No abstract

No abstract

Applications of connected vehicles (CVs) will be widely deployed in the near future owing to the rapid development of vehicle-to-everything (V2X) communication technology. However, when CVs are running in a real traffic environment, they may encounter some problems (i.e., traffic adaptability problems) that are not noticed in simulations, hardware/software-in-the-loop tests, and closed area tests. This leads to an unexpected poor performance of CV technology in a real traffic environment. Therefore, there is a need to test and assess CV technology in a real traffic environment before the deployment of CV applications. This study concentrates on a platoon driving scenario to explore the testing and assessment methods for the traffic adaptability of CV applications. The concept of traffic adaptability, which includes the aspects of efficiency, safety, and comfortableness, is defined, and an indicator system of traffic adaptability is established as the approval standard of CV traffic adaptability. A dedicated and decentralized field test system that can provide a simple CV environment was developed and used for field tests in real urban traffic environments in Beijing. Based on the data acquired from the field test, a traffic adaptability assessment of CV under platoon driving scenario utilizing the relevant indicator system is executed. The results show that with the assistance of CV technology provided by the developed field test system, that is, CV-DAVS, the traffic adaptability values of the CV platoon on the efficiency, safety, and comfort aspects are 109.98%, 113.07%, and 103.85%, respectively. Therefore, the traffic adaptability of CV under platoon driving scenario can be approved, and its overall traffic adaptability is 108.97%.INDEX TERMS connected vehicle, traffic adaptability, platoon driving, field test, testing system development, indicator analysis

With the emerging application of low-level driving automation technology, heterogeneous traffic flow mixed with human-driven vehicles and low-level autonomous vehicles is dawning. In this context, it is imperative to investigate its effect on mixed traffic flow. As a key component for adaptive cruise control (ACC) which is a practical low-level application of driving automation, the time gap policy determines the dynamic of ACC-equipped vehicles and plays a crucial role in traffic flow stability and efficiency. There are two main time gap policies used for ACC at present, namely, constant time gap (CTG) policy and variable time gap (VTG) policy. In this study, we carried out a detailed comparison between these time gap policies to investigate their potential effect on mixed traffic flow, where the analytical- and simulation-based approaches are both considered. Analytical results show that VTG policy is superior to CTG policy in stabilizing the mixed traffic flow. In addition, numerical simulations are also conducted and simulation results further support the analytical results. As for throughput, there is no difference between CTG policy and VTG policy in analytical progress when the same time gap is set at the equilibrium. However, simulation results based on an on-ramp scenario show that the throughput of mixed traffic flow with VTG policy is slightly higher than that of CTG policy. Meanwhile, the scatter of mixed traffic flow with VTG policy in the flow-density diagram gradually clusters in the middle range of density (i.e., 20–40 veh/km) with the increase of the penetration rates of ACC vehicles, where the traffic flow operates more efficiently. These results indicate that VTG policy is better than CTG policy when designing controllers for ACC in the context of traffic flow operation and control.