弯道道路下驾驶行为个体特征及个体差异性研究

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (617 KB) HTML ()
输出: BibTeX | EndNote (RIS)

摘要 Driving behavior is closely related to several aspects of traffic research. Individual difference is an important factor that degrades the accuracy of driving behavior research. The individual characteristics of driving behavior were considered to study individual differences further. 22 participants' driving behavior data in curve road were collected through simulated driving. The data characteristics confirmed the existence of individual differences in driving behavior. With the use of a correlation analysis method, 12 indicators of driving behavior were analyzed to evaluate individual characteristics and differences. Results show that the mean and standard deviation of acceleration, standard deviation of steering wheel angle, and mean of throttle can explain individual characteristics and differences. These four indicators are thus important in studying individual characteristics and differences. Furthermore, the mean of steering wheel angle, mean of speed, and mean and standard deviation of brake can be used to analyze individual characteristics. The conclusions provide the foundation for accurate studies of driving behavior.

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	张兴俭
	赵晓华
	荣建
	杜洪吉

关键词 ： traffic engineering, driving behavior, simulated driving, individual characteristics, individual differences

Abstract：Driving behavior is closely related to several aspects of traffic research. Individual difference is an important factor that degrades the accuracy of driving behavior research. The individual characteristics of driving behavior were considered to study individual differences further. 22 participants' driving behavior data in curve road were collected through simulated driving. The data characteristics confirmed the existence of individual differences in driving behavior. With the use of a correlation analysis method, 12 indicators of driving behavior were analyzed to evaluate individual characteristics and differences. Results show that the mean and standard deviation of acceleration, standard deviation of steering wheel angle, and mean of throttle can explain individual characteristics and differences. These four indicators are thus important in studying individual characteristics and differences. Furthermore, the mean of steering wheel angle, mean of speed, and mean and standard deviation of brake can be used to analyze individual characteristics. The conclusions provide the foundation for accurate studies of driving behavior.

Key words： traffic engineering driving behavior simulated driving individual characteristics individual differences

收稿日期: 2014-05-03

基金资助:Supported by the National Natural Science Foundation of China (No.51108011);the Beijing Natural Science Foundation (No.8112004);the Science Research Starting Foundation of Civil Aviation University of China (No.2014QD02X)

通讯作者: ZHANG Xing-jian, E-mail:jzhyoung@163.com E-mail: jzhyoung@163.com

引用本文:

张兴俭, 赵晓华, 荣建, 杜洪吉. 弯道道路下驾驶行为个体特征及个体差异性研究[J]. Journal of Highway and Transportation Research and Development, 2015, 9(1): 99-104.
ZHANG Xing-jian, ZHAO Xiao-hua, RONG Jian, DU Hong-ji. Study on the Individual Characteristics and Differences of Driving Behavior in Curves. Journal of Highway and Transportation Research and Development, 2015, 9(1): 99-104.

链接本文:

http://manu27.magtech.com.cn/Jwk_gljtkj_en/CN/ 或 http://manu27.magtech.com.cn/Jwk_gljtkj_en/CN/Y2015/V9/I1/99

[1] FELLENDORF M, VORTISCH P. Validation of the Microscopic Traffic Flow Model VISSIM in Different Real-World Situations[C]//Transportation Research Board 80th Annual Meeting. Washington, D.C.:Transportation Research Board, 2001:2101-2109.
[2] KESTING A, TREIBER M, HELBING D. Enhanced Intelligent Driver Model to Access the Impact of Driving Strategies on Traffic Capacity[J]. Philosophical Transactions of the Royal Society A:Mathematical, Physical and Engineering Sciences, 2010, 368(1928):4585-4605.
[3] RONG J, MAO K, MA J. Effects of Individual Differences on Driving Behavior and Traffic Flow Characteristics[J]. Transportation Research Record:Journal of the Transportation Research Board, 2011, 2248(1):1-9.
[4] ARTAUD P, PLANQUE S, LAVERGNE C, et al. An On-board System for Detecting Lapses of Alertness in Car Driving[C]//Proceedings of the 14th International Technical Conference on Experimental Safety Vehicle. Washington,D.C.:National Highway Traffic Safety Administration, 1995:350-359.
[5] VERWEY W B, ZAIDEL D M. Predicting Drowsiness Ac-cidents from Personal Attributes Eye Blinks and Ongoing Driving Behavior[J]. Personality and Individual Differences, 2000, 28(1):123-142.
[6] ARNETT J J, OFFER D, FINE M A. Reckless Driving in Adolescence:‘State’ and ‘Trait’ Factors[J]. Accident Analysis & Prevention, 1997, 29(1):57-63.
[7] UNDERWOOD G, CHAPMAN P, WRIGHT S, et al. Anger while Driving[J]. Transportation Research Part F:Traffic Psychology and Behaviour, 1999, 2(1):55-68.
[8] WAKITA T, OZAWA K, MIYAJIMA C, et al. Driver Identification Using Driving Behavior Signals[J]. IEICE Transactions on Information and Systems, 2006, 89(3):1188-1194.
[9] MIYAJIMA C, NISHIWAKI Y, OZAWA K, et al. Driver Modeling Based on Driving Behavior and Its Evaluation in Driver Identification[J]. Proceedings of the IEEE, 2007, 95(2):427-437.
[10] SEKIZAWA S, INAGAKI S, SUZUKI T, et al. Modeling and Recognition of Driving Behavior Based on Stochastic Switched ARX Model[J]. IEEE Transactions on Intelligent Transportation Systems, 2007, 8(4):593-606.
[11] OLIVER N, PENTLAND A P. Graphical Models for Driver Behavior Recognition in a Smart Car[C]//Proceedings of the IEEE Intelligent Vehicles Symposium. Dearborn:IEEE, 2000:7-12.
[12] KUMAGAI T, SAKAGUCHI Y, OKUWA M, et al. Prediction of Driving Behavior through Probabilistic Inference[C]//Proceedings of the Eighth International Conference on Engineering Applications of Neural Networks. Malaga:Springer-Verlag Berlin Heidelberg, 2003:117-123.
[13] ABE K, MIYATAKE H, OGURI K. A Study on Switching AR-HMM Driving Behavior Model Depending on Driver's States[C]//Intelligent Transportation Systems Conference. Seattle:IEEE, 2007:806-811.
[14] KISHIMOTO Y, OGURI K. A Modeling Method for Predicting Driving Behavior Concerning with Driver's Past Movements[C]//Vehicular Electronics and Safety. Columbus:IEEE, 2008:132-136.
[15] OTMANI S, ROGE J, MUZET A. Sleepiness in Professional Drivers:Effect of Age and Time of Day[J]. Accident Analysis & Prevention, 2005, 37(5):930-937.
[16] PACK A I, PACK A M, RODGMAN E, et al. Characteristics of Crashes Attributed to the Driver Having Fallen Asleep[J]. Accident Analysis & Prevention, 1995, 27(6):769-775.