An Integrated Framework for Virtual Testing of Autonomous Vehicles in Mixed Urban Traffic
DOI:
https://doi.org/10.4108/eetsc.9193Keywords:
Cooperative Connected and Automated Mobility (CCAM), Autonomous Vehicles (AV), Traffic Management, Traffic Simulation, Virtual Testing, Urban TransportationAbstract
INTRODUCTION: As cities gradually begin integrating autonomous vehicles into existing transport systems, it becomes essential to assess their potential impacts on traffic dynamics and safety in a comprehensive and systematic manner — particularly through tools that can anticipate impacts before actual on-road deployment.
OBJECTIVES: This paper aims to develop a data-driven and modular framework to evaluate the integration of autonomous mobility solutions in mixed traffic conditions.
METHODS: A data-driven approach combining sensor data collected during autonomous shuttle trials with video-based behavioural analysis of road users and calibrated traffic microsimulation is employed to perform ex-ante assessment of different deployment scenarios.
RESULTS: The framework enables the evaluation of the impacts of autonomous mobility solutions on traffic performance and safety, providing insights across multiple scenarios.
CONCLUSION: The framework supports informed decision-making and enhances the understanding of how autonomous mobility can be effectively integrated into urban environments.
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Copyright (c) 2025 Brunella Caroleo, Javad Sadeghi, Cristiana Botta, Shadi Nikneshan, Maurizio Arnone
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