Impact of autonomous vehicles on the performance of a signalized intersection under different mixed traffic conditions: A simulation-based investigation

Autonomous driving can overcome the limitations of stochastic human behavior. Therefore, implementing autonomous vehicles (AVs) could improve efficiency road networks. This study investigates impacts AV implementation on performance a signalized intersection considering mixed traffic environment comprising regular (RVs) and AVs through microscopic simulations. Accordingly, 24 scenarios with different rates, models, volume conditions, were developed evaluated using Vissim simulation software. The results indicated that even partial operational compared to full RV traffic. reduced vehicle delay, stopped queue length. expected improvements are primarily based rate, higher at rates (≥50%). highest moderate volumes. Compared level, partially replacing RVs free-flow conditions does not significantly impact intersection. Under congested from mitigated by high Considering models employed herein, connected (CAV) model exhibited best performance.