Key Laboratory of Autonomous Transportation Technology for Special Vehicles under Ministry of Industry and Information Technology, Beihang University
Hefei Innovation Research Institute, Beihang University
Guoneng Beidian Shengli Energy Co.,Ltd.

Driving risk assessment and protection is the critical technology of unmanned transportation systems in openpits.In order to warrant the safe operation of unmanned vehicles in open-pits, the Driving Security Model (DSM) based onthe vehicle-road-cloud transportation system is established. Based on the multi-source information from the vehicle, roadside, and cloud platform, the DSM can assess the driving risk level of driverless vehicles and provide corresponding drivingrisk prevention strategies. The DSM comprises driving state awareness, driving risk assessment, and driving risk protection.In terms of driving risk assessment, the threshold of pre-collision time is corrected through the road slope ahead ofthe 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 collisionrisk of autonomous vehicles in open-pits. Then, a collision risk protection system that considers different driving risks isthen designed based on a finite state machine. A smooth braking control strategy is developed to meet the minimum safetydistance. Finally, a digital twin simulation system that corresponds to the autonomous vehicle in an open-pit is built basedon the PreScan and Matlab co-simulation technology and some simulation tests in the horizontal, uphill-downhill road andfull load scenes are carried out. The simulation results show that the DSM's comprehensive risk assessment strategy canevaluate suitable risk levels in advance and timely brake, which indicates that the introduction of road slope informationcan improve the driving safety of the vehicle up and downhill scenes. By introducing vehicle load information, the designedminimum safe braking distance index can detect potential collision risk in time. The DSM's emergency brakingcontrol strategy can smoothly stop the vehicle before 10 m safe distance, which improves the stability of heavy-dutyvehicles during emergency braking.

国家重点研发计划资助项目(2020YFB1600302)

陈志发，余贵珍，张传莹，等. 露天矿区无人驾驶行车风险评估及防控策略仿真研究[J]. 煤炭学报，2023，48(4)：1782−1797

CHEN Zhifa，YU Guizhen，ZHANG Chuanying，et al. Driving risk assessment and prevention strategies for autonomous vehicle in open-pits[J]. Journal of China Coal Society，2023，48(4)：1782−1797