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作 者:夏启 王舒楠 齐连军[4] 褚立庆 徐振博 XIA Qi;WANG Shunan;QI Lianjun;CHU Liqing;XU Zhengbo(Key Laboratory of Autonomous Transportation Technology for Special Vehicles,Ministry of Industry and Information Technology,School of Transportation Science and Engineering,Beihang University,Beijing 100191,China;Beijing Tage IDriver Technology Co.,Ltd.,Beijing 100083,China;China Chemical Geology and Mine Bureau,Beijing 100013,China;Huolinhe Opencut Coal Industry Corporation Limited of Inner Mongolia,Tongliao 028001,Inner Mongolia,China)
机构地区:[1]北京航空航天大学交通科学与工程学院特种车辆无人运输技术工业和信息化部重点实验室,北京100191 [2]北京踏歌智行科技有限公司,北京100083 [3]中化地质矿山总局,北京100013 [4]内蒙古霍林河露天煤业股份有限公司,内蒙古通辽028001
出 处:《汽车工程学报》2022年第1期23-32,共10页Chinese Journal of Automotive Engineering
基 金:国家自然科学基金(51775016)。
摘 要:为防止自动驾驶条件下矿用货车发生侧翻,对依靠规划控制层实现侧翻事故的主动预防方法进行研究。针对该问题先建立矿用货车侧倾数学模型,推导静态稳定因子(Static Stability Factor,SSF)与车辆侧倾稳定极限(Roll Stability Limit,RSL)公式。利用TruckSim仿真软件完成水平路面10%横坡的阶跃转向与Fishhook转向试验,比较SSF值和RSL值对侧翻的预警效果。在此基础上,采用车辆二自由度模型估算出转弯半径,结合RSL值中的最大侧向加速度推导出极限车速公式。引入动态调节因子,得出自动驾驶矿用货车行驶的车速阈值。结果表明,考虑车辆侧翻临界参数条件,对自动驾驶系统规划控制层输出的期望车速进行限制,能有效提升自动驾驶矿用货车的行驶安全性。In order to prevent mining truck rollovers under autonomous driving conditions,the method of preventing rollover accidents based on the planning control layer was studied.Firstly,the mathematical model of the mining truck rollover was established to derive the formulas of static stability factor(SSF) and roll stability limit(RSL).Then the step steering and fishhook steering at 10% cross-fall on the road being level were simulated by using the Trucksim to compare the rollover warning effects between SSF and RSL.The speed limit was deduced based on the turning radius calculated by the 2-DOF vehicle model and the maximum lateral acceleration.Finally,the dynamic adjustment factor was introduced to obtain the speed threshold for the autonomous mining truck.The results show that considering the autonomous driving conditions and engineering experiences,limiting the maximum speed by the planning control layer can effectively prevent rollovers and improve the safety of autonomous mining trucks.
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