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Adaptive Cruise Control System Test Scenario Generation Method Based on Reinforcement Learning Algorithm
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Deyin Zhao1, Yan Gao1, Yilin Qin1, Peixing Zhang2, Jiaming Zhang1
Automotive Digest | 2026, (2) : 32 - 36
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Automotive Digest | 2026, (2): 32-36
• Special Topic on Autonomous Driving Technology •
Adaptive Cruise Control System Test Scenario Generation Method Based on Reinforcement Learning Algorithm
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Deyin Zhao1, Yan Gao1, Yilin Qin1, Peixing Zhang2, Jiaming Zhang1
Affiliations
  • 1.Global R&D Center, China FAW Corporation Limited, Changchun 130013
  • 2.College of Automotive Engineering, Jilin University, Changchun 130025
Published: 2026-02-05 doi: 10.19822/j.cnki.1671-6329.20250156
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In order to improve the testing efficiency and comprehensiveness of the Adaptive Cruise Control (ACC) system, this paper proposes a test scenario generation method based on the Deep Deterministic Policy Gradient (DDPG) algorithm. Firstly, typical driving scenarios are designed, and a test scenario model is constructed, which includes scenario initialization, the definition of state and control variables, the agent-environment interaction mechanism, and a reward function. Then, an agent is designed based on a reinforcement learning algorithm, and generate challenging test scenarios. a reward function integrating exposure rate, adversarial factors, and unreasonable collision penalties is developed, guiding the agent to generate scenarios that are not only highly risky but also consistent with real traffic rules. Finally, simulation experiments on left/right cut-in and cut-out scenarios are conducted to validate the effectiveness of the proposed method. The results demonstrate that this approach can automatically generate critical hazardous scenarios for ACC, improve test coverage and specificity, and provide significant value for ensuring system safety testing.

Adaptive cruise control system  /  Test scenario generation  /  Reinforcement learning  /  DDPG algorithm
赵德银, 高艳, 秦熠琳, 张培兴, 张家铭. 基于强化学习算法的自适应巡航控制系统测试场景生成方法. 汽车文摘, 2026 , (2) : 32 -36 . DOI: 10.19822/j.cnki.1671-6329.20250156
Deyin Zhao, Yan Gao, Yilin Qin, Peixing Zhang, Jiaming Zhang. Adaptive Cruise Control System Test Scenario Generation Method Based on Reinforcement Learning Algorithm[J]. Automotive Digest, 2026 , (2) : 32 -36 . DOI: 10.19822/j.cnki.1671-6329.20250156
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doi: 10.19822/j.cnki.1671-6329.20250156
  • Online Date：2026-09-23
  • Published：2026-02-05
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Affiliations
    1.Global R&D Center, China FAW Corporation Limited, Changchun 130013
    2.College of Automotive Engineering, Jilin University, Changchun 130025
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