Two-Level Hierarchical Planning in a Known Semi-Structured Environment
Karan Narula, Stewart Worrall, E. Nebot · 2020
The application of motion planning for autonomous vehicles has been primarily focused either in highly structured or unstructured environments. However, many environments in the real-world share the characteristics of both and can be classified as semi-structured. The adaptation of the strategies from other environments to that of semi-structured, although possible, do not produce trajectories with the required characteristics, especially when the environment is dynamic. To that end, this paper introduced a two-level hierarchical planning strategy consisting of a discrete lane-network-based global planner and a Hybrid A*local planner that: (i) generates a smooth, safe and kinematically feasible path in real-time; (ii) considers structural constraints of the environment from an a priori map. Furthermore, a valid lane-network-based sub-goaling strategy is proposed for providing a reference goal during the local planning process. Simulation and live tests have been conducted to evaluate the functionality of the strategy in several case studies. The implementation choices of: (i) using an open-source highly automated driving (HAD) map framework, Lanelet2, (ii) developing as plugins to an open-source navigation stack, Move Base Flex (MBF), allow the proposed strategy to be easily adopted on other autonomous platforms.