Volume 3,Issue 7
路面附着系数预估与行车风险智能预警系统研究
针对冰雪等低附着路面行车安全,本文提出“附着系数估算—LSTM 风险预测— 多参数分级预警”一体化方法。基于视觉分割、激光雷达反射特性与车路协同融合前瞻估计μ;构建LSTM 融合IMU、车速、车距等时序特征预测未来风险;以侧滑率、制动距离比、横向附着利用率及ΔT 等阈值判定危险等级并触发预警。仿真显示该方法在低附着工况下显著提升纵向控制与稳定性,附着识别前瞻准确率达99.3%,可提前数秒识别高风险状态,为冰雪道路主动安全提供支撑。
[1] 张洪 昌, 刘恒, 王舒航, 等. 基于车- 路互联的路面附着系数测算方法研究[J]. 公路交通科技,2023,40(07):176-184.
[2] 胡宏宇, 唐明弘, 高菲, 等. 基于点云反射特性的前方道路附着系数估计方法研究[J]. 汽车工程,2024,46(10):1842-1852.
[3] 刘洁美. 基于路面附着系数预估的智能汽车纵向速度规划及控制策略研究[D]. 吉林大学,2023.
[4] 赵林峰, 丰肖, 方婷, 等. 基于前车轨迹预测的智能车辆高速主动避撞方法[J]. 机械工程学报,2024,60(10):289-301.
[5]B Leng,D Jin,L Xiong,et al.Estimation of tire-road peak adhesion coefficient for intelligent electric vehicles based on camera and tire dynamics information fusion.Mechanical Systems and Signal Processing,2021,150:107275.
[6]K Singh,M Arat,S Taheri.An intelligent tire based tire-road friction estimation technique and adaptive wheel slip controller for antilock brake system.Journal of Dynamic Systems Measurement and Control–Transactions of the ASME,2013,135(3):31002–31002.
[7]M Kim,J Park,S Choi.Road type identification ahead of the tire using D-CNN and reflected ultrasonic signals.International Journal of Automotive Technology,2021,22(1):47–54.
[8]M Ergun,S Iyinam,A F Iyinam.Prediction of road surface friction coefficient using only macro-and microtexture measurements.Journal of Transportation Engineering–ASCE,2005,131(4):311–319.
[9]G Erdogan,L Alexander,R Rajamani.Estimation of tire-road friction coefficient using a novel wireless piezoelectric tire sensor.IEEE Sensors Journal,2011,11(2):267–279.
[10] 易礼智. 基于道路摩擦系数估计的智能小车紧急避障策略研究[J]. 测控技术,2017,36(09):96-99+113.
[11] 邓刚. 基于路面摩擦特性的车辆避撞系统安全行车的研究与仿真[D]. 长安大学,2015.
[12] 郭卫卫. 路面摩擦特性研究与预测[D]. 长安大学,2012.