A vehicle speed harmonization strategy for minimizing inter-vehicle crash risks

Recent technological advancements have facilitated the implementation of speed harmonization based on connected and automated vehicles (CAV) to prevent crashes on the road. In addition, trajectory-level vehicle controls are receiving substantial attention as sensors, wireless communications, and control systems are rapidly advancing. This study proposes a novel vehicle speed control strategy to minimize inter-vehicle crash risks in automated driving environments. The proposed methodology consists of the following three components: a risk estimation module, a risk map construction module, and a vehicle speed control module. The essence of the proposed strategy is to adjust the subject vehicle speed based on an analysis of the interactions among a subject vehicle and the surrounding vehicles. Crash risks are quantified by a fault tree analysis (FTA) method to integrate the crash occurrence potential and crash severity at every time step. A crash risk map is then constructed by projecting the integrated risk of the subject vehicle into a two-dimensional space composed of relative speed and relative spacing data. Next, the vehicle speed is continuously controlled to reach the target speed using risk map analysis to prevent a crash. The performance of the proposed methodology is evaluated by a VISSIM simulator with various traffic congestion levels and market penetration rates (MPR) of controlled vehicles. For example, an approximate 50% reduction rate of the crash potential was achievable without a loss of the operational performance of the traffic stream when all vehicles were controlled by the proposed methodology under the level of service (LOS) C conditions. This study is meaningful in that vehicle speed control is performed for the purpose of speed harmonization in a traffic stream based on a comprehensive analysis of inter-vehicle risks. It is expected that the outcome of this study will be valuable for supporting the development of vehicle control systems for preventing crashes in automated driving environments.