吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (1): 55-61.doi: 10.13229/j.cnki.jdxbgxb201501009

• 论文 • 上一篇    下一篇

考虑驾驶员特征的快速路合流区间隙接受模型构建

贾洪飞，谭云龙，李强，杨东   

  1. 吉林大学 交通学院，长春 130022
  • 收稿日期:2013-10-17 出版日期:2015-02-01 发布日期:2015-02-01
  • 通讯作者: 谭云龙(1979),男,博士研究生.研究方向:交通运输系统仿真.E-mail:sundaytyl@163.com
  • 作者简介:贾洪飞(1969)，男，教授，博士生导师.研究方向:交通规划与管理，交通运输系统仿真.E-mail:jiahf@jlu.edu.cn
  • 基金资助:
    国家自然科学基金项目(51278221).

Gap acceptance model of expressway weaving area based on driver characteristics

JIA Hong-fei, TAN Yun-long, LI Qiang, YANG Dong   

  1. College of Transportation, Jilin University, Changchun 130022, China
  • Received:2013-10-17 Online:2015-02-01 Published:2015-02-01

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摘要： 针对现有驾驶员行为模型对驾驶员特征因素考虑较少的不足，以快速路合流区为研究对象，运用模糊聚类方法与K-S检验法构建连续的驾驶员类型整合模型。在合流区换道过程中引入相互协作机制，并考虑驾驶特征差异对驾驶行为的影响，建立车道变换间隙接受模型。最后，以微观交通仿真系统MTSS为仿真平台，建立快速路合流区仿真模型，并进行了仿真验证，结果表明:仿真值与实测值的误差小于10%，表明构建的模型可以较好地表示驾驶员类型对驾驶行为的影响。

关键词: 交通运输系统工程, 驾驶员特征, 快速路合流区, 间隙接受模型, 模型验证

Abstract: The existing driver model less considers the driver characteristic factors. To overcome this shortcoming, the expressway weaving area is chosen as the research object to build a gap acceptance model. First, a large number of vehicle trajectory data is generated using the video processing software VEVID. Second, a continuous driver type integration model is proposed using fuzzy clustering theory and K-S test method. Third, the mutual cooperation mechanism is introduced into the lane change process of the expressway weaving area, and the influence of driver characteristics on the driving behavior is considered to build the gap acceptance model. Finally, the microscopic traffic simulation system MTSS is taken as the simulation platform to build a merging simulation model to validate the gap acceptance model. Results show that the error between the simulation value and real measured value is less than 10%, which indicates that the proposed gap acceptance model can be used to describe the impact of driver type on driving behavior.

Key words: engineering of communications and transportation, driver characteristic, expressway weaving area, gap acceptance model, model validation

中图分类号: 

  • U491
[1] Hidas Peter. Modeling vehicle intersections in microscopic simulation of merging and weaving[J]. Transportation Research Part C, 2005, 13(1): 37- 62.
[2] 孙剑,李克平,杨晓光. 拥挤交通流交织区车道变换行为仿真[J]. 系统仿真学报, 2009,21(13): 4174-4178.
Sun Jian, Li Ke-ping, Yang Xiao-guang. Simulation on lane-changing behavior under congested weaving sections[J]. Journal of System Simulation, 2009, 21(13): 4174-4178.
[3] Kondyli Alexandra, Elefteriadou Lily. Modeling driver behavior at freeway-ramp merges[C]∥TRB Annual Meeting, 2011, 2249:29-37.
[4] 熊胜辉,李星毅,施化吉. 基于元胞自动机的快速路交织区交通流仿真建模[J]. 计算机应用,2010,30(2):551-554.
Xiong Sheng-hui, Li Xing-yi, Shi Hua-ji. Traffic modeling and simulation of expressway weaving area based on cellular automata[J].Journal of Computer Applications, 2010, 30(2): 551-554.
[5] 江金胜,董力耕. 基于元胞自动机模型的C型交织区交通流特性[J]. 力学学报,2012,44(6):996-1004.
Jiang Jin-sheng, Dong Li-geng. Investigation on traffic flow characteristics around a type C weaving section based on cellular automaton model[J]. Chinese Journal of Theoretical and Applied Mechanics, 2012, 44(6): 996-1004.
[6] Lajunen Timo, Summala Heikki. Can we trust self-reports of driving ? Effects of impression management on driver behavior questionnaire responses[J]. Transportation Research Part F, 2003, 6(2): 97-107.
[7] 徐英俊. 城市微观交通仿真车道变换模型研究[D].长春:吉林大学,2005.
Xu Ying-jun. Study on lane-changing model in urban microscopic traffic simulation[D]. Changchun: Jilin University, 2005.
[8] Reason J.Driving errors,driving violations and accident involvement[J].Ergonomics,1995,38(5):1036-1048.
[9] Kondyli Alexandra, Elefteriadou Lily. Driver behavior at freeway-ramp merging areas: focus group findings[C]∥TRB Annual Meeting, 2009:2-22.
[10] 鹿应荣,杨印生,吕锋. 基于模糊聚类分析的车辆优化调度[J]. 吉林大学学报:工学版,2006,36(增刊2):147-151.
Lu Ying-rong,Yang Yin-sheng, Lv Feng. Optimal vehicle routing problem based on fuzzy clustering analysis[J]. Journal of Jilin University (Engineering and Technology Edition), 2006, 36(Sup.2):147-151.
[11] Tomer T. Integrated driving behavior modeling[D]. Massachusetts: Massachusetts Institute of Technology, 2003:34-43.
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