How will autonomous vehicles affect sustainable urban mobility? A decision support framework

Autonomous vehicles (AVs) hold immense potential in revolutionizing transportation systems, aiming to boost safety, infrastructure efficiency, and sustainable energy use. However, deploying AVs in cities without seamless integration into transportation systems poses challenges to sustainable urban mobility goals. This research explores the intersection of AVs and sustainable urban mobility, focusing on mixed traffic scenarios and addressing unique challenges. The sustainability measures identified as highly important with the help of Fuzzy Analytic Hierarchy Process (F-AHP) were monitored in dynamic simulations with scenarios focused on autonomy level and induced demand. Critical penetration levels are identified through scoring techniques, and then decision support-based measures are developed. Simulations in urban mobility environments reveal critical autonomy levels requiring preventive measures: 10% for Level 1, 10% for Level 2, 20% for Level 3, 25% for Level 4, and 15% for Level 5, according to Scenario-5 (SCN5). Emphasizing the significance of monitoring and controlling these levels, a scoring system-based linear regression model aids Decision Support Systems (DSS) in overseeing autonomous vehicle (AV) autonomy distribution. As society embraces AV technology, this study supports policymakers, urban planners, and transportation authorities in prioritizing sustainability and optimizing transportation efficiency.