{"title":"Comparative analysis of drowsiness and performance in conditionally automated driving and manual driving considering the effect of circadian rhythm","authors":"Qi Zhang , Chaozhong Wu , Hui Zhang , Sara Ferreira","doi":"10.1080/15472450.2022.2130292","DOIUrl":null,"url":null,"abstract":"<div><p>Drowsiness in manual driving (MD) is influenced by circadian rhythms. Conditionally automated driving (CAD) affects drivers’ drowsiness. We conducted a simulator study with 30 participants (every ten subjects in morning group, afternoon group, and evening group) to investigate the effect of circadian rhythm on the changes in drivers’ drowsiness and performance in different driving modes. Each subject was required to complete CAD experiment first and MD experiment later, and experienced 8 risk scenarios in each experiment. The self-reported Karolinska Sleepiness Scale (KSS) was recorded by an investigator every time when the subject drove past the scenario as the drowsiness measurement. The speed, acceleration, time-related metrics, and vehicle lane position were collected as the performance measurements. KSS data were statistically analyzed, and the Spearman’s Rho test was used to confirm the correlation among performance measurements, KSS, and scenarios. The result of the KSS statistical analysis showed that the effect of circadian rhythm on fatigue in MD groups is consistent with the previous studies, but the existence of CAD changes the effect of the circadian rhythm. Compared with the MD, CAD slowed down the drowsiness growth rate in the morning group and promoted the drowsiness growth rate in the evening group. The brake input rate, mean longitude acceleration, max Standard Deviation of Lane Position (SDLP), and the time to pass (TTP) were significantly related to the driver´s drowsiness in both driving modes.</p></div>","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"28 3","pages":"Pages 340-351"},"PeriodicalIF":2.8000,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Intelligent Transportation Systems","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/org/science/article/pii/S154724502300021X","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0
Abstract
Drowsiness in manual driving (MD) is influenced by circadian rhythms. Conditionally automated driving (CAD) affects drivers’ drowsiness. We conducted a simulator study with 30 participants (every ten subjects in morning group, afternoon group, and evening group) to investigate the effect of circadian rhythm on the changes in drivers’ drowsiness and performance in different driving modes. Each subject was required to complete CAD experiment first and MD experiment later, and experienced 8 risk scenarios in each experiment. The self-reported Karolinska Sleepiness Scale (KSS) was recorded by an investigator every time when the subject drove past the scenario as the drowsiness measurement. The speed, acceleration, time-related metrics, and vehicle lane position were collected as the performance measurements. KSS data were statistically analyzed, and the Spearman’s Rho test was used to confirm the correlation among performance measurements, KSS, and scenarios. The result of the KSS statistical analysis showed that the effect of circadian rhythm on fatigue in MD groups is consistent with the previous studies, but the existence of CAD changes the effect of the circadian rhythm. Compared with the MD, CAD slowed down the drowsiness growth rate in the morning group and promoted the drowsiness growth rate in the evening group. The brake input rate, mean longitude acceleration, max Standard Deviation of Lane Position (SDLP), and the time to pass (TTP) were significantly related to the driver´s drowsiness in both driving modes.
期刊介绍:
The Journal of Intelligent Transportation Systems is devoted to scholarly research on the development, planning, management, operation and evaluation of intelligent transportation systems. Intelligent transportation systems are innovative solutions that address contemporary transportation problems. They are characterized by information, dynamic feedback and automation that allow people and goods to move efficiently. They encompass the full scope of information technologies used in transportation, including control, computation and communication, as well as the algorithms, databases, models and human interfaces. The emergence of these technologies as a new pathway for transportation is relatively new.
The Journal of Intelligent Transportation Systems is especially interested in research that leads to improved planning and operation of the transportation system through the application of new technologies. The journal is particularly interested in research that adds to the scientific understanding of the impacts that intelligent transportation systems can have on accessibility, congestion, pollution, safety, security, noise, and energy and resource consumption.
The journal is inter-disciplinary, and accepts work from fields of engineering, economics, planning, policy, business and management, as well as any other disciplines that contribute to the scientific understanding of intelligent transportation systems. The journal is also multi-modal, and accepts work on intelligent transportation for all forms of ground, air and water transportation. Example topics include the role of information systems in transportation, traffic flow and control, vehicle control, routing and scheduling, traveler response to dynamic information, planning for ITS innovations, evaluations of ITS field operational tests, ITS deployment experiences, automated highway systems, vehicle control systems, diffusion of ITS, and tools/software for analysis of ITS.