Enhancing Mixed Traffic Flow Safety via Connected and Autonomous Vehicle Trajectory Planning with a Reinforcement Learning Approach
The longitudinal trajectory planning of connected and autonomous vehicle (CAV) has been widely studied in the literature to reduce travel time or fuel consumptions. The safety impact of CAV trajectory planning to the mixed traffic flow with both CAV and human-driven vehicle (HDV), however, is not we...
Main Authors: | Yanqiu Cheng, Chenxi Chen, Xianbiao Hu, Kuanmin Chen, Qing Tang, Yang Song |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi-Wiley
2021-01-01
|
Series: | Journal of Advanced Transportation |
Online Access: | http://dx.doi.org/10.1155/2021/6117890 |
Similar Items
-
Coordinated Intersection Signal Design for Mixed Traffic Flow of Human-Driven and Connected and Autonomous Vehicles
by: Hongsheng Qi, et al.
Published: (2020-01-01) -
Trip Cost Estimation of Connected Autonomous Vehicle Mixed Traffic Flow in a Two-Route Traffic Network
by: Zhizhen Liu, et al.
Published: (2020-01-01) -
Trajectory planning for autonomous underwater vehicles
by: Petres, Clement
Published: (2007) -
Safe trajectory planning of autonomous vehicles
by: Schouwenaars, Tom
Published: (2007) -
Influence of Lane Policies on Freeway Traffic Mixed with Manual and Connected and Autonomous Vehicles
by: Xuedong Hua, et al.
Published: (2020-01-01)