Velocity Planning of the Autonomous Rail Rapid Transit with Consideration of Obstacles

A velocity planning strategy for the autonomous-rail rapid transit (ART) based on the pseudospectral (PS) method is proposed in this paper. The PS method is used as a replanning algorithm provided with its real-time performance. The multi-particle model is adopted in the dynamics model of ART. The energy consumption of ART is chosen as the optimization goal, and the arrival time and arrival velocity are taken as constraints to ensure economic efficiency and punctuality of the ART. When encountering obstacles such as pedestrians and lower-speed vehicles, the velocity planning strategy based on the PS method is applied to re-plan velocity of the ART. Performance of the proposed strategy is evaluated by comparing with the strategy to track the original velocity planned offline by dynamic programming (DP) algorithm. The simulation results in Matlab/Simulink- Trucksim environment illustrate that the PS based method has better real-time performance than the DP based method. The proposed planning strategy also makes ART arrive at the next station punctually, as well as leading to 36.21% reduction of energy consumption compared with the DP based method. Results of the jerk of the ART with PS strategy also show better performance in passenger comfort.