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A Case-Based Approach for Modelling the Risk of Driver Fatigue

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Název: A Case-Based Approach for Modelling the Risk of Driver Fatigue
Autoři: Zhong, Qiaoting, Zhang, Guangnan
Přispěvatelé: Sun Yat-sen University Guangzhou (SYSU), Zhongzhi Shi, Ben Goertzel, Jiali Feng, TC 12
Zdroj: IFIP Advances in Information and Communication Technology ; 2nd International Conference on Intelligence Science (ICIS) ; https://inria.hal.science/hal-01820935 ; 2nd International Conference on Intelligence Science (ICIS), Oct 2017, Shanghai, China. pp.45-56, ⟨10.1007/978-3-319-68121-4_5⟩
Informace o vydavateli: CCSD
Springer International Publishing
Rok vydání: 2017
Témata: Intelligent information processing, Intelligent decision making, Case-based reasoning, Traffic safety management, Driver fatigue, [INFO]Computer Science [cs]
Geografické téma: Shanghai, China
Popis: Part 2: Cognitive Computing ; International audience ; Fatigue-related crashes are one of the major threats to road safety worldwide. Despite the substantial work in the domain of transportation science by both the industry and academia, there are few studies in applying case-based reasoning (CBR) approach to modelling the risk of driver fatigue. This research explores the potential for fatigued driving using a database of 16,459 traffic crashes reported from 21 cities in Guangdong province, China from 2006 to 2010. The CBR system under development differentiates between fatigued-driving and non-fatigued-driving cases based on various personal and environmental traffic characteristics. The advantage of using CBR in modelling fatigued driving has been demonstrated through empirical evaluation.
Druh dokumentu: conference object
Jazyk: English
DOI: 10.1007/978-3-319-68121-4_5
Dostupnost: https://inria.hal.science/hal-01820935
https://inria.hal.science/hal-01820935v1/document
https://inria.hal.science/hal-01820935v1/file/978-3-319-68121-4_5_Chapter.pdf
https://doi.org/10.1007/978-3-319-68121-4_5
Rights: http://creativecommons.org/licenses/by/ ; info:eu-repo/semantics/OpenAccess
Přístupové číslo: edsbas.F8222360
Databáze: BASE
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  Data: A Case-Based Approach for Modelling the Risk of Driver Fatigue
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  Data: <searchLink fieldCode="AR" term="%22Zhong%2C+Qiaoting%22">Zhong, Qiaoting</searchLink><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Guangnan%22">Zhang, Guangnan</searchLink>
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  Data: Sun Yat-sen University Guangzhou (SYSU)<br />Zhongzhi Shi<br />Ben Goertzel<br />Jiali Feng<br />TC 12
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  Data: IFIP Advances in Information and Communication Technology ; 2nd International Conference on Intelligence Science (ICIS) ; https://inria.hal.science/hal-01820935 ; 2nd International Conference on Intelligence Science (ICIS), Oct 2017, Shanghai, China. pp.45-56, ⟨10.1007/978-3-319-68121-4_5⟩
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  Data: 2017
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  Data: Part 2: Cognitive Computing ; International audience ; Fatigue-related crashes are one of the major threats to road safety worldwide. Despite the substantial work in the domain of transportation science by both the industry and academia, there are few studies in applying case-based reasoning (CBR) approach to modelling the risk of driver fatigue. This research explores the potential for fatigued driving using a database of 16,459 traffic crashes reported from 21 cities in Guangdong province, China from 2006 to 2010. The CBR system under development differentiates between fatigued-driving and non-fatigued-driving cases based on various personal and environmental traffic characteristics. The advantage of using CBR in modelling fatigued driving has been demonstrated through empirical evaluation.
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  Data: 10.1007/978-3-319-68121-4_5
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