Editorial
An Integrated Framework for Virtual Testing of Autonomous Vehicles in Mixed Urban Traffic
@ARTICLE{10.4108/eetsc.9193, author={Brunella Caroleo and Javad Sadeghi and Cristiana Botta and Shadi Nikneshan and Maurizio Arnone}, title={An Integrated Framework for Virtual Testing of Autonomous Vehicles in Mixed Urban Traffic}, journal={EAI Endorsed Transactions on Smart Cities}, volume={8}, number={1}, publisher={EAI}, journal_a={SC}, year={2026}, month={4}, keywords={Cooperative Connected and Automated Mobility (CCAM), Autonomous Vehicles (AV), Traffic Management, Traffic Simulation, Virtual Testing, Urban Transportation}, doi={10.4108/eetsc.9193} }- Brunella Caroleo
Javad Sadeghi
Cristiana Botta
Shadi Nikneshan
Maurizio Arnone
Year: 2026
An Integrated Framework for Virtual Testing of Autonomous Vehicles in Mixed Urban Traffic
SC
EAI
DOI: 10.4108/eetsc.9193
Abstract
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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