ICT Infrastructure for Cooperative, Connected and Automated Transport in Transition Areas

One of the challenges of automated road transport is to manage the coexistence of conventional and highly automated vehicles, in order to ensure an uninterrupted level of safety and efficiency. Vehicles driving at a higher automation level may have to change to a lower level of automation in a certain area under certain circumstances and certain (e.g. road and weather) conditions. The paper targets the transition phases between different levels of automation. It will review related research, introduce a concept to investigate automation level changes, present some recent research results, i.e. assessing key performance indicators for both analysing driver behaviour and traffic management in light of autonomous vehicles, an initial simulation architecture, and address further research topics on investigation of the traffic management in such areas (called "Transition Areas") when the automation level changes, and development of traffic management procedures and protocols to enable smooth coexistence of automated, cooperative, connected vehicles and conventional vehicles, especially in an urban environment

Modelling Future Mobility - Scenario Simulation at Macro Level

The aim of the report is to simulate policy scenarios for passenger transport using Europe-wide transport models, estimate their potential impacts and demonstrate how do they differ from each other and from the reference scenario for 2030. In more detail, the main objectives of the deliverable can be given as follows: - to model future multi-modal mobility scenarios for passengers formulated within the previous tasks of the project, - to simulate impacts of identified trends and selected strategies on demand, supply and technology at macro level, - to analyse impacts of selected policies and identified trends on mobility patterns such as in travel demand and modal split, - to estimate potential impacts of selected policy measures on environmental indicators via transport emissions and vehicle fleet sizes, - to compare impacts of different scenario options in quantitative terms and provide useful insights for exploring best policy scenarios and strategies for sustainable passenger transport. The research has been conducted under the OPTIMISM project which was received funding from the European Union's Seventh Framework Programme (FP7/2007-2013), grant agreement n° 284892. The report has been produced as the OPTIMISM project deliverable 3.4: Modelling Future Mobility - Scenario Simulation at Macro Level.JRC.J.1-Economics of Climate Change, Energy and Transpor

Cellular Automata Models of Road Traffic

In this paper, we give an elaborate and understandable review of traffic cellular automata (TCA) models, which are a class of computationally efficient microscopic traffic flow models. TCA models arise from the physics discipline of statistical mechanics, having the goal of reproducing the correct macroscopic behaviour based on a minimal description of microscopic interactions. After giving an overview of cellular automata (CA) models, their background and physical setup, we introduce the mathematical notations, show how to perform measurements on a TCA model's lattice of cells, as well as how to convert these quantities into real-world units and vice versa. The majority of this paper then relays an extensive account of the behavioural aspects of several TCA models encountered in literature. Already, several reviews of TCA models exist, but none of them consider all the models exclusively from the behavioural point of view. In this respect, our overview fills this void, as it focusses on the behaviour of the TCA models, by means of time-space and phase-space diagrams, and histograms showing the distributions of vehicles' speeds, space, and time gaps. In the report, we subsequently give a concise overview of TCA models that are employed in a multi-lane setting, and some of the TCA models used to describe city traffic as a two-dimensional grid of cells, or as a road network with explicitly modelled intersections. The final part of the paper illustrates some of the more common analytical approximations to single-cell TCA models.Comment: Accepted for publication in "Physics Reports". A version of this paper with high-quality images can be found at: http://phdsven.dyns.cx (go to "Papers written"

Enhanced Traffic Management Procedures of Connected and Autonomous Vehicles in Transition Areas

In light of the increasing trend towards vehicle connectivity and automation, there will be areas and situations on the roads where high automation can be granted, and others where it is not allowed or not possible. These are termed ‘Transition Areas’. Without proper traffic management, such areas may lead to vehicles issuing take-over requests (TORs), which in turn can trigger transitions of control (ToCs), or even minimum-risk manoeuvres (MRMs). In this respect, the TransAID Horizon 2020 project develops and demonstrates traffic management procedures and protocols to enable smooth coexistence of automated, connected, andconventional vehicles, with the goal of avoiding ToCs and MRMs, or at least postponing/accommodating them. Our simulations confirmed that proper traffic management, taking the traffic mix into account, can prevent drops in traffic efficiency, which in turn leads to a more performant, safer, and cleaner traffic system, when taking the capabilities of connected and autonomous vehicles into account

TransAID Deliverable 6.2/2 - Assessment of Traffic Management Procedures in Transition Areas

This Deliverable 6.2 of the TransAID project presents and evaluates the simulation results obtained for the scenarios considered during the project's first and second iterations. To this end, driver- and AV-models designed in WP3, traffic management procedures developed in WP4, and V2X communication protocols and models from WP5 were implemented within the iTETRIS simulation framework. Previous main results from Deliverable 4.2, where baseline and traffic management measures without V2X communication were compared, have been confirmed. While not all TransAID scenarios' traffic KPIs were affected, the realistic simulation of V2X communication has shown a discernible impact on some of them, which makes it an indispensable modelling aspect for a realistic performance evaluation of V2X traffic scenarios. Flaws of the first iteration's traffic management algorithms concerning wireless V2X communication and the accompanying possibility of packet loss were identified and have been addressed during the project's second iteration. Finally, lessons learned while working on these simulation results and assessments have additionally been described in the form of recommendations for the real-world prototype to be developed in WP7. We conclude that all results obtained for all scenarios when employing ideal communication confirmed the statistical trends of the results from the original TM scenarios as reported in Deliverable 4.2 where no V2X communication was considered. Furthermore, the performance evaluation of the considered scenarios and parameter combinations has shown the following, which held true in both the first and second iterations: (1) The realistic simulation of V2X communication has an impact on traffic scenarios, which makes them indispensable for a realistic performance evaluation of V2X traffic scenarios. (2) Traffic management algorithms need to account for sporadic packet loss of various message types in some way. (3) Although important, the realistic modelling and simulation of V2X communication also induces a significant computational overhead. Thus, from a general perspective, a trade-off between computation time and degree of realism should be considered

Modelling Traffic on Motorways: State-of-the-Art, Numerical Data Analysis, and Dynamic Traffic Assignment (Modelleren van verkeer op autosnelwegen: State-of-the-Art, numerieke data analyse, en dynamische verkeerstoedeling)

Zie hoger.06/06nrpages: 458status: publishe