At present，driverless mining truck is gradually applied in the production of open-pit mine，however，the road structure of open-pit mine is complex，and the mining truck is prone to collision in driving due to the conflicting driving trajectories and perception limitations，and the existing sensor-based perception obstacle avoidance methods are prone to decisions such as emergency braking and emergency stopping and decelerating and stopping before starting，which not only cause tire wear and fuel waste，but also seriously affect the passing efficiency.In order to solve the above problems，based on the prominent features of the open-pit mine passage scene such as single traffic background，planning，organization and closure，and the advantage that driverless mine cards can accurately execute the planning speed，a mining card full passage speed optimization and collaborative planning method based on time distance constraint dissipation workshop conflict and planning speed based on adaptive trapezoidal speed planning method was proposed.The method first abstractly models the road network scenario based on road information and specifies the corresponding maximum speed limit according to the actual situation of different road sections.The second step is to combine the information of the traveling mine cards in the road network to detect the conflict between mine cards at each node in the target mine card traveling path.The third step is to add time distance constraint to each node to dissipate the conflict between mining cards according to the type of conflict between mining cards，and finally to use adaptive trapezoidal speed planning method to generate the whole collaborative passing speed scheme for the target mining card.The experiments use the traditional stop-and-go obstacle avoidance algorithm as a comparison，and the results show that the method can dissipate the conflicts between mining cards and maintain the safe distance between the front and rear vehicles without affecting the normal passage of other moving mining cards，and improve the smoothness of the speed of the target mining card in driving，while reducing the passage time by 21% compared with the traditional stop-and-go obstacle avoidance algorithm.

http://www.goldsci.ac.cn/article/2022/1005-2518/1005-2518-2022-30-3-460.shtml