• Title/Summary/Keyword: Traffic-law QA

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An Exploratory Study on ChatGPT's Performance to Answer to Police-related Traffic Laws: Using the Driver's License Test and the Road Traffic Accident Appraiser (ChatGPT의 경찰 관련 교통법규 응답 능력에 대한 탐색적 연구 - 운전면허 학과시험과 도로교통사고감정사 1차 시험을 대상으로 -)

  • Sang-yub Lee
    • Journal of Digital Policy
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    • v.2 no.4
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    • pp.1-10
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    • 2023
  • This study conducted preliminary study to identify effective ways to use ChatGPT in traffic policing by analyzing ChatGPT's responses to the driver's license test and the road traffic accident appraiser test. I collected ChatGPT responses for the driver's license test item pool and the road traffic accident appraiser test using the OpenAI API with Python code for 30 iterative experiments, and analyzed the percentage of correct answers by test, year, section, and consistency. First, the average correct answer rate for the driver's license test and the for road traffic accident appraisers test was 44.60% and 35.45%, respectively, which was lower than the pass criteria, and the correct answer rate after 2022 was lower than the average correct answer rate. Second, the percentage of correct answers by section ranged from 29.69% to 56.80%, showing a significant difference. Third, it consistently produced the same response more than 95% of the time when the answer was correct. To effectively utilize ChatGPT, it is necessary to have user expertise, evaluation data and analysis methods, design a quality traffic law corpus and periodic learning.