{"title":"Estimating safety benefit of in-vehicle work zone safety technology alerts: A counterfactual Monte-Carlo simulation approach","authors":"Qishen Ye , Yihai Fang , Nan Zheng","doi":"10.1016/j.aap.2025.108014","DOIUrl":null,"url":null,"abstract":"<div><div>Work Zone Safety Technologies (WSTs) have exhibited great potential to improve road work zone safety by detecting safety risks and providing warnings to drivers and workers involved. Yet, it remains extremely challenging to quantify the actual safety benefits of such technologies in reducing work zone intrusion accidents, mainly due to a lack of empirical data and robust evaluation methods. This paper aims to explore the patterns of drivers’ behavioural responses when approaching work zones and estimate the safety benefits of in-vehicle WSTs. First, a VR-based driving simulation experiment was conducted to collect human behavioural data on drivers’ responses when approaching work zones in critical scenarios. Second, a Linear Mixed Effect (LME) model was developed to capture the impact of in-vehicle WST alerts and scenario criticality, i.e., speed and Time-to-Collision (TTC), on drivers’ behavioural responses. Finally, the safety benefits of in-vehicle WST alerts were estimated through counterfactual Monte-Carlo simulations of vehicle trajectories. The findings highlight the mechanism by which in-vehicle WST alerts improve driver response in various critical driving scenarios involving work zones and provide crucial evidence for future decision-making regarding the evaluation of WSTs.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"215 ","pages":"Article 108014"},"PeriodicalIF":5.7000,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accident; analysis and prevention","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0001457525001009","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ERGONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Work Zone Safety Technologies (WSTs) have exhibited great potential to improve road work zone safety by detecting safety risks and providing warnings to drivers and workers involved. Yet, it remains extremely challenging to quantify the actual safety benefits of such technologies in reducing work zone intrusion accidents, mainly due to a lack of empirical data and robust evaluation methods. This paper aims to explore the patterns of drivers’ behavioural responses when approaching work zones and estimate the safety benefits of in-vehicle WSTs. First, a VR-based driving simulation experiment was conducted to collect human behavioural data on drivers’ responses when approaching work zones in critical scenarios. Second, a Linear Mixed Effect (LME) model was developed to capture the impact of in-vehicle WST alerts and scenario criticality, i.e., speed and Time-to-Collision (TTC), on drivers’ behavioural responses. Finally, the safety benefits of in-vehicle WST alerts were estimated through counterfactual Monte-Carlo simulations of vehicle trajectories. The findings highlight the mechanism by which in-vehicle WST alerts improve driver response in various critical driving scenarios involving work zones and provide crucial evidence for future decision-making regarding the evaluation of WSTs.
期刊介绍:
Accident Analysis & Prevention provides wide coverage of the general areas relating to accidental injury and damage, including the pre-injury and immediate post-injury phases. Published papers deal with medical, legal, economic, educational, behavioral, theoretical or empirical aspects of transportation accidents, as well as with accidents at other sites. Selected topics within the scope of the Journal may include: studies of human, environmental and vehicular factors influencing the occurrence, type and severity of accidents and injury; the design, implementation and evaluation of countermeasures; biomechanics of impact and human tolerance limits to injury; modelling and statistical analysis of accident data; policy, planning and decision-making in safety.