Combining Decision Making and Trajectory Planning for Lane Changing Using Deep Reinforcement Learning-Reference-Cited by-同舟云学术

Combining Decision Making and Trajectory Planning for Lane Changing Using Deep Reinforcement Learning

Published:2022-09 Issue:9 Volume:23 Page:16110-16136
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Li Shurong¹^ORCID,Wei Chong¹^ORCID,Wang Ying¹^ORCID

Affiliation:

1. MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/9893028/09726894.pdf?arnumber=9726894

Reference70 articles.

1. A Review of Motion Planning for Highway Autonomous Driving

2. Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model

3. A model for the structure of lane-changing decisions

4. A Hybrid Submicroscopic-Microscopic Traffic Flow Simulation Framework

5. Modelling vehicle interactions in microscopic simulation of merging and weaving

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