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 the 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%.
Highlights
Significant developments in vehicle-to-everything (V2X) communication technology have been achieved during the last few years, making it possible for connected vehicles (CVs) to communicate with other traffic elements such as vehicles or road infrastructures nearby and detect the kinematic status of those elements.Unlike autonomous vehicles (AVs), which use relatively expensive on-board detection technologies, such as ultrasonic sensors, high-definition cameras, millimeter wave radar, and LiDAR, to acquire the ability to perceive the surrounding traffic environment, CVs mainly rely on V2X devices and high-precision positioning techniques, such as real-time kinematic (RTK), whose positioning accuracy can be controlled up to the millimeter level, to form the same ability at a much lower cost
This study explored the testing and assessment method of CV traffic adaptability under platoon driving scenario
The concept of traffic adaptability was defined, and an indicator system for traffic adaptability was established as the approval standard for CV traffic adaptability
Summary
Significant developments in vehicle-to-everything (V2X) communication technology have been achieved during the last few years, making it possible for connected vehicles (CVs) to communicate with other traffic elements such as vehicles or road infrastructures nearby and detect the kinematic status of those elements. This study focuses on the traffic adaptability issues of CV platoon controlled by human drivers, such as efficiency, safety, and comfortableness For this purpose, by utilizing LTE-V communication and high-precision positioning techniques, a dedicated and decentralized connected vehicle driving assistance validation system(CV-DAVS) is designed, including hardware architecture, software architecture, network architecture, communication protocol, and control logic. It can be noticed that the initial statuses of scenario-based experiments were pre-set and those experiments were executed according to specific testing scripts in most of the current research This deliberate testing mode will lead to the learning effect that human drivers will try to predict the testing purposes based on their experiences during the experiments and present different behavior patterns from those when driving daily, making the experiment results untrustworthy.
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