  Left-turn planning is one of the formidable challenges for autonomous
vehicles, especially at unsignalized intersections due to the unknown
intentions of oncoming vehicles. This paper addresses the challenge by
proposing a critical turning point (CTP) based hierarchical planning approach.
This includes a high-level candidate path generator and a low-level partially
observable Markov decision process (POMDP) based planner. The proposed (CTP)
concept, inspired by human-driving behaviors at intersections, aims to increase
the computational efficiency of the low-level planner and to enable
human-friendly autonomous driving. The POMDP based low-level planner takes
unknown intentions of oncoming vehicles into considerations to perform less
conservative yet safe actions. With proper integration, the proposed
hierarchical approach is capable of achieving safe planning results with high
commute efficiency at unsignalized intersections in real time.
