Connected vehicle-based road safety information system (CROSS): Framework and evaluation

Abstract

Valuable high-resolution data representing the maneuvering of both individual subject vehicles and adjacent vehicles are available in the era of the connected vehicle systems, which is also referred to as cooperative intelligent transportation systems (C-ITS). C-ITS can share useful traffic information between connected vehicles (CV) and between vehicles and infrastructure in support of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) wireless communications. An excellent feature of a C-ITS pre-deployment project in Korean freeways that CVs are equipped with an in-vehicle forward collision warning system. This technical support provides a useful opportunity to evaluate crash risks more objectively and scientifically based on the analysis of vehicle interactions, which motivates our study. The purpose of this study is to develop a road safety information system based on the analysis of CV data. The proposed system estimates individual vehicle crash risks based on the crash potential index (CPI) and further utilizes them to develop a methodology for assessing road safety risks on freeways. High CPIs were observed in toll plaza area, recurrent congestion sections, and on and off-ramp areas. An encouraging result showed that the relationship between the estimated CPI and the actual crash frequencies was statistically meaningful. In addition, the impact of the CV market penetration rate (MPR) on the feasibility of the proposed road risk monitoring method was explored by microscopic traffic simulation experiments using VISSIM. A safety evaluation equivalent to 100 % MPR was obtainable with 30 % MPR. The outcomes of this study are expected to be utilized as fundamental to support the development of novel road risk monitoring systems in C-ITS environments.