Abstract

Proceedings of the Academic Track at State of the Map 2020 - Online (originally planned in Cape Town, South Africa), July 4-6, 2020. Editors Marco Minghini – European Commission, Joint Research Centre (JRC), Ispra, Italy Serena Coetzee, Department of Geography, Geoinformatics and Meteorology, University of Pretoria Levente Juhász – GIS Center, Florida International University, Miami, FL, United States A. Yair Grinberger – Department of Geography, The Hebrew University of Jerusalem, Israel Peter Mooney – Department of Computer Science, Maynooth University, Maynooth, Ireland Godwin Yeboah – Institute for Global Sustainable Development, School of Cross-faculty Studies, University of Warwick, Coventry, United Kingdom

Abstract

State of the Map featured a full day of academic talks. Building upon the motto of SotM 2019 in "Bridging the Map" the Academic Track session was aimed to provide the bridge to join together the experience, understanding, ideas, concepts and skills from different groups of researchers, academics and scientists from around the world. In particular, the Academic Track session was meant to build this bridge that connects members of the OpenStreetMap community and the academic community by providing an open passage for exchange of ideas, communication and opportunities for increased collaboration. These proceedings include 14 abstracts accepted as oral presentations and 6 abstracts presented as posters. Contributions were received from different academic fields, for example geography, remote sensing, computer and information sciences, geomatics, GIScience, the humanities and social sciences, and even from industry actors. We are particularly delighted to have included abstracts from both experienced researchers and students. Overall, it is our hope that these proceedings accurately showcase the ongoing innovation and maturity of scientific investigations and research into OpenStreetMap, showing how it as a research object converges multiple research areas together. Our aim is to show how the sum total of investigations of issues like Volunteered Geographic Information, geo-information, and geo-digital processes and representation shed light on the relations between crowds, real-world applications, technological developments, and scientific research. Document type: Book

Abstract

Because of their critical strategic role, ports have all traditionally been subject to some form of government control even if the legal form and the intensity of this control have varied across countries. The member countries of the European Union have not been different from the rest of the world in this respect. A significant difference however is the recurrent effort to integrate, in a coordinated way, the port sector in a trans-European transport network (TEN-T) through the adoption of a common legal framework. In this context, if the objective of the reforms is to ensure that port networks, integrated in combined transport networks, become competitors of the road network, the concept of port efficiency becomes central. This paper provides an overview of the evolution of the European Port Legislation and shows how comparative economic measures can be used to highlight the scope for port efficiency improvements, essential to allow short sea shipping transport to compete with road transport in Europe. To our knowledge, this paper is also the first effort of estimating technical efficiency of European Port Authorities. The average port efficiency in 2002 was estimated to be around 60%, denoting that ports could have handled 40% more traffic with the same resources. Maritime Economics & Logistics (2007) 9, 148–171. doi:10.1057/palgrave.mel.9100177

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itle"Abstract"/jats:title" "jats:p"In the North West of England the issue of a perceived infrastructure gap is of increasing concern. Investment needs to be made to improve the transport infrastructure of the region if it is to be expected to promote the development of its own regional logistics gateway. Funding tools have been set up to address the challenges arising from the imbalance in infrastructure development that exists between regions in the north of the United Kingdom and those in the south. For regions with well developed economies the outlook is promising as the availability of modern transport infrastructure looks set to improve. However, some sources believe that the development of new transport infrastructure will have a negative impact upon sustainable development. It is expected that this will occur in a range of both direct and indirect ways. As a result, it is critical that planning for the creation of new intermodal transport infrastructure, or the upgrading of that which already exists, takes into account the impact that these developments will have on the sustainable development of the host region. A scenario based development methodology is proposed in this paper. It was developed to provide a way to identify potential scenarios that may arise within a given region as a result of transport infrastructure projects. To create significant scenarios the methodology is dependent on the availability of a sufficient quantity of quality data. For this paper that data was collected through a focus group composed of stakeholders from the region in question. This was further supported by the performance of an impact survey using the same group of stakeholders. Document type: Article

Abstract

The well-known traffic congestion problem in urban environments has negative impact on many areas including economy, environment, health and lifestyle. Recently, a number of solutions based on vehicle-to-vehicle communications were proposed for traffic congestion detection and management. In this paper we present an algorithm designed to enable each vehicle in the network to detect and quantify the level of traffic congestion in completely distributed way, independent of any supporting infrastructure and additional information such as traffic data from local authorities. Based on observations of traffic congestion by every vehicle, and by adapting the broadcast interval, it enables dissemination of the traffic information to other vehicles. The algorithm also makes every vehicle aware about the congestion level on the streets that are spatially separated from their current location by several streets. Its robustness keeps the vehicle's overall knowledge about congestion consistent, despite the short-term changes in vehicle's motion. Since the quantification of congestion is based on per-vehicle basis, the algorithm is able to operate even when only 10% of vehicles in the network are VANET enabled. Data aggregation and adaptive broadcasting are used to ensure that vehicles do not send redundant information about the traffic congestion. The simulations are conducted in Veins framework based on OMNeT++ network simulator and SUMO vehicular mobility simulator.

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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.

Abstract

The aim of this paper is to present and apply a new evaluation framework for traffic management and Intelligent Transport Systems, to assist urban transport authorities in assessing relevant policies and technologies as to their performance. The principles behind performance measures and indices are outlined, along with a description of theframework development methodology. Two Key Performance Indicators (KPIs) for the topics of mobility and traffic accidents respectively are formulated and operative definitions are presented. Then, the new KPIs are applied to a case study in the city of Paris, involving the introduction of a scheme granting priority to buses at signalised junctions. The results from the before- and after-analysis are reported and interpreted, not only in terms of the case study itself, but most importantly from the standpoint of the applicability of the evaluation framework. Document type: Conference object

Abstract

The analysis of driving behaviour is a challenging task in the transport field that has numerous applications, ranging from highway design to micro-simulation and the development of advanced driver assistance systems. There has been evidence suggesting changes in the driving behaviour in response to changes in traffic conditions, and this is known as adaptive driving behaviour. Identifying these changes and the conditions under which they happen, and describing them in a systematic way, contributes greatly to the accuracy of micro-simulation, and more importantly to the understanding of the traffic flow, and therefore paves the way for introducing further improvements with respect to the efficiency of the transport network. In this paper adaptive driving behaviour is linked to changes in the parameters of a given car-following model. These changes are tracked using a dynamic system identification method, called particle filtering. Subsequently, the dynamic parameter estimates are further processed to identify critical points where significant changes in the system take place.

Abstract

Nowadays, sustainability and resilience have become a major consideration that cannot be neglected in urban development. People are starting to consider utilizing the urban infrastructure environment to maintain and improve the functionality and availability of the urban system when unexpected events take place. Traffic congestion is always a major issue in urban planning, especially when the vehicles in the roadway keep growing and the local authorities are lack of solutions to manage or distribute the traffics in the city. It has huge impact on urban sustainability and resilience such as overload of the city’s infrastructure, and air pollution, etc. This paper presents a survey on the challenges of developing sustainable and resilient transportation networks and the current urban traffic optimisation methods, as a possible solution to address such challenges. It aims to describe and define the state of the art on the research on sustainable and resilient transportation networks in urban development and a taxonomy of different traffic optimisation methods used for avoiding traffic congestion and improve urban traffic management.

Abstract

dvanced urban traffic control systems are often based on feed-back algorithms. For instance, current traffic control systems often operate on the basis of adaptive green phases and flexible co-ordination in road (sub) networks based on measured traffic conditions. However, these approaches are still not very efficient during unforeseen situations such as road incidents when changes in traffic are requested in a short time interval. Therefore, we need self-managing systems that can plan and act effectively in order to restore an unexpected road traffic situations into the normal order. A significant step towards this is exploiting Automated Planning techniques which can reason about unforeseen situations in the road network and come up with plans (sequences of actions) achieving a desired traffic situation. In this paper, we introduce the problem of self-management of a road traffic network as a temporal planning problem in order to effectively navigate cars throughout a road network. We demonstrate the feasibility of such a concept and discuss our preliminary evaluation in order to identify strengths and weaknesses of our approach and point to some promising directions of future research.