Efficient Speed Planning for Autonomous Driving in Dynamic Environment With Interaction Point Model

Author:

Chen Yingbing1ORCID,Xin Ren1ORCID,Cheng Jie2ORCID,Zhang Qingwen1ORCID,Mei Xiaodong2ORCID,Liu Ming1ORCID,Wang Lujia2ORCID

Affiliation:

1. Robotics Institute, HKUST, Hong Kong SAR, China

2. Robotics Institute, the HKUST, Hong Kong SAR, China

Funder

Basic and Applied Basic Research Foundation of Guangdong Province

Zhongshan Science and Technology Bureau Fundunder

Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Reference33 articles.

1. MMFN: Multi-modal fusion net for end-to-end autonomous driving;zhang;Proc Int Conf Intel Rob Syst,0

2. Pytorch: An imperative style, high-performance deep learning library;paszke;Proc 33rd Int Conf Neural Inf Process Syst,2019

3. Carla: An open urban driving simulator;dosovitskiy;Proc IEEE Conf Rob Learn,0

4. A Multilevel Collision Mitigation Approach—Its Situation Assessment, Decision Making, and Performance Tradeoffs

5. Interpretable Goal Recognition in the Presence of Occluded Factors for Autonomous Vehicles

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