An Integrated Framework for Virtual Testing of Autonomous Vehicles in Mixed Urban Traffic - Caroleo, Brunella; Sadeghi, Javad; Botta, Cristiana; Nikneshan, Shadi; Arnone, Maurizio (EAI Endorsed Transactions on Smart Cities, 2026)
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.
Keywords: Cooperative Connected and Automated Mobility (CCAM); Autonomous Vehicles (AV); Traffic Management; Traffic Simulation; Virtual Testing; Urban Transportation