Digital Twins for Assessing the Impact of Autonomous Vehicles on Built-Environment Changes

This chapter explores the multifaceted impact of Autonomous Vehicles (AVs) on the built environment and identifies limitations in traditional methodologies for prediction. Proposing a transformative solution, the chapter advocates for integrating Digital Twin technology as a dynamic and data-driven assessment tool to evaluate the impact of AVs on urban density, diversity, design, distance to other transits, and destination accessibility (5Ds). In this case, Urban Digital Twins offer real-time data analysis, modeling, and simulation of AVs interaction with the users and built environment, leveraging artificial intelligence/machine learning, and immersive 3D visualization. The discussion underscores the importance of a comprehensive Urban Digital Twin architecture to monitor and simulate the AV’s impacts on 5Ds and provide robust safety and security measures to ensure reliability of deploying AVs to the city environment. The chapter envisions a future where Urban Digital Twins play a pivotal role in informed decision-making, proactive urban planning, and adaptive development amid the transformative integration of Autonomous Vehicles.