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Left-turn planning is one of the formidable challenges for autonomousvehicles, especially at unsignalized intersections due to the unknownintentions of oncoming vehicles. This paper addresses the challenge byproposing a critical turning point (CTP) based hierarchical planning approach.This includes a high-level candidate path generator and a low-level partiallyobservable Markov decision process (POMDP) based planner. The proposed (CTP)concept, inspired by human-driving behaviors at intersections, aims to increasethe computational efficiency of the low-level planner and to enablehuman-friendly autonomous driving. The POMDP based low-level planner takesunknown intentions of oncoming vehicles into considerations to perform lessconservative yet safe actions. With proper integration, the proposedhierarchical approach is capable of achieving safe planning results with highcommute efficiency at unsignalized intersections in real time.

Autonomous Driving at Intersections: A Critical-Turning-Point Approach for Left Turns