Journal of System Simulation
Abstract
Abstract: Aiming at the problem of high collision rate and low efficiency of traditional serial behavior tree in autonomous vehicle control, a solution based on improved parallel behavior tree architecture is discussed to achieve safe behavior control. A safety behavior control strategy under dynamic road conditions is proposed, and behavior models for observation, decision-making, and movement are constructed, as well as their temporal constraint relationships; an improved parallel behavior tree control architecture is proposed, which achieves parallel execution and real-time interaction of behaviors through parallel control nodes, improving the real-time performance of decision control. The results show that compared with traditional serial behavior trees, the parallel behavior tree architecture reduces collision rates by 23%, increases average speed by 5.4%, and reduces response time by 56.6%; compared with the architecture based on MPC, the collision rate is reduced by 2%, the average speed increased by 1.6%, and the response time is reduced by 15.7%
Recommended Citation
Yuan, Jianchao; Yang, Shuo; Zhang, Qi; and Li, Ge
(2025)
"Research on Behavior Control Techniques for Autonomous Vehicles Based on Parallel Behavior Tree Architecture,"
Journal of System Simulation: Vol. 37:
Iss.
6, Article 18.
DOI: 10.16182/j.issn1004731x.joss.24-0126
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol37/iss6/18
First Page
1542
Last Page
1554
CLC
TP391
Recommended Citation
Yuan Jianchao, Yang Shuo, Zhang Qi, et al. Research on Behavior Control Techniques for Autonomous Vehicles Based on Parallel Behavior Tree Architecture[J]. Journal of System Simulation, 2025, 37(6): 1542-1554.
DOI
10.16182/j.issn1004731x.joss.24-0126
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