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Experimental research on horizontal curve alignment indexs of highway in high-altitude area based on driver fatigue(PDF)


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Experimental research on horizontal curve alignment indexs of highway in high-altitude area based on driver fatigue
Tian Lin1Xu Jinliang2Jia Xingli2Fang Jianhong3
1.School of Civil Engineering,Yantai University,Yantai 264005,China; 2.Key Laboratory for Special Area Highway Engineering of Ministry of Education, Chang’an University,Xi’an 710064,China; 3. Qinghai Research Institute of Transportation,Xining 810007,Ch
road engineering driver fatigue high-altitude area highways horizontal curves alignment indexs change rate of curvature
Driver fatigue is tested by experiments to ensure operational safety in horizontal curve section of highway in high-altitude area. A driver’s heart rate,oximetry and the vehicle speed are collected by a heart rate tester and a non-contact photoelectric speed sensor as the driver is driving in horizontal curve section of highway in high-altitude area. The driver’s fatigue behavior in the section is analyzed,and a relational model of the driver’s fatigue degree and the change rate of curvature is established. Experimental results show that a long straight section or a large radius circle curve followed by a circular curve with the change rate of curvature of 0.06(°)/m or the radius of 800 m in high-altitude area can relieve driver’s driving fatigue effectively.


[1] Vanlaar W,Simpson H,Dan M,et al. Fatigued and drowsy driving:A survey of attitudes,opinions and behaviors[J]. Journal of Safety Research,2008,39(3):303-309. [2]Lal S K,Craig A. A critical review of the psychophysiology of driver fatigue[J]. Biological Psychology,2001,55(7):173-194. [3]Singh R R,Conjeti S,Banerjee R. A comparative evaluation of neural network classifiers for stress level analysis of automotive drivers using physiological signals[J]. Biomedical Signal Processing & Control,2013,8(6):740-754. [4]Schier M A. Changes in EEG alpha power during simulated driving:A demonstration[J]. International Journal of Psychophysiology,2000,37(5):155-162. [5]Ronen A,Orongilad T,Gershon P. The combination of short rest and energy drink consumption as fatigue countermeasures during a prolonged drive of professional truck drivers[J]. Journal of Safety Research,2014,49(6):39-43. [6]潘晓东. 人体信息技术在道路交通环境与安全性评价中的应用[J]. 中国公路学报,2001,14(增刊):109-111. Pan Xiaodong. The application of body information technology on road and traffic environment and safety evaluation[J]. China Journal of Highway and Transport,2001,14(sup):109-111. [7] Pan X,Gotou J,Yamamoto M. Studies on evaluation of forest roads surface by driver’s psychological and physiological responses[J]. Applied Forest Science,2001,10(2):27-30. [8]乔建刚. 基于驾驶员因素的山区双车道公路关键参数研究[D]. 北京:北京工业大学建筑工程学院,2006. [9]乔建刚,温影影,周荣贵. 基于驾驶行为的高原区公路纵坡折减[J]. 公路交通科技,2012,29(1):128-133. Qiao Jiangang,Wen Yingying,Zhou Ronggui. Grade compensation of highway in plateau area based on driving behavior[J]. Journal of Highway and Transportation Research and Development,2012,29(1):128-133. [10]郑柯. 基于驾驶员心理生理反应的高速公路线形研究[D].北京:北京工业大学建筑工程学院. 2003. [11]付川云. 疲劳状态下驾驶人生理及眼动特征研究[D]. 哈尔滨:哈尔滨工业大学交通科学与工程学院,2011. [12]刘先勇,袁长迎,段保福,等. SPSS10. 0 统计分析软件与应用[M]. 北京:国防工业出版社,2001. [13]何晓群,何文卿. 应用回归分析[M]. 北京:中国人民大学出版社,2001. [14]彭艳斌,艾解清. 基于相关向量机的协商决策模型[J]. 南京理工大学学报,2012,36(4):600-605. Peng Yanbin,Ai Jieqing. Relevance vector machine based negotiation decision model[J]. Journal of Nanjing University of Science and Technology,2012,36(4):600-605. [15]杨赛,赵春霞. 基于空间概率乘积核函数的图像分类算法[J]. 南京理工大学学报,2014,38(3):325-331. Yang Sai,Zhao Chunxia. Image classification algorithm based on spatial probability product kernel[J]. Journal of Nanjing University of Science and Technology,2014,38(3):325-331.


Last Update: 2018-06-30