{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T13:53:54Z","timestamp":1790344434609,"version":"4.1.0"},"reference-count":43,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2017,2,17]],"date-time":"2017-02-17T00:00:00Z","timestamp":1487289600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Nature Science Foundation of China","award":["51678460"],"award-info":[{"award-number":["51678460"]}]},{"name":"National Nature Science Foundation of China","award":["U1664262"],"award-info":[{"award-number":["U1664262"]}]},{"name":"the Ministry of Transportation application Foundation Project of China","award":["2014319811200"],"award-info":[{"award-number":["2014319811200"]}]},{"name":"the higher institutions scientific research project of Guangxi","award":["ky2016YB151"],"award-info":[{"award-number":["ky2016YB151"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Complex traffic situations and high driving workload are the leading contributing factors to traffic crashes. There is a strong correlation between driving performance and driving workload, such as visual workload from traffic signs on highway off-ramps. This study aimed to evaluate traffic safety by analyzing drivers\u2019 behavior and performance under the cognitive workload in complex environment areas. First, the driving workload of drivers was tested based on traffic signs with different quantities of information. Forty-four drivers were recruited to conduct a traffic sign cognition experiment under static controlled environment conditions. Different complex traffic signs were used for applying the cognitive workload. The static experiment results reveal that workload is highly related to the amount of information on traffic signs and reaction time increases with the information grade, while driving experience and gender effect are not significant. This shows that the cognitive workload of subsequent driving experiments can be controlled by the amount of information on traffic signs. Second, driving characteristics and driving performance were analyzed under different secondary task driving workload levels using a driving simulator. Drivers were required to drive at the required speed on a designed highway off-ramp scene. The cognitive workload was controlled by reading traffic signs with different information, which were divided into four levels. Drivers had to make choices by pushing buttons after reading traffic signs. Meanwhile, the driving performance information was recorded. Questionnaires on objective workload were collected right after each driving task. The results show that speed maintenance and lane deviations are significantly different under different levels of cognitive workload, and the effects of driving experience and gender groups are significant. The research results can be used to analyze traffic safety in highway environments, while considering more drivers\u2019 cognitive and driving performance.<\/jats:p>","DOI":"10.3390\/ijerph14020203","type":"journal-article","created":{"date-parts":[[2017,2,17]],"date-time":"2017-02-17T12:10:34Z","timestamp":1487333434000},"page":"203","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":132,"title":["Driver\u2019s Cognitive Workload and Driving Performance under Traffic Sign Information Exposure in Complex Environments: A Case  Study of the Highways in China"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0926-9140","authenticated-orcid":false,"given":"Nengchao","family":"Lyu","sequence":"first","affiliation":[{"name":"Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China"},{"name":"Engineering Research Center for Transportation Safety, Ministry of Education, Wuhan 430063, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lian","family":"Xie","sequence":"additional","affiliation":[{"name":"Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China"},{"name":"Engineering Research Center for Transportation Safety, Ministry of Education, Wuhan 430063, China"},{"name":"School of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin 541004, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chaozhong","family":"Wu","sequence":"additional","affiliation":[{"name":"Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China"},{"name":"Engineering Research Center for Transportation Safety, Ministry of Education, Wuhan 430063, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiang","family":"Fu","sequence":"additional","affiliation":[{"name":"Traffic Management Research Institute of the Ministry of Public Security, Wuxi 214151, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao","family":"Deng","sequence":"additional","affiliation":[{"name":"Intelligent Transportation Systems Research Center, Wuhan University of Technology, Wuhan 430063, China"},{"name":"Engineering Research Center for Transportation Safety, Ministry of Education, Wuhan 430063, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,2,17]]},"reference":[{"key":"ref_1","unstructured":"AASHTO (2011). 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