Towards Hybrid Traffic Laws for Mixed Flow of Human-driven Vehicles and Connected Autonomous Vehicles

Abstract: Hybrid traffic laws represent an innovative approach to managing mixed environments of connected autonomous vehicles (CAVs) and human-driven (HD) vehicles by introducing separate sets of regulations for each vehicle type. These laws are designed to leverage the unique capabilities of CAVs while ensuring both types of cars coexist effectively, ultimately aiming to enhance overall social welfare. This study uses the SUMO simulation platform to explore hybrid traffic laws. The main focus is on a restricted lane scenario, where we evaluate static and dynamic lane access policies under varying traffic demands and CAV penetration rates. The policies aim to minimize average passenger delay and encourage the incorporation of autonomous vehicles with higher occupancy rates. Results demonstrate that dynamic policies significantly improve traffic flow, especially at low CAV penetration rates, compared to traditional dedicated bus lane strategies. These findings highlight the potential of hybrid traffic laws to enhance traffic efficiency and accelerate the transition to autonomous technology. Other scenarios will also be presented for future work and further research.