[1]王昊,刘振全,张志学,等.考虑双前导车的跟驰与换道联合模型[J].东南大学学报(自然科学版),2015,45(5):985-989.[doi:10.3969/j.issn.1001-0505.2015.05.029]
 Wang Hao,Liu Zhenquan,Zhang Zhixue,et al.Double-head car-following and lane-changing combined model[J].Journal of Southeast University (Natural Science Edition),2015,45(5):985-989.[doi:10.3969/j.issn.1001-0505.2015.05.029]
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考虑双前导车的跟驰与换道联合模型()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
45
期数:
2015年第5期
页码:
985-989
栏目:
交通运输工程
出版日期:
2015-09-20

文章信息/Info

Title:
Double-head car-following and lane-changing combined model
作者:
王昊12刘振全3张志学4李烨12王炜12
1东南大学城市智能交通江苏省重点实验室, 南京 210096; 2东南大学现代城市交通技术江苏高校协同创新中心, 南京 210096; 3辽宁省交通规划设计院, 沈阳 110166; 4天津市市政工程设计研究院, 天津 300051
Author(s):
Wang Hao12 Liu Zhenquan3 Zhang Zhixue4 Li Ye12 Wang Wei12
1Jiangsu Key Laboratory of Urban Intelligent Transportation System, Southeast University, Nanjing 210096, China
2Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 210096, China
3Liaoning Provincial Communication Planning and Design Institute, Shenyang 110166, China
4Tianjing Municipal Engineering Design and Research Institute, Tianjing 300051, China
关键词:
交通流 跟驰模型 换道模型 双前导车
Keywords:
traffic flow car-following model lane-changing model double-head
分类号:
U491.112
DOI:
10.3969/j.issn.1001-0505.2015.05.029
摘要:
针对现有跟驰与换道模型没有同时考虑驾驶者决策过程中前瞻性的问题,在全速差跟驰模型及概率式换道模型的基础上,提出了一种考虑双前导车的跟驰与换道联合模型,并给出了模型参数的辨识方法.应用美国NGSIM开源交通流数据库中美国I80高速公路Emeryville路段的车辆行驶轨迹数据,分别采用轨迹标定法和极大似然法对所提模型中的跟驰模型和换道模型进行了参数标定,并参照NGSIM数据库中的交通环境设计了数值仿真实验.仿真实验结果显示,交通流平均速度、车速离散度与实测数据的误差均在5.0%左右,换道次数和换道率的误差均小于20%.所提出的模型能够准确描述多车道高速公路交通流的微观特性,适合用于模拟实际多车道高速公路交通流的动态特征.
Abstract:
Due to the fact that the traditional car-following and lane-changing combined models fail to take the driver’s anticipation into consideration, based on full velocity difference car-following model and probabilistic lane-changing model, a double-head car-following and lane-changing combined model was proposed, and the method of model calibration was presented as well. The traffic data of Emeryville section in American freeway I 80 from next generation simulation(NGSIM)open data source were used to calibrate the proposed model. The trajectory-based method and maximal likelihood method were carried out to calibrate car-following model and lane-changing model, respectively. Numerical simulation according to the real freeway traffic scenario in NGSIM was designed. The results indicate that both the average speed and the speed dispersion in the simulation have the errors around 5.0%, and the errors for both the times and rate of lane changes are less than 20.0%. Therefore, the proposed model can describe the microscopic characteristics of traffic flow appropriately and simulate the real freeway traffic dynamics successfully.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2015-01-29.
作者简介: 王昊(1980—),男,博士,副教授,博士生导师,haowang@seu.edu.cn.
基金项目: 国家自然科学基金资助项目(51478113)、东南大学优秀青年教师教学科研资助项目(2242015R30028).
引用本文: 王昊,刘振全,张志学,等.考虑双前导车的跟驰与换道联合模型[J].东南大学学报:自然科学版,2015,45(5):985-989. [doi:10.3969/j.issn.1001-0505.2015.05.029]
更新日期/Last Update: 2015-09-20