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Simulation Test Scenario Generation for Autonomous Driving Based on Large Language Models
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Zhen CHEN1, Jingtai LI2, Huang GUO3, Beibei JIA4, Guangyou LI2
Chinese Journal of Automotive Engineering | 2025, 15(3) : 329 - 339
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Chinese Journal of Automotive Engineering | 2025, 15(3): 329-339
• Intelligent & Connected Technologies Section/Editor in Chief：GAO Zhenhai •
Simulation Test Scenario Generation for Autonomous Driving Based on Large Language Models
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Zhen CHEN1, Jingtai LI2, Huang GUO3, Beibei JIA4, Guangyou LI2
Affiliations
  • 1 Beijing Dysprosium Stone Data Technology Co.，Ltd.，Beijing 100176，China
  • 2 Equipment Industry Development Center， Ministry of Industry and Information Technology，Beijing 100846，China
  • 3 Bejing Saimo Technology Co.，Ltd.，Beijing 100080，China
  • 4 Beijing Electric Vehicle Co.，Ltd.，Beijing 100176，China
Published: 2025-05-20 doi: 10.3969/j.issn.2095–1469.2025.03.06
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The rapid development of autonomous driving technology has increased the demand for the authentic and diverse simulation test scenarios. However, traditional methods for constructing autonomous driving simulation scenarios heavily rely on manual editing, which is not only costly but also limited by the combination and complexity of scene elements, making it difficult to meet the comprehensive testing and validation needs of autonomous driving systems. To address this issue, this paper proposes a method for generating autonomous driving simulation test scenarios based on Large Language Models (LLMs). This approach utilizes a pre-trained LLM, enhanced through LoRA fine-tuning, and integrates a scenario language parser to produce a structured interpretive language, which is used to generate scenario files. The generated text is processed by a parser to convert it into usable scenario files, effectively addressing the issues of overly long texts and model hallucinations, while also achieving the specialization of a general model's capabilities.

artificial intelligence  /  autonomous driving  /  scenario generation model  /  simulation
Zhen CHEN, Jingtai LI, Huang GUO, Beibei JIA, Guangyou LI. Simulation Test Scenario Generation for Autonomous Driving Based on Large Language Models[J]. Chinese Journal of Automotive Engineering, 2025 , 15 (3) : 329 -339 . DOI: 10.3969/j.issn.2095–1469.2025.03.06
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Article Info
doi: 10.3969/j.issn.2095–1469.2025.03.06
  • Receive Date：2025-01-22
  • Online Date：2025-07-18
  • Published：2025-05-20
Article Data
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History
  • Received：2025-01-22
  • Revised：2025-04-09
Funding
Affiliations
    1 Beijing Dysprosium Stone Data Technology Co.，Ltd.，Beijing 100176，China
    2 Equipment Industry Development Center， Ministry of Industry and Information Technology，Beijing 100846，China
    3 Bejing Saimo Technology Co.，Ltd.，Beijing 100080，China
    4 Beijing Electric Vehicle Co.，Ltd.，Beijing 100176，China
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https://castjournals.cast.org.cn/joweb/qcgcxb/EN/10.3969/j.issn.2095–1469.2025.03.06
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