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

• Published in: Accident analysis and prevention Vol. 128; pp. 230 - 239
• Main Authors: Park, Hyunjin, Oh, Cheol
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.07.2019
• Subjects: Risk estimation; Risk map; Risk minimization; Speed control; Vehicle trajectory data; Risk estimation; Risk minimization; Vehicle trajectory data; Speed control; Risk map
• ISSN: 0001-4575; 1879-2057
• DOI: 10.1016/j.aap.2019.04.014

•A novel vehicle speed management strategy is proposed for preventing crashes.•Vehicle interactions are evaluated in terms of comprehensive crash risks.•VISSIM simulation experiments are conducted to investigate the feasibility of the proposed methodology.•The outcome will be valuable for supporting the management of individual vehicle speeds in automated driving environments. 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.