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Article

A Collision Relationship-Based Driving Behavior Decision-Making Method for an Intelligent Land Vehicle at a Disorderly Intersection via DRQN

by 1,2,*, 1,2, 1,2 and 1,2
1
School of Automation, Central South University, Changsha 410083, China
2
Hunan Xiangjiang Artificial Intelligence Academy, Changsha 410000, China
*
Author to whom correspondence should be addressed.
Academic Editor: Javier Alonso Ruiz
Sensors 2022, 22(2), 636; https://doi.org/10.3390/s22020636
Received: 1 December 2021 / Revised: 31 December 2021 / Accepted: 10 January 2022 / Published: 14 January 2022
An intelligent land vehicle utilizes onboard sensors to acquire observed states at a disorderly intersection. However, partial observation of the environment occurs due to sensor noise. This causes decision failure easily. A collision relationship-based driving behavior decision-making method via deep recurrent Q network (CR-DRQN) is proposed for intelligent land vehicles. First, the collision relationship between the intelligent land vehicle and surrounding vehicles is designed as the input. The collision relationship is extracted from the observed states with the sensor noise. This avoids a CR-DRQN dimension explosion and speeds up the network training. Then, DRQN is utilized to attenuate the impact of the input noise and achieve driving behavior decision-making. Finally, some comparative experiments are conducted to verify the effectiveness of the proposed method. CR-DRQN maintains a high decision success rate at a disorderly intersection with partially observable states. In addition, the proposed method is outstanding in the aspects of safety, the ability of collision risk prediction, and comfort. View Full-Text
Keywords: deep recurrent Q network; intelligent land vehicle; decision-making; collision relationship; partially observable Markov decision process deep recurrent Q network; intelligent land vehicle; decision-making; collision relationship; partially observable Markov decision process
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MDPI and ACS Style

Yu, L.; Huo, S.; Li, K.; Wei, Y. A Collision Relationship-Based Driving Behavior Decision-Making Method for an Intelligent Land Vehicle at a Disorderly Intersection via DRQN. Sensors 2022, 22, 636. https://doi.org/10.3390/s22020636

AMA Style

Yu L, Huo S, Li K, Wei Y. A Collision Relationship-Based Driving Behavior Decision-Making Method for an Intelligent Land Vehicle at a Disorderly Intersection via DRQN. Sensors. 2022; 22(2):636. https://doi.org/10.3390/s22020636

Chicago/Turabian Style

Yu, Lingli, Shuxin Huo, Keyi Li, and Yadong Wei. 2022. "A Collision Relationship-Based Driving Behavior Decision-Making Method for an Intelligent Land Vehicle at a Disorderly Intersection via DRQN" Sensors 22, no. 2: 636. https://doi.org/10.3390/s22020636

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