Scipedia: Documents published in 2017

Study on energy saving of subway station based on orthogonal experimental method

Scipedia content — Tue, 02 Feb 2021 03:00:23 +0100

With the characteristics of quick, efficient and large amount transport, the subway has become an important way to solve urban traffic congestion. As the subway environment will follow the change of external environment factors such as temperature and load of personnel changes, three-dimensional numerical simulations study is conducted by using CFD software for air distribution of subway platform. The influence of different loads (the supply air temperature and velocity of air condition, personnel load, heat flux of the wall) on the subway platform flow field are also analysed. The orthogonal experiment method is applied to the numerical simulation analysis for human comfort under different parameters. Based on those results, the functional relationship between human comfort and the boundary conditions of the platform is produced by multiple linear regression fitting method, the order of major boundary conditions which affect human comfort is obtained. The above study provides a theoretical basis for the ...

Thermal segregation of asphalt material in road repair

Scipedia content — Tue, 02 Feb 2021 02:58:48 +0100

This paper presents results from a field study of asphaltic pavement patching operations performed by three different contractors working in a total of ten sites. It forms part of an ongoing research programme towards improving the performance of pothole repairs. Thermal imaging technology was used to record temperatures of the patching material throughout the entire exercise, from the stage of material collection, through transportation to repair site, patch forming, and compaction. Practical complications occurring during patch repairs were also identified. It was found that depending on the weather conditions, duration of the travel and poor insulation of the transported hot asphalt mix, its temperature can drop as high as 116.6 °C over the period that the reinstatement team travel to the site and prepare the patch. This impacting is on the durability and performance of the executed repairs. Cold spots on the asphalt mat and temperature differentials between the new hot-fill asphalt mix and existing pavement were also identified as poorly compacted areas that were prone to premature failure. For example, over the five-minute period, the temperature at one point reduced by 33% whereas the temperatures of nearby areas decreased by 65% and 71%. A return visit to the repair sites, three months later, revealed that locations where thermal segregation was noted, during the patching operation, had failed prematurely.

Document type: Conference object

An Improved Distribution Policy with a Maintenance Aspect for an Urban Logistic Problem

Scipedia content — Tue, 02 Feb 2021 02:48:00 +0100

In this paper, we present an improved distribution plan supporting an urban distribution center (UDC) to solve the last mile problem of urban freight. This is motivated by the need of UDCs to satisfy daily demand in time under a high service level in allocated urban areas. Moreover, these demands could not be satisfied in individual cases because the delivery rate can be less than daily demand and/or affected by random failure or maintenance actions of vehicles. The scope of our work is to focus on a UDC, which needs to satisfy demands in a finite horizon. To that end, we consider a distribution policy on two sequential plans, a distribution plan correlated to a maintenance plan using a subcontracting strategy with several potential urban distribution centers (UDCs) and performing preventive maintenance to ensure deliveries for their allocated urban area. The choice of subcontractor will depend on distance, environmental and availability criteria. In doing so, we define a mathematical model for searching the best distribution and maintenance plans using a subcontracting strategy. Moreover, we consider delay for the next periods with an expensive penalty. Finally, we present a numerical example illustrating the benefits of our approach.

Document type: Article

The Liquid Ammonia Tanker Road Transport Safety Management Based on Fault-Tree-Analysis Method

Scipedia content — Tue, 02 Feb 2021 02:44:29 +0100

Systems engineering approach to design and modelling of smart cities

Scipedia content — Tue, 02 Feb 2021 02:44:12 +0100

city is a very complex area with complex governing bodies and a number of decision makers. More often, cities are engines of economic development and are attractive places for people seeking employment and better quality of living [1]. As a consequence, cities are now facing a growing urban population which imposes stresses on urban quality of life and the environment. Among the major challenges faced by cities around the world, urban population growth is at the forefront as it is expected that future cities will be home for more than 70% of the global population by 2050. Other associated challenges include traffic congestion, environmental degradation, security, level of quality of public services, and effective resources management. To ensure sustainable development of cities with such a boom of urbanisation, cities around the world are embracing technology and adopting smart cities concept following the recorded development of information and communication technologies and internet of things. However, the literature [2] shows that the concept of smart cities is not being approached efficiently. A smart city is a system of subsystems and should be approached as a whole as opposed to infusing technology into subsystems one by one. To achieve this, there is a requirement of a standard platform to integrate all the subsystems of a smart city system. This work proposes a holistic model which integrates all the subsystems of a smart city system. The proposed model is based on systems engineering approach and Systems Engineering Modelling Language (SysML) is adapted as a potential modelling language. It is a general purpose visual modelling language for Systems Engineering applications and for complex systems such as smart cities and can handle better complexity and challenges such as documentation, communication, and management.

A Finite State Machine modeling language and the associated tools allowing fast prototyping for FPGA devices

Scipedia content — Tue, 02 Feb 2021 02:40:57 +0100

International audience; The VHDL hardware description language is commonly used to describe Finite State Machine(FSM) models to be implemented on Field Programmable Gate Array(FPGA) devices. However, its versatility permits to describe behaviors that deviate from a true FSM leading to systems that are complex to prove, to document and to maintain. The purpose of this work is to propose a language and the associated tools to create FSMs through a dedicated and intuitive textual description. This language is inspired by the dot language used in Graphviz, a tool to define graphs, and adds all the necessary elements required to describe complex FSM models (using for instance memorized or non memorized actions and actions on states or transitions). Moreover some additional elements are proposed to enrich the standard FSM model such as the genericity that permits to define simultaneously multiple states, transitions or actions using a generative description. A multi-platform open source JAVA program named FSMPro-cess [1] is introduced. Based on the ANTLR parser generator, it achieves the automatic generation of all the required .vhdl files (component, package, instantiation example and testbench) and a .dot file that is used to generate an always up-to-date graphical representation of the model (hence its documentation). This tool also supports simple model checking and integration of additional VHDL code. It can be used conjointly with version control systems and is coupled with the open source GHDL simulator to allow fast prototyping. It can be used either with its Graphical User Interface either as a command line compiler for integration in makefiles.

P4-based multi-layer traffic engineering encompassing cyber security

Scipedia content — Tue, 02 Feb 2021 02:39:08 +0100

The design and experimental validation of effective P4-based solutions for dynamic optical bypass, traffic offload and cyber security without involving SDN controller are proposed. P4 switch latency scalability versus installed flow entry size is demonstrated.

Integrated Zoning For Aquaculture And Biodiversity Using A Spatial Decision-Support Tool

Scipedia content — Tue, 02 Feb 2021 02:33:58 +0100

Spatial decision-support tools can guide decision-makers towards knowledge-based spatial planning. Their application for multiple-objective zoning is beneficial for supporting the on-going Maritime Spatial Planning (MSP) process, in particular in areas of high density of uses like the Adriatic-Ionian region (AIR)."/p" "p"In this work, we give contribution to the sustainable development of the aquaculture, as one of the main maritime activities for sustainable Blue Growth in the AIR. Aquaculture expansion should occur alongside the protection of biodiversity and the conservation of sites where aquaculture and its synergic uses can coexist. Planning for these objectives independently from one another has been shown to produce inefficiencies in costs, area, and conflicts across sectors. The objective of this research is to operationalize multi-objective zoning for aquaculture expansion and biodiversity protection (seabed habitats, marine mammals, seabirds and turtles species distribution, nursery and spawning areas of commercially important fish species). The area of analyses is the coastal area of the Emilia Romagna Region (Italian Northern Adriatic Sea). This area is the main producer of mussels in Italy and it is currently intensively crowded by several maritime uses, which are expected to grow over next years resulting in increase of conflicts and pressures on sensitive environments (Natura 2000 sites; Biological Protection zone)."/p" "p"The decision support tool Marxan and its advanced version Marxan with Zones were applied to develop planning scenarios. Firstly, we prioritise biodiversity conservation, through Marxan, while minimizing conflicts with other anthropic uses. Secondly, we carry out an aquaculture suitability analysis using a multicriteria evaluation approach based on environmental, biological and socio-economic conditions. Next, we simultaneously prioritize both aquaculture and biodiversity, through Marxan with Zones, while minimizing impacts on seven other industries operating in the Emilia Romagna Region."/p" "p"We discuss an integrated zoning plan that meets targets for multiple objectives, and which adheres to several constraints regarding the location of aquaculture farms offshore in order to both allow the use of bigger technologies for mussel catch and minimize the impacts on coastal environments (pollution impact, visual impact)."/p" "p"Our analysis can guide multiple stakeholders and decision-makers towards cost-efficient solutions that are scientifically based, thus contributing to the marine spatial planning process and sustainable growth in the Adriatic-Ionian region.

An analysis of the impact of larger aircraft (A-380) on flight frequency

Scipedia content — Tue, 02 Feb 2021 02:32:57 +0100

International audience; Innovations in the airline industry can have a significant impact on the behavior of air transport stakeholders: airline companies, airports and passengers. In this paper, we consider the introduction of a double-deck plane, the A-380, which is currently the largest aircraft available. Due to its size, it is able to carry at once approximately twice as many passengers as any other medium-sized aircraft. When associated with a reduction in flight frequencies , the operation of such aircraft is expected to lower the environmental impact. However, flight frequency depends on factors others than the aircraft size, such as airport fees, demand and strategic decisions of companies to maximize their profits under competition. Using a monthly panel data set on airlines' supply over 10 years, on 118 routes, we test if the use of the A-380 impacts airlines' flight frequency at a route-level. Results suggest that heavy use of the A-380 leads airlines to reduce their own flight frequency. We also find that when facing the introduction of the A-380 on a route, airlines will tend to react by increasing their own flight frequency.

New Journal of Physics

Scipedia content — Tue, 02 Feb 2021 02:29:14 +0100

Contrary to traditional thinking and driver intuition, here we show that there is no benefit to ground vehicles increasing their packing density at stoppages. By systematically controlling the packing density of vehicles queued at a traffic light on a Smart Road, drone footage revealed that the benefit of an initial increase in displacement for close-packed vehicles is completely offset by the lag time inherent to changing back into a ‘liquid phase’ when flowresumes. This lag is analogous to the thermodynamic concept of the latent heat of fusion, as the ‘temperature’ (kinetic energy) of the vehicles cannot increase until the traffic ‘melts’ into the liquid phase.These findings suggest that in situations where gridlock is not an issue, drivers should not decrease their spacing during stoppages in order to lessen the likelihood of collisions with no loss in flowefficiency. In contrast, motion capture experiments of a line of people walking from rest showed higher flow efficiency with increased packing densities, indicating that the importance of latent heat becomes trivial for slower moving systems. Department of Biomedical Engineering and Mechanics at Virginia Tech Institute for Creativity, Arts, and Technology

Document type: Article

The Current Problem of Traffic Congestion on Highways

Scipedia content — Tue, 02 Feb 2021 02:25:03 +0100

Joint Learning from Earth Observation and OpenStreetMap Data to Get Faster Better Semantic Maps

Scipedia content — Tue, 02 Feb 2021 02:22:14 +0100

International audience; In this work, we investigate the use of OpenStreetMap data for semantic labeling of Earth Observation images. Deep neural networks have been used in the past for remote sensing data classification from various sensors, including multispectral, hyperspectral, SAR and LiDAR data. While OpenStreetMap has already been used as ground truth data for training such networks, this abundant data source remains rarely exploited as an input information layer. In this paper, we study different use cases and deep network architectures to leverage OpenStreetMap data for semantic labeling of aerial and satellite images. Especially , we look into fusion based architectures and coarse-to-fine segmentation to include the OpenStreetMap layer into multispectral-based deep fully convolutional networks. We illustrate how these methods can be successfully used on two public datasets: ISPRS Potsdam and DFC2017. We show that OpenStreetMap data can efficiently be integrated into the vision-based deep learning models and that it significantly improves both the accuracy performance and the convergence speed of the networks.

A novel visual pipework inspection system

Scipedia content — Tue, 02 Feb 2021 02:18:20 +0100

The interior visual inspection of pipelines in the nuclear industry is a safety critical activity conducted during outages to ensure the continued safe and reliable operation of plant. Typically, the video output by a manually deployed probe is viewed by an operator looking to identify and localise surface defects such as corrosion, erosion and pitting. However, it is very challenging to estimate the nature and extent of defects by viewing a large structure through a relatively small field of view. This work describes a new visual inspection system employing photogrammetry using a fisheye camera and a structured light system to map the internal geometry of pipelines by generating a photorealistic, geometrically accurate surface model. The error of the system output was evaluated through comparison to a ground truth laser scan (ATOS GOM Triple Scan) of a nuclear grade split pipe sample (stainless steel 304L, 80mm internal diameter) containing defects representative of the application – the error was found to be submillimetre across the sample.

Traffic avoidance and separation system

Scipedia content — Tue, 02 Feb 2021 02:12:50 +0100

ft need to be separated from other aircraft by either a minimum vertical distance of 1000ft or by a minimum horizontal distance of 5NM to avoid mid-air collisions. Traffic Alert and Collision Avoidance System (TCAS) work well as a tactical safety backups to avoid collision, but cannot perform separation assurance. This paper presents the design aspects of system that would predict separation infringement and provide flight crew with necessary guidance for maintaining separation. This paper discusses formulation of system function based on ADS-B, mathematical models, simulation and results. A system model has been implemented in MATLAB and various encounters with different speed ratios at various conflict angles has been fed as input to system model with a goal of avoidance and recovery to original waypoint. Both Heading and Speed maneuvers are evaluated and results are presented. The required strength of resolution maneuver as a function of conflict geometry is studied and automatic maneuver selection function is implemented in system model and maneuver selection function is evaluated with discussion of results.

Driver's Behavior and Workload Assessment for New In-Vehicle Technologies Design

Scipedia content — Tue, 02 Feb 2021 02:08:51 +0100

Innovative technology can induce improvement in road safety, as long as its acceptability and its adequacy are checked, taking into account the diversified driver’s population needs and functional abilities through a Human Centred Design process. Relevant methodology has to be developed in this purpose. Evaluation of the driver’s mental workload is an important parameter, complementary to objective ones such as control of the vehicle and driver’s visual strategies. This paper describes experiments conducted in the framework of the European project AIDE aiming at validating the DALI (Driving Activity Load Index), a tool set up to allow evaluation of mental workload while using in-vehicle systems; the main results and conclusion from this approach are presented.

Traffic Flow Prediction Based on Combined Model of ARIMA and RBF Neural Network

Scipedia content — Tue, 02 Feb 2021 02:08:32 +0100

Motivating urban cycling through a blockchain-based financial incentives system

Scipedia content — Tue, 02 Feb 2021 02:01:12 +0100

cities become increasingly dense, they must turn to novel technologies and frameworks to address the mobility challenges that will arise. 50% of trips in the U.S. are less than 3 miles, and could be replaced by a more sustainable and space-efficient mode of transportation, such as bicycling, if effective policies and incentives were implemented. This abstract presents a financial incentives system to increase the prevalence of urban cycling. The blockchain-based system allows cyclists to receive financial compensation from organizations, such as city governments or local businesses, that would like to sponsor cyclists. Using bicycle-powered sensors, cyclists collect and redeem their activity data through smart contracts stored and executed on an Ethereum blockchain. The use of blockchain technology makes transactions secure, trustworthy, and timely. This project envisions expanding this data platform to include additional bicycle-based sensors that cyclists use to collect and sell data, monetizing their commuting habits, and building a scalable and stable solution for encouraging sustainable transportation in cities.

Using a Structural Root System Model to Evaluate and Improve the Accuracy of Root Image Analysis Pipelines

Scipedia content — Tue, 02 Feb 2021 01:58:57 +0100

Root system analysis is a complex task, often performed using fully automated image analysis pipelines. However, these pipelines are usually evaluated with a limited number of ground-truth root images, most likely of limited size and complexity. We have used a root model, ArchiSimple to create a large and diverse library of ground-truth root system images (10.000). This library was used to evaluate the accuracy and usefulness of several image descriptors classicaly used in root image analysis pipelines. Our analysis highlighted that the accuracy of the different metrics is strongly linked to the type of root system analyzed (e.g. dicot or monocot) as well as their size and complexity. Metrics that have been shown to be accurate for small dicot root systems might fail for large dicots root systems or small monocot root systems. Our study also demonstrated that the usefulness of the different metrics when trying to discriminate genotypes or experimental conditions may vary. Overall, our analysis is a call to caution when automatically analyzing root images. If a thorough calibration is not performed on the dataset of interest, unexpected errors might arise, especially for large and complex root images. To facilitate such calibration, both the image library and the different codes used in the study have been made available to the community.

Document type: Preprint

On the limits of machine learning-based test: a calibrated mixed-signal system case study

Scipedia content — Tue, 02 Feb 2021 01:57:58 +0100

International audience; Testing analog, mixed-signal and RF circuits rep- resents the main cost component for testing complex SoCs. A promising solution to alleviate this cost is the machine learning- based test strategy. These test techniques are an indirect test approach that replaces costly specification measurements by simpler signatures. Machine learning algorithms are used to map these signatures to the performance parameters. Although this approach has a number of undoubtable advantages, it also opens new issues that have to be addressed before it can be widely adopted by the industry. In this paper we present a machine learning-based test for a complex mixed-signal system –i.e. a state-of-the-art pipeline ADC– that includes digital calibration. This paper shows how the introduction of digital calibration for the ADC has a serious impact in the proposed test as calibration completely decorrelates signatures from the target specification in the presence of local mismatch.

Heavy-Hitter Detection Entirely in the Data Plane

Scipedia content — Tue, 02 Feb 2021 01:57:12 +0100

Identifying the "heavy hitter" flows or flows with large traffic volumes in the data plane is important for several applications e.g., flow-size aware routing, DoS detection, and traffic engineering. However, measurement in the data plane is constrained by the need for line-rate processing (at 10-100Gb/s) and limited memory in switching hardware. We propose HashPipe, a heavy hitter detection algorithm using emerging programmable data planes. HashPipe implements a pipeline of hash tables which retain counters for heavy flows while evicting lighter flows over time. We prototype HashPipe in P4 and evaluate it with packet traces from an ISP backbone link and a data center. On the ISP trace (which contains over 400,000 flows), we find that HashPipe identifies 95% of the 300 heaviest flows with less than 80KB of memory.

Comment: SOSR 2017, Santa Clara, CA

Planning process for an operational management platform for a public transport

Scipedia content — Tue, 02 Feb 2021 01:39:38 +0100

This work addresses the planning process of a public passenger transport operator, including the generation of schedules and services for vehicles and drivers, in the framework of a previously agreed service. This problem will be studied in the context of all stages of the planning process: parameterization, preparation, production of performance indicators and the generation of results for different operational scenarios. info:eu-repo/semantics/publishedVersion

THE STUDY OF PASSIVE VIBRATION DAMPERS IN PIPELINES USING PIV-METHODOLOGY FOR SINGLE PHASE FLOW

Scipedia content — Tue, 02 Feb 2021 01:25:47 +0100

Electric cars compared to ultra-light electric vehicles and global warming

Scipedia content — Tue, 02 Feb 2021 01:12:03 +0100

hough some effort has been done, if the full global warming effect is considered, also the parasitic methane emissions should be taken in account and not only CO2 for electric vehicles. Not just -20% (2020), but big changes are needed to counter the global warming problem. Drastic solutions are ultralight electric vehicles instead of the actual heavy ones. If the technology is well developed, it can reduce CO2 emissions by a factor 5 compared to usual electric vehicles (2050 target). It has also effect on the indirect CH4 emissions in electricity, but also at tire dust, which might be even the biggest source of particulate matter PM10-PM2.5. A vehicle concept F2E for two electric is proposed, towards a very good compromise between energy, comfort, cost, global warming and pollution.

Deciding to be Distracted

Scipedia content — Tue, 02 Feb 2021 01:09:26 +0100

This project investigated the decision process involved in a driver’s willingness to engage in various technology-related and non-technology tasks. The project included focus groups and an on-road study, both employing participants who used in-vehicle technologies to at least some degree, from four age groups: teen, young, middle, and older. The focus groups discussed the perceptions, motivations, attitudes, and decision factors that underlie driver choices. The on-road study had two phases: an on-road drive and a take-home booklet. Participants drove their own vehicles over a specified route. They did not actually engage in in-vehicle tasks, but at specified points they rated their willingness to engage in some specific task at that time and place. Eighty-one different situations (combination of in-vehicle task and driving circumstances) were included. Further information was collected in the take-home booklet regarding the participant’s familiarity with various in-vehicle technologies, additional situations for willingness and risk ratings, stated reasons underlying ratings, and self-ratings of certain aspects of driving behavior and decision-making style. Together, the focus groups and on-road study provided complementary findings about how drivers decide when to engage in potentially distracting tasks. Driver willingness to engage in various in-vehicle tasks was related to technology type, specific task attributes, driving conditions, personal motivations, driving style, and decision style. Specific project findings were related to potential countermeasure approaches, including public education; driver or device user training; user interface design; needs for warnings and information; criteria for function lock-outs; and driver assist system criteria.

Monitoring systems for pipeline safety based on FBG sensors

Scipedia content — Tue, 02 Feb 2021 00:56:46 +0100

Too Close for Comfort: Evaluating a Reward-Based Approach to Increase Drivers' Headway

Scipedia content — Tue, 02 Feb 2021 00:51:45 +0100

Tailgating is often implicated as a leading contributor to rear-end collisions but this behaviour is difficult to remediate because drivers are poor at estimating their own headway. The authors' first goal was to compare novice and fully licensed drivers as they applied existing headway interventions in a driving simulator. Their second goal was to develop an automated, reward-based approach to encourage longer headways. The authors first compared headway in the driving simulator to previous studies on real-world car following behaviour by asking drivers to (i) achieve what they perceived to be the minimum safe headway or to (ii) employ the common “2 second rule” intervention. The authors observed a close agreement between the headways achieved in the simulator and those achieved in prior real-world car-following paradigms. They then implemented their headway evaluation system and compared headway across instruction type: (i) minimum safe headway, (ii) “2 second rule”, or (iii) the headway evaluation system. The authors observed that fully licensed motorists maintained the longest headways while using their system. While drivers reported that the headway evaluation system was easy and appealing to use, they did not foresee continuing to use the device in the future. The current system may be beneficial for driver training applications or to promote situation awareness during the use of automated driver assistance systems such as adaptive cruise control.

Intelligent Transport Decision Analysis System Based on Big Data Mining

Scipedia content — Tue, 02 Feb 2021 00:39:01 +0100

Arrival trade-offs considering total flight and passenger delays and fairness

Scipedia content — Tue, 02 Feb 2021 00:29:05 +0100

This work has been partly financed thanks to the Generalitat de Catalunya (Grant number 2017-SGR-1278).

This paper studies trade-offs between flight and passenger delays and fairness when assigning delay pre-tactically (on-ground at origin airport) due to reduced airport capacity. The paper also defines and analyses efficiency-fairness tradeoffs. The optimisation model is based on the ground holding problem and uses various objective functions: total delay for flights (considering reactionary delay), total delay for passengers (considering outbound connections), and deviation from a Ration By Schedule solution (to get a measure of the fairness of the solution). The scenario considered takes place at Paris Charles de Gaulle airport, a busy European hub airport, and includes realistic values of traffic.

Peer Reviewed

Direct 3D stylization pipelines

Scipedia content — Tue, 02 Feb 2021 00:27:20 +0100

International audience; Using 3D computer graphics to emulate watercolor presents a special challenge. Complex stylizations are commonly processed offline, by combining multiple passes in compositing, where art directing is slow and non-intuitive because the stylized result is not immediate. This direct 3D stylization pipeline allows art direction to happen in real time. Using the framework, artists can assign their desired local and global effects directly in the 3D scene, see the stylized results immediately, and intuitively adapt them to fit their stylized vision. The technique can be used and applied in 3D animations, games, VR, visualizations, illustrations, and interactive art.

The calculation of the highest leak level of water pipe lines region at PDAM Tirta Kahuripan using fuzzy C–means and ArcGIS method analysis

Scipedia content — Tue, 02 Feb 2021 00:13:01 +0100

Water is a basic necessity for human’s life. Water, which is distributed to the public, should in decent condition, healthy, and protected from metal pollutants. In Indonesia, it is handled by a government institution, commonly is PDAM (Indonesian regional water utility company). A PDAM Tirta Kahuripan handles water distribution in Bogor area and part of Depok cities. Based on data, PDAM Tirta Kahuripan had approximately more than 46 % water loss, due to geological factor, human activity, etc. Therefore in this paper, we try to make a decision system of water loss at PDAM pipelines, using cluster Fuzzy C – Means method analysis. Then, mapped into ArcGIS software. Based on this method, we can be determine the region which shows the most water loss and also identify the highest leaks level from water pipelines at PDAM Tirta Kahuripan.

Subject Matter Expert Evaluation of Multi-Flight Common Route Advisories

Scipedia content — Tue, 02 Feb 2021 00:06:19 +0100

The Collection-And-Delivery Points Implementation Process from the Courier, Express and Parcel Operator's Perspective

Scipedia content — Tue, 02 Feb 2021 00:01:25 +0100

Collection-and-Delivery Points (CDP) have become increasingly important for couriers operating in the e-commerce sector. Through this way of delivery, it is possible to mitigate many issues related to the traditional home delivery (e.g. missing delivery, complex routing planning, and traffic delays). Despite this, there are still obstacles that prevent the CDP to become a dominant mode of parcel delivery. Through semi-structured interviews to companies working in the courier, express and parcel sector, this work aims to understand the enablers and barriers to the spread of the CDP mode of delivery, with a focus on the Italian market.

OpenSky report 2017: Mode S and ADS-B usage of military and other state aircraft

Scipedia content — Mon, 01 Feb 2021 23:52:05 +0100

This paper provides up-to-date statistics on SSR Mode S and 1090ES ADS-B usage by military and state aircraft from the OpenSky Network. By analysing the large host of real-world data collected by OpenSky using more than 700 receivers, we provide insights on the equipage of these state aircraft, their capabilities, usage patterns and much more. We publish up-to-date, empirically validated numbers on the status of the ongoing ADS-B deployment based on data collected over large areas in Europe, North America, and other continents, and categorize these aircraft by incorporating publicly available data sources. Our measurements indicate that ADS-B equipage of military aircraft is 42.9%, which is considerably less than ADS-B deployment in civil aviation. While there is considerable variation between countries, our results show that there is a long way to go to for a safe and efficient integration of military and state air traffic into the next generation civil air transportation system.

Evaluating citywide bus service reliability using noisy GPS data

Scipedia content — Mon, 01 Feb 2021 23:50:22 +0100

n increasing number of people use smartphone applications to plan their trips. Unfortunately, for various reasons, bus trips suggested by such applications are not as reliable as other trip types (e.g. by car, on foot, or by bicycle), which can result in excessive waiting time, or even the need to revise a planned trip. Traditional punctuality-based bus service reliability metrics do not capture route deviations, which are especially frequent in rapid changing urban environments due to rapidly changing road conditions caused by traffic congestion, road maintenance, etc. The prevalence of GPS data allows buses to be tracked and route deviations to be captured. We use such data to propose and calculate a novel reliability score for bus trips. This score is a linear weighted combination of distance, time, and speed deviations from an expected, pre-defined bus trip. GPS trajectory data is large and noisy which makes it challenging to process. This paper also presents an efficient framework that can de-noise and semantically split raw GPS data by pre-defined bus trips in citywide. Finally, the paper presents a comparative case study that applies the proposed reliability score to publicly available open bus data from Rio de Janeiro in Brazil and Dublin in Ireland.

PULSim: User-Based Adaptable Simulation Tool for Railway Planning and Operations

Scipedia content — Mon, 01 Feb 2021 23:49:04 +0100

Simulation methods are widely used in the field of railway planning and operations. Currently, several commercial software tools are available that not only provide functionality for railway simulation but also enable further evaluation and optimisation of the network for scheduling, dispatching, and capacity research. However, the various tools are all lacking with respect to the standards they utilise as well as their published interfaces. For an end-user, the basic mechanism and the assumptions built into a simulation tool are unknown, which means that the true potential of these software tools is limited. One of the most critical issues is the lack of the ability of users to define a sophisticated workflow, integrated in several rounds of simulation with adjustable parameters and settings. This paper develops and describes a user-based, customisable platform. As the preconditions of the platform, the design aspects for modelling the components of a railway system and building the workflow of railway simulation are elaborated in detail. Based on the model and the workflow, an integrated simulation platform with open interfaces is developed. Users and researchers gain the ability to rapidly develop their own algorithms, supported by the tailored simulation process in a flexible manner. The productivity of using simulation tools for further evaluation and optimisation will be significantly improved through the user-adaptable open interfaces.

Analysis of bike sharing system by clustering: the Vélib' case

Scipedia content — Mon, 01 Feb 2021 23:44:49 +0100

International audience; Bicycle sharing system has become more and more popular as it can help partly solve the problems such as CO2 over-emission and traffic congestion. Some systems have been operated for several years and the analysis work is very necessary for controlling and redesigning the system in purpose of getting better performances. In this paper we analyze the bike-sharing stations by clustering algorithms in order to mine the inner-station patterns, and these clustering results are essential for the system control and redesign. In this study, we take Vélib' bike sharing system in Paris as the study case.

On the Fifth Generation Communication Automotive Research and Innovation Project5GCAR – The Vehicular 5G PPP Phase 2 Project

Scipedia content — Mon, 01 Feb 2021 23:43:40 +0100

Connected vehicles and cooperative intelligent transport systems (ITS) are foreseen to improve road traffic safety and efficiency; vehicle-to-anything (V2X) communication is one important enabler. While first V2X services will target assisted driving, based on communication technologies like ITS G5 and in future LTE/LTE-A/5G V2X. In the longer run advanced V2X services will evolve towards cooperative automated driving and collective perception of complex road traffic situations. The upcoming 5G standard will target such advanced V2X use cases with a promise of ultra-reliable low latency communications (URLLC) with guaranteed latencies down to 5 ms, support for high data rates, a system scalable to high vehicles densities, and with a flexible network architecture that also supports new business models. Besides the development and evaluation of 5G concepts in time for the 5G standardization, the 5G PPP Phase 2 5GCAR project will demonstrate three advanced V2X use cases with prototype network equipment on an automotive test track.

Evaluating the Impact of SDN-Induced Frequent Route Changes on TCP Flows

Scipedia content — Mon, 01 Feb 2021 23:30:28 +0100

International audience; Traffic engineering technologies such as MPLS have been proposed to adjust the paths of data flows according to network availability. Although the time interval between traffic optimisations is often on the scale of hours or minutes, modern SDN techniques enable reconfiguring the network more frequently. It is argued, however, that changing the paths of TCP flows too often could severely impact their performance by incurring packet loss and reordering. This work analyses and evaluates the impact of frequent route changes on the performance of TCP flows. Experiments carried out on a network testbed show that rerouting a flow can affect its throughput when reassigning it a path either longer or shorter than the original path. Packet reordering has a negligible impact when compared to the increase of RTT. Moreover, constant rerouting influences the performance of the congestion control algorithm. Designed to assess the limits on SDN-induced reconfiguration, a scenario where the traffic is rerouted every 0.1s demonstrates that the throughput can be as low as 35% of that achieved without rerouting.

Pedestrian in the Loop: An approach using virtual reality

Scipedia content — Mon, 01 Feb 2021 23:23:19 +0100

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 Virtual Reality techniques. This method can be seen as a new Pedestrian in the Loop testing procedure. ispartof: 2017 XXVI INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATION AND AUTOMATION TECHNOLOGIES (ICAT) vol:2017-December ispartof: ICAT 2017 (International Conference on Information, Communication and Automation Technologies) location:Sarajevo, Bosnia & Herzegovina date:26 Oct - 28 Oct 2017 status: published

Document type: Conference object

The Impact of Coastal Urban Logistics Economic Development on International Trade Development

Scipedia content — Mon, 01 Feb 2021 23:18:45 +0100

Practical network-wide packet behavior identification by AP classifier

Scipedia content — Mon, 01 Feb 2021 23:14:24 +0100

Identifying the network-wide forwarding behaviors of a packet is essential for many network management applications, including rule verification, policy enforcement, attack detection, traffic engineering, and fault localization. Current tools that can perform packet behavior identification either incur large time and memory costs or do not support real-time updates. In this paper, we present AP Classifier, a control plane tool for packet behavior identification. AP Classifier is developed based on the concept of atomic predicates, which can be used to characterize the forwarding behaviors of packets. Experiments using the data plane network state of two real networks show that the processing speed of AP Classifier is faster than existing tools by at least an order of magnitude. Furthermore, AP Classifier uses very small memory and is able to support real-time updates.

Regional Well-to-Wheel Carbon, Energy, and Water Footprint Analysis of Electric Vehicles

Scipedia content — Mon, 01 Feb 2021 23:11:57 +0100

doption of alternative vehicle technologies such as electric vehicles (EVs), plug-in hybrid electric vehicles (PHEVs), and hybrid electric vehicles (HEVs) have the potential of reducing some of the environmental impacts and reducing oil-dependency of the U.S transportation sector. However, this potential depends on the regional driving patterns and the source of the electricity generation to power PHEVs and EVs. In this study, state-specific electricity generation mix scenarios and driving patterns in Alabama, Florida, and Hawaii are considered to calculate regional impacts associated with alternative vehicle technologies (HEVs, PHEVs, EVs) compared to internal combustion vehicles (ICVs). Three electricity generation mix scenario are evaluated, which are namely; average electricity generation mix, marginal electricity generation mix, and 100% solar electricity generation mix. Well-to-wheel carbon, energy, and water footprint of these vehicles are quantified for each state and potential environmental reductions are evaluated. According to comparative evaluation for the proposed scenarios, shifting to low carbon, energy, and water intensive electricity generation mix by utilization of solar energy is crucial to achieve environmental friendly transportation in the U.S. https://doi.org/10.2991/apte-18.2019.23

Analysis of asphalt mix surface-tread rubber interaction by using finite element method

Scipedia content — Mon, 01 Feb 2021 23:06:45 +0100

The surface texture of the pavement plays a very important role in driving the frictional properties at the tire rubber-pavement interface. Particularly, the hysteretic friction due to viscoelastic deformations of rubber depends mainly on the pavement surface texture. In the present paper, the effect of micromechanical pavement surface morphology on rubber block friction was brought in by comparing the friction results for three different asphalt mix morphological surfaces, named stone mastic asphalt (SMA), ultra-thin surfacing (UTS) and porous asphalt (PA). The asphalt surface morphologies of these mixes were captured by using an X-ray tomographer, from which the resulting images micromechanical finite element (FE) meshes for SMA, UTS and PA pavements were developed by means of the SimpleWare software. In the FE model, the rubber and asphalt binder were modeled as viscoelastic (VE) materials and the formulation was given in the large deformation framework. FE simulations were then carried out by using contact algorithm between rubber and the road surface. It was observed that the rubber friction inversely varies with the sliding speed and positively varies with the pressure for all the pavement morphological and stiffness conditions. Furthermore, it was observed that the highly porous pavement surface results in large dissipation of energy, hence, large rubber friction which shows that the mix characteristics of pavements have a significant effect on rubber friction.

An autonomous taxi service for sustainable urban transportation

Scipedia content — Mon, 01 Feb 2021 23:02:39 +0100

n autonomous taxi service has been proposed as a sustainable urban transport system for current and future cities. A critical review was conducted to examine whether the proposed technology can alleviate the negative side effects of urban transportation. The study investigated issues related to environmental impact, social sustainability and required infrastructure. A methodology was proposed to estimate the levels of demand and define the system performance requirements for an autonomous taxi to serve Addenbrooke's, which is a medical and research campus at the University of Cambridge UK. The size of the fleet, the capacity of the on-board battery and a charging infrastructure were suggested. Implications for the electricity supply network were also explored. A financial analysis showed that such a system is financial viable.

Voltage Unbalance and Overvoltage Mitigation by Using the Three-phase Damping Control Strategy in Battery Storage Applications

Scipedia content — Mon, 01 Feb 2021 22:55:13 +0100

The constantly decreasing prices of the battery storage systems make them a very attractive solution for mitigating over voltages and voltage unbalance in low voltage grids with high penetration of renewable energy resources. A centralised storage device, connected at the end of the feeder can be a very effective solution for dealing with over voltages. The classical positive-sequence control strategy is usually employed in these devices to ensure a power exchange between the grid and the battery and vice versa. Nevertheless, the voltage unbalance cannot be mitigated by the classical control strategies. In this article, a modified three-phase damping control strategy is used to discharge and charge the battery storage system. This control strategy has an improved resistive behavior towards the zero- and negative-sequence components which mitigates the voltage unbalance by injecting or drawing asymmetrical phase currents. Thus both power quality problems are mitigated.

Estimation and prediction of weather variables from surveillance data using spatio-temporal Kriging

Scipedia content — Mon, 01 Feb 2021 22:52:30 +0100

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Best paper award in Weather session at the 36th DASC - Digital Avionics Systems Conference

State-of-the-art weather data obtained from numerical weather predictions are unlikely to satisfy the requirements of the future air traffic management system. A potential approach to improve the resolution and accuracy of the weather predictions could consist on using airborne aircraft as meteorological sensors, which would provide up-to-date weather observations to the sur- rounding aircraft and ground systems. This paper proposes to use Kriging, a geostatistical interpolation technique, to create short- term weather predictions from scattered weather observations derived from surveillance data. Results show that this method can accurately capture the spatio-temporal distribution of the temperature and wind fields, allowing to obtain high-quality local, short-term weather predictions and providing at the same time a measure of the uncertainty associated with the prediction.

Peer Reviewed

Award-winning

Document type: Conference object

Synchronised 4-Phase Resonant Power Clock Supply for Energy Efficient Adiabatic Logic

Scipedia content — Mon, 01 Feb 2021 22:47:40 +0100

International audience; Adiabatic logic is an alternative architecture design style to reduce the power consumption of digital cores by using AC power supply instead of DC ones. The energy saving of the digital gates is strongly related to the efficiency of adiabatic AC power supplies. In this paper, we propose a resonant reversible power-clock supply design with four different phases. The resonance deviation between the four power-clock supplies is synchronized thanks to 12 control signals (3 controls signals per power-clock supply). We derive the energy dissipation of a 4-stage PFAL pipeline circuit supplied with the proposed resonant powerclock supply, which can dissipate up to 2.9 times less energy than a non-adiabatic CMOS pipeline.

The current problem of traffic congestion on highway

Scipedia content — Mon, 01 Feb 2021 22:42:02 +0100

Simulation of electric vehicle driver behaviour in road transport and electric power networks

Scipedia content — Mon, 01 Feb 2021 22:32:13 +0100

The integration of electric vehicles (EVs) will affect both electricity and transport systems and research is needed on finding possible ways to make a smooth transition to the electrification of the road transport. To fully understand the EV integration consequences, the behaviour of the EV drivers and its impact on these two systems should be studied. This paper describes an integrated simulation-based approach, modelling the EV and its interactions in both road transport and electric power systems. The main components of both systems have been considered, and the EV driver behaviour was modelled using a multi-agent simulation platform. Considering a fleet of 1000 EV agents, two behavioural profiles were studied (Unaware/Aware) to model EV driver behaviour. The two behavioural profiles represent the EV driver in different stages of EV adoption starting with Unaware EV drivers when the public acceptance of EVs is limited, and developing to Aware EV drivers as the electrification of road transport is promoted in an overall context. The EV agents were modelled to follow a realistic activity-based trip pattern, and the impact of EV driver behaviour was simulated on a road transport and electricity grid. It was found that the EV agents’ behaviour has direct and indirect impact on both the road transport network and the electricity grid, affecting the traffic of the roads, the stress of the distribution network and the utilization of the charging infrastructure.

A Model to Analyze the Design of the Toll Plaza

Scipedia content — Mon, 01 Feb 2021 22:21:18 +0100

Driving Performance in a Simulator as a Function of Pavement and Shoulder Width, Edge Line Presence, and Oncoming Traffic

Scipedia content — Mon, 01 Feb 2021 22:19:49 +0100

Driving simulation has primarily been used to study issues of driver distraction and to evaluate in-vehicle devices. The visualization and driver performance capabilities of simulators can be applied to more traditional traffic engineering problems as well. This project aims to demonstrate the usefulness of a driving simulator in evaluating geometric designs for two-lane roads. Paved surface width has been shown to be correlated with crashrates and travel speeds on two-lane rural roads throughout Texas. The current project examines how travel lane width, edge line striping, and shoulder width affect driver errors on these roadway types. Issues of simulatorvalidity, scenario development, and simulator sickness are discussed.

Modelling and Simulation of the Riga International Airport to Reduce Turnaround Times of Crucial Clearance Processes

Scipedia content — Mon, 01 Feb 2021 22:18:06 +0100

This paper focused on prioritisation of certain ground vehicles and improving the turnaround time of airplanes at the airport. This leads to acceleration of ground operations at the airport. Key indicators to measure delay and improvement within the system are the non-operation period of an airplane. Depending on the increasing number of passengers in the next few years, it is necessary to shorten this time and accelerate the processes of handling operations. The built conceptual model contains all necessary processes relating aircraft and ground vehicles and their movement. Based on the conceptual model a rough calculation was developed. The simulation model will be based on the rough calculation, therefore. Through the evaluation of gained data, new insights and new ideas for future simulation studies will be produced.

Deep Stochastic Radar Models

Scipedia content — Mon, 01 Feb 2021 22:13:50 +0100

urate simulation and validation of advanced driver assistance systems requires accurate sensor models. Modeling automotive radar is complicated by effects such as multipath reflections, interference, reflective surfaces, discrete cells, and attenuation. Detailed radar simulations based on physical principles exist but are computationally intractable for realistic automotive scenes. This paper describes a methodology for the construction of stochastic automotive radar models based on deep learning with adversarial loss connected to real-world data. The resulting model exhibits fundamental radar effects while remaining real-time capable.

Comment: IEEE Intelligent Vehicles Symposium 2017. Accepted for plenary presentation

Charging Electrically Driven Buses Considering Load Balancing in the Power Grid

Scipedia content — Mon, 01 Feb 2021 22:13:29 +0100

Electrically powered buses in public transportation are increasingly being put into operation. The energy supply needs a careful planning just to keep all busses continuously in operation and to avoid power peaks in the grid. This problem is solved by a two-step planning procedure which is based on a linear model. The first step is an analytical optimization under simplified constraints. In a second step a simulator works on an extended model. The planning objectives are to minimize the investment and to minimize the power peaks. Additionally a simple decision algorithm computes the charging power at run time. The models are developed in detail and a small numerical example illustrates the work.

Operational temporary speed reductions on the ETCS-DMI

Scipedia content — Mon, 01 Feb 2021 22:05:54 +0100

Dealing with congested railway area becomes an important topic in railway operation management. Significant efforts are made to develop Driver Advisory System (DAS) in connection with the trackside Train Management System (TMS). Many advantages are expected from smoothing train dynamic speed profiles: timetable resilience, significant reduction of both the energy consumption and the wear and tear and, finally, positive impacts on the comfort for passengers. Today, on one hand, only a few Centrally Guided Train Operation Systems (CGTO) are already in operation on European major railways. On the other hand, the European Train Control System (ETCS) spreads rapidly. Such combination offers a great opportunity to promote a European standard CGTO system using the ETCS-DMI opportunities. The present paper describes many options using either the "Monitoring" area, or the "Supplementary Driving Info" area, or the “Planning" area, or the “Speed Info” area; or a combination of them on the ETCS Diver Machine Interface (DMI). Some of them give only advices or guidance but some of them indicate operational temporary speed reductions (O_TSR) that are mandatory. Historical research, current experiments, and dispatching concepts in bottlenecks areas militate in favour of the compulsory character of temporary speed limits due to congestion. Therefore, the last option presented here should be more examined more in depth.

Evaluation of Traffic Control Systems as ITS Infrastructure for Automated Driving

Scipedia content — Mon, 01 Feb 2021 22:00:15 +0100

Vehicles with automated driving systems require more sensor information about their environment than non-automated vehicles. Detection with camera, lidar or other sensors is already state of the art in newer vehicles. As of today though, they only work in close proximity and lack the incorporation of existing traffic information from local authorities. In this paper, we present a novel way of providing traffic management information to vehicles, sent directly from Road Authorities. We use existing ITS (Intelligent Transport Systems) infrastructure and assess how information on traffic control and reroutes, displayed on variable message signs, can be used as sensory input for vehicles. We examine real world data from a South German Road Authority. The evaluation of latency, reliability and integrity of traffic information has been conducted end-to-end as well as between the six stations that are involved. We show the general feasibility of our proposal and discuss which obstacles need to be overcome for a wider use in other road systems.

Integrated Demand Management (IDM) - Minimizing Unanticipated Excessive Departure Delay while Ensuring Fairness from a Traffic Management Initiative

Scipedia content — Mon, 01 Feb 2021 21:57:08 +0100

Scalable deep traffic flow neural networks for urban traffic congestion prediction

Scipedia content — Mon, 01 Feb 2021 21:52:51 +0100

Tracking congestion throughout the network road is a critical component of Intelligent transportation network management systems. Understanding how the traffic flows and short-term prediction of congestion occurrence due to rush-hour or incidents can be beneficial to such systems to effectively manage and direct the traffic to the most appropriate detours. Many of the current traffic flow prediction systems are designed by utilizing a central processing component where the prediction is carried out through aggregation of the information gathered from all measuring stations. However, centralized systems are not scalable and fail provide real-time feedback to the system whereas in a decentralized scheme, each node is responsible to predict its own short-term congestion based on the local current measurements in neighboring nodes. We propose a decentralized deep learning-based method where each node accurately predicts its own congestion state in real-time based on the congestion state of the neighboring stations. Moreover, historical data from the deployment site is not required, which makes the proposed method more suitable for newly installed stations. In order to achieve higher performance, we introduce a regularized Euclidean loss function that favors high congestion samples over low congestion samples to avoid the impact of the unbalanced training dataset. A novel dataset for this purpose is designed based on the traffic data obtained from traffic control stations in northern California. Extensive experiments conducted on the designed benchmark reflect a successful congestion prediction.

Developing an Advanced Cloud-Based Vehicle Routing and Scheduling System for Urban Freight Transportation

Scipedia content — Mon, 01 Feb 2021 21:51:05 +0100

Part 3: Smart City Interoperability and Cross-Platform Implementation; International audience; In today’s challenging sector of logistics and transportation, companies, seek to adapt software which leads to efficient solutions at an acceptable cost. Conventional routing software is developed to solve vehicle routing problem and help managers and planners in decision making. Simultaneously, specific constraints and different VRP (Vehicle Routing Problem) variants are considered each time, such as the Capacitated, the Multi Depot and the Pickup and Delivery VRP. However, the last few years the need for more reliable deliveries and better customer services arose. In addition, reducing travel distance, travel cost and environmental impact are important factors encountered in urban freight transportation. Therefore, routing software needs to take into account multiple constraints. Such constraints are traffic congestion, speed limits, transportation regulations and restricted zones. These constraints affect mainly Time dependent VRP, VRP with Time Windows, Dynamic VRP and Green VRP. Data collection and processing are essential in routing software for solving these variants and offering the best solution. The methods for solving these problems, along with technological achievements, including cloud computing, can lead to efficient, easily adaptable routing software. Such software solutions can eventually render companies with complex transportation and logistics problems, competitive. The scope of this paper is to describe the concept and methodological approach for the development of such a routing and scheduling system, operating in a cloud environment. The definition of its requirements and the development of the system is the main purpose of an ongoing research project, being in its first stages of system’s analysis and design.

Document type: Conference object

Exploring the Relationship between False Alarms and Driver Acceptance of a Pedestrian Alert System during Simulated Driving

Scipedia content — Mon, 01 Feb 2021 21:47:13 +0100

In-vehicle pedestrian-alert-systems (PASs) can be prone to ‘false positive’ declarations, with the likelihood of false interventions increasing as time-to-collision (TTC) extends. A high number of false alarms can annoy drivers and lead to poor acceptance and low trust in the technology. To explore this relationship, 24 experienced drivers negotiated a single-lane urban high-street – moderately populated with pedestrians – during 12 five-minute drives in a medium-fidelity driving simulator. PAS warnings were presented in response to pedestrians who approached the roadside, either as a static visual alert icon presented on a HUD and/or auditory icon. The number of accurately detected pedestrians (i.e. those who entered the roadway rather than waiting at the kerbside) decreased with increasing TTC, giving rise to ‘false positive alarms’. Subjectively, participants associated the highest level of trust, confidence and desirability, and lower levels of annoyance, when warnings were presented at intermediate TTCs (3.0 and 4.0-seconds, corresponding to false-alarm rates of 40% and 60%, respectively); trust and confidence reduced significantly with both increasing and decreasing TTC. Driving performance data show that earlier warnings encouraged drivers to begin braking sooner and apply braking force more gradually, ultimately stopping further from the pedestrian – on average 18.0m following 5.0-second warnings compared to 6.2m with 2.0-second warnings. Nevertheless, evidence suggests that some drivers may have disregarded the system at longer TTCs, choosing to rely on their own judgement. The results have implications for the design, evaluation and acceptance of PASs.

The impact of flooding on road transport: A depth-disruption function

Scipedia content — Mon, 01 Feb 2021 21:41:25 +0100

Transport networks underpin economic activity by enabling the movement of goods and people. During extreme weather events transport infrastructure can be directly or indirectly damaged, posing a threat to human safety, and causing significant disruption and associated economic and social impacts. Flooding, especially as a result of intense precipitation, is the predominant cause of weather-related disruption to the transport sector. Existing approaches to assess the disruptive impact of flooding on road transport fail to capture the interactions between floodwater and the transport system, typically assuming a road is fully operational or fully blocked, which is not supported by observations. In this paper we develop a relationship between depth of standing water and vehicle speed. The function that describes this relationship has been constructed by fitting a curve to video analysis supplemented by a range of quantitative data that has be extracted from existing studies and other safety literature. The proposed relationship is a good fit to the observed data, with an R-squared of 0.95. The significance of this work is that it is simple to incorporate our function into existing transport models to produce better estimates of flood induced delays and we demonstrate this with an example from the 28"sup"th"/sup" June 2012 flood in Newcastle upon Tyne, UK.

Document type: Article

Sustainable Transport in the Developing World: A Case Study of Bogota’s Mobility Strategy

Scipedia content — Mon, 01 Feb 2021 21:33:35 +0100

Design and Validation of a Tool for Prognosis of the Energy Consumption and Performance in Electric Vehicles

Scipedia content — Mon, 01 Feb 2021 21:28:59 +0100

Conference on Transport Engineering, CIT2018 (13th, 2018, Gijón, Asturias, Spain)

This work was supported by the Science of Innovation Spanish Ministry and FEDER funds under the Proej ct TEC2016-80700 -R (AEI/FEDER, UE), by the Principality of Asturias Government under proej ct FC -15-GRUPIN14 -073 and the University Ins titute of Industrial Technology of Asturias (IUTA) under proej ct SV -15-GIJON -1.13.

Multi-objective optimization for short distance trips in an urban area: choosing between motor vehicle or cycling mobility for a safe, smooth and less polluted route

Scipedia content — Mon, 01 Feb 2021 21:25:36 +0100

Mobility in urban areas is highly complex because of the variety of possible facilities and routes, the multitude of origins and destinations, the increase of population density and traffic. Furthermore, people are willing to use more environmentally friendly transportation modes, such as cycling, to do short-distance trips in urban areas. This paper develops a multi-objective model for passengers in urban transportation network for short trips using bicycle or motor vehicle. The main objective of this paper is to improve the urban network mobility in order to decrease traffic congestion, road conflicts between road users and pollution. Furthermore, optimization objectives could comprehensively reflect expectations of passengers from the dimension of traffic and emissions as criteria and use a motor vehicle or a bicycle as an alternative. The methodology of this study was applied based on the real world case study in the city of Aveiro, Portugal. The present work uses a microscopic simulation platform of traffic (VISSIM), road safety (SSAM) and emissions (Vehicle Specific Power – VSP) to analyze traffic operations, road conflicts and to estimate carbon dioxide (CO2) and nitrogen oxide (NOX) emissions. Three-dimensional Pareto Fronts, which were expressed through traffic performance, road conflicts between motor vehicles and bicycles and emissions, were optimized using the fast Non-Dominated Genetic Algorithm (NSGA-II).

LOADING/UNLOADING SPACES LOCATION AND EVALUATION: AN APPROACH THROUGH REAL DATA

Scipedia content — Mon, 01 Feb 2021 21:24:59 +0100

International audience; This study presents a real-data approach that aims at optimizing the location of urban loading-unloading (L/U) spaces. The originality of this paper is twofold: first, it proposes a data collection methodology in order to integrate real and up-to-date information regarding cartography, L/U parking demand and existing L/U spaces. Second, an optimization model is developed in order to determine the location of new L/U spaces by taking into account real distances, influence radius and physical constraints. Such optimization model can be used to evaluate the relevance of the existing L/U spaces and/or to determine the optimal location of new ones. For this we propose to combine the use of OpenStreetMap, Google Maps APIs, and Open Data portals. This paper provides a framework composed by 3 models, namely: data collection, demand generation and location optimization. The proposed approach is applied to the city of Paris in order to illustrate different case studies and to assess the effectiveness of the framework.

High performance fault tolerance through predictive instruction re-execution

Scipedia content — Mon, 01 Feb 2021 21:22:52 +0100

Processor designers face the challenge of defect formation, leading to permanent faults, during fabrication and operation. Permanent or hard fault tolerance is an important problem in computing systems, solutions to which can help improve yield during fabrication and reduce the cost of transistor mortality during the service life of the processor. This paper presents PreFix, a method to handle hard errors to keep a faulty core running and correctly executing instructions. Instead of turning off faulty structures, PreFix predicts early on whether an instruction is likely to use faulty components, then refines this prediction later in the pipeline to actually detect when an error has occurred. Instructions marked as possibly- faulty in the front-end are queued for duplicate execution on a separate core. At commit, results from the original and duplicate instructions are compared. Upon a mismatch, the original instruction is patched up, the pipeline flushed and execution continues. Using PreFix, faulty components can continue performing useful work when their errors do not manifest in architecturally visible state changes. This enhances processor lifetime with minimal performance overhead.

GPS/Optical/Inertial Integration for 3D Navigation Using Multi-Copter Platforms

Scipedia content — Mon, 01 Feb 2021 21:13:55 +0100

Fortnite

Scipedia content — Mon, 01 Feb 2021 21:10:16 +0100

Game engine technology, when applied to traditional linear animation production pipelines, can positively alter the dynamics of animated content creation. With realtime interactivity, the iterative revision process improves, flexibility during scene assembly increases, and rendering overhead is potentially eliminated.

Why Should I Use ADAS? Advanced Driver Assistance Systems and the Elderly: Knowledge, Experience and Usage Barriers

Scipedia content — Mon, 01 Feb 2021 21:08:37 +0100

vast number of Advanced Driver Assistance Systems (ADAS) are commercially available, all of which have the potential to increase the safety and comfort of driving a car. Due to age-specific performance limitations, older drivers could benefit a great deal from such in-vehicle technologies, provided that they are purchased and used. Based on the results of several market research studies, awareness of ADAS is significantly higher than their usage rate, which is still very low. To analyze the discrepancy between awareness and willingness to use ADAS, 32 older car drivers were surveyed in a semi-structured interview study. This paper examines the knowledge, experience, and barriers toward the use of ADAS in the elderly.

Maximization of Attractiveness EV Tourist Routes

Scipedia content — Mon, 01 Feb 2021 21:07:15 +0100

Part 6: Modelling and Optimization; International audience; This paper presents model and an algorithmic approach for the problem of generation optimal tourist route for electric vehicles (EVs). In the discussed problem a starting and a final point of a route are EV charging stations where tourist could charge the battery and then continue a journey. The main objective is to select to the route points of interests (POIs) which maximizing tourist attractiveness. Furthermore maximum length of the route is limited by the number of kilometers that the car can travel on a single battery charge. The model applied by us is the graph routing problem named as the Orienteering Problem with Time Windows (OPTW). In OPTW each location has positive score and a specific time interval in which a location can be visited. The solution of OPTW is a route (from the given starting to the ending point) with a fixed limit of length including a subset of locations. Moreover the route maximizes the total score of the locations visited in the predefined time intervals. As a solution we present the evolutionary algorithm with combines path relinking method instead crossover. Computational experiments are conducted on realistic database POIs and EV charging stations of Podlasie region in Poland. Tests results and execution time of the algorithm shows that the described solution could be a part of EV software module with generates the most interesting route.

Document type: Part of book or chapter of book

IoT-aware Multi-layer Transport SDN and Cloud Architecture for Traffic Congestion Avoidance Through Dynamic Distribution of IoT Analytics

Scipedia content — Mon, 01 Feb 2021 20:57:04 +0100

We present and experimentally assess the first IoT-aware SDN and cloud architecture that deploys IoT flow monitoring and traffic-congestion avoidance techniques in order to dynamically and efficiently distribute the processing of IoT analytics from core datacentres to the network edge. Grant numbers : This research was partially funded by MINECO project DESTELLO (TEC2015-69256-R).

Document type: Conference object

The Research of Oil Pipeline Patrol by UAV in the First Sub-Factory of PCOC

Scipedia content — Mon, 01 Feb 2021 20:42:07 +0100

Application of Artificial Intelligence Techniques to Traffic Prediction and Route Planning, the vision of TIMON project

Scipedia content — Mon, 01 Feb 2021 20:31:46 +0100

TIMON is an European research project under the Horizon 2020 programme. The main objective of"br" this project is to provide real-time services through a web based platform and a mobile APP for drivers,"br" Vulnerable Road Users (VRUs) and businesses. These services will contribute to increasing drivers"br" and VRUs assistance and safety. To provide these services, one of the core technologies developed"br" inside TIMON will be the design and development of Artificial Intelligence (AI) techniques for traffic"br" prediction and route planning. The DeustoTech-Mobility research group is in charge of this part of the"br" project. The objective of this technical paper is to describe the approach followed in TIMON to"br" develop traffic congestion prediction and route planning services based on AI techniques and the"br" progress done so far. Additionally, the deployment and the result obtained in the first test done is also"br" detailed in this study.

Validating a European ATM Security System Architecture

Scipedia content — Mon, 01 Feb 2021 20:30:05 +0100

The awareness about security threats and vulnerabilities in Air Traffic Management (ATM) has been steadily growing over the last years. The number of recent security research projects shows that the effort taken to close these vulnerabilities and to make air traffic more robust against security attacks is increasing in the same way. As Air Traffic Management is often done across national borders, related security incidents could affect several air navigation service providers and stakeholders in different nations at the same time. A quick and efficient exchange of security-relevant information as well as a multi-national level of security management is needed. In the frame of the Global ATM Security Management Project (GAMMA), several prototypic security systems were developed and designed as part of a European security management system architecture. This concept foresees a local, a national and a European level of security management while essential information is shared between those levels. In order to validate this approach, several real-time humanin-the-loop simulations were conducted in the first half of 2017. Both, the connected security systems and also the validation environment were set up in a geo-distributed way across Europe integrating different components from several project partners. During these trials, special attention was payed to information exchange and transmission times, the performance of automatic correlation as well as the role of human operators embedded in this system of systems. The trials showed that – even in a geo-distributed setup – information can be exchanged and countermeasures can be initiated in less than 2 minutes through the different levels of security management. This paper provides information about the experimental setup and conduction of the GAMMA project’s third geo-distributed validation exercise. It illustrates selected results as well as provides a discussion and an outlook.

On the Construction of a Safety Gap Prediction Model for Freeway Bus Lane-Changing Maneuver Using Driving Simulator Data

Scipedia content — Mon, 01 Feb 2021 20:25:47 +0100

Lane-change crashes are not only responsible for an important portion of vehicular fatalities, but also for crash-caused traffic delays, often resulting in congestion. The type of discretionary lane change was the focus of this research, in which a safety gap prediction model was constructed for potential application in the development of lane-change support systems. Data for analysis and model fitting were collected from a fixed-based bus driving simulator. The experimental scene designed for the driving simulator consisted of a straight section of two-lane freeway mainline with daylight and vehicular flows traveling at different speed levels on the road. Ten professional coach drivers were recruited to perform lane-change experiments. Results of two-way ANOVA revealed a significant lane-change direction × vehicle speed on the target lane interaction, and further analyses demonstrated that there was a simple effect for vehicle speed on the target lane in the left-to-right group of the type of lane-change direction factor. A safety gap forecasting model with the time gap between lead and lag vehicle on the target lane as the forecasted variable was constructed, and tests of true out-of-sample forecast accuracy of the prediction model showed promising results for its potential application in the development of lane-change support systems.

Contribution of artificial intelligence to the assessment of rail safety

Scipedia content — Mon, 01 Feb 2021 20:21:07 +0100

International audience; This article describes a contribution to improving the usual safety analysis methods used in the certification of railway transport systems. The methodology is based on the complementary and simultaneous use of knowledge acquisition and machine learning. We used the ACASYA software environment to support the safety analysis aid methodology. ACASYA aims to provide experts with suggestions of potential failures which have not been considered by the manufacturer and which are capable of jeopardizing the safety of a new rail transport system. ACASYA consists of two main modules: CLASCA and EVALSCA, respectively dedicated to the classification and evaluation of accident scenarios. CLASCA is an inductive, incremental and interactive learning system. EVALSCA, built around a learning system called CHARADE, aims to provide experts with suggestions of potential failures which have not been considered by the manufacturer and which are capable of jeopardizing the safety of a new rail transport system.

Rerouting algorithms solving the air traffic congestion

Scipedia content — Mon, 01 Feb 2021 20:19:46 +0100

Congestion in the air traffic network is a problem with an increasing relevance for airlines costs as well as airspace safety. One of the major issue is the limited operative capacity of the air network. In this work an Autonomous Agent approach is proposed to solve in real time the problem of air traffic congestion. The air traffic infrastructures are modeled with a graph and are considered partitioned in different sectors. Each sector has its own decision agent dealing with the air traffic control involved in it. Each agent sector imposes a real time aircraft scheduling to respect both delay and capacity constrains. When a congestion is predicted, a new aircraft scheduling is computed. Congestion is solved when the capacity constrains are satisfied once again. This can be done by delaying on ground aircraft or/and rerouting aircraft and/or postponing the congestion. We have tested two different algorithms that calculate K feasible paths for each aircraft involved in the congestion. Some results are repo...

The Effects of an Eco-Driving Interface on Driver Safety and Fuel Efficiency

Scipedia content — Mon, 01 Feb 2021 20:17:35 +0100

Real-time, in-vehicle guidance on eco-driving is likely to produce substantial improvements in vehicle fuel economy. However, the benefits of such in-vehicle systems should be achieved without impairing driver safety. A simulator study evaluated both visual and haptic eco-driving feedback systems, which provided advice on gas pedal usage. Hill driving scenarios with variable traffic density were used to test drivers’ prioritization of safe and fuel-efficient driving. A visual, second-order display and a haptic force feedback gas pedal created the smallest errors in gas pedal usage and so maximized fuel efficiency. The visual display increased time spent looking away from the road, implying reduced driver safety. Participants were worse at eco-driving in more demanding, high traffic conditions. Drivers appeared to prioritize safety over eco-driving, however safety margins were shorter in the high density traffic condition, despite the degradation in eco-driving performance. The findings suggest which modality could be most appropriate for presenting in-vehicle eco-driving guidance, and hint that these systems should advise drivers based on the prevailing traffic conditions.

Applying Graph Theory to Problems in Air Traffic Management

Scipedia content — Mon, 01 Feb 2021 20:16:00 +0100

Understanding and Predicting Trends in Urban Freight Transport

Scipedia content — Mon, 01 Feb 2021 20:14:09 +0100

Date of Conference: 29 May-1 June 2017 Conference name: 18th IEEE International Conference on Mobile Data Management (MDM), 2017 Among different components of urban mobility, urban freight transport is usually considered as the least sustainable. Limited traffic infrastructures and increasing demands in dense urban regions lead to frequent delivery runs with smaller freight vehicles. This increases the traffic in urban areas and has negative impacts upon the quality of life in urban populations. Data driven optimizations are essential to better utilize existing urban transport infrastructures and to reduce the negative effects of freight deliveries for the cities. However, there is limited work and data driven research on urban delivery areas and freight transportation networks. In this paper, we collect and analyse data on urban freight deliveries and parking areas towards an optimized urban freight transportation system. Using a new check-in based mobile parking system for freight vehicles, we aim to understand and optimize freight distribution processes. We explore the relationship between areas' availability patterns and underlying traffic behaviour in order to understand the trends in urban freight transport. By applying the detected patterns we predict the availabilities of loading/unloading areas, and thus open up new possibilities for delivery route planning and better managing of freight transport infrastructures. © 2017 IEEE.

Impacts of vessel speed on bunker cost in short sea shipping: A cross-examination

Scipedia content — Mon, 01 Feb 2021 20:13:41 +0100

Air emissions of shipping have decreased in SECA regions after 2015. Environmental impacts of regulation policies are identifiable and measurable, as a study from the port of Gothenburg recently exposed. In addition to emissions, it is important to understand how regulations and decisions, focusing on environmental sustainability, impact on the maritime business indicators such as transport costs and marginal revenues. When SECA decision was made, the oil and bunker prices were historically high. Prices were also highly volatile. Numerous studies estimated difficulties for shipping companies, and maritime transport dependent export companies. The oil price dropped dramatically in 2016 remaining at the same level till the early 2018. This empirical case study examines and simulates bunker price data in relation to different vessel speeds. The paper looks at how different speed and oil price combinations impact transport costs and export business. The results of this simulation can be summarized with the notion that the negative economic impacts of the oil price variation can be mitigated to some extent by using lower vessel speeds, thus slow steaming, on short sea shipping (SSS). However, variable relations are not straightforward and they require additional studies.

Document type: Article

Object Detection from a Vehicle Using Deep Learning Network and Future Integration with Multi-Sensor Fusion Algorithm

Scipedia content — Mon, 01 Feb 2021 20:06:08 +0100

Self-driving Cars and Lidar

Scipedia content — Mon, 01 Feb 2021 20:04:00 +0100

Before graduating from X as Waymo, Google's self-driving car project had been using custom lidars for several years. In their latest revision, the lidars are designed to meet the challenging requirements we discovered in autonomously driving 2 million highly-telemetered miles on public roads. Our goal is to approach price points required for advanced driver assistance systems (ADAS) while meeting the performance needed for safe self-driving. This talk will review some history of the project and describe a few use-cases for lidars on Waymo cars. Out of that will emerge key differences between lidars for self-driving and traditional applications (e.g. mapping) which may provide opportunities for semiconductor lasers.

HAZARD IDENTIFICATION APPROACH FOR FUTURE HIGHLY-AUTOMATED AIR TRAFFIC MANAGEMENT CONCEPTS OF OPERATION: EXPERIENCES FROM THE AUTOPACE PROJECT

Scipedia content — Mon, 01 Feb 2021 20:03:26 +0100

From car to bike. Marketing and dialogue as a driver of change

Scipedia content — Mon, 01 Feb 2021 19:58:47 +0100

The Paris Climate Agreement has sent a key message to the international community regarding the need to increase efforts to move towards a low-carbon economy and help slow climate change, while underpinning global long-term economic growth and sustainable development. COP 21 recognizes the social, economic and environmental value of voluntary mitigation actions and their co-benefits for adaptation, health and sustainable development. In this framework, the PTP Cycle project, running from 2013 to 2016 and funded by the European Commission through the Intelligent Energy Europe program, introduces a non-market approach through voluntary participation in the adoption of sustainable transport modes such as cycling, based on marketing to potential customers through Personalized Travel Plans. The medium-sized city of Burgos (Spain) and the cities of Ljubljana, Riga, Antwerp and London (boroughs of Haringey and Greenwich) developed a new policy instrument (Personalized Travel Plans) in order to increase bike patronage. Beyond potential savings of CO2, the results show that PTP as a form of Active Mobility Consultancy is a suitable instrument to influence modal shift to public transport, walking and cycling, and to address the challenges of climate change, while fostering sustainable transportation by changing mobility behaviour. These results, matching with the state-of-the-art of studies and pilot applications in other countries, allows deriving differentiated results for medium-size and large urban areas.

Document type: Conference object

Demand-based Placement of LDACS Ground Stations to Achieve RNP 0.3 Accuracy for APNT

Scipedia content — Mon, 01 Feb 2021 19:52:18 +0100

Regions with dense air traffic has lower separation between aircrafts to maintain the throughput. Terminal area generally requires high throughput and some of the airports need to maintain 3 nmi separation between two aircrafts. To provide 3 nmi separation RNP 0.3 is required. In this paper we propose two possible ways to fulfill RNP 0.3 NSE requirement using LDACS as an alternate system. The first way is to use LDACS in standalone configuration and the other way is to use a hybrid configuration, where position solution is obtained using LDACS combined with DME. The results show that both the proposed methods, standalone and hybrid configuration fulfill RNP 0.3 NSE requirement. Where standalone configuration is more accurate than hybrid, due to the low ranging error of LDACS system. For our analysis the surveillance data for terminal area of Munich and Frankfurt airports were used. In standalone configuration 5 LDACS stations for Frankfurt and 6 LDACS stations for Munich are sufficient to fulfill RNP 0.3 NSE requirement. In hybrid mode both Frankfurt and Munich only need 3 LDACS stations.

Statistical Analysis of Aircraft Trajectories: a Functional Data Analysis Approach

Scipedia content — Mon, 01 Feb 2021 19:50:24 +0100

International audience; In Functional Data Analysis, the underlying structure of a raw observation is functional and data are assumed to be sample paths from a single stochastic process. When data considered are functional in nature thus infinite-dimensional, like curves or images, the multivariate statistical procedures have to be generalized to the infinite-dimensional case. By approximating random functions by a finite number of random score vectors, the Principal Component Analysis approach appears as a dimension reduction technique and offers a visual tool to assess the dominant modes of variation, pattern of interest, clusters in the data and outlier detection. A functional statistics approach is applied to univariate and multivariate aircraft trajectories.

Semantics-based summarization of ATM data to manage information overload in pilot briefings

Scipedia content — Mon, 01 Feb 2021 19:47:42 +0100

Pilot briefings, in their traditional form, drown pilots in a sea of information. Rather than unfocused swathes of air traffic management (ATM) information,pilots require only the information for their specific flight. In this paper, we introduce the notion of ATM information cubes. We propose a conceptual framework with merge and abstraction operations for the combination and summarization of the information that is organized in ATM information cubes. A merge operation combines ATM information from individual cells of an ATM information cube. An abstraction operation summarizes the data items within a cell, replacing individual data items by more abstract data items with summary information. The result is a managementsummary of relevant information

Wireless Sensors Network for Traffic surveillance and management in Smart Cities

Scipedia content — Mon, 01 Feb 2021 19:41:49 +0100

The efficiency of a city’s own transportation system heavily influences its economic growth due to the increasing need to transport labour force, consumers and cargo. The use of the latest technologies to solve traffic problems is the main theme of ITS “Intelligent transportation system”, several solutions are already in use in many cities around the world and it is an indispensable part of the smart cities project. Our research focuses on developing a solution to manage road traffic in a smart city environment by utilizing wireless sensor network as medium to surveille the traffic. In this paper, we propose a set of countermeasures to avoid congestion and improve the flow of the traffic. The proposed countermeasures were simulated, and the results showed that our plan reduced the traffic congestion, minimized gases emission and increased fuel usage efficiency.

Document type: Conference object

Wheelmap: the wheelchair accessibility crowdsourcing platform

Scipedia content — Mon, 01 Feb 2021 19:36:09 +0100

Crowdsourcing (geo-) information and participatory GIS are among the current hot topics in research and industry. Various projects are implementing participatory sensing concepts within their workflow in order to benefit from the power of volunteers, and improve their product quality and efficiency. Wheelmap is a crowdsourcing platform where volunteers contribute information about wheelchair-accessible places. This article presents information about the technical framework of Wheelmap, and information on how it could be used in projects dealing with accessibility and/or multimodal transportation.

Document type: Article

3DBodyTex: Textured 3D Body Dataset

Scipedia content — Mon, 01 Feb 2021 19:35:29 +0100

In this paper, a dataset, named 3DBodyTex, of static 3D body scans with high-quality texture information is presented along with a fully automatic method for body model fitting to a 3D scan. 3D shape modelling is a fundamental area of computer vision that has a wide range of applications in the industry. It is becoming even more important as 3D sensing technologies are entering consumer devices such as smartphones. As the main output of these sensors is the 3D shape, many methods rely on this information alone. The 3D shape information is, however, very high dimensional and leads to models that must handle many degrees of freedom from limited information. Coupling texture and 3D shape alleviates this burden, as the texture of 3D objects is complementary to their shape. Unfortunately, high-quality texture content is lacking from commonly available datasets, and in particular in datasets of 3D body scans. The proposed 3DBodyTex dataset aims to fill this gap with hundreds of high-quality 3D body scans with high-resolution texture. Moreover, a novel fully automatic pipeline to fit a body model to a 3D scan is proposed. It includes a robust 3D landmark estimator that takes advantage of the high-resolution texture of 3DBodyTex. The pipeline is applied to the scans, and the results are reported and discussed, showcasing the diversity of the features in the dataset.

DAX - The Next Generation: Towards One Million Processes on Commodity Hardware

Scipedia content — Mon, 01 Feb 2021 19:34:16 +0100

Large scale image processing demands a standardized way of not only storage but also a method for job distribution and scheduling. The eXtensible Neuroimaging Archive Toolkit (XNAT) is one of several platforms that seeks to solve the storage issues. Distributed Automation for XNAT (DAX) is a job control and distribution manager. Recent massive data projects have revealed several bottlenecks for projects with "100,000 assessors (i.e., data processing pipelines in XNAT). In order to address these concerns, we have developed a new API, which exposes a direct connection to the database rather than REST API calls to accomplish the generation of assessors. This method, consistent with XNAT, keeps a full history for auditing purposes. Additionally, we have optimized DAX to keep track of processing status on disk (called DISKQ) rather than on XNAT, which greatly reduces load on XNAT by vastly dropping the number of API calls. Finally, we have integrated DAX into a Docker container with the idea of using it as a Docker controller to launch Docker containers of image processing pipelines. Using our new API, we reduced the time to create 1,000 assessors (a sub-cohort of our case project) from 65040 seconds to 229 seconds (a decrease of over 270 fold). DISKQ, using pyXnat, allows launching of 400 jobs in under 10 seconds which previously took 2,000 seconds. Together these updates position DAX to support projects with hundreds of thousands of scans and to run them in a time-efficient manner.

Analysis of Traffic Engineering capabilities for SDN-based Data Center Networks

Scipedia content — Mon, 01 Feb 2021 19:34:00 +0100

In the recent years more and more existing services have moved from local execution environments into the cloud. In addition, new cloud-based services are emerging, which are characterized by very stringent delay requirements. This trend puts a stress in the existing monolithic architecture of Data Center Networks (DCN), thus creating the need to evolve them. Traffic Engineering (TE) has long been the way of attacking this problem, but as with DCN, needs to evolve by encompassing new technologies and paradigms. This paper provides a comprehensive analysis of current DCN operational and TE techniques focusing on their limitations. Then, it highlights the benefits of incorporating the Software Defined Networking (SDN) paradigm to address these limitations. Furthermore, it illustrates two methodologies and addresses the scalability aspect of DCN-oriented TE, network and service testing, by presenting a hybrid physical-simulated SDN enabled testbed for TE studies.

Towards Adaptive Fault Tolerance on ROS for Advanced Driver Assistance Systems

Scipedia content — Mon, 01 Feb 2021 19:32:56 +0100

International audience; The use of over-the-air updates has attracted very much interest these last few years with the software-intensive development of embedded systems in the car industry. The development of autonomous driving and ADAS (Advanced Driver Assistance Systems) renders over-the-air updates mandatory, for both user satisfaction and economic reasons. How to make sure that remote updates of critical ADAS do not have an impact on safety? This is the question we tackle in our work with a major car manufacturer. This paper is a progress report. We summarize our approach involving AFT (Adaptive Fault Tolerance) implemented on ROS (Robot Operating System), describe the simulation platform we have developed to experiment and validate over-the-air updates of ADAS and AFT, and finally draw some lessons learnt and perspectives.

Adaptive QoS for data transfers using software-defined networking

Scipedia content — Mon, 01 Feb 2021 19:31:00 +0100

The research community has devoted much attention to the use of classic network technologies for advanced traffic engineering, but the use of software-defined networking (SDN) for this purpose, particularly in regards to Quality of Service (QoS) optimizations, remains relatively unexplored. We have developed a QoS framework that leverages SDN capabilities to achieve optimal throughputs for all QoS flows on a congested network. Specifically, we propose an approach that reassigns bandwidth unused by one or more flows to other flows in priority order, while simultaneously ensuring that QoS flows can reclaim their reassigned bandwidth whenever they are able to use that bandwidth. At the heart of our framework is the Adaptive Quality of Service (AQoS) algorithm, inspired by Integrated Services (IntServ) principles, which enables fine-tuned, real-time control over per-flow bandwidth allocations, combined with classic Differentiated Services (DiffServ) priority classes that determine how bandwidth is distributed. We evaluate and compare the results of the AQoS throughput optimizations to those achieved by several baseline algorithms common to both classic and SDN networks, with promising results.

An Empirical Analysis of On-demand Ride-sharing and Traffic Congestion

Scipedia content — Mon, 01 Feb 2021 16:32:24 +0100

Sharing economy, which leverages information technology to re-distribute unused or underutilized assets to people who are willing to pay for the services, has received tremendous attention in the last few years. Its creative business model has disrupted many traditional industries (e.g., transportation, hotel) by fundamentally changing the mechanism to facilitate the matching of demand with supply in real time. In this research, we investigate how Uber, a peer-to-peer mobile ride-sharing platform, affects traffic congestion in the urban areas of the United States. Combining data from Uber and the Urban Mobility Report, we empirically examine whether and how the entry of Uber car services affect traffic congestion using a difference-in-difference framework. Findings from this research provide evidence on the potential effect of ride sharing services in the transportation industry, contributing to the understanding of the sharing economy and government policy decisions.

Visualization of Gas–Oil–Water Flow in Horizontal Pipeline Using Dual-Modality Electrical Tomographic Systems

Scipedia content — Mon, 01 Feb 2021 16:10:21 +0100

Employing dual-modality tomography inherently involves data from multiple dimensions, and thus a coherent approach is required to fully exploit the information from various dimensions. This paper describes a novel approach for dual-modality electrical resistance and capacitance tomography (ERT-ECT) to visualize gas–oil–water flow in horizontal pipeline. Compared with the conventional methods with dual-modality tomographic systems, the approach based on thresholding takes the account of multi-dimensional data, which therefore is capable of providing insights into investigated flow in both spatial and temporal terms. The experimental results demonstrate the feasibility of the approach, by which six common flow regimes in horizontal pipeline flow are visualized based on the multi-dimensional data with ERT-ECT systems, including (wavy) stratified flow, plug flow, slug flow, annular flow, and bubbly flow. Although the present approach is proposed for data acquired with an ERT-ECT system, it is potentially adaptable to other dual-modality tomographic systems that use concentration tomograms as inputs.

Document type: Article

Toward the automated analysis of complex diseases in genome-wide association studies using genetic programming

Scipedia content — Fri, 29 Jan 2021 01:02:14 +0100

Machine learning has been gaining traction in recent years to meet the demand for tools that can efficiently analyze and make sense of the ever-growing databases of biomedical data in health care systems around the world. However, effectively using machine learning methods requires considerable domain expertise, which can be a barrier of entry for bioinformaticians new to computational data science methods. Therefore, off-the-shelf tools that make machine learning more accessible can prove invaluable for bioinformaticians. To this end, we have developed an open source pipeline optimization tool (TPOT-MDR) that uses genetic programming to automatically design machine learning pipelines for bioinformatics studies. In TPOT-MDR, we implement Multifactor Dimensionality Reduction (MDR) as a feature construction method for modeling higher-order feature interactions, and combine it with a new expert knowledge-guided feature selector for large biomedical data sets. We demonstrate TPOT-MDR's capabilities using a combination of simulated and real world data sets from human genetics and find that TPOT-MDR significantly outperforms modern machine learning methods such as logistic regression and eXtreme Gradient Boosting (XGBoost). We further analyze the best pipeline discovered by TPOT-MDR for a real world problem and highlight TPOT-MDR's ability to produce a high-accuracy solution that is also easily interpretable.

Comment: 9 pages, 4 figures, submitted to GECCO 2017 conference and currently under review

Road transport and CO2 emissions: What are the challenges?

Scipedia content — Fri, 29 Jan 2021 01:01:27 +0100

In order for the world to stay within the safety threshold of a 2�C increase in average temperature agreed by\\ud virtually all governments, the transport sector needs to be decarbonized. The two main obstacles that have\\ud prevented this from happening have been the absence of a global legally binding deal and the high relative cost of\\ud clean vehicle/energy technologies. The Paris Agreement, which commits countries to reductions of GHG emissions,\\ud has virtually solved the first problem and paved the way for countries to implement environmental taxes\\ud and subsidies in order to change the relative costs of clean alternatives, which would solve the second problem.\\ud These policy actions combined with investment in clean infrastructure and regulation can decarbonize the\\ud transport sector.

Document type: Article

Online Multicast Traffic Engineering for Software-Defined Networks

Scipedia content — Fri, 29 Jan 2021 00:56:37 +0100

Previous research on SDN traffic engineering mostly focuses on static traffic, whereas dynamic traffic, though more practical, has drawn much less attention. Especially, online SDN multicast that supports IETF dynamic group membership (i.e., any user can join or leave at any time) has not been explored. Different from traditional shortest-path trees (SPT) and graph theoretical Steiner trees (ST), which concentrate on routing one tree at any instant, online SDN multicast traffic engineering is more challenging because it needs to support dynamic group membership and optimize a sequence of correlated trees without the knowledge of future join and leave, whereas the scalability of SDN due to limited TCAM is also crucial. In this paper, therefore, we formulate a new optimization problem, named Online Branch-aware Steiner Tree (OBST), to jointly consider the bandwidth consumption, SDN multicast scalability, and rerouting overhead. We prove that OBST is NP-hard and does not have a $|D_{max}|^{1-\\epsilon}$-competitive algorithm for any $\\epsilon "0$, where $|D_{max}|$ is the largest group size at any time. We design a $|D_{max}|$-competitive algorithm equipped with the notion of the budget, the deposit, and Reference Tree to achieve the tightest bound. The simulations and implementation on real SDNs with YouTube traffic manifest that the total cost can be reduced by at least 25% compared with SPT and ST, and the computation time is small for massive SDN.

Comment: Full version (accepted by INFOCOM 2018)