会议论文

Yan, JC;He, T

英文

Proceedings of the AAAI Conference on Artificial Intelligence

2159-5399

2025

14558-14566

AAAI'25/IAAI'25/EAAI'25: Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence and Thirty-Seventh Conference on Innovative Applications of Artificial Intelligence and Fifteenth Symposium on Educational Advances in Artificial Intelligence

Philadelphia, PA

[Chen, Xiaolei;Yan, Junchi] Shanghai Jiao Tong Univ, Sch Artificial Intelligence, Shanghai, Peoples R China.^[Chen, Xiaolei;Yan, Junchi] Shanghai Jiao Tong Univ, Dept CSE, Shanghai, Peoples R China.^[Chen, Xiaolei;Yan, Junchi] Shanghai Jiao Tong Univ, MoE Lab AI, Shanghai, Peoples R China.^[Chen, Xiaolei;Liao, Wenlong;He, Tao;Peng, Pai] COWAROBOT Co Ltd, Wuhu, Peoples R China.^[He, Tao] Univ South China, Sch Elect Engn, Hengyang, Peoples R China.

Walsh, T Shah, J Kolter, Z

AAAI Press

978-1-57735-897-8

10.1609/aaai.v39i14.33595

Shanghai Municipal Science and Technology Project [22Z510901584, 2021SHZDZX0102]

本校为通讯机构

Motion planning is a critical module in autonomous driving, with the primary challenge of uncertainty caused by interactions with other participants. As most previous methods treat prediction and planning as separate tasks, it is difficult to model these interactions. Furthermore, since the route path navigates ego vehicles to a predefined destination, it provides relatively stable intentions for ego vehicles and helps constrain uncertainty. On this basis, we construct Int2Planner, an Intention-based Integrated motion Planner achieves multi-modal planning and prediction. Instead of static inte...