{"title":"驾驶员在接管过程中对周围车辆的态势感知:驾驶模拟器研究提供的证据","authors":"Lesong Jia, Chenglue Huang, Na Du","doi":"10.1016/j.trf.2024.08.016","DOIUrl":null,"url":null,"abstract":"<div><p>This study aimed to understand the influence of surrounding vehicle configuration, driving lane, and traffic density on drivers’ situational awareness (SA), takeover performance, and eye-tracking behaviors in conditionally automated driving. An experiment was conducted with the participation of 40 university students using a fixed-base driving simulator configured to simulate SAE Level 3 automation. During the experiment, participants were engaged in playing Tetris on a tablet as a non-driving related task in automated driving mode. Upon hearing an auditory takeover request, participants were instructed to take control of the vehicle, and then complete a scene reconstruction task to report their SA after transferring control back to the automated driving system. Our findings showed that drivers often neglected vehicles at their sides and rear during the takeover, which was associated with higher collision risks. Higher oncoming traffic density led to drivers’ worse SA of surrounding vehicles but more cautious driving behavior. Driving in the right lane generally resulted in smoother takeovers with lower collision risks. Interestingly, while SA did moderate the impacts of driving conditions on safety margins, a higher level of SA did not consistently relate to improved performance, especially in complex scenarios. This suggests the need for support systems that guide drivers to focus on safety–critical objects rather than simply amplifying SA in general. These insights have significant implications for the design of driver monitoring and support systems in automated vehicles.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"106 ","pages":"Pages 340-355"},"PeriodicalIF":3.5000,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1369847824002237/pdfft?md5=60b516a001050223d88884e0d602f205&pid=1-s2.0-S1369847824002237-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Drivers’ situational awareness of surrounding vehicles during takeovers: Evidence from a driving simulator study\",\"authors\":\"Lesong Jia, Chenglue Huang, Na Du\",\"doi\":\"10.1016/j.trf.2024.08.016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study aimed to understand the influence of surrounding vehicle configuration, driving lane, and traffic density on drivers’ situational awareness (SA), takeover performance, and eye-tracking behaviors in conditionally automated driving. An experiment was conducted with the participation of 40 university students using a fixed-base driving simulator configured to simulate SAE Level 3 automation. During the experiment, participants were engaged in playing Tetris on a tablet as a non-driving related task in automated driving mode. Upon hearing an auditory takeover request, participants were instructed to take control of the vehicle, and then complete a scene reconstruction task to report their SA after transferring control back to the automated driving system. Our findings showed that drivers often neglected vehicles at their sides and rear during the takeover, which was associated with higher collision risks. Higher oncoming traffic density led to drivers’ worse SA of surrounding vehicles but more cautious driving behavior. Driving in the right lane generally resulted in smoother takeovers with lower collision risks. Interestingly, while SA did moderate the impacts of driving conditions on safety margins, a higher level of SA did not consistently relate to improved performance, especially in complex scenarios. This suggests the need for support systems that guide drivers to focus on safety–critical objects rather than simply amplifying SA in general. These insights have significant implications for the design of driver monitoring and support systems in automated vehicles.</p></div>\",\"PeriodicalId\":48355,\"journal\":{\"name\":\"Transportation Research Part F-Traffic Psychology and Behaviour\",\"volume\":\"106 \",\"pages\":\"Pages 340-355\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1369847824002237/pdfft?md5=60b516a001050223d88884e0d602f205&pid=1-s2.0-S1369847824002237-main.pdf\",\"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/S1369847824002237\",\"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/S1369847824002237","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}
Drivers’ situational awareness of surrounding vehicles during takeovers: Evidence from a driving simulator study
This study aimed to understand the influence of surrounding vehicle configuration, driving lane, and traffic density on drivers’ situational awareness (SA), takeover performance, and eye-tracking behaviors in conditionally automated driving. An experiment was conducted with the participation of 40 university students using a fixed-base driving simulator configured to simulate SAE Level 3 automation. During the experiment, participants were engaged in playing Tetris on a tablet as a non-driving related task in automated driving mode. Upon hearing an auditory takeover request, participants were instructed to take control of the vehicle, and then complete a scene reconstruction task to report their SA after transferring control back to the automated driving system. Our findings showed that drivers often neglected vehicles at their sides and rear during the takeover, which was associated with higher collision risks. Higher oncoming traffic density led to drivers’ worse SA of surrounding vehicles but more cautious driving behavior. Driving in the right lane generally resulted in smoother takeovers with lower collision risks. Interestingly, while SA did moderate the impacts of driving conditions on safety margins, a higher level of SA did not consistently relate to improved performance, especially in complex scenarios. This suggests the need for support systems that guide drivers to focus on safety–critical objects rather than simply amplifying SA in general. These insights have significant implications for the design of driver monitoring and support systems in automated vehicles.
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.