{"title":"基于漂移-扩散模型的交叉口黄灯信号阶段驾驶员决策过程建模","authors":"Pengfei Liu , Jing Zhao , Fanlei Zhang , Hwasoo Yeo","doi":"10.1016/j.trf.2024.07.020","DOIUrl":null,"url":null,"abstract":"<div><p>The decision-making behavior of drivers during the yellow signal phase has a significant impact on intersection safety. To analyze the decision-making process, we conducted surveys on driver behavior during yellow signal phase. A drift–diffusion model was established to analyze factors associated with driver decisions. The model can accurately predict driving decision outcomes (whether to proceed through the intersection during the yellow signal phase) and the decision-making times of different drivers. Driving data were collected using a driving simulator, including 15 participants in 210 tests in seven scenarios (3150 experimental samples). Drivers with similar driving behaviors were grouped. The model was validated using both in-sample and out-of-sample data for both individual and representative drivers. It was found that the error rate of the predicted data was approximately 7 %. Different arrival times had a significant impact on decision response time. Drivers tended to make faster decisions when the arrival time was less than 2 s due to the urgency of the decision. The findings can help understand the underlying cognitive mechanisms of driver behavior during the yellow signal phase.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling decision-making process of drivers during yellow signal phase at intersections based on drift–diffusion model\",\"authors\":\"Pengfei Liu , Jing Zhao , Fanlei Zhang , Hwasoo Yeo\",\"doi\":\"10.1016/j.trf.2024.07.020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The decision-making behavior of drivers during the yellow signal phase has a significant impact on intersection safety. To analyze the decision-making process, we conducted surveys on driver behavior during yellow signal phase. A drift–diffusion model was established to analyze factors associated with driver decisions. The model can accurately predict driving decision outcomes (whether to proceed through the intersection during the yellow signal phase) and the decision-making times of different drivers. Driving data were collected using a driving simulator, including 15 participants in 210 tests in seven scenarios (3150 experimental samples). Drivers with similar driving behaviors were grouped. The model was validated using both in-sample and out-of-sample data for both individual and representative drivers. It was found that the error rate of the predicted data was approximately 7 %. Different arrival times had a significant impact on decision response time. Drivers tended to make faster decisions when the arrival time was less than 2 s due to the urgency of the decision. The findings can help understand the underlying cognitive mechanisms of driver behavior during the yellow signal phase.</p></div>\",\"PeriodicalId\":48355,\"journal\":{\"name\":\"Transportation Research Part F-Traffic Psychology and Behaviour\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part F-Traffic Psychology and Behaviour\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S136984782400189X\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PSYCHOLOGY, APPLIED\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part F-Traffic Psychology and Behaviour","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S136984782400189X","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, APPLIED","Score":null,"Total":0}
Modeling decision-making process of drivers during yellow signal phase at intersections based on drift–diffusion model
The decision-making behavior of drivers during the yellow signal phase has a significant impact on intersection safety. To analyze the decision-making process, we conducted surveys on driver behavior during yellow signal phase. A drift–diffusion model was established to analyze factors associated with driver decisions. The model can accurately predict driving decision outcomes (whether to proceed through the intersection during the yellow signal phase) and the decision-making times of different drivers. Driving data were collected using a driving simulator, including 15 participants in 210 tests in seven scenarios (3150 experimental samples). Drivers with similar driving behaviors were grouped. The model was validated using both in-sample and out-of-sample data for both individual and representative drivers. It was found that the error rate of the predicted data was approximately 7 %. Different arrival times had a significant impact on decision response time. Drivers tended to make faster decisions when the arrival time was less than 2 s due to the urgency of the decision. The findings can help understand the underlying cognitive mechanisms of driver behavior during the yellow signal phase.
期刊介绍:
Transportation Research Part F: Traffic Psychology and Behaviour focuses on the behavioural and psychological aspects of traffic and transport. The aim of the journal is to enhance theory development, improve the quality of empirical studies and to stimulate the application of research findings in practice. TRF provides a focus and a means of communication for the considerable amount of research activities that are now being carried out in this field. The journal provides a forum for transportation researchers, psychologists, ergonomists, engineers and policy-makers with an interest in traffic and transport psychology.