面向自动驾驶的低附着弯坡路段车辆制动性能边界研究

Research on Braking Performance Boundaries of Vehicles on Low-Friction Curved Slopes for Autonomous Driving

摘要

在覆水或覆冰雪的弯坡路段，车辆在制动过程中容易发生滑移并失去控制，是多雨及寒冷地区亟待解决的重要交通安全问题。文章首先分析了低附着系数弯坡路段中车辆对路面附着力的消耗特点，在此基础上，融合公路平、纵、横断面线形参数及路面附着系数、轮胎滚动阻力、车辆行驶空气阻力等行驶力学因素，求解得到低附着系数弯坡路段中车辆行驶速度与最大制动减速度的关系。结合车辆制动滑移率，提出适用于低附着系数弯坡路段的车辆最小制动距离预测模型，并通过CarSim车辆动力学仿真试验对模型进行验证。研究可为低附着系数弯坡路段自动驾驶车辆行驶速度与制动减速度协同优化控制提供参考，也可为多雨雪地区的互通立交匝道中车辆跟驰安全分析与风险预警提供支持。

Abstract

On curved slopes covered with water, snow or ice, vehicles are prone to skidding and losing control during braking, which is a critical traffic safety issue that needs to be addressed in rainy or cold regions. The characteristics of tire-road friction capacity demand of vehicles on low-friction curved slopes were first analyzed. Based on this, the geometric design parameters of highway horizontal alignment, vertical alignment, and cross slope—were integrated with driving mechanical factors such as road friction coefficient, tire rolling resistance, and aerodynamic drag to derive the relationship between vehicle speed and maximum achievable braking deceleration. Considering the braking slip ratio, a predictive model for the minimum braking distance on low-friction curved slopes was proposed, and the model was validated through CarSim-based vehicle dynamics simulations. The study can provide a reference for the coordinated optimization of speed and braking deceleration of autonomous vehicles on low-friction curved slopes, and also offer support for car-following safety assessment and risk warning on interchange ramps in rainy or snowy regions.

关键词

交通工程 / 交通安全 / 自动驾驶 / 附着系数 / 弯坡路段 / 减速度 / 制动距离

Key words

traffic engineering / traffic safety / autonomous driving / friction coefficient / curved slopes / deceleration / braking distance

参考文献

[1] DAN H C, HE L H, XU B . Experimental investigation on skid resistance of asphalt pavement under various slippery conditions[J]. International Journal of Pavement Engineering, 2017, 18(6): 485-499.

[2] NEAMȚU G . The importance and role of tyres on road vehicles: their influence on breaking distance[J]. International Journal of Advanced Multidisciplinary Research and Studies, 2024, 4(4): 1088-1101.

[3] ANDREY J, YAGAR S . A temporal analysis of rain—related crash risk[J]. Accident Analysis & Prevention, 1993, 25(4): 465-472.

[4] 张驰, 孟良, 汪双杰, 等 . 高速公路曲线路段小客车制动行为侧滑风险仿真分析[J]. 中国公路学报, 2015, 28(12): 134-142.

[5] ZHANG C, MENG L, WANG S J, et al. Sideslip risk simulation analysis of passenger car braking behavior on expressway curved sections[J]. China Journal of Highway and Transport, 2015, 28(12): 134-142.

[6] 方成, 李元辉, 燕北瑞, 等 . 高速公路转弯匝道雨天小客车行车安全性及限速研究[J]. 交通运输研究, 2021, 7(4): 85-94.

[7] FANG C, LI Y H, YAN B R, et al. Car driving safety and speed limit on expressway turning ramps in rainy weather[J]. Transport Research, 2021, 7(4): 85-94.

[8] 刘建蓓, 罗京, 郭腾峰 . 基于安全容许速度的雨天公路可变限速方法[J]. 中国公路学报, 2015, 28(12): 128-133.

[9] LIU J B, LUO J, GUO T F . Variable speed limit method based on safe permissible speed under wet weather[J]. China Journal of Highway and Transport, 2015, 28(12): 128-133.

[10] 吴善根, 李涛, 林宣财, 等 . 基于制动减速度的高速公路停车视距研究[J]. 公路交通科技, 2021, 38(9): 51-59.

[11] WU S G, LI T, LIN X C, et al. Study on parking sight distance of expressway based on braking deceleration[J]. Journal of Highway and Transportation Research and Development, 2021, 38(9): 51-59.

[12] ABDI KORDANI A, RAHMANI O, ABDOLLAHZADEH NASIRI A S, et al. Effect of adverse weather conditions on vehicle braking distance of highways[J]. Civil Engineering Journal, 2018, 4(1): 46-57.

[13] 李志鹏, 彭涛, 王茜, 等 . 融雪剂路面上汽车制动距离计算模型[J]. 交通运输工程学报, 2012, 12(1): 50-54.

[14] LI Z P, PENG T, WANG Q, et al. Calculation model of automobile braking distance on pavement with deicing salt[J]. Journal of Traffic and Transportation Engineering, 2012, 12(1): 50-54.

[15] XIA R X, WU D H, HE J, et al. A new model of stopping sight distance of curve braking based on vehicle dynamics[J]. Discrete Dynamics in Nature and Society, 2016: 4260705.

[16] YE Z J, WEI Y, YANG S L, et al. IoT—enhanced smart road infrastructure systems for comprehensive real—time monitoring[J]. Internet of Things and Cyber—Physical Systems, 2024, 4: 235-249.

[17] GUERRERO—IBÁÑEZ J, ZEADALLY S, CONTRERAS—CASTILLO J . Sensor technologies for intelligent transportation systems[J]. Sensors, 2018, 18(4): 1212.

[18] PARDILLO MAYORA J M, JURADO PIÑA R . An assessment of the skid resistance effect on traffic safety under wet—pavement conditions[J]. Accident Analysis & Prevention, 2009, 41(4): 881-886.

[19] 赵鸿铎, 伍梦竹, 吴世涛 . 沥青道面摩擦系数随水膜厚度的变化规律[J]. 中国民航大学学报, 2015, 33(2): 47-52.

[20] ZHAO H D, WU M Z, WU S T . Variation of asphalt pavement friction coefficient with change of water film thickness[J]. Journal of Civil Aviation University of China, 2015, 33(2): 47-52.

[21] 罗京, 刘建蓓, 王元庆 . 路面水膜深度预测模型验证试验[J]. 中国公路学报, 2015, 28(12): 57-63.

[22] LUO J, LIU J B, WANG Y Q . Validation test on pavement water film depth prediction model[J]. China Journal of Highway and Transport, 2015, 28(12): 57-63.

[23] KAORU I, MAKOTO M . Skid resistance of snow— or ice—covered roads[C]// Dartmouth: Symposium on Snow Removal and Ice Control Research, 1970.

[24] 王国栋, 刘立, 孟宇, 等 . 自动驾驶汽车避撞极限研究[J]. 汽车工程, 2024, 46(6): 985-994.

[25] WANG G D, LIU L, MENG Y, et al. Research on collision avoidance limit of autonomous vehicles[J]. Automotive Engineering, 2024, 46(6): 985-994.

[26] ZHU S W, FAN X B, QI G X, et al. Review of control algorithms of vehicle anti—lock braking system[J]. Recent Patents on Engineering, 2023, 17(2): e240322202610.

基金资助

国家自然科学基金项目(52372336)