Terrain-Adaptive Hierarchical Speed Planning Method for Off-Road Environments

The off-road environment is characterized by complex terrains, which have a significant impact on vehicle safety and ride comfort. To ensure the safe and smooth operation of the vehicle driving in off-road environment, the speed profile should be terrain adaptive, meaning that it can ensure the vehicle's vertical response remains within a reasonable range and the safety distance between the vehicle and obstacles can vary with the terrain. Therefore, this paper proposes a terrain-adaptive hierarchical speed planning (TAHSP) method for off-road environments. This method consists of an upper-layer three-dimensional jerk-limited time-optimal speed planning algorithm (3D JL-TOSP) and a lower-layer speed replanning algorithm. Firstly, in the upper layer, a vertically responsive speed profile for a given 3D path represented by a set of waypoints is desired. To achieve this, the relationship between time and vehicle responses is reconstructed, and the speed planning problem is formulated as a temporal optimization problem with constraints, solved iteratively using the slack convex feasible set (SCFS) algorithm. Secondly, the lower layer aims to plan a collision-free speed profile. To accurately quantify the impact of terrain on safety, a terrain adaptive safety distance model (TASDM) which comprehensively considers the impact of varying terrain and vehicle motion states on safety distance is designed. The TASDM is introduced to quantify the risk of collision, and the speed planning problem is described as a multi-stage decision problem. Terrain adaptive speed profile can be obtained by combining upper and lower layers. Finally, the results of co-simulation and hardware-in-the-loop (HiL) experiments indicate that the proposed method significantly improves the ride comfort and safety of the vehicle, the real off-road vertical responses are reduced by an average of 20.69%. Moreover, it exhibited great real-time performance and excellent generalization to off-road environments, the average success rate under different driving conditions is 96.85%.