Heterogeneous Traffic Mixing Regular and Connected Vehicles: Modeling and Stabilization

TLDR

Connected vehicles are expected to join regular traffic in coming decades, altering traffic flow characteristics. The study proposes a generic car‑following framework to model heterogeneous traffic mixing regular and connected vehicles. The authors develop this framework, instantiate it with the Intelligent Driver Model, and design a distributed feedback control driver‑assistance strategy for connected vehicles. The derived linear stability condition shows that traffic stability depends on connected‑vehicle penetration and spatial distribution, and simulations confirm that connected vehicles and the proposed driver‑assistance strategy improve stability and efficiency, especially under congestion.

Abstract

In the upcoming decades, connected vehicles will join regular vehicles to appear on roads, and the characteristics of traffic flow will be changed accordingly. To model the heterogeneous traffic mixing regular and connected vehicles, a generic car-following framework is first proposed in this paper. A linear stability condition is theoretically derived, which indicates that the stability of the heterogeneous traffic is closely related to the penetration rate and the spatial distribution of connected vehicles. The generic car-following framework is applied by taking the Intelligent Driver Model as an example, and it is shown that connected vehicles can obviously enhance the stability of traffic flow and improve traffic efficiency in particular when traffic is in congestion. Moreover, a driver assistance strategy based on distributed feedback control is developed for connected vehicles, and the simulation results show that the proposed driver assistance strategy performs satisfactorily in stabilizing traffic as well as improving traffic efficiency.