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Automatic Generation Method of Autonomous Driving Simulation Test Scenarios Based on Tree-Structured Parzen Estimator
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Qin Qin1, Zhisheng Yang1, Daoxin Li1, Zhiwei Shen2, Xiaolin Cao3
Automobile Technology | 2025, (5) : 39 - 46
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Automobile Technology | 2025, (5): 39-46
Automatic Generation Method of Autonomous Driving Simulation Test Scenarios Based on Tree-Structured Parzen Estimator
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Qin Qin1, Zhisheng Yang1, Daoxin Li1, Zhiwei Shen2, Xiaolin Cao3
Affiliations
  • 1 Shanghai Polytechnic University, School of Intelligent Manufacturing and Control Engineering, Shanghai 201209
  • 2 School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney 2052
  • 3 College of Automotive Engineering, Jilin University, Changchun 130015
Published: 2025-05-24 doi: 10.19620/j.cnki.1000-3703.20240092
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In view of the exponential increase in the number of key scene scenarios generated in high-dimensional space, and the difficulty of traditional artificial construction or random search methods to balance coverage and efficiency, this paper proposes a search method based on single-objective Tree structure Parzen Estimator (TPE) and Multi-ObjectiveTree structure Parzen Estimator (MOTPE). A software-in-the-loop automated simulation testing framework is built by using the CARLA simulator. Taking weather elements as an example, the critical scenario generation effects of the different search algorithms are compared. The experimental results indicate that the TPE-based search method and the MOTPE-based method increase the number of key scenarios generated by 3.11 times and 2.06 times, respectively, compared to the random search method. The MOTPE method is 1.53 times better than TPE in terms of scenario quality. When combined with scenario automaed generation and testing frameworks, these methods effectively address the issue of exploding scenario numbers, allowing for the discovery of scenarios with high testing value.

Autonomous driving  /  Scenario generation  /  Tree-structured Parzen Estimator (TPE)  /  Multi-Objective Tree-structured Parzen Estimator (MOTPE)  /  CARLA
Qin Qin, Zhisheng Yang, Daoxin Li, Zhiwei Shen, Xiaolin Cao. Automatic Generation Method of Autonomous Driving Simulation Test Scenarios Based on Tree-Structured Parzen Estimator[J]. Automobile Technology, 2025 , (5) : 39 -46 . DOI: 10.19620/j.cnki.1000-3703.20240092
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doi: 10.19620/j.cnki.1000-3703.20240092
  • Online Date：2025-11-14
  • Published：2025-05-24
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  • Revised：2024-04-15
Affiliations
    1 Shanghai Polytechnic University, School of Intelligent Manufacturing and Control Engineering, Shanghai 201209
    2 School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney 2052
    3 College of Automotive Engineering, Jilin University, Changchun 130015
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https://castjournals.cast.org.cn/joweb/qcjs/EN/10.19620/j.cnki.1000-3703.20240092
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