The increasing presence of autonomous vehicles (AVs) in urban environments introduces both opportunities and challenges, particularly regarding their interactions with traditional vehicles and other road users. This paper presents a comprehensive framework designed to assess the integration of AVs in mixed traffic scenarios. The framework is built upon real-world data collected from AV trials conducted in Turin, Italy. By leveraging traffic microsimulation along with machine learning techniques, the study proposes a framework aimed at assessing ex-ante the impacts on traffic of AVs introduction, thus constituting a relevant tool of virtual testing of CCAM (Cooperative, Connected, and Automated Mobility) trials before the physical introduction of autonomous vehicles on public roads. The integration of High-Performance Computing (HPC) ensures the efficiency of these simulations, enabling real-time analysis and testing. The proposed framework not only provides decision-makers with a tool for virtual testing of AV deployment, but also offers actionable insights into traffic management strategies. The study’s findings contribute to a deeper understanding of the role AVs can play in future urban mobility systems, particularly as cities prepare for the broader adoption of CCAM technologies.


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    Title :

    A Data-Driven Integrated Framework for Virtual Testing of Autonomous Vehicles in Mixed Traffic Scenarios


    Additional title:

    Lect.Notes Social.Inform.



    Conference:

    International Conference on Intelligent Transport Systems ; 2024 ; Pisa, Italy December 05, 2024 - December 06, 2024



    Publication date :

    2025-04-03


    Size :

    18 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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    A Geographically Distributed Simulation Framework for the Analysis of Mixed Traffic Scenarios Involving Conventional and Autonomous Vehicles

    Benatti, Simone / Schwarz, Chris / Young, Aaron et al. | British Library Conference Proceedings | 2022