A Two-Lane Car-Following Model for Connected Vehicles Under Connected Traffic Environment

Connected vehicles (CVs) are conductive to promoting the transition from purely regular vehicles to purely connected autonomous vehicles where CVs are regarded as regular vehicles equipped with driver assistance systems (DASs). CVs can share status information (i.e., position, velocity, etc.) between each other through vehicle-to-vehicle communication technology, and DASs can provide CV drivers with motion suggestions (e.g., optimal velocity, etc.) based on the shared information. However, CV drivers may not completely follow these suggestions, and may combine them with their own driving experience and perception of traffic information which may be influenced by the interference of vehicles on the adjacent lane. Hence, this paper proposes a two-lane car-following model to simulate CVs under connected environment. The proposed model incorporates the compliance rate of CV drivers to DASs and considers the interference of vehicles on the adjacent lane to CV drivers by introducing the visual angle and its change rate of CV drivers. Linear stability analysis and numerical simulations of homogeneous and heterogeneous traffic flow are performed. Results show that the increases in the penetration rate of CVs and the compliance rate of CV drivers promote traffic stability, while the interference of vehicles on the adjacent lane reduces traffic stability.