Shi Ye , Tiantian Chen , Oscar Oviedo-Trespalacios , Yasir Ali , Taeho Oh , Inhi Kim
{"title":"在困境区,驾驶员对基于c - v2x的不同通信条件有何反应?驾驶模拟器研究","authors":"Shi Ye , Tiantian Chen , Oscar Oviedo-Trespalacios , Yasir Ali , Taeho Oh , Inhi Kim","doi":"10.1016/j.aap.2025.108208","DOIUrl":null,"url":null,"abstract":"<div><div>Drivers should react quickly in dilemma zones at signalized intersections, where ill-timed decisions may result in rear-end or angular collisions with other vehicles. Recent advancements in connected vehicle (CV) technologies, particularly cellular vehicle-to-everything (C-V2X), are expected to enhance driver decision-making by providing real-time traffic information. Despite this, most previous studies have not considered the latest C-V2X specifications, leaving critical questions unanswered about how drivers interact with and benefit from this technology in dilemma-zone scenarios. To address this gap, this study builds a co-simulation platform that integrates Unity and VISSIM to simulate four communication conditions: (1) no communication (baseline), (2) perfect communication (green-light countdown), (3) interrupted communication (green-light countdown with loading delays), and (4) communication loss due to the absence of smart infrastructure (out of service information). Sixty-two licensed drivers participated in four randomized trials, each with multiple unpredictable green-to-yellow transitions designed to capture dilemma-zone responses. Driving performance was assessed in terms of stop-or-go decisions and red-light running outcomes. Results of the random parameters binary logit model for stop-or-go decisions indicate that, compared to no communication, drivers are more inclined to proceed through the intersection when communication is lost. In contrast, perfect communication and communication interruption generally reduce this tendency. Furthermore, significant interaction effects revealed the observed heterogeneity, indicating that drivers with specific driving histories respond differently under communication interruption and loss conditions. For the red-light running outcomes, the descriptive analysis shows that under the perfect communication condition, the proportion of red-light running decreases by 3.44% among drivers. Interestingly, even interrupted communication leads to a 2.19% decrease in the proportion of red-light running outcomes. These findings demonstrate the complex ways in which C-V2X-based information can influence driver decisions, emphasizing the need for robust implementation strategies that are context-aware. This study sheds light on how drivers interact with emerging C-V2X systems and provides insights for road authorities and policymakers seeking to enhance safety and reduce crash risks at signalized intersections.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"221 ","pages":"Article 108208"},"PeriodicalIF":6.2000,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"How do the drivers react to different C-V2X-based communication conditions in dilemma zones? A driving simulator study\",\"authors\":\"Shi Ye , Tiantian Chen , Oscar Oviedo-Trespalacios , Yasir Ali , Taeho Oh , Inhi Kim\",\"doi\":\"10.1016/j.aap.2025.108208\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Drivers should react quickly in dilemma zones at signalized intersections, where ill-timed decisions may result in rear-end or angular collisions with other vehicles. Recent advancements in connected vehicle (CV) technologies, particularly cellular vehicle-to-everything (C-V2X), are expected to enhance driver decision-making by providing real-time traffic information. Despite this, most previous studies have not considered the latest C-V2X specifications, leaving critical questions unanswered about how drivers interact with and benefit from this technology in dilemma-zone scenarios. To address this gap, this study builds a co-simulation platform that integrates Unity and VISSIM to simulate four communication conditions: (1) no communication (baseline), (2) perfect communication (green-light countdown), (3) interrupted communication (green-light countdown with loading delays), and (4) communication loss due to the absence of smart infrastructure (out of service information). Sixty-two licensed drivers participated in four randomized trials, each with multiple unpredictable green-to-yellow transitions designed to capture dilemma-zone responses. Driving performance was assessed in terms of stop-or-go decisions and red-light running outcomes. Results of the random parameters binary logit model for stop-or-go decisions indicate that, compared to no communication, drivers are more inclined to proceed through the intersection when communication is lost. In contrast, perfect communication and communication interruption generally reduce this tendency. Furthermore, significant interaction effects revealed the observed heterogeneity, indicating that drivers with specific driving histories respond differently under communication interruption and loss conditions. For the red-light running outcomes, the descriptive analysis shows that under the perfect communication condition, the proportion of red-light running decreases by 3.44% among drivers. Interestingly, even interrupted communication leads to a 2.19% decrease in the proportion of red-light running outcomes. These findings demonstrate the complex ways in which C-V2X-based information can influence driver decisions, emphasizing the need for robust implementation strategies that are context-aware. This study sheds light on how drivers interact with emerging C-V2X systems and provides insights for road authorities and policymakers seeking to enhance safety and reduce crash risks at signalized intersections.</div></div>\",\"PeriodicalId\":6926,\"journal\":{\"name\":\"Accident; analysis and prevention\",\"volume\":\"221 \",\"pages\":\"Article 108208\"},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2025-08-20\",\"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/S0001457525002945\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ERGONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accident; analysis and prevention","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0001457525002945","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ERGONOMICS","Score":null,"Total":0}
How do the drivers react to different C-V2X-based communication conditions in dilemma zones? A driving simulator study
Drivers should react quickly in dilemma zones at signalized intersections, where ill-timed decisions may result in rear-end or angular collisions with other vehicles. Recent advancements in connected vehicle (CV) technologies, particularly cellular vehicle-to-everything (C-V2X), are expected to enhance driver decision-making by providing real-time traffic information. Despite this, most previous studies have not considered the latest C-V2X specifications, leaving critical questions unanswered about how drivers interact with and benefit from this technology in dilemma-zone scenarios. To address this gap, this study builds a co-simulation platform that integrates Unity and VISSIM to simulate four communication conditions: (1) no communication (baseline), (2) perfect communication (green-light countdown), (3) interrupted communication (green-light countdown with loading delays), and (4) communication loss due to the absence of smart infrastructure (out of service information). Sixty-two licensed drivers participated in four randomized trials, each with multiple unpredictable green-to-yellow transitions designed to capture dilemma-zone responses. Driving performance was assessed in terms of stop-or-go decisions and red-light running outcomes. Results of the random parameters binary logit model for stop-or-go decisions indicate that, compared to no communication, drivers are more inclined to proceed through the intersection when communication is lost. In contrast, perfect communication and communication interruption generally reduce this tendency. Furthermore, significant interaction effects revealed the observed heterogeneity, indicating that drivers with specific driving histories respond differently under communication interruption and loss conditions. For the red-light running outcomes, the descriptive analysis shows that under the perfect communication condition, the proportion of red-light running decreases by 3.44% among drivers. Interestingly, even interrupted communication leads to a 2.19% decrease in the proportion of red-light running outcomes. These findings demonstrate the complex ways in which C-V2X-based information can influence driver decisions, emphasizing the need for robust implementation strategies that are context-aware. This study sheds light on how drivers interact with emerging C-V2X systems and provides insights for road authorities and policymakers seeking to enhance safety and reduce crash risks at signalized intersections.
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.