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, roadside, and cloud platform, the DSM can assess the driving risk level of driverless vehicles and provide corresponding driving risk 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 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 designed 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 emergency braking
