries. The project also permitted to address topics which have never been addressed before. The involvement of France and Spain in SIMNORAT and in the EU-DG Mare sister projects SIMWESTMED and SIMCelt was useful for them to develop a global vision with their neighbours in the Western Mediterranean. At the end of this exercise, it is stated the need of pursuing the work and dialogue in particular through common tools, but at this stage, the SIMNORAT project has constituted a common knowledge and background. D I S C L A I M E R: The contents and conclusions of this report, including the maps and figures were developed by the participating partners with the best available knowledge at the time. They do not necessarily reflect the national governments' positions and are not official documents, nor data. The European Commission or Executive Agency for Small and Medium sized Enterprises is not responsible for any use that may be made of the information it contains.

Support for HTCondor High-Throughput Computing Workflows in the REANA Reusable Analysis Platform

Scipedia content — Wed, 03 Feb 2021 21:52:08 +0100

REANA is a reusable and reproducible data analysis platform allowing researchers to structure their analysis pipelines and run them on remote containerised compute clouds. REANA supports several different workflows systems (CWL, Serial, Yadage) and uses Kubernetes' job execution backend. We have designed an abstract job execution component that extends the REANA platform job execution capabilities to support multiple compute backends. We have tested the abstract job execution component with HTCondor and verified the scalability of the designed solution. The results show that the REANA platform would be able to support hybrid scientific workflows where different parts of the analysis pipelines can be executed on multiple computing backends.

Optimising neonatal fMRI data analysis: Design and validation of an extended dHCP preprocessing pipeline to characterise noxious-evoked brain activity in infants.

Scipedia content — Wed, 03 Feb 2021 21:51:26 +0100

The infant brain is unlike the adult brain, with considerable differences in morphological, neurodynamic, and haemodynamic features. As the majority of current MRI analysis tools were designed for use in adults, a primary objective of the Developing Human Connectome Project (dHCP) is to develop optimised methodological pipelines for the analysis of neonatal structural, resting state, and diffusion MRI data. Here, in an independent neonatal dataset we have extended and optimised the dHCP fMRI preprocessing pipeline for the analysis of stimulus-response fMRI data. We describe and validate this extended dHCP fMRI preprocessing pipeline to analyse changes in brain activity evoked following an acute noxious stimulus applied to the infant's foot. We compare the results obtained from this extended dHCP pipeline to results obtained from a typical FSL FEAT-based analysis pipeline, evaluating the pipelines' outputs using a wide range of tests. We demonstrate that a substantial increase in spatial specificity and sensitivity to signal can be attained with a bespoke neonatal preprocessing pipeline through optimised motion and distortion correction, ICA-based denoising, and haemodynamic modelling. The improved sensitivity and specificity, made possible with this extended dHCP pipeline, will be paramount in making further progress in our understanding of the development of sensory processing in the infant brain.

Highlights • The dHCP fMRI preprocessing pipeline is generalizable to stimulus-evoked datasets. • Customised FIX denoising in infant fMRI data substantially improves data quality. • The dHCP pipeline greatly improves spatial specificity and sensitivity to signal. • Bespoke fMRI data analysis outperforms typical analytical methods for neonatal data.

PLANNING AND SUSTAINABLE DEVELOPMENT OF URBAN LOGISTICS: FROM INTERNATIONAL GOALS TO REGIONAL REALIZATION

Scipedia content — Wed, 03 Feb 2021 21:37:57 +0100

The Approach to Probabilistic Prediction of Pipelines Safety for Quantitative Rationale Preventive Measures of Control during Design and Operation

Scipedia content — Wed, 03 Feb 2021 21:34:32 +0100

Radiation Aware Mobility Paths in Wirelessly Powered Communication Networks

Scipedia content — Wed, 03 Feb 2021 21:32:52 +0100

Wireless power transfer (WPT) is an emerging technology that is used in ad hoc networks of battery-powered devices, to deliver energy and keep the network functional. Existing state-of-the-art studies have mainly focused on applying this technology, but the potential risk of electromagnetic radiation (EMR) exposure is really overlooked by them. This still holds for the general case of the RF Wireless Communication networks. Hence, we consider The Minimum Radiation Path Problem of finding the lowest radiation trajectory of an agent moving from a source to a destination point in a network plane. Different from previous works, we attempt to study (for the first time in the state-of-the-art) path radiation under a more realistic WPT model than the usual one-dimensional models, that have been used in the past and cannot capture interesting superadditive and cancellation effects between distinct electromagnetic sources. In the light of the above, we design and evaluate both an algorithm and a heuristic that achieve different trade-offs between radiation and trajectory length of a moving agent.

Document type: Conference object

Solution-Space-based ATC support for 4DT heterogeneous aircraft-mix control

Scipedia content — Wed, 03 Feb 2021 21:30:49 +0100

Future Air Traffic Management concepts will require air traffic controllers to move from a tactical to a strategic way of operation. This paper evaluates two novel concepts which support controllers to perform four-dimensional trajectory management in a contingency situation. The Travel Space Representation and Time-Space Diagram are both solution-space based displays where automation calculates all possible actions in real-time. All decision-making is still to be done by the operator but is greatly facilitated by this automation, as it shows all possible actions at a glance. An experiment is described which evaluated the performance of novice controllers in managing a sector where suddenly a bad weather cell emerged, requiring them to re-route traffic in space and time. Results show that the display concepts work well and support operators even in complex situations with a heterogeneous mix of aircraft types and speeds. Performance and workload indicators become worse for the higher-density, higher-heterogeneity situations.

Clustering Algorithm in Vehicular Ad-hoc Networks: A Brief Summary

Scipedia content — Wed, 03 Feb 2021 21:29:42 +0100

n Intelligent Transportation System (ITS) application requires vehicles to be connected to each other and to roadside units to share information, thus reducing fatalities and improving traffic congestion. Vehicular Ad hoc Networks (VANETs) is one of the main forms of network designed for ITS in which information is broadcasted amongst vehicular nodes. However, the broadcast reliability in VANETs face a number of challenges - dynamic routing being one of the major issues. Clustering, a technique used to group nodes based on certain criteria, has been suggested as a solution to this problem. This paper gives a summary of the core criteria of some of the clustering algorithms issues along with a performance comparison and a development evolution roadmap, in an attempt to understand and differentiate different aspects of the current research and suggest future research insights.

The influence of the cinematic parameters of movement and sprung mass vibrations of wheeled vehicles on the move along the curvedlinear sections of the way

Scipedia content — Wed, 03 Feb 2021 21:23:40 +0100

This paper presents a study outcome whereby the method of analyzing the stability with regard to the skid of wheeled vehicles with the consideration of variable velocity value along the curvilinear sections of the way and longitudinal angular oscillations of the sprung part has been developed. The longitudinal - angular oscillations of the sprung part reduce the critical speed value of steady motion; accelerated movement of the vehicle along the curvilinear section of the way for larger values of acceleration of the front axle skid occurs at lower velocity values (rear for the larger ones), for slow motion on the contrary. As for the impact of the power characteristics of the sprung system, then for the same values of all other parameters (amplitudes of longitudinal - angular oscillations, static deformations, acceleration (deceleration)), the progressive characteristic of the sprinkler system corresponds to the greater value of the critical speed of the stable motion as a regressive one. The theoretical contribution of the reported study in that the obtained results can serve as a base for study the influence of the kinematic parameters of the vehicle's motion on its controllability.

Corporate Editors in the Evolving Landscape of OpenStreetMap: A Close Investigation of the Impact to the Map & Community

Scipedia content — Wed, 03 Feb 2021 21:20:00 +0100

nderson et al. (2019). Corporate Editors in the Evolving Landscape of OpenStreetMap: A Close Investigation of the Impact to the Map & Community In: Minghini, M., Grinberger, A.Y., Juhász, L., Yeboah, G., Mooney, P. (Eds.). Proceedings of the Academic Track at the State of the Map 2019, 17-18. Heidelberg, Germany, September 21-23, 2019. Available at https://zenodo.org/communities/sotm-2019 DOI: 10.5281/zenodo.3387693

Design of a zero emission aircraft towing system

Scipedia content — Wed, 03 Feb 2021 21:13:20 +0100

Even though aircraft have become less pollutant over the years, the increase in air traffic results in a growing production of emissions in the aviation industry. In other words, the annual decrease in pollution due to more fuel efficient aircraft, cannot compete with the increase of pollution caused by air traffic growth. Unlike the aviation sector, most sectors can replace fossil fuels with alternate energy sources, but the airline industry is currently confined to kerosene for flight operations. On the ground, electric taxiing is an alternative to conventional taxiing, which would have less impact on the environment and could solve aircraft congestion problems at airports. This research focuses on the feasibility of an airport based electric towing system, which eliminates the need for using fossil fuels while on the ground as much as possible.

Acoustic Emission Sensing of Pipe-Soil Interaction: Development of an Early Warning System for Buried Pipe Deformation

Scipedia content — Wed, 03 Feb 2021 21:12:44 +0100

This paper describes a programme of research that aims to develop a continuous, real-time acoustic emission (AE) monitoring system that can be distributed at discrete locations along buried pipelines to sense pipe/soil interaction and provide early warning of adverse behaviour to enable targeted and timely interventions. Pipe/soil interaction-generated AE propagates as guided waves along pipelines. Novel AE interpretation is allowing the evolution of the pipe/soil interaction behaviour to be characterised, and the rate and magnitude of deformation to be quantified. New understanding of AE propagation and attenuation in buried pipes is enabling source localisation methodologies to be developed. Results from normal faulting experiments performed on buried full-scale steel pipes at the buried infrastructure research facility at Queen’s University, Canada, are presented to demonstrate the potential of the AE technique for early detection of buried pipe deformation.

Multiple path prediction for traffic scenes using LSTMs and mixture density models

Scipedia content — Wed, 03 Feb 2021 21:09:16 +0100

This work presents an analysis of predicting multiple future paths of moving objects in traffic scenes by leveraging Long Short-Term Memory architectures (LSTMs) and Mixture Density Networks (MDNs) in a single-shot manner. Path prediction allows estimating the future positions of objects. This is useful in important applications such as security monitoring systems, Autonomous Driver Assistance Systems and assistive technologies. Normal approaches use observed positions (tracklets) of objects in video frames to predict their future paths as a sequence of position values. This can be treated as a time series. LSTMs have achieved good performance when dealing with time series. However, LSTMs have the limitation of only predicting a single path per tracklet. Path prediction is not a deterministic task and requires predicting with a level of uncertainty. Predicting multiple paths instead of a single one is therefore a more realistic manner of approaching this task. In this work, predicting a set of future paths with associated uncertainty was archived by combining LSTMs and MDNs. The evaluation was made on the KITTI and the CityFlow datasets on three type of objects, four prediction horizons and two different points of view (image coordinates and birds-eye view

Privacy-Preserving Smart Parking System Using Blockchain and Private Information Retrieval

Scipedia content — Wed, 03 Feb 2021 21:07:27 +0100

Searching for available parking spaces is a major problem for drivers in big cities, causing traffic congestion and air pollution, and wasting drivers' time. Smart parking systems enable drivers to have real-time parking information for pre-booking. However, current smart parking requires drivers to disclose their private information, such as desired destinations. Moreover, the existing schemes are centralized and vulnerable to the bottleneck of the single point of failure and data breaches. In this paper, we propose a distributed privacy-preserving smart parking system using blockchain. A consortium blockchain created by different parking lot owners to ensure security, transparency, and availability is proposed to store their parking offers on the blockchain. To preserve drivers' location privacy, we adopt private information retrieval (PIR) technique to enable drivers to retrieve parking offers from blockchain nodes privately, without revealing which parking offers are retrieved. Furthermore, a short randomizable signature is used to enable drivers to reserve available parking slots in an anonymous manner. Besides, we introduce an anonymous payment system that cannot link drivers' to specific parking locations. Our performance evaluations demonstrate that the proposed scheme can preserve drivers' privacy with low communication and computation overhead.

Contamination assessment of mine infrastructure areas for closure and relinquishment: Hazelwood Coal Mine, Victoria, Australia

Scipedia content — Wed, 03 Feb 2021 21:06:37 +0100

The Hazelwood coal mine and power station, near Morwell in the Latrobe Valley, Victoria, ceased operation in March 2017. A water filled mine void with potential for recreational, agricultural, commercial and industrial uses is envisioned for the surrounding area following mine licence relinquishment. Critical to achieving this is the assessment and management of infrastructure and potential contamination that is present in the mine licence area. This paper presents the approach to this assessment so that land management options and, if necessary, remediation can be identified and implemented early in the rehabilitation project. In Victoria, the Environmental Protection Agency (EPA) is the lead agency for land and water pollution; Department of Jobs, Precincts and Regions (DJPR) leads the mine rehabilitation process. These processes run in parallel, influencing each other. For the mine void the owner, ENGIE, has implemented a strategy that is consistent with EPA requirements, removing most equipment whilst leaving some in place. Infrastructure surrounding the mine, including conveyors, ash and water pipelines, and lay-down yards is being addressed through principles aligning with the National Environment Protection (Assessment of Site Contamination) Measure (ASC NEPM) contaminated site assessment approach, in parallel with mine closure and rehabilitation requirements. A preliminary site investigation (PSI) is underway that is based on former operational and sub-catchment areas and which includes a comprehensive history of former site activities and environmental condition. A key challenge at Hazelwood is the scale. The pit perimeter is over 16 km and the mine license area exceeds 1,200 ha. Former activities in and around the mine include: coal and coal ash handling; coal ash, hard rubbish and asbestos disposal; fuel storage and handling; pipe works, and surrounding commercial, industrial, and agricultural activities. The PSI will identify the likely level of contamination so that some areas may be able to be excised from further works while others move to detailed site investigation (DSI) and, if necessary, remediation. A sub-catchment approach to sub-areas allows source-pathway-receptor conceptual site models to be developed that are consistent with the NEPM regardless of whether areas progress to DSI and remediation stages, or are closed out at PSI stage.

Traffic Engineering and Maintenance Domains in WDM Carrier Ethernet Networks

Scipedia content — Wed, 03 Feb 2021 21:04:49 +0100

Improved Defect Detection Using Adaptive Leaky NLMS Filter in Guided-Wave Testing of Pipelines

Scipedia content — Wed, 03 Feb 2021 21:03:35 +0100

Ultrasonic guided wave (UGW) testing of pipelines allows long range assessments of pipe integrity from a single point of inspection. This technology uses a number of arrays of transducers, linearly placed apart from each other to generate a single axisymmetric wave mode. The general propagation routine of the device results in a single time domain signal, which is then used by the inspectors to detect the axisymmetric wave for any defect location. Nonetheless, due to inherited characteristics of the UGW and non-ideal testing conditions, non-axisymmetric (flexural) waves will be transmitted and received in the tests. This adds to the complexity of results’ interpretation. In this paper, we implement an adaptive leaky normalized least mean square (NLMS) filter for reducing the effect of non-axisymmetric waves and enhancement of axisymmetric waves. In this approach, no modification in the device hardware is required. This method is validated using the synthesized signal generated by a finite element model (FEM) and real test data gathered from laboratory trials. In laboratory trials, six different sizes of defects with cross-sectional area (CSA) material loss of 8% to 3% (steps of 1%) were tested. To find the optimum frequency, several excitation frequencies in the region of 30–50 kHz (steps of 2 kHz) were used. Furthermore, two sets of parameters were used for the adaptive filter wherein the first set of tests the optimum parameters were set to the FEM test case and, in the second set of tests, the data from the pipe with 4% CSA defect was used. The results demonstrated the capability of this algorithm for enhancing a defect’s signal-to-noise ratio (SNR).

A Time-predictable Branch Predictor

Scipedia content — Wed, 03 Feb 2021 21:03:09 +0100

International audience; Long pipelines need good branch predictors to keep the pipeline running. Current branch predictors are optimized for the average case, which might not be a good fit for real-time systems and worst- case execution time analysis.This paper presents a time-predictable branch predictor co-designed with the associated worst-case execution time analysis. The branch predictor uses a fully-associative cache to track branch outcomes and destination addresses. The fully-associative cache avoids any false sharing of entries between branches. Therefore, we can analyze program scopes that contain a number of branches lower than or equal to the number of branches in the prediction table. Experimental results show that the worst-case execution time bounds of programs using the proposed predictor are lower than using static branch predictors at a moderate hardware cost.

Moving a taxi sector to become electric

Scipedia content — Wed, 03 Feb 2021 21:01:03 +0100

The increased adoption of electric vehicles worldwide is largely caused by the uptake of private electric cars. In parallel other segments such as busses, city logistics and taxis, are increasingly becoming electrified. Amsterdam is an interesting case, as the municipality and the taxi sector have signed a voluntary agreement to realise a full electric taxi fleet by 2025. This paper investigates the results of a survey that was distributed amongst 3000 taxi drivers to examine perceptions and attitudes on the municipal charging incentives as well as taxi ride characteristics.

Tailings transport on high yield stress requirements: turbulent or laminar flow?

Scipedia content — Wed, 03 Feb 2021 20:59:39 +0100

In the mining industry, especially in Chile, tailings impoundment projects are tending to update their thickening technology or improve beach slopes due to environmental concerns, water scarcity, capacity restriction or economic variables. Projects in Chile either being designed or in operation under the concept of high-density tailings do not exceed a yield stress (fully sheared) of approximately 40–50 Pa, and their tailings transport systems may operate in turbulent regimes. There are currently significant research and development projects to improve thickening technology, impoundment deposition strategies and beach slopes management. However, do we have sufficient information and criteria relating to the long distance and large pipeline diameter for the transportation of tailings between the thickening and deposition points for high yield stress requirements? What happens to the transportation of tailings if it must be designed under the concept of high density with a yield stress (fully sheared) above 40–50 Pa but still cannot be considered a paste tailings? Can we expend efforts in thickening and depositing if we do not adequately handle what happens in between (transport)? Generally, for high-density tailings, transportation is designed to operate under the concept of turbulent flow. However, at yield stress above 40–50 Pa, turbulent flow will mean excessive internal wear on the pipelines, due to high velocities and a significant energy demand. What should the criteria be that govern the tailings transport for the high-density zone above 40–50 Pa? Design under turbulent regime or laminar regime? The paper will present an analysis of studies developed to date, identifying and evaluating the variables that govern the design of high-density transport systems within the proposed yield stress ranges. A technical and economic case will be evaluated for a tailings transport project on the proposed yield stress ranges, showing the differences that may exist based on the assumed criteria. The criteria and results of the analysis will be presented in this paper.

Creating repeatable, reusable experimentation pipelines with popper

Scipedia content — Wed, 03 Feb 2021 20:59:05 +0100

Popper is an experimentation protocol for conducting scientific explorations and writing academic articles following a DevOps approach. The Popper CLI tool helps researchers automate the execution and validation of an experimentation pipeline. In this tutorial we give an introduction to the concepts and CLI tool, and go over hands-on exercises that help.

TPM: A GPS-based Trajectory Pattern Mining System

Scipedia content — Wed, 03 Feb 2021 20:50:24 +0100

With the development of big data and artificial intelligence, the technology of urban computing becomes more mature and widely used. In urban computing, using GPS-based trajectory data to discover urban dense areas, extract similar urban trajectories, predict urban traffic, and solve traffic congestion problems are all important issues. This paper presents a GPS-based trajectory pattern mining system called TPM. Firstly, the TPM can mine urban dense areas via clustering the spatial-temporal data, and automatically generate trajectories after the timing trajectory identification. Mainly, we propose a method for trajectory similarity matching, and similar trajectories can be extracted via the trajectory similarity matching in this system. The TPM can be applied to the trajectory system equipped with the GPS device, such as the vehicle trajectory, the bicycle trajectory, the electronic bracelet trajectory, etc., to provide services for traffic navigation and journey recommendation. Meantime, the system can provide support in the decision for urban resource allocation, urban functional region identification, traffic congestion and so on.

When DevOps Meets Meta-Learning: A Portfolio to Rule them all

Scipedia content — Wed, 03 Feb 2021 20:49:57 +0100

International audience; The Machine Learning (ML) world is in constant evolution, as the amount of different algorithms in this context is evolving quickly. Until now, it is the responsibility of data scientists to create ad-hoc ML pipelines for each situation they encounter, gaining knowledge about the adequacy between their context and the chosen pipeline. Considering that it is not possible at a human scale to analyze the exponential number of potential pipelines, picking the right pipeline that combines the proper preprocessing and algorithms is a hard task that requires knowledge and experience. In front of the complexity of building a right ML pipeline, algorithm portfolios aim to drive algorithm selection, learning from the past in a continuous process. However, building a portfolio requires that (i) data scientists develop and test pipelines and (ii) portfolio maintainers ensure the quality of the portfolio and enrich it. The firsts are the developers, while the seconds are the operators. In this paper, we present a set of criteria to be respected, and propose a pipeline-based meta-model, to support a DevOps approach in the context of Machine Learning Pipelines. The exploitation of this meta-model, both as a graph and as a logical expression, serves to ensure continuity between Dev and Ops. We depict our proposition through the simplified study of two primary use cases, one with developer's point-of-view, the other with ops'.

USE OF NON-DIMENSIONAL TRANSIENT PRESSURE TRACES TO CHARACTERIZE LEAKS IN WATER PIPELINES

Scipedia content — Wed, 03 Feb 2021 20:47:38 +0100

LiDAR Performance Review in Arctic Conditions

Scipedia content — Wed, 03 Feb 2021 20:43:02 +0100

This article aims to outline the key results of testing and encountered challenges of various LiDARs, radar and stereo camera in arctic weather conditions. The test session was conducted in two different urban areas in Finland in the middle of January 2019. The arctic conditions turned out to be challenging for the sensors dedicated more to areas where temperature stays relatively warm. The aim of this one-week test session was to assess performance deterioration when powdered snow, salted road, snowy ground and sun light influence reliability of the future automated driving functions. This study focuses mainly on the issues with hardware that are basic building blocks for the situation awareness software modules. Furthermore, the countermeasures such as protecting sensors and mounting positions have been proposed.The test results indicate that some sensors significantly lose performance when temperature drops to less than -10 degrees centigrade. The problem is not merely mechanical freezing of the spinning LiDAR components but properties of laser illumination may change due to temperature variation, too. Since LiDAR is an optical device, they also suffer when there is turbulent snow in front of the sensor. The turbulence looks like a noise and partially blocks the laser echoes from surrounding environment. The performance, measured by laser pulse echo count, can with some sensors drop more than 50 percent. This seriously diminishes the sensing range and furthermore, makes pattern recognition unreliable. The two other sensor types which were taken into account are stereo vision and radar. They have a role in automated driving to compensate performance degradation of LiDARs due to arctic conditions.

Learning Real Trajectory Data to Enhance Conflict Detection Accuracy in Closest Point of Approach

Scipedia content — Wed, 03 Feb 2021 20:42:26 +0100

Closest Point of Approach (CPA) is one of the main problems in aircraft Conflict Detection (CD). It aims to find out the minimum distance and the associated time between two aircraft on the same altitude with crossing traffic. Conventional CPA prediction model generally assumes that the speed and heading of the aircraft are constant. But the uncertainties in real operations lead to the inaccuracy of CPA prediction. In this paper, we introduce a novel CD framework with Machine Learning (ML) methods. It aims to improve the CPA prediction accuracy with the help of real trajectory data. The new model contributes to not only reduce the number of fault short-mid term conflict alert for air traffic controllers but also support the implementation of future free flight concept, so as to reduce fuel consumption and emission. In our study, we firstly propose a data processing method to generate a close-to-reality simulation data from Mode-S observations. Then, feature engineering is used to transform the raw data into suitable features, which will enable the ML models to make predictions with high- performance. Six prevailing ML methods (MLR, SVM, FFNNs, KNN, GBM, RF) are used to predict the CPA time and distance. Their prediction results are compared with the conventional CPA model (baseline). The simulation results demonstrate that the GBM is the best prediction model both in CPA prediction and conflict detection. However, the results also prove that not all ML models outperform the baseline CPA model. Suitable ML methods can greatly enhance the accuracy of conflict detection. Refereed/Peer-reviewed

Demand capacity balancing in multi-modal transportation through optimization and simulation

Scipedia content — Wed, 03 Feb 2021 20:41:57 +0100

International audience; The current Air traffic System in Europe relies on airspace and airport capacity estimates computed by the Air National Service Providers (ANSPs) using demand forecast and Air traffic Controllers operations schedules. The Demand Capacity Balancing (DCB) aims at reducing the Air Traffic Management resources held in reserve to cope with demand peaks by providing the system with demand smoothing means. A recent study on the subject suggests introducing a congestion-based route fee that encourages users to avoid crowded slots for a given departure and arrival airport [1]. An optimal equilibrium point can then be reached through a clever choice of penalties incurred by flying at departure times adversely impacting congestion. Alternative routes may also be considered in the planning, as for a whole category of customers price tag is more important than travel time. However, taking into account that for short haul flights alternative means of transportation may be a viable option, DCB can be addressed in a wider scope by considering surface vehicles along aircraft. A side effect of this holistic approach is the ability to cope with disruptive events. The present work describes a simulation and optimization model tailored to this particular problem.

“Pedestrian in the Loop”: An Approach Using Augmented Reality

Scipedia content — Wed, 03 Feb 2021 20:38:03 +0100

© 2018 SAE International. All Rights Reserved. A large number of testing procedures have been developed to ensure vehicle safety in common and extreme driving situations. However, these conventional testing procedures are insufficient for testing autonomous vehicles. They have to handle unexpected scenarios with the same or less risk a human driver would take. Currently, safety related systems are not adequately tested, e.g. in collision avoidance scenarios with pedestrians. Examples are the change of pedestrian behaviour caused by interaction, environmental influences and personal aspects, which cannot be tested in real environments. It is proposed to use augmented reality techniques. This method can be seen as a new (Augmented) Pedestrian in the Loop testing procedure. ispartof: SAE Technical Papers vol:2018-April ispartof: WCX™: SAE World Congress Experience location:Detroit, Michigan, United States date:10 Apr - 14 Apr 2018 status: published

Document type: Conference object

Evaluation of the European road freight market for longer and heavier vehicles on the long haul and conclusions to new vehicle concepts

Scipedia content — Wed, 03 Feb 2021 20:35:25 +0100

potential European freight transport market for longer and heavier commercial vehicles (LHVs) on the long haul is quantified by analyzing the European Road Freight Survey. In particular, we carry out a detailed analysis of the actual usage of high load capacity vehicles with respect to important market segments at a journey level, including type of journey, loading unit and load factor. LHVs increase the vehicle capacity and allow for reduced costs, if the average load is also increasing. Our analysis suggests that only 50% of the analyzed transports by ton-kilometres are fully loaded. In addition, it was found that Full Truckload (FTL) transports currently dominate long-distance transports with heavy vehicles, with pallets being used predominantly. New vehicle concepts should take these figures into account.

Work-in-Progress: Synchronous Intersection Management Protocol for Mixed Traffic Flows

Scipedia content — Wed, 03 Feb 2021 20:32:53 +0100

RTSS 2019 originally postponed from December 2019 (Hong-Kong) to February 2020 (York, UK) was cancelled. Urban traffic management (UTM) is responsible for planning and controlling traffic on road infrastructures, including lane closures, full freeway closures, and pedestrian access. An essential element in UTM is the Intersection Management (IM) that deals with traffic control and is vulnerable to traffic congestion and accidents. In this paper, we propose an intelligent intersection management architecture along with the synchronous intersection management protocol (SIMP) instantiated in two versions. Simulation results show the advantages of SIMP-M (one of the versions) over the well known TraCI IM protocol, in terms of both worst-case and average vehicle speed passing through one intersection. info:eu-repo/semantics/publishedVersion

Service for optimization of charging stations selection for electric vehicles users during long distances drives

Scipedia content — Wed, 03 Feb 2021 20:29:03 +0100

International audience; One of the major curb to electric vehicles (EV) acceptability is their constraints when performing long distance trips. Even if improvements made on fast charging technology enable to recover up to 400 km range in 20 minutes, the low density of this kind of infrastructure and the variability in their availability can lead to significant waiting times for users. Many articles develop communication scenario between vehicles in order to coordinate users charging places choices, permitting a better distribution that minimize waiting queue. The authors compare their approaches performances with theoretical resolution of the relaxed problem. In this article, the authors deal with a situation where many electric vehicles run along a highway with few charging stations, representing a usual daily traffic flow. It provides an approach that permits to find an optimal charging schedule for all users, minimizing their waiting and charging time at charging stations, using an all-knowing point of view. A differential evolution algorithm is used, with some improvements to better adapt it to this problem and speed the convergence.

COPING WITH CLASS IMBALANCE IN CLASSIFICATION OF TRAFFIC CRASH SEVERITY BASED ON SENSOR AND ROAD DATA: A FEATURE SELECTION AND DATA AUGMENTATION APPROACH

Scipedia content — Wed, 03 Feb 2021 20:27:14 +0100

This paper presents machine learning-based approaches to classification of historical traffic crashes in Kansas by severity, applied to a data set consisting of highway geometry, weather, and road sensor data. The goal of this work is to identify relevant features using a variety of loss measures and algorithms for feature selection. This is shown to facilitate the discovery of the most relevant sensors for the task of learning to predict severe crashes (those involving bodily injury). The key technical challenges are to cope with class imbalance (as a 75% majority of crashes are non-severe) and a highly correlated and redundant set of features from multiple coalesced sources. The major novel contributions of this work are the development of a random oversampling strategy for data augmentation, combined with the systematic application of multiple feature selection measures over a range of supervised inductive learning models and algorithms. Positive results from this approach, on a data set of 277 initial ground features and 20,000 vehicle crashes collected over 9 years (2007 – 2015) by the Kansas Department of Transportation (KDOT), included models trained using 30 features (out of 277) that achieve cross-validation precision and recall comparable to those obtained using the full set of features. These and other results point towards potential use of feature selection findings and the resultant models in planning future road construction.

Methodological approach to estimating the efficiency of the stock complex facing of transport and logistic centers in Ukraine

Scipedia content — Wed, 03 Feb 2021 20:26:45 +0100

The aim of this paper is to present a methodological approach to estimating technological process in the warehouse complex of the transport and logistics centers with respect to their efficiency. It was determined that one of the main directions of modern transport policy is the transition to transport logistics in the transport and logistics system, which allows us to provide comprehensive services to consumers of transport services, creating conditions for the development of combined transport, reducing the harmful influence on the environment. It is established that in order to carry out the successful implementation of the entire complex of works and reduce the cost of operations in the transport and logistics centers, as an important component of it, it is necessary to implement transport and technological processes, which must be based on progressive techniques and advanced methods. While constructing a mathematical model of an object, it was taken into account that the value of the general criterion of effectiveness depends on the values of the characteristics of the criteria of the effectiveness of the active elements of the system. The technological process of functioning of the warehouse complex of the transport and logistics centers, which is proposed in this paper, allows us to see the whole chain of operations from the moment of arrival of the vehicle with the load to the warehouse until the moment the consignment is shipped to the recipient. The approach to determine the efficient organization of the work of the warehouse complex of the transport and logistics center, according to the criterion, includes the total costs affected by: the intensity of the types cargo flows, the cost of one unit work and one hour work of one worker, the time of execution of the operation, and the amount of resources involved to perform each operation. The analytical models of determination of the estimation parameter are developed. In order to obtain the most reliable data on changes in the parameters of the warehouse process it has been determined the required number of observations be established . Based on the analysis of the order flow parameters of most transport and logistics centers of Ukraine, it has been found that the intensity of the input, internal and output flow of cargo is distributed according to the exponential law. This conclusion was confirmed by an appropriate level of confidence. The experiment, conducted in accordance with the principle of constructing a full-factor plan for the experiment, obtained the results of research on the proposed criterion for determining the efficient organization of the transport and logistics centers warehouse complex for three variants. Relying on the basic data regression models (linear and power) were constructed. An analysis of these models shows that the regression model in linear form with non-zero coefficients is the most adequate one, since the value of the indicator R² is the largest and it is equal to unity. On the received models the values of the criterion of efficiency are defined as total costs, for each variant. On the basis of the received changes in total costs for the organization of the warehouse complex, significant influence of the intensity of the incoming flow of goods has been identified, which in turn requires higher expenses of resources in the zone of acceptance of goods.

THE POSSIBILITIES AND CHALLENGES FOR SUSTAINABLE TRANSPORT IN ALBANIA (CASE STUDY: SHKODRA CITY)

Scipedia content — Wed, 03 Feb 2021 20:20:09 +0100

CluFlow: cluster-based flow management in software-defined wireless sensor networks

Scipedia content — Wed, 03 Feb 2021 20:15:54 +0100

Software-defined networking (SDN) is a cornerstone of next-generation networks and has already led to numerous advantages for data-center networks and wide-area networks, for instance in terms of reduced management complexity and more fine-grained traffic engineering. However, the design and implementation of SDN within wireless sensor networks (WSN) have received far less attention. Unfortunately, because of the multi-hop type of communication in WSN, a direct reuse of the wired SDN architecture could lead to excessive commu- nication overhead. In this paper, we propose a cluster-based flow management approach that makes a trade-off between the granularity of monitoring by an SDN controller and the communication overhead of flow management. A network is partitioned into clusters with a minimum number of border nodes. Instead of having to handle the individual flows of all nodes, the SDN controller only manages incoming and outgoing traffic flows of clusters through border nodes. Our proof-of- concept implementations in software and hardware show that, when compared with benchmark solutions, our approach is significantly more efficient with respect to the number of nodes that must be managed and the number of control messages exchanged.

Simulating ADAS Sensors, their Placement and Environment

Scipedia content — Wed, 03 Feb 2021 20:15:15 +0100

With the advent of autonomous vehicles, carmakers are increasingly involved in developments of Active Safety and Advanced Driver Assistance Systems. Those systems are part of complex electronic equipment, that – with its sensors, microcontrollers, cable harnesses – will represent up to 40% of the total manufacturing cost. Today, virtual prototyping is integral part of development process, assuring fast innovation cycles and minimizing costs. A multiscale hybrid strategy is proposed to simulate Advanced Driver Assistance Systems (ADAS) in both Short Radar Range (SRR) and Long Radar Range (LRR). While SRR devices (typically blind spot/dead-angle radars) are operating at 24 GHz, the LRR devices used for Adaptive Cruise Control systems are utilizing the 77 GHz band. The sensor itself is modeled using FDTD or MoM/MLFMM methods. Then, the related electromagnetic environment is computed by means of Physical Optics (PO). Dedicated PO upgrades are utilized to handle plastic parts (bumper, front grille) in front of a sensor.

Potentials of the waste-to-energy sector for an unconventional district heating system

Scipedia content — Wed, 03 Feb 2021 20:11:46 +0100

In spite of being a process that exploits a renewable source of energy, the combustion of wood-based biomass contributes to deteriorate outdoor and indoor air quality. Critical situations for human exposure may occur in mountainous areas, where wood-based biomass is usually abundant and the complex morphology may favour the stagnation of air pollutants in valleys. Replacing wood/pellet stoves with centralised systems would reduce the impact, but the construction of district heating systems may not be convenient in areas with low density of houses. A possible solution could rely on direct electrical heating (DEH) systems, preferably fed by thermochemical processes that help achieve environmental goals for the local community, like the reduction of waste landfilling and the valorisation of the energy content of waste. This paper aims at presenting a comparison between the impacts expected by household wood/pellet stoves and by a modern waste-to-energy (WtE) plant, in terms of emissions of air pollutants into the atmosphere, when replacing wood stoves with a DEH system fed by the electric energy generated by the WtE plant. The comparison shows that the replacement of household stoves with an equivalent DEH system would be beneficial in terms of impacts on the local air quality. Such an approach could be considered to reduce the health impacts from biomass burning in critical areas like the Alpine region.

Practice ecology of sustainable travel: The importance of institutional policy-making processes beyond the traveller

Scipedia content — Wed, 03 Feb 2021 20:09:19 +0100

Changing mobility behaviour towards activities and actions that have a less detrimental impact on the environment, public health and society is an objective of transport policy jurisdictions globally. In line with a burgeoning body of research examining behaviour and social change, this paper explores the governmental systems that influence mobility behaviours through a social practice lens. This paper blends two social practice theoretical models, the ‘3-Elements Model’ and ‘Systems of Provision’, as a means of understanding the delivery of the Local Sustainable Transport Fund (LSTF), a central government grant scheme for English local authorities. We examine how the meanings, materials and competences within the practices of bid writing by local authorities and scheme selection by government influenced the distribution of funding to local authorities. The research starts from the principle that, where funding is provided by central government, in the case of this research that of the UK, an opportunity is created for mobility practices to change. The significance of funding is not easily theorised by the 3-Elements model but is more helpfully explained when that model is blended with the wider Systems of Provision model to create a model of practice ecology. Our theorisation allows for a rigorous exploration of the ‘practice scaffolding’ which shapes how people travel. Policymakers are recommended to consider a practice ecology approach when developing mobility management schemes to tackle air quality, climate change and obesity issues more effectively.

Document type: Article

Stream-IT: Continuous and dynamic processing of production systems data - throughput bottlenecks as a case-study

Scipedia content — Wed, 03 Feb 2021 20:08:42 +0100

Considering the needs for continuous availability of information out of data generated in Cyber-Physical production systems, we investigate the use of continuous stream processing as a paradigm for generating useful information out of the data, to support efficient and safe operation, as well as planning activities.Our contributions and expected benefits: (i) we show possibilities to automate and pipeline the validation and analysis of the data, hence providing an automated way to improve the quality of the latter and parallelizing the two phases; (ii) we show how to induce lower latency in generating the desired information, enabling it to be continuously made available, before whole batches of data are gathered, in cost-efficient ways; (iii) besides the automation of the above procedures that are commonly done in a batch fashion and with significant manual effort by the production system analysts, we show additional options for configuring ways in which to automate deeper analysis of the data; in particular, we provide evidences about how the rich semantics of stream processing frameworks can ease the development and deployment of data analysis applications in production systems.Moreover, using the problem of bottleneck detection as a sample scenario, we illustrate the above in a concrete fashion, on cost-efficient systems, that are plausible to have in existing deployments. The experimental study is on a 2-year data-set with more than 8.5 million entries, from a system including more than 30 interconnected machines and it demonstrates the benefits of the proposed methods, in providing timely and multidimensional information from the data, enabling possibilities for deeper analyses.

Partially Detected Intelligent Traffic Signal Control: Environmental Adaptation

Scipedia content — Wed, 03 Feb 2021 20:05:53 +0100

Partially Detected Intelligent Traffic Signal Control (PD-ITSC) systems that can optimize traffic signals based on limited detected information could be a cost-efficient solution for mitigating traffic congestion in the future. In this paper, we focus on a particular problem in PD-ITSC - adaptation to changing environments. To this end, we investigate different reinforcement learning algorithms, including Q-learning, Proximal Policy Optimization (PPO), Advantage Actor-Critic (A2C), and Actor-Critic with Kronecker-Factored Trust Region (ACKTR). Our findings suggest that RL algorithms can find optimal strategies under partial vehicle detection; however, policy-based algorithms can adapt to changing environments more efficiently than value-based algorithms. We use these findings to draw conclusions about the value of different models for PD-ITSC systems.

Comment: Accepted by ICMLA 2019

Hot Spot Analysis over Big Trajectory Data

Scipedia content — Wed, 03 Feb 2021 20:04:27 +0100

Hot spot analysis is the problem of identifying statistically significant spatial clusters from an underlying data set. In this paper, we study the problem of hot spot analysis for massive trajectory data of moving objects, which has many real-life applications in different domains, especially in the analysis of vast repositories of historical traces of spatio-temporal data (cars, vessels, aircrafts). In order to identify hot spots, we propose an approach that relies on the Getis-Ord statistic, which has been used successfully in the past for point data. Since trajectory data is more than just a collection of individual points, we formulate the problem of trajectory hot spot analysis, using the Getis-Ord statistic. We propose a parallel and scalable algorithm for this problem, called THS, which provides an exact solution and can operate on vast-sized data sets. Moreover, we introduce an approximate algorithm (aTHS) that avoids exhaustive computation and trades-off accuracy for efficiency in a controlled manner. In essence, we provide a method that quantifies the maximum induced error in the approximation, in relation with the achieved computational savings. We develop our algorithms in Apache Spark and demonstrate the scalability and efficiency of our approach using a large, historical, real-life trajectory data set of vessels sailing in the Eastern Mediterranean for a period of three years.

Document type: Conference object

Human Factors Evaluation of ATC Operational Procedures in Relation to Use of 3D Display

Scipedia content — Wed, 03 Feb 2021 20:03:29 +0100

In this paper, Holding Stack Management (HSM), Continuous Climb Operations (CCO), Continuous Descent Operations (CDO), and Trajectory Based Operations (TBO) procedures are assessed in relation to the use of an additional 3D display. Two display seetings are compared, namely 2D+3D and 2D only. Twelve Air Traffic Control Officers (ATCOs) took part in the experiment. Traditional questionnaires such as NASA TLX, TRUST, etc. were given at the end of each 30-minute trial for each display setting. Electroencephalogram (EEG) was recorded during the experiments to continuously monitor the changes of the brain states of the ATCOs. The results of the data analyses show that by using 2D+3D display setting, more positive emotions, but higher stress and workload levels were experienced by ATCOs in TBO, CCO and CDO procedures than in 2D setting. In HSM, reduced stress and significantly lower cognitive workload were experienced by ATCOs when they were using 2D+3D setting.

Reduction of energy losses on car movement while using a combined electromechanical drive of leading wheels

Scipedia content — Wed, 03 Feb 2021 19:54:17 +0100

This article addresses the problem that fluctuations in the torque of an internal combustion engine (ICE) lead to additional energy losses, as it causes fluctuations in the speed and kinetic energy of the car. These losses increase as the frequency of oscillations of the torque of the internal combustion engine approaches the frequency of free (natural oscillations) of the running gear of the car in the longitudinal direction. If there is an elastic connection between the traction force and the movement of the car, the movement of the latter can be represented as complex. At the same time, the portable movement is uniform, and the relative movement is oscillatory. This article presents the results of the study of these losses for cars with mechanical and combined electromechanical drive wheels. Analytical expressions are obtained, which allows to take into account additional energy losses including the tangential rigidity of the tire and the rigidity of the suspension in the longitudinal direction. When using a combined electromechanical drive of the drive wheels as well as in the case of a mechanical transmission of a car, the resonance is dangerous. But with the increase in the share of torque "em"k"sub"em"/sub""/em" on the wheel generated by the electric motor, the relative additional energy losses for the movement of the car are reduced.

Improving Ridesplitting Service Using Optimization Procedures on Shareability Network: A Case Study of Chengdu, China

Scipedia content — Wed, 03 Feb 2021 19:53:18 +0100

ITSC 2019, IEEE Intelligent Transportation Systems Conference, Auckland, NOUVELLE-ZELANDE, 27-/10/2019 - 30/10/2019; Ridesourcing services play a crucial role in metropolitan transportation systems and aggravate urban traffic congestion and air pollution. Ridesplitting is one possible way to reduce these adverse effects and improve transport efficiency. This paper aims to explore the potential of ridesplitting in peak hours using empirical ridesourcing data of Chengdu, China provided by DiDi Chuxing. A ridesplitting trip identification algorithm based on a shareability network is developed to quantify the potential of ridesplitting. Then, we evaluate the gap between the potential and actual scales of ridesplitting, which the literature has not yet reported. We compare the potential of ridesplitting under three different objectives. The results show that the objective of minimizing the total travel cost produces better performance than the objectives of maximizing shared trips and time savings. Under the objective of maximizing cost savings, the percentage of potential cost savings is 18.47% with an average delay of 4.76 minutes, whereas the actual percentage is 1.22% with an average delay of 9.86 minutes. The potential percentage of shared trips is 90.69%, while the actual percentage is 7.85%. Furthermore, the potential time savings can reach 25.75%, while the actual time savings are 2.38% in the real world. The findings of this study can help transportation management agencies and ridesourcing companies develop sensible policies to improve ridesplitting services.

Dynamic collision avoidance using local cooperative airplanes decisions

Scipedia content — Wed, 03 Feb 2021 19:49:26 +0100

International audience; In the near future, air traffic control (ATC) will have to cope with a radical change in the structure of air transport [1]. Apart from the increase in traffic that will push the system to its limits, the insertion of new aerial vehicles such as drones into the airspace, with different flight performances, will increase its heterogeneity. Current research aims at increasing the level of automation and partial delegation of the control to on-board systems. In this work, we investigate the collision avoidance management problem using a decentralized distributed approach. We propose an autonomous and generic multi-agent system to address this complex problem. We validate our system using state-of-the-art benchmarks. The results underline the adequacy of our local and cooperative approaches to efficiently solve the studied problem.

Preserving Uncertainty in Demand Prediction for Autonomous Mobility Services

Scipedia content — Wed, 03 Feb 2021 19:43:37 +0100

Unlike traditional bus fleets, autonomous mobility services are naturally amenable to dynamic, demand-responsive adaptation of itinerary. Accurate prediction of demand for such services can thus improve their utilization and decrease their operational costs. Although demand for transit services is inherently stochastic, models of demand often reduce its distribution to point estimates, thus losing useful information for subsequent decision making. In this paper, we advocate for preserving the full predictive distribution through quantile regression, so that the structure of uncertainty in future demand is preserved. To demonstrate our approach, we present a real-world case study of an autonomous shuttle service in a Danish university campus, for which we have several weeks of crowd movement counts, as reconstructed from campus WiFi records. We devise several types of quantile regression models for demand prediction, analyze their performance, and discuss their applicability to the case study. Our modeling methodology can be extended to autonomous fleets of higher scale, thus promoting sustainable shared mobility.

Involving Hearing, Haptics and Kinesthetics into Non-visual Interaction Concepts for an Augmented Remote Tower Environment

Scipedia content — Wed, 03 Feb 2021 19:38:27 +0100

International audience; We investigated the contribution of specific HCI concepts to provide multimodal information to Air Traffic Controlers in the context of Remote Control Towers (i.e. when an airport is controlled from a distant location). We considered interactive spatial sound, tactile stimulation and body movements to design four different interaction and feedback modalities. Each of these modalities have been designed to provide specific solutions to typical Air Traffic Control identified use cases. Sixteen professional Air Traffic Controllers (ATCos) participated in the experiment, which was structured in four distinct scenarios. ATCos were immersed in an ecological setup, in which they were asked to control (i) one airport without augmentations modalities, (ii) two airports without augmentations, (iii) one airport with augmentations and (iv) two airports with augmentations. These experimental conditions constituted the four distinct experimental scenarios. Behavioral results shown a significant increase in overall participants’ performance when augmentation modalities were activated in remote control tower operations for one airport.

Design of electric vehicles grid related energy systems for optimal mobility service

Scipedia content — Wed, 03 Feb 2021 19:35:38 +0100

International audience; The major priority of the carmakers is to reduce the energy consumption and the emissions of the future passenger cars and to deliver an efficient mobility service for the customers. The number of electrified vehicles increases in the mobility market. The range and the energy storage of the vehicle on board are important. The recharging of the vehicles and their connection to the energy grid became an important question. In this article, the energy system is extended and includes the energy storage and conversion of vehicles and their connection to the grid. The extended energy system is modelled on vehicles flows on the highway and a single objective optimization is performed to define the optimal energy storage capacity of the vehicles and the optimal number of recharges of from the grid. The time and the occupation rates of the chargers are as well evaluated. The optimality is researched for long way drives on electric mode. The results illustrate a method to rethink the usage and the energy management on the vehicle during the driving. As well it is researched how to adapt the recharging capacities and their location on the grid, by using a holistic approach. The target is to propose a high quality service for the electric mobility for long way drives.

Multi-actuated ground vehicle tyre force estimation through a coupled 1D simulation-estimation framework

Scipedia content — Wed, 03 Feb 2021 19:30:43 +0100

This paper disseminates the use of a coupled 1D simulation-estimation framework employed for multi-actuated ground vehicle tyre force virtual sensing. The forces generated in the tyre contact patches govern the vehicle motion and behaviour on the road. Therefore, they are highly relevant for Advanced Driver Assistance Systems (ADAS) and Automated Driving (AD) technologies, especially when it comes to ensuring vehicle stability and driving safety in extreme manoeuvres. However, some ADAS and AD features require accurate and robust estimation of additional vehicle dynamics related quantities. Thus, this paper proposes a framework for the consistent use of 1D vehicle models of different complexity together with state-of-the-art estimation techniques to enable joint state, disturbance, parameter (SDP) estimation. ispartof: 2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE) proceedings ispartof: 2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE) location:Graz, Austria date:4 Nov - 8 Nov 2019 status: Published online

Optimizing Successive Airspace Configurations with a Sequential A * Algorithm

Scipedia content — Wed, 03 Feb 2021 19:29:54 +0100

International audience; In this paper, we introduce exact tree search algorithms which explore all the possible sequences of airspace partitions , taking into account some constraints on the transitions between two successive airspace configurations. The transitions should be simple enough to allow air traffic controllers to maintain their situation awareness during the airspace configuration changes. For the same reason, once a sector is opened it should remain so for a minimum duration. The proposed method is a sequential A * algorithm with a rolling horizon. It finds a sequence of airspace configurations minimizing a cost related to the workload and the usage of manpower resources, while satisfying the transition constraints. This approach shows good results on 9 months of data from the french ATCC Aix (East), when compared with two baseline methods, one with a greedy approach and the other with no transition constraints.

Brain–Computer Interface-Based Adaptive Automation to Prevent Out-Of-The-Loop Phenomenon in Air Traffic Controllers Dealing With Highly Automated Systems

Scipedia content — Wed, 03 Feb 2021 19:29:39 +0100

International audience; Increasing the level of automation in air traffic management is seen as a measure to increase the performance of the service to satisfy the predicted future demand. This is expected to result in new roles for the human operator: he will mainly monitor highly automated systems and seldom intervene. Therefore, air traffic controllers (ATCos) would often work in a supervisory or control mode rather than in a direct operating mode. However, it has been demonstrated how human operators in such a role are affected by human performance issues, known as Out-Of-The-Loop (OOTL) phenomenon, consisting in lack of attention, loss of situational awareness and de-skilling. A countermeasure to this phenomenon has been identified in the adaptive automation (AA), i.e., a system able to allocate the operative tasks to the machine or to the operator depending on their needs. In this context, psychophysiological measures have been highlighted as powerful tool to provide a reliable, unobtrusive and real-time assessment of the ATCo’s mental state to be used as control logic for AA-based systems. In this paper, it is presented the so-called “Vigilance and Attention Controller”, a system based on electroencephalography (EEG) and eye-tracking (ET) techniques, aimed to assess in real time the vigilance level of an ATCo dealing with a highly automated human–machine interface and to use this measure to adapt the level of automation of the interface itself. The system has been tested on 14 professional ATCos performing two highly realistic scenarios, one with the system disabled and one with the system enabled. The results confirmed that (i) long high automated tasks induce vigilance decreasing and OOTL-related phenomena; (ii) EEG measures are sensitive to these kinds of mental impairments; and (iii) AA was able to counteract this negative effect by keeping the ATCo more involved within the operative task. The results were confirmed by EEG and ET measures as well as by performance and subjective ones, providing a clear example of potential applications and related benefits of AA.

Document type: Article

Analyzing the Sensitivity of GPU Pipeline Registers to Single Events Upsets

Scipedia content — Wed, 03 Feb 2021 19:28:49 +0100

Graphics processing units are available solutions for high-performance safety-critical applications, such as self-driving cars. In this application domain, functional-safety and reliability are major concerns. Thus, the adoption of fault tolerance techniques is mandatory to detect or correct faults, since these devices must work properly, even when faults are present. GPUs are designed and implemented with cutting-edge technologies, which makes them sensitive to faults caused by radiation interference, such as single event upsets. These effects can lead the system to a failure, which is unacceptable in safety-critical applications. Therefore, effective detection and mitigation strategies must be adopted to harden the GPU operation. In this paper, we analyze transient effects in the pipeline registers of a GPU architecture. We run four applications at three GPU configurations, considering the source of the fault, its effect on the GPU, and the use of software-based hardening techniques. The evaluation was performed using a general-purpose soft-core GPU based on the NVIDIA G80 architecture. Results can guide designers in building more resilient GPU architectures.

The largest piston diaphragm pump in the world: from drawing board to operational experience

Scipedia content — Wed, 03 Feb 2021 19:26:01 +0100

Over the years, it has become apparent that the demand for high flow rate pipelines, either for concentrate or tailings slurry, is continuously increasing. At the same time the industry recognized the advantages of piston diaphragm pumps when compared to multistage centrifugal pump installations. As previously the unit capacity of conventional piston diaphragm pumps was limited, a large number of low capacity piston diaphragm pumps needed to be installed in parallel to meet required high flow rates. This resulted in high costs for purchase of these pumps, as well as high costs for infrastructure around the pumps, such as piping, cabling, booster pumps etc. For this reason, FELUWA decided to develop a large piston diaphragm pump with a capacity of up to 1000 m³/hr (4400 gpm), which increases the unit capacity of such pumps by about 50%. The new pump is of 5 cylinder, single acting configuration and is equipped with double hoses diaphragms, rather than with single flat and circular diaphragms. A number of these pumps have been installed and the first operational experience has become available. This paper describes the project and application, as well as the background for the development of this type of pump, its most important features, the hydraulic design of the pipeline and operational experience. In addition, the paper explains in detail why piston diaphragm pumps were selected for this application in favour of centrifugal slurry pumps and how their costs compare.

Improvement of Air Transport Environmental Safety by Implementing Alternative Jet Fuels

Scipedia content — Wed, 03 Feb 2021 19:25:26 +0100

The study is devoted to evaluation of exhaust gases emissions from aircrafts using conventional oil-derived jet fuel and alternative jet fuels, obtained by blending of conventional fuel with plant oil bio-additives. The evaluation was done by calculation of emission indexes of carbon dioxide, water vapor, sulfur oxide and nitrogen oxide and calculation of emission levels of each pollutant in a result of one standard landing – take-off cycle. In a result of the study it was found that samples of alternative jet fuels blended with plant oil bio-additives are characterized by lower emission level comparing to conventional jet fuels. These alternative jet fuels may also provide reduction of total emissions levels. Thus it was concluded that application of alternative jet fuels containing plant oil bio-additives may contribute to improvement of environmental safety of modern air transport.

MUV: A Game to Encourage Sustainable Mobility Habits

Scipedia content — Wed, 03 Feb 2021 19:23:00 +0100

This working paper investigates the question of changing people mobility towards more sustainable habits involving them in an engaging gameplay. The work is performed within MUV H2020 research and innovation action. The game design, definition and features have been co-created through the involvement of different citizens and stakeholders in six European neighbourhoods. The paper discusses the game design as resulting from co-creation and co-design experiences with each neighbourhood communities involved in initial phases. The paper argues that the local co-design activities have influenced the game definition, together with the community engagement approach. The MUV gameplay approach results thus a demand-side measure able to encouraging people to sustainable mobility modes in the awareness of their potential role as agents of urban livability. The data collected by the players will be used to support a citizen-centric approach to facilitate equity and mobility justice in urban policies.

The Influence of Node Velocity and Traffic Congestion on The Performance of AODV in MANET

Scipedia content — Wed, 03 Feb 2021 19:13:08 +0100

BREAK-EVEN DISTANCE ESTIMATION BETWEEN COMBINED AND UNIMODAL ROAD FREIGHT TRANSPORT

Scipedia content — Wed, 03 Feb 2021 19:10:23 +0100

The purpose of this research is to examine the impact of distance on choosing between combined and unimodal road transport. In doing so, the break-even distances between the two modes are calculated. The calculation relies on a Monte Carlo simulation that takes account of a randomly generated shipper and receiver?s locations in two separated market areas, independently of a certain transport corridor. Methodically, the ideas and elements of the transport system analytical modelling found in the literature are used. The results confirm the importance of distance on the mode choice and show there is not only one but in fact many break-even distances between the two modes. They vary considerably depending on different travel plans, and shipper/receiver locations within market areas. Despite the inevitable assumptions made in such general analysis, the results reveal combined transport can provide a good alternative to unimodal road transport even over relatively very short distances if the drayage costs are not too high. We believe the research helps better understand competitiveness in the freight transport sector and may also be useful for policy- and other decision-makers seeking to improve their evaluation of the opportunities and competitiveness of combined transport. Nevertheless that could lead to a more sustainable transport system.

Towards Automated Machine Learning: Evaluation and Comparison of AutoML Approaches and Tools

Scipedia content — Wed, 03 Feb 2021 19:08:30 +0100

There has been considerable growth and interest in industrial applications of machine learning (ML) in recent years. ML engineers, as a consequence, are in high demand across the industry, yet improving the efficiency of ML engineers remains a fundamental challenge. Automated machine learning (AutoML) has emerged as a way to save time and effort on repetitive tasks in ML pipelines, such as data pre-processing, feature engineering, model selection, hyperparameter optimization, and prediction result analysis. In this paper, we investigate the current state of AutoML tools aiming to automate these tasks. We conduct various evaluations of the tools on many datasets, in different data segments, to examine their performance, and compare their advantages and disadvantages on different test cases.

Optimising the structure of a cascaded modular battery system for enhancing the performance of battery packs

Scipedia content — Wed, 03 Feb 2021 19:08:16 +0100

The overall performance of battery packs may be affected by imbalances between the series connected cells which is more likely in packs with high number of cells needed to provide a high voltage as needed for example in electric vehicles. In this case, the overall capacity and power capability of the pack are limited by the weakest cell in the stack which results in incomplete utilisation of the pack's capabilities. In traditional centralised battery systems (TCBS), this is addressed by implementing cell active/passive balancing circuitry/techniques which restore some of the pack's energy capability. This paper proposes the use of cascaded modular battery systems (CMBS) to remove the need for extra balancing circuitry and maximises the performance and reliability of a battery system containing unequal matched/aged cells. The analysis is assessing the CMBS overall system efficiency, reliability and weight compared to the TCBS for a design of a 300 V/3.6 kW battery system as a case study.

Social and economic impacts of Autonomous Shuttles for Collective Transport: an in- depth benchmark study

Scipedia content — Wed, 03 Feb 2021 19:07:39 +0100

International audience; Most of current managerial studies on Autonomous Vehicles (AVs) focus on future social and economic impacts of privately-owned AVs. In contrast, the present study aimed on carrying out an in-depth benchmark on successful experimentations with Autonomous Shuttles for Collective Transport (ASCTs), identifying the most relevant social and economic findings as well as understanding how such results may contribute to future projects and trials. The research was designed as an in-depth qualitative benchmark of exploratory and descriptive nature on three selected European projects with ASCTs: CityMobil2, GATEway, SHOJOA. Results mainly focused on the trials' social aspects (e.g., user acceptance, trust, willingness to use and, shuttles' interactions with mixed-traffic). Economic impacts were not widely disclosed and/or explored (results were mainly centered on users' willingness to pay and potential to reduce fares). Thereby, we advocate that economic aspects shall not be considered as "ceteris paribus" while measuring user acceptance. From the perspective of social sciences, the study sheds light into what is currently being evaluated on ASCTs' trials. Results are relevant for future ASCTs projects to focus on neglected aspects and also to improve upon the trials' successful results in a sense that, to date, no current studies were found aiming to understand and evaluate the social and economic impacts of ASCTs deployments.

Vision-Based Lane-Changing Behavior Detection Using Deep Residual Neural Network

Scipedia content — Wed, 03 Feb 2021 18:59:10 +0100

urate lane localization and lane change detection are crucial in advanced driver assistance systems and autonomous driving systems for safer and more efficient trajectory planning. Conventional localization devices such as Global Positioning System only provide road-level resolution for car navigation, which is incompetent to assist in lane-level decision making. The state of art technique for lane localization is to use Light Detection and Ranging sensors to correct the global localization error and achieve centimeter-level accuracy, but the real-time implementation and popularization for LiDAR is still limited by its computational burden and current cost. As a cost-effective alternative, vision-based lane change detection has been highly regarded for affordable autonomous vehicles to support lane-level localization. A deep learning-based computer vision system is developed to detect the lane change behavior using the images captured by a front-view camera mounted on the vehicle and data from the inertial measurement unit for highway driving. Testing results on real-world driving data have shown that the proposed method is robust with real-time working ability and could achieve around 87% lane change detection accuracy. Compared to the average human reaction to visual stimuli, the proposed computer vision system works 9 times faster, which makes it capable of helping make life-saving decisions in time.

Toolbox for Test Planning and Test Realization of Scenario-Based Field Tests for Automated and Connected Driving

Scipedia content — Wed, 03 Feb 2021 18:57:31 +0100

Current test and validation procedures for automated and connected driving functions use field tests on public roads primarily to identify unknown critical scenarios. These scenarios are then validated or varied within simulations or on closed proving grounds. In order to validate complex urban driving scenarios, this approach may need to be supplemented by the method of scenario-based field tests in real traffic environments. Scenario-based tests constitutes the methodical basis for an efficient and purposive test of automated and connected driving functions in public testbeds. This paper focuses on concepts for the design, planning and implementation of scenario-based tests of automated and connected driving functions under real traffic conditions. The developed toolbox will be explained using the example of the “Digital Testbed Dresden / Saxony" as part of the initiative “Synchrone Mobilität 2023”.

Integration of Regional and Asset Satellite Observations for Assessment of Infrastructure Resilience

Scipedia content — Wed, 03 Feb 2021 18:51:01 +0100

Non-invasive sensor network to map stationary bed heights and moving dunes along pipelines larger than NB150

Scipedia content — Wed, 03 Feb 2021 18:46:23 +0100

Open access paper presented at the 21st International Seminar on Paste and Thickened Tailings, 11-13 April 2018, Perth, Australi

Defining urban logistics profile zones in South American metropolis by combining functional and spatial clustering techniques

Scipedia content — Wed, 03 Feb 2021 18:42:02 +0100

This paper proposes a framework to define a zoning strategy taking into account both functional and spatial patterns. This partition allows further development of territorial intelligence analytics indicators, mainly in the context of urban logistics in developing countries. First, the main notions of territorial intelligence and analytics are proposed, as well as the needs of producing standard, transferable spatial and zoning data. Then, the main framework, based on functional and spatial clustering techniques, is presented. After that, the framework is illustrated via an application to the metropolitan area of Lima-Callao, Peru. Results show that functional elementary zones of same type mainly have a continuity, but some actions need to be taken in a small set of zones. Finally, main research and practice implications are addressed, showing a generic, replicable methodology based on open data.

Choosing the best available techniques of using the alternative engine fuels in automotive engineering

Scipedia content — Wed, 03 Feb 2021 18:40:25 +0100

ong"Purpose"/strong""strong":"/strong""strong" "/strong"The aim of our research work was to choose the best available technology of using the alternative engine fuels in vehicle and tractor technique use. "strong"Methodology"/strong""strong":"/strong" The methodology of multicriterial optimization was adopted for the purpose of the research. "strong"Results"/strong""strong":"/strong" There are given the results of calculating researches related to the choice of the best available techniques of the alternative engine fuels in vehicle and tractor technique use by the method of complex evaluation of fuel and power indexes of alternative fuels and engine, ecological safety and economic feasibility of vehicle exploitation. Fuel and power indexes of the fuels and of the engine are estimated by the criterion of adaptation, which is calculated by the method of hierarchies, ecological safety is evaluated taking into consideration the number of pollutant emissions with exhaust gases, their maximum permissible concentrations and safety class, economic feasibility of technique exploitation is estimated by the economic feasibility criterion which is calculated taking into account the economy of exploitation charges while using alternative fuels and placement of funds for technique re-equipment. The highest value of general criterion of the choice of suitable technique of fuel use which integrates the listed criteria, belongs to the technique of natural gas using in the gas engine re-equipped from the diesel one, petrol diesel fuel has the lowest value. "strong"The theoretical contribution"/strong""strong":"/strong" is The research findings have contributed to the development of a common methodology of estimating the factors of vehicles functioning on alternative fuels on criteria of technical suitability, environmental safety and economic efficiency of operation. "strong"Practical implications: "/strong"The proposed methodology allows to estimate the technique indexes while its functioning on different types of fuel by one general criterion, which simplifies a lot the choice of technique of rational type of fuel use.

Microservice Architectures for Advanced Driver Assistance Systems: A Case-Study

Scipedia content — Wed, 03 Feb 2021 18:29:44 +0100

The technological advancements of recent years have steadily increased the complexity of vehicle-internal software systems, and the ongoing development towards autonomous driving will further aggravate this situation. This is leading to a level of complexity that is pushing the limits of existing vehicle software architectures and system designs. By changing the software structure to a service-based architecture, companies in other domains successfully managed the rising complexity and created a more agile and future-oriented development process. This paper presents a case-study investigating the feasibility and possible effects of changing the software architecture for a complex driver assistance function to a microservice architecture. The complete procedure is described, starting with the description of the software-environment and the corresponding requirements, followed by the implementation, and the final testing. In addition, this paper provides a high-level evaluation of the microservice architecture for the automotive use-case. The results show that microservice architectures can reduce complexity and time-consuming process steps and makes the automotive software systems prepared for upcoming challenges as long as the principles of microservice architectures are carefully followed.

Design and Evaluation of a Tool to Support Air Traffic Control with 2D and 3D Visualizations

Scipedia content — Wed, 03 Feb 2021 18:29:16 +0100

traffic control officers (ATCOs) are specialized workers responsible to monitor and guide airplanes in their assigned airspace. Such a task is highly visual and mainly supported by 2D visualizations. In this paper, we designed and assessed an application for visualizing air traffic in both orthographic (2D) and perspective (3D) views. A user study was then performed to compare these two types of representations in terms of situation awareness, workload, performance, and user acceptance. Results show that the 3D view yielded both higher situation awareness and less workload than the 2D view condition. However, such a performance does not match the opinion of the ATCOs about the 3D representation.

Algorithm and Architecture for Path Metric Aided Bit-Flipping Decoding of Polar Codes

Scipedia content — Wed, 03 Feb 2021 18:24:37 +0100

Polar codes attract more and more attention of researchers in recent years, since its capacity achieving property. However, their error-correction performance under successive cancellation (SC) decoding is inferior to other modern channel codes at short or moderate blocklengths. SC-Flip (SCF) decoding algorithm shows higher performance than SC decoding by identifying possibly erroneous decisions made in initial SC decoding and flipping them in the sequential decoding attempts. However, it performs not well when there are more than one erroneous decisions in a codeword. In this paper, we propose a path metric aided bit-flipping decoding algorithm to identify and correct more errors efficiently. In this algorithm, the bit-flipping list is generated based on both log likelihood ratio (LLR) based path metric and bit-flipping metric. The path metric is used to verify the effectiveness of bit-flipping. In order to reduce the decoding latency and computational complexity, its corresponding pipeline architecture is designed. By applying these decoding algorithms and pipeline architecture, an improvement on error-correction performance can be got up to 0.25dB compared with SCF decoding at the frame error rate of $10^{-4}$, with low average decoding latency.

Comment: 6 pages, 6 figures, IEEE Wireless Communications and Networking Conference (2019 WCNC)

Modelling travel time uncertainty in urban networks based on floating taxi data

Scipedia content — Wed, 03 Feb 2021 18:24:13 +0100

"jats:p"The prediction of the uncertainty of route travel time predictions for all possible routes in an urban road network is of importance for example for logistics. Such predictions need to take the essential features of the data set as well as the underlying traffic dynamics into account.In this paper a large floating taxi data set is used in order to derive predictions of route travel time uncertainty based on link travel time uncertainty predictions. Prediction errors, that is actual travel times minus predicted travel times, are differentiated from model errors, that is measured travel times minus predicted travel times. These two errors are related, but not identical, as model errors contain measurement noise while the prediction errors do not. Detailed models for the variance of the link travel time prediction errors as well as the correlation between the model errors for different links are derived. The models are validated in depth using two different validation data sets.Estimates for the variance of prediction errors are obtained. The standardized model error distributions show a remarkable stability, such that modelling the variance appears to be sufficient for quantifying the uncertainty of the model errors.Furthermore we show that the model errors for adjacent links are highly correlated but correlations fade with increasing distance. Additionally usage of the road network plays a role with high correlation for links along common routes and low correlations for links along seldom used routes. We assume identical features for the prediction errors which is partly validated based on additional data.The paper provides a way to estimate the complete distribution of route travel time prediction errors for any given route in the street network.

Document type: Article

On-Board System Concept for Drones in the European U-space

Scipedia content — Wed, 03 Feb 2021 18:23:29 +0100

This paper describes the findings of the AIRPASS (Advanced Integrated RPAS Avionics Safety Suite) project. The project aims to develop an on-board system concept to be used for drones that intend to operate in the European U-space. The Single European Sky ATM Research Joint Undertaking (SESAR JU) drafted the U-space blueprint to describe a set of services that shall enable the safe, efficient and secure integration of a large number of drones into non-segregated airspace, especially for Very Low Level (VLL) operations). Services are not limited to drones but are also intended to support manned flights in VLL as well as drones carrying passengers. The U-space concept also supports the EASA classes of operation, covering open, specific and certified.

Variable Record Table: A Run-time Solution for Mitigating Buffer Overflow Attack

Scipedia content — Wed, 03 Feb 2021 18:22:59 +0100

We present a novel approach to mitigate buffer overflow attack using Variable Record Table (VRT). Dedicated memory space is used to automatically record base and bound information of variables extracted during runtime. We instrument frame pointer and function(s) related registers to decode variable memory space in stack and heap. We have modified Simplescalar/PISA simulator to extract variables space of six (6) benchmark suites from MiBench. We have tested 290 small C programs (MIT corpus suite) having 22 different buffer overflow vulnerabilities in stack and heap. Experimental results show that our approach can detect buffer overflow attack with zero instruction overhead with the memory space requirement up to 13Kb to maintain VRT for a program with 324 variables.

Comment: Accepted for publication in MWSCAS2019

The Deployment of Low Carbon Technologies in Modern Distribution Networks

Scipedia content — Wed, 03 Feb 2021 18:14:58 +0100

Most modern distribution networks are experiencing an energy evolution to satisfy the need of sustainable, secure and clean sources of energy. New technologies are driving this transition, including photovoltaics, energy storage systems and electric vehicles. The integration and deployment of these technologies in the distribution network is having a positive impact on system efficiency. However, their behaviour in the power system introduces technical challenges such as reverse power flow, voltage variation and other power quality issues. The integration of these technologies requires careful planning and operation to maintain or improve system stability and reliability. This work reviews the challenges imposed by deploying these low carbon technologies on low voltage systems. The main contributions of this study can be summarized as follows: Firstly, it generally reviews the solution methodologies and power management strategies applied in the distribution network in the presence of low carbon technologies. Secondly, it outlines some important facts and statistics about their deployment. Finally, it discusses the energy evolution of the Northern Ireland network highlighting challenges and solutions and providing recommendations for future research.

Remanufacturing of electric vehicles: Challenges in production management

Scipedia content — Wed, 03 Feb 2021 18:14:33 +0100

Due to the conceptual degrees of freedom in their product structure, electric vehicles offer high potential for remanufacturing-oriented product design. This potential is, however, not realized yet. Remanufacturing as one fundamental element of a circular economy is characterized by specific challenges caused by uncertain information about the condition and the timing of the returning product. By means of a case study within the remanufacturing industry, the effects of uncertainties on remanufacturing operations are examined and different approaches within the field of production management to meet these specific challenges are pointed out. Based on the result of the case study a production management framework outlining fields of action to deal with remanufacturing specific uncertainties is developed. In this context, the requirements for remanufacturing of electric vehicles are derived by analyzing similarities from other industry sectors. In conclusion, a solution approach for the implementation for electric vehicles is presented for strategic, tactical and operational procurement logistics and remanufacturing operations.

Document type: Article

Sound-based Transportation Mode Recognition with Smartphones

Scipedia content — Wed, 03 Feb 2021 18:09:17 +0100

Smartphone-based identification of the mode of transportation of the user is important for context-aware services. We investigate the feasibility of recognizing the 8 most common modes of locomotion and transportation from the sound recorded by a smartphone carried by the user. We propose a convolutional neural network based recognition pipeline, which operates on the short- time Fourier transform (STFT) spectrogram of the sound in the log domain. Experiment with the Sussex-Huawei locomotion- transportation (SHL) dataset on 366 hours of data shows promising results where the proposed pipeline can recognize the activities Still, Walk, Run, Bike, Car, Bus, Train and Subway with a global accuracy of 86.6%, which is 23% higher than classical machine learning pipelines. It is shown that sound is particularly useful for distinguishing between various vehicle activities (e.g. Car vs Bus, Train vs Subway). This discriminablity is complementary to the widely used motion sensors, which are poor at distinguish between rail and road transport.

Trends and Opportunities for Traffic Engineering Paradigms Across Mobile Cellular Network Generations

Scipedia content — Wed, 03 Feb 2021 18:09:03 +0100

Part 4: Local Technical Papers; International audience; Traffic engineering is at the heart of telecommunications engineering. In telecommunication engineering, we have recently experienced a revolution in the form of mobile cellular network generations. History shows a close relationship between the advancements in both telecommunications networks and their corresponding engineering methods. This survey employed qualitative document analysis to chronologically explore the evolution of, and interrelationships between traffic engineering and the mobile cellular networks from 1990s todate. It is evidently a case of the causality dilemma on which of the two influences the other. Nevertheless, we are currently at the right point in time to make giant leaps in both traffic engineering methods and network technology revolution. This study points out the opportunities that the current state of affairs avails to research in these fields.

Document type: Conference object

Experimental Investigation of the Effect of Geogrid Reinforced Backfill Compaction on Buried Pipelines Response

Scipedia content — Wed, 03 Feb 2021 18:04:11 +0100

Text/Conference Paper

Scipedia content — Wed, 03 Feb 2021 18:02:33 +0100

Die derzeitigen Entwicklungen und Herausforderungen in Wirtschaft und Gesellschaft im Rahmen von Digitalisierung und Digitaler Transformation stellen enorme Anforderungen an die Informatik und Wirtschaftsinformatik. Nur durch die aktiv getriebene Weiterentwicklung und den gezielten Einsatz von IT-Technologien, -verfahren und -methoden können wir es schaffen, uns den Herausforderungen unserer Zeit erfolgreich zu stellen und nachhaltige, zielkonforme, wirtschaftliche Lösungen zu entwickeln. Beispieldomänen hierfür sind das agile Management (lokal und global) bei sich ändernden politischen und wirtschaftlichen Randbedingungen (z.B. Brexit), das flexible Steuern und Überwachen großer Verkehrs- und -Versorgungsnetze, das Schaffen und Betreiben agiler effizienter Unternehmensverbünde und die Energiewende. Wesentliche Aspekte hierfür sind „agilitätsbegünstigende“ und transparente Modellierung sowie die Optimierung von Prozessen und die Planung und Steuerung von effizienten und nachhaltigen Ressourcennutzungen. Der Workshop adressiert Aspekte der transparenten Modellierung, der Optimierung und der Simulation hochkomplexer Systeme im o.g. Sinne. Im Vergleich zu seinen Vorgängerworkshops fällt der MOC 2019, bezogen auf den vorgesehenen zeitlichen Umfang, gering aus. Neben der Beitragspräsentation liegen die Schwerpunkte auf kooperativem Brainstorming und Diskussion der thematisierten Aspekte. Hierfür sind impulsgebende Slots zu den Themengebieten „Shapley-Wert“ sowie „Deklarativität und KI“ vorgesehen. Generell soll der Workshop Fachleuten, Anwendern und Interessierten die Möglichkeit zum Austausch und zur nutzbringenden Diskussion von Ideen, Ansätzen, Verfahren und Problemlösungen geben, wobei hierbei idealer Weise Grundlagen für zukünftige, im o.g. Sinne zielführende, Forschungsarbeiten entstehen sollen.

An Advanced Simulation Framework of an Integrated Vehicle-Powertrain Eco-Operation System for Electric Buses

Scipedia content — Wed, 03 Feb 2021 17:56:17 +0100

vities of transit buses traveling along arterial roads and city streets consist of frequent stops and idling events at many predictable occasions, e.g., loading/unloading passengers at bus stops, approaching traffic signals or stop signs, and going through recurrent traffic congestion, etc. Besides designing transit buses with electric powertrain systems that can save a noticeable amount of energy thanks to regenerative breaking, this urban traffic environment also unfolds a number of opportunities to further improve their energy efficiency via vehicle connectivity and autonomy. Therefore, this paper proposes a complete and novel simulation framework of integrated vehicle/powertrain eco-operation system for electric buses (Eco-bus) by co-optimizing the vehicle dynamics and powertrain (VD&PT) controls. A comprehensive evaluation of the proposed system on mobility benefits and energy savings has been conducted over various traffic conditions. Simulation results are presented to showcase the superiority of the proposed simulation framework of the Eco-bus compared to the conventional bus, particularly in terms of mobility and energy efficiency aspects.

Cybersecurity Aspects of 5G Connectivity in Smart Cities Ecosystem via Connected and Autonomous Vehicles Use Cases

Scipedia content — Wed, 03 Feb 2021 17:51:42 +0100

This work presents the necessity of the implementation of mitigation techniques to counter the cybersecurity issues and threats that arise from the fifth generation (5G) embodiment in a smart city ecosystem. During the past few years, the popularity and growth of cellular technology has led the 5G networks to be considered as the emerging domain of future’s communication architecture. Moreover, the connected and autonomous vehicles constitute an essential part of smart cities infrastructure, providing the answer for the city’s mobility demands. With human safety being at stake, the security assurance is of the utmost importance. The requirement of ensuring a safe transportation system with complete trust to the smart city ecosystem is sufficiently described, while proper counter-measures within the scope of 5G connectivity are proposed. This work was supported by the European Union's Horizon 2020 Research and Innovation Programme Autonomous Vehicles to Evolve to a New Urban Experience (AVENUE) under Grant Agreement No 769033.

Characteristics and thermomechanical modes of aluminum alloys hot deformation

Scipedia content — Wed, 03 Feb 2021 17:50:08 +0100

The widespread use of aluminum alloys is determined by their technical, physical and mechanical properties. The purpose of this paper is to present the characteristics of thermomechanical models of aluminum alloys hot deformation and to explain how they impact the properties of the these alloys. The application of the workpiece rolling process under the conditions of isothermal deformation makes it possible to maximize the effect of ductility. The deformation of hot workpieces is done by the tool heated to the same temperature (or close to them). Such a scheme of hot deformation will reduce the effort by increasing the ductility of the treated metal which occurs due to the full course of stabilizing processes. Uniform deformation of the workpiece provides a good and comprehensive reconstruction of the structure, in the absence of complicated deformation zones and local overheating. And, as a result, it reduces the dispersion of properties in the workpiece volume. It was established that workpieces rolling in conditions of isothermal deformation are reduced the of metal pressure on a roll in 1.8 times or even more.

Analysis on the Influencing Factors of the Development of Air Transport Industry in China

Scipedia content — Wed, 03 Feb 2021 17:45:58 +0100

JOURNAL PAPERS Year 2 (5/2018 to 10/2018) Part 2

Scipedia content — Wed, 03 Feb 2021 17:44:58 +0100

Year 2 (5/2018 to 10/2018) Journal Papers part 2 from the University Transportation Center for Underground Transportation Infrastructure (UTC-UTI).

Air Transport in Chechen Republic: Retrospective, Condition and Development Potential

Scipedia content — Wed, 03 Feb 2021 17:41:44 +0100

An assessment of Voluntary Travel Behaviour Change delivery in England as an alternative to highway construction

Scipedia content — Wed, 03 Feb 2021 17:41:09 +0100

There is a growing body of international evidence available that shows highway construction fails to solve issues of congestion and improvements to the local economy. There is also evidence that due to changes of land use and expectations of being able to travel from the land opened for development that traffic is induced to the highway network. Alternative methods of managing travel demand; such has Voluntary Travel Behaviour Change (VTBC) initiatives have been delivered internationally. A significant VTBC scheme, called the Local Sustainable Transport Fund (LSTF), was delivered in the United Kingdom between 2011 and 2015. This paper focuses on the people who delivered these initiatives, rather than the individuals required to change their behaviour. This is to understand how transport planners’ views influence the type of VTBC initiatives that were delivered. The study included a survey of 69 bid managers for LSTF projects and interviews with 17 council officers. The survey found that 80% transport planning officers understood the concept of induced traffic compared to just 10% of the wider population. It was also evident that the sample group was a homogenous group, where their views on issues such as climate change, congestion and the factors that influence how we travel were remarkably similar. The findings show that despite the evidence that highway construction does not provide a solution to travel demand, the decisions about which schemes are funded remain with non-transport experts, such as government ministers and local politicians, and this invariably leads to highway ‘solutions’ being chosen which limit the potential success of any VTBC initiative to create long-term change to travel behaviour.

Document type: Article

Real-time ride-sharing systems performance considering network congestion

Scipedia content — Wed, 03 Feb 2021 17:40:18 +0100

hEART 2019, 8th Symposium of the European Association for Research in Transportation, Budapest, HONGRIE, 04-/09/2019 - 06/09/2019; In recent years, intelligent transportation systems made it possible for operators to adapt in real-time the transportation supply to travel demand via new mobility services. Among these services, ride-sharing is becoming popular. The dynamic ride-sharing problem involves two sub-problems: (1) How to serve the upcoming trips (Optimal fleet management) and (2) How to accurately predict the travel times to determine vehicles availability and pick up/drop off times. In this paper, we express the optimal fleet management problem as a constrained multi objective integer linear programming. Our aim is to find the global optimal solution for the ride-sharing problem without uncertainty in demand to have a vision of these services performance in optimal situation. Then we compare the results and experiments with the exact optimal condition. We have designed an algorithm to find the exact solution for matching problem based on the branch and bound algorithm. To solve the second sub-problem, we define two different models to assess the impact of traffic conditions on the dynamic ride-sharing system performance for large-scale problems.

A global map of Amenities: Public Goods, Ethnic Divisions and Decentralization

Scipedia content — Wed, 03 Feb 2021 17:37:04 +0100

I analyze the effects of ethnic divisions on the provision of public goods. Using OpenStreetMap data, I construct a new global dataset of locations of public amenities, such as schools, hospital and libraries. I allow for the possibility that the data may be systematically incomplete using two new proxies for mapping completeness. I provide strong evidence that more autonomous subnational regions with a high degree of ethnic fractionalization provide significantly fewer productive public goods. Therefore, my findings indicate that decentralization can lead to a failure in the provision of local public goods when it increases ethnical fractionalization among the policy makers responsible for collectively supplying public goods.

Driver Distraction Identification with an Ensemble of Convolutional Neural Networks

Scipedia content — Wed, 03 Feb 2021 17:32:43 +0100

The World Health Organization (WHO) reported 1.25 million deaths yearly due to road traffic accidents worldwide and the number has been continuously increasing over the last few years. Nearly fifth of these accidents are caused by distracted drivers. Existing work of distracted driver detection is concerned with a small set of distractions (mostly, cell phone usage). Unreliable ad-hoc methods are often used.In this paper, we present the first publicly available dataset for driver distraction identification with more distraction postures than existing alternatives. In addition, we propose a reliable deep learning-based solution that achieves a 90% accuracy. The system consists of a genetically-weighted ensemble of convolutional neural networks, we show that a weighted ensemble of classifiers using a genetic algorithm yields in a better classification confidence. We also study the effect of different visual elements in distraction detection by means of face and hand localizations, and skin segmentation. Finally, we present a thinned version of our ensemble that could achieve 84.64% classification accuracy and operate in a real-time environment.

Comment: arXiv admin note: substantial text overlap with arXiv:1706.09498

Document type: Article

LACI: Low-effort Automatic Calibration of Infrastructure Sensors

Scipedia content — Wed, 03 Feb 2021 17:29:38 +0100

Sensor calibration usually is a time consuming yet important task. While classical approaches are sensor-specific and often need calibration targets as well as a widely overlapping field of view (FOV), within this work, a cooperative intelligent vehicle is used as callibration target. The vehicleis detected in the sensor frame and then matched with the information received from the cooperative awareness messagessend by the coperative intelligent vehicle. The presented algorithm is fully automated as well as sensor-independent, relying only on a very common set of assumptions. Due to the direct registration on the world frame, no overlapping FOV is necessary. The algorithm is evaluated through experiment for four laserscanners as well as one pair of stereo cameras showing a repetition error within the measurement uncertainty of the sensors. A plausibility check rules out systematic errors that might not have been covered by evaluating the repetition error.

Comment: 6 pages, published at ITSC 2019

Visual assessment deterioration analysis of runways at Sultan Aji Muhammad Sulaiman Sepinggan Airport Balikpapan

Scipedia content — Wed, 03 Feb 2021 17:22:55 +0100

Sultan Aji Muhammad Sulaiman Sepinggan (SAMS) Airport has an important role as the gateway of economic activity in Balikpapan, East Kalimantan. Elements of the airport consist of runways, taxiway, apron and the terminal building of departure and arrival. The runway has an important role as a key element in airport infrastructure, this is related to aircraft and passenger safety in air traffic at SAMS Airport, which is currently one of the best airports in Indonesia that meets the International Standard qualification. The purpose of this study is to perform visual assessment of runway deterioration at SAMS Airport using PCI (Pavement Condition Index) method, to know the factors affecting runway deterioration and the effective distress treatment to overcome deterioration at a runway. The visual assessment data are collected from PT. Angkasa Pura I (Persero) Sepinggan, by measuring the types and area of deterioration occurring on the runway during 1-month period (in September 2018), then PCI is analyzed by using ASTM D 5340 – 98. The results show that the PCI value is 80.4 which means the rating is excellent. The most common typical distress occurred at Threshold Runway 25 section 1 with the type of distress is block cracking which mainly caused by asphalt concrete shrinkage and daily temperature condition resulting in stress or strain series, another type is depression initially caused by the settlement from the soil foundation or construction process. Since PCI shows excellent state, the distress repair treatment to be performed is surface repair or routine maintenance with partial mill and overlay method.