메타 분석을 활용한 자율주행차량 혼재 시 고위험 요인 도출 Using Meta-Analysis to Derive High-Risk Factors for Mixing Autonomous Vehicles
pp.37-47
Autonomous vehicles are widely expected to be commercialized in the near future. This would naturally lead to situations in which existing vehicles and autonomous vehicles would be on the road at the same time, which would pose a notable hazard to traffic safety. From this perspective, high-risk factors relating to this deployment should be identified to prepare measures to promote traffic safety. However, at this point, deriving high-risk factors based on actual data is problematic because autonomous vehicles have not yet been widely commercialized. In this study, we derive high-risk factors that would apply if autonomous vehicles were allowed to drive alongside vehicles driven by humans using a meta-analysis. We synthesized factors related to autonomous vehicles mentioned in the relevant literature. An analysis was conducted based on a total of 58 documents according to five keywords related to autonomous vehicles (crash factors, scenarios, predictive models, laws, and regulations). We also performed a binary meta-analysis of factors related to autonomous vehicles according to these keywords and a meta-analysis of effect size according to the relative size of factors to evaluate them comprehensively. We found that many different aspects of driving such as navigating intersections, lanes, fog, rain, acceleration and deceleration, rear-end collisions, inter-vehicle spacing, and pedestrian collisions were notable as high-risk factors. This study provides basic data to identify high-risk factors to support the development of related prediction models.
1. 서론
2. 선행연구
2.1. 자율주행차량 위험요인 관련 선행연구
2.2. 메타분석 기반 기존 교통안전관련 선행연구
2.3. 선행 연구와의 차별성
3. 분석 절차
4. 분석 결과
4.1. 요인별 상관분석 결과
4.2. 이항형 메타분석 결과
4.3. 효과크기 메타분석 결과
4.4. 이항형-효과크기 메타분석 결과 종합
5. 결론
ACKNOWLEDGMENTS
REFERENCES