Test Scenarios Development and Data Collection Methods for the Evaluation of Vehicle Road Departure Prevention Systems

作者：Dan Shen, Qiang Yi, Lingxi Li, Renran Tian, Stanley Chien, Yaobin Chen, Rini Sherony · 发表于：IEEE Transactions on Intelligent Vehicles · 年份：2019 · DOI：10.1109/tiv.2019.2919430 · 被引用次数：22 · 研究领域：Traffic Prediction and Management Techniques、Traffic control and management、Traffic and Road Safety

Road departure prevention systems (RDPSs) for mitigating/avoiding road departure crashes have been developed and equipped in some high-end production vehicles in recent years. In order to provide a standardized and objective performance evaluation of RDPSs, this paper describes the test scenario development and the associated data acquisition and data postprocessing systems. Seven key variables are identified and analyzed, and their possible values are used to describe the most representative road departure test scenarios on both straight roads and curved roads. The overall structure and components of data collection and postprocessing systems for RDPSs' evaluation are devised and presented. The algorithms for computing vehicle dynamic information are developed. Experiments are performed on the test track under various scenarios. The results show that the sensing system and data postprocessing system can capture all necessary signals accurately and display the test vehicle motion profile effectively.