Details

Autor(en) / Beteiligte

• Haoyu Bai
• Shaojun Cai
• Nan Ye
• Hsu, David
• Wee Sun Lee

Titel

Intention-aware online POMDP planning for autonomous driving in a crowd

Ist Teil von

• 2015 IEEE International Conference on Robotics and Automation (ICRA), 2015, p.454-460

Ort / Verlag

IEEE

Erscheinungsjahr

2015

Quelle

IEEE Electronic Library Online

Beschreibungen/Notizen

• This paper presents an intention-aware online planning approach for autonomous driving amid many pedestrians. To drive near pedestrians safely, efficiently, and smoothly, autonomous vehicles must estimate unknown pedestrian intentions and hedge against the uncertainty in intention estimates in order to choose actions that are effective and robust. A key feature of our approach is to use the partially observable Markov decision process (POMDP) for systematic, robust decision making under uncertainty. Although there are concerns about the potentially high computational complexity of POMDP planning, experiments show that our POMDP-based planner runs in near real time, at 3 Hz, on a robot golf cart in a complex, dynamic environment. This indicates that POMDP planning is improving fast in computational efficiency and becoming increasingly practical as a tool for robot planning under uncertainty.