A Car-Following Model for Mixed Traffic Flows in Intelligent Connected Vehicle Environment Considering Driver Response Characteristics

Autonomous driving technology and vehicle-to-vehicle communication make the hybrid of connected automated vehicles (CAVs) regular (RVs) a long-existing phenomenon in coming future. Among existing studies, IDM models are mostly used to study performance homogeneous traffic flow. To explore stability mixed flow, an extended intelligent driver model (IDM) based car-following was proposed for flow (MTF) with both CAVs RVs, considering headway, speed acceleration multiple front vehicles, as well response characteristics RV drivers. Through linear analysis, criterion MTFs derived, relationship among penetration rate CAVs, equilibrium velocity MTF discussed. Based on above theoretical model, numerical simulation conducted two typical scenarios starting braking. The results showed that, at microscopic scale, vehicle Cooperative Adaptive Cruise Control (CACC) mode could significantly decelerate interference from other same environment. At macroscopic increased, overall fluctuation decreased. higher density coincided MTF. When 50%, degree distribution had greatest impact exceeded 70%, little This research can provide basic support management control