2,263 research outputs found

    Integrating spatial and temporal approaches for explaining bicycle crashes in high-risk areas in Antwerp (Belgium)

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    The majority of bicycle crash studies aim at determining risk factors and estimating crash risks by employing statistics. Accordingly, the goal of this paper is to evaluate bicycle-motor vehicle crashes by using spatial and temporal approaches to statistical data. The spatial approach (a weighted kernel density estimation approach) preliminarily estimates crash risks at the macro level, thereby avoiding the expensive work of collecting traffic counts; meanwhile, the temporal approach (negative binomial regression approach) focuses on crash data that occurred on urban arterials and includes traffic exposure at the micro level. The crash risk and risk factors of arterial roads associated with bicycle facilities and road environments were assessed using a database built from field surveys and five government agencies. This study analysed 4120 geocoded bicycle crashes in the city of Antwerp (CA, Belgium). The data sets covered five years (2014 to 2018), including all bicycle-motorized vehicle (BMV) crashes from police reports. Urban arterials were highlighted as high-risk areas through the spatial approach. This was as expected given that, due to heavy traffic and limited road space, bicycle facilities on arterial roads face many design problems. Through spatial and temporal approaches, the environmental characteristics of bicycle crashes on arterial roads were analysed at the micro level. Finally, this paper provides an insight that can be used by both the geography and transport fields to improve cycling safety on urban arterial roads

    Integrated Multimodal Transportation Dashboard

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    Na área dos sistemas de transportes atualmente existem vários sistemas inteligentes que permitem a monitorização, controlo e outras funções relevantes para um dado tipo de transportes. Entretanto, o tratamento individualizado dos diferentes modos, não favorece a geração de políticas e mecanismos integrados de gestão de transporte multimodal; são pouquíssimas as soluções que juntam diferentes tipos de transportes numa só aplicação. Surgiu, portanto, a necessidade dum painel de monitorização multimodal, que permitirá unir vários tipos de sistemas de transportes e fornecerá a visão geral para a observação se todos os sistemas estão funcionais e operantes a um nível de serviço aceitável. Uma vez que tais sistemas fornecem serviços e dados de alcance diferente e com os níveis de qualidade e detalhes variáveis, a detecção de funcionamento abnormal dum sistema é um desafio que requer a identificação, aplicação, adaptação ou criação de métricas de funcionamento normal para cada sistema de transportes, tendo como base os dados fornecidos por protocolos utilizados por ITSs integrados na solução. Este problema é abordado por projeto "Integrated Multimodal Transportation Dashboard" ou Painel Integrado de Monitorização de Transportes Multimodais em Portugues que tem como objetivo a elaboração dum protótipo funcional de uma ferramenta para a monitorização de transportes multimodais.At present time there exist various intelligent systems in Transportation area that permit monitoring, control and other relevant functionalities for a given transport means. However, individual solutions for different transport means don't favor multimodal transport management; there are a very few solutions that combine different transport types in one application. Therefore, a need for a multimodal supervision dashboard arouse - a dashboard that would permit to combine transportation systems of different types and that would provide a comprehensive view in order to observe whether all the systems are functional and operating at an acceptable Level of Service (LOS). Since these systems supply services and data of different scope and varied detail and quality levels, the detection of an abnormal functioning of a certain transportation system is a challenge. It requires identification, application, adaptation or creation of metrics for each transportation system functioning. The metrics should be based on the data supplied by the protocols used by the ITSs integrated in the solution. This problem is addressed by the project "Integrated Multimodal Transportation Dashboard" and has as an aim the elaboration of a functional prototype of a tool for the monitoring of multimodal transports

    Mobility mining for time-dependent urban network modeling

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    170 p.Mobility planning, monitoring and analysis in such a complex ecosystem as a city are very challenging.Our contributions are expected to be a small step forward towards a more integrated vision of mobilitymanagement. The main hypothesis behind this thesis is that the transportation offer and the mobilitydemand are greatly coupled, and thus, both need to be thoroughly and consistently represented in a digitalmanner so as to enable good quality data-driven advanced analysis. Data-driven analytics solutions relyon measurements. However, sensors do only provide a measure of movements that have already occurred(and associated magnitudes, such as vehicles per hour). For a movement to happen there are two mainrequirements: i) the demand (the need or interest) and ii) the offer (the feasibility and resources). Inaddition, for good measurement, the sensor needs to be located at an adequate location and be able tocollect data at the right moment. All this information needs to be digitalised accordingly in order to applyadvanced data analytic methods and take advantage of good digital transportation resource representation.Our main contributions, focused on mobility data mining over urban transportation networks, can besummarised in three groups. The first group consists of a comprehensive description of a digitalmultimodal transport infrastructure representation from global and local perspectives. The second groupis oriented towards matching diverse sensor data onto the transportation network representation,including a quantitative analysis of map-matching algorithms. The final group of contributions covers theprediction of short-term demand based on various measures of urban mobility

    Integrating tools for an effective testing of connected and automated vehicles technologies

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    The development of connected and automated driving functions involves that the interaction of autonomous/ automated vehicles with the surrounding environment will increase. Accordingly, there is a necessity for an improvement in the usage of traditional tools of the automotive development process. This is a critical problem since the classic development process used in the automotive field uses a very simplified driver model and the traffic environment, while nowadays it should contemplate a realistic representation of these elements. To overcome this issue, the authors proposed an integrated simulation environment, based on the co-simulation of Matlab/Simulink environment with simulation of urban mobility, which allows for a realistic model of vehicle dynamic, control logics, driver behaviour and traffic conditions. Simulation tests have been performed to prove the reasoning for such a tool, and to show the capabilities of the instrument. By using the proposed platform, vehicles may be modelled with a higher level of details (with respect to microscopic simulators), while the autonomous/automated driving functions can be tested in realistic traffic scenarios where the features of the road traffic environment can be varied to verify in a realistic way the level of robustness of the on-board implemented functions

    Mobility mining for time-dependent urban network modeling

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    170 p.Mobility planning, monitoring and analysis in such a complex ecosystem as a city are very challenging.Our contributions are expected to be a small step forward towards a more integrated vision of mobilitymanagement. The main hypothesis behind this thesis is that the transportation offer and the mobilitydemand are greatly coupled, and thus, both need to be thoroughly and consistently represented in a digitalmanner so as to enable good quality data-driven advanced analysis. Data-driven analytics solutions relyon measurements. However, sensors do only provide a measure of movements that have already occurred(and associated magnitudes, such as vehicles per hour). For a movement to happen there are two mainrequirements: i) the demand (the need or interest) and ii) the offer (the feasibility and resources). Inaddition, for good measurement, the sensor needs to be located at an adequate location and be able tocollect data at the right moment. All this information needs to be digitalised accordingly in order to applyadvanced data analytic methods and take advantage of good digital transportation resource representation.Our main contributions, focused on mobility data mining over urban transportation networks, can besummarised in three groups. The first group consists of a comprehensive description of a digitalmultimodal transport infrastructure representation from global and local perspectives. The second groupis oriented towards matching diverse sensor data onto the transportation network representation,including a quantitative analysis of map-matching algorithms. The final group of contributions covers theprediction of short-term demand based on various measures of urban mobility

    Optimization of vehicular networks in smart cities: from agile optimization to learnheuristics and simheuristics

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    Vehicular ad hoc networks (VANETs) are a fundamental component of intelligent transportation systems in smart cities. With the support of open and real-time data, these networks of inter-connected vehicles constitute an ‘Internet of vehicles’ with the potential to significantly enhance citizens’ mobility and last-mile delivery in urban, peri-urban, and metropolitan areas. However, the proper coordination and logistics of VANETs raise a number of optimization challenges that need to be solved. After reviewing the state of the art on the concepts of VANET optimization and open data in smart cities, this paper discusses some of the most relevant optimization challenges in this area. Since most of the optimization problems are related to the need for real-time solutions or to the consideration of uncertainty and dynamic environments, the paper also discusses how some VANET challenges can be addressed with the use of agile optimization algorithms and the combination of metaheuristics with simulation and machine learning methods. The paper also offers a numerical analysis that measures the impact of using these optimization techniques in some related problems. Our numerical analysis, based on real data from Open Data Barcelona, demonstrates that the constructive heuristic outperforms the random scenario in the CDP combined with vehicular networks, resulting in maximizing the minimum distance between facilities while meeting capacity requirements with the fewest facilities.Peer ReviewedPostprint (published version

    Individual accessibility and segregation on activity spaces: an agent-based modelling approach

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    One of the main challenges of cities is the increasing social inequality imposed by the way population groups, jobs, amenities and services, as well as the transportation infrastructure, are distributed across urban space. In this thesis, the concepts of accessibility and segregation are used to study these inequalities. They can be defined as the interaction of individuals with urban opportunities and with individuals from other population groups, respectively. Interactions are made possible by people’s activities and movement within a city, which characterise accessibility and segregation as inherently dynamic and individual-based concepts. Nevertheless, they are largely studied from a static and place-based perspective. This thesis proposes an analytical and exploratory framework for studying individual-based accessibility and segregation in cities using individuals’ travel trajectories in space and time. An agent-based simulation model was developed to generate individual trajectories dynamically, employing standard datasets such as census and OD matrices and allowing for multiple perspectives of analysis by grouping individuals based on their attributes. The model’s ability to simulate people’s trajectories realistically was validated through systematic sensitivity tests and statistical comparison with real-world trajectories from Rio de Janeiro, Brazil, and travel times from London, UK. The approach was applied to two exploratory studies: São Paulo, Brazil, and London, UK. The first revealed inequalities in accessibility by income, education and gender and also unveiled within-group differences beyond place-based patterns. The latter explored ethnic segregation, unveiling patterns of potential interaction among ethnic groups in the urban space beyond their residential and workplace locations. Those studies demonstrated how inequality in accessibility and segregation can be studied both at large metropolitan scales and at fine level of detail, using standard datasets, with modest computational requirements and ease of operationalisation. The proposed approach opens up avenues for the study of complex dynamics of interaction of urban populations in a variety of urban contexts
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