摘要
行车风险评估及防控是露天矿区无人运输系统的关键技术之一,为保障无人驾驶车辆在露天矿区安全运行,从露天矿区车-路-云的运输场景出发,建立了行车安全保障模型。综合车端-路侧-云平台的多源信息,对无人驾驶车辆进行行车风险等级评估并设计了相应的行车风险防控策略。行车安全保障模型由行车状态感知模块、行车风险评估模块和行车风险防控模块3部分组成。在行车风险评估方面,引入车辆前方道路坡度信息对预碰撞时间指标的阈值进行修正,引入车辆前方道路坡度及车辆载重状态信息对最小制动安全距离指标进行修正,结合预碰撞时间指标和最小制动安全距离指标提出了综合行车风险评估策略,可以对露天矿区无人驾驶车辆实时行车碰撞风险进行等级量化。然后,基于有限状态机设计了考虑不同行车风险等级的碰撞风险防控决策系统,针对不同状态制定了满足最小安全距离要求的车辆平稳制动控制策略。最后,基于PreScan与Matlab联合仿真技术,搭建了某露天矿区无人驾驶车辆的数字孪生仿真系统,并进行了水平道路场景、上下坡道场景和满载工况的车辆遇障停车仿真测试。仿真结果表明:行车风险评估模块在下坡道场景可以提前评估风险并及时制动停车,说明引入前方道路坡度信息的综合行车风险评估策略可以提高上下坡道场景车辆的行车安全;同时,通过引入车辆载重信息来修正最小制动安全距离指标,可及时评估满载车辆前方的潜在碰撞风险,提高了露天矿区满载车辆的行车安全;行车风险防控模块的紧急制动控制策略可以在10 m安全距离前实现平稳制动停车,提高了大载重车辆在遇障停车时的平稳性。
Driving risk assessment and protection is the critical technology of unmanned transportation systems in open-pits.In order to warrant the safe operation of unmanned vehicles in open-pits,the Driving Security Model(DSM)based on the vehicle-road-cloud transportation system is established.Based on the multi-source information from the vehicle,road-side,and cloud platform,the DSM can assess the driving risk level of driverless vehicles and provide corresponding driv-ing risk prevention strategies.The DSM comprises driving state awareness,driving risk assessment,and driving risk pro-tection.In terms of driving risk assessment,the threshold of pre-collision time is corrected through the road slope ahead of the vehicle,and the minimum braking safety distance is modified by the information of road slope and vehicle load state.In the meantime,a comprehensive driving risk assessment strategy is proposed,which can quantify the real-time collision risk of autonomous vehicles in open-pits.Then,a collision risk protection system that considers different driving risks is then designed based on a finite state machine.A smooth braking control strategy is developed to meet the minimum safety distance.Finally,a digital twin simulation system that corresponds to the autonomous vehicle in an open-pit is built based on the PreScan and Matlab co-simulation technology and some simulation tests in the horizontal,uphill-downhill road and full load scenes are carried out.The simulation results show that the DSM’s comprehensive risk assessment strategy can evaluate suitable risk levels in advance and timely brake,which indicates that the introduction of road slope information can improve the driving safety of the vehicle up and downhill scenes.By introducing vehicle load information,the de-signed minimum safe braking distance index can detect potential collision risk in time.The DSM’s emergency braking control strategy can smoothly stop the vehicle before 10 m safe distance,which improves the stability of heavy-duty vehicles during emer
作者
陈志发
余贵珍
张传莹
丁能根
周彬
李在友
欧阳东哲
CHEN Zhifa;YU Guizhen;ZHANG Chuanying;DING Nenggen;ZHOU Bin;LI Zaiyou;OUYANG Dongzhe(Key Laboratory of Autonomous Transportation Technology for Special Vehicles under Ministry of Industry and Information Technology,Beihang Uni-versity,Beijing 100191,China;Hefei Innovation Research Institute,Beihang University,Hefei 230012,China;Guoneng Beidian Shengli Energy Co.,Ltd.,Xilinhot 026000,China)
出处
《煤炭学报》
EI
CAS
CSCD
北大核心
2023年第4期1782-1797,共16页
Journal of China Coal Society
基金
国家重点研发计划资助项目(2020YFB1600302)。
