Modeling and Simulation of Mixed Traffic Flow Considering Autonomous Vehicles and the Impact of Trucks

Heavy trucks play a crucial role in shaping highway traffic dynamics. Their slower speed and unique acceleration and deceleration patterns can greatly influence the efficiency and stability of mixed traffic streams. This study explores a traffic scenario involving both heavy trucks and Connected and Autonomous Vehicles (CAVs), presenting an innovative model for mixed traffic flow and establishing specific lane-changing protocols for autonomous vehicles. Utilizing numerical simulations and comparative analyses, the research explores how heavy trucks affect traffic speed and lane-changing dynamics across different levels of CAV integration and varying traffic conditions. The findings of the study indicate that with lower rates of CAV penetration, increased traffic flow heightens the frequency of vehicle interactions, resulting in more pronounced variations in traffic speed. Conversely, when CAV penetration rates are elevated, there is a marked improvement in average traffic speed, alongside a significant reduction in speed fluctuations, particularly in high-density traffic situations.