• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 31 Issue 2
Apr.  2018
Turn off MathJax
Article Contents
YAO Zhihong, JIANG Yangsheng. Dynamic Robertson's Platoon Dispersion Model in Connected Vehicle Environment[J]. Journal of Southwest Jiaotong University, 2018, 53(2): 385-391. doi: 10.3969/j.issn.0258-2724.2018.02.023
Citation: YAO Zhihong, JIANG Yangsheng. Dynamic Robertson's Platoon Dispersion Model in Connected Vehicle Environment[J]. Journal of Southwest Jiaotong University, 2018, 53(2): 385-391. doi: 10.3969/j.issn.0258-2724.2018.02.023

Dynamic Robertson's Platoon Dispersion Model in Connected Vehicle Environment

doi: 10.3969/j.issn.0258-2724.2018.02.023
  • Received Date: 12 Dec 2016
  • Publish Date: 25 Apr 2018
  • The parameters of the traditional Robertson's platoon dispersion model are based on historical data, and thus, it cannot provide a good reflection of the dynamic characteristics of traffic flow. In order to solve this problem, a connected vehicle environment is considered, and the travel time of the vehicles is easily obtained. The relevant parameters of the Robertson's model can be estimated in real time based on this. Then, a dynamic Robertson's platoon dispersion model was proposed. Later, the relationship between the arrival flow rate of the downstream intersection and the departing flow rate of the upstream intersection was analysed using the proposed model with field collected data, and compared with those obtained using the traditional Robertson's model and actual data. The results show that the proposed model can better describe the law of dispersion in traffic flow, and the mean squared error of prediction is reduced by approximately 30.68%, compared with the traditional Robertson's model.

     

  • loading
  • ROESS R P, PRASSAS E S, MCSHANE W R. Traffic engineering:united states edition[M]. Englewood Cliffs:Prentice-Hall, 2010:5-10.
    JIANG Yangsheng, YAO Zhihong, LUO Xiaoling, et al. Heterogeneous platoon flow dispersion model based on truncated mixed simplified phase-type distribution of travel speed[J]. Journal of Advanced Transportation, 2016, 50:2160-2173. doi: 10.1002/atr.v50.8
    BONNESON J, PRATT M, VANDEHEY M. Predicting arrival flow profiles and platoon dispersion for urban street segments[J]. Transportation Research Record:Journal of the Transportation Research Board, 2010, 2173:28-35. doi: 10.3141/2173-04
    JIANG Yangsheng, YAO Zhihong, DING Xiao, et al. Mixed platoon flow dispersion model based on truncated mixed phase distribution of speed//Transportation Research Board of the National Academies.[2016-05-17]. https://pubsindex.trb.org/view/2016/C/1393937.
    JIANG Yi, LI Shuo, SHAMO D E. A platoon-based traffic signal timing algorithm for major-minor intersection types[J]. Transportation Research Part B Methodological, 2006, 40(7):543-562. doi: 10.1016/j.trb.2005.07.003
    PACEY G M. The progress of a bunch of vehicles released from a traffic signal[R]. London: Transport and Road Research Laboratory, 1956.
    GRACE M J, POTTS R B. A theory of the diffusion of traffic platoons[J]. Operations Research, 1964, 12(2):255-275. doi: 10.1287/opre.12.2.255
    ROBERTSON D I. TRANSYT: a traffic network study tool[R]. London: Transport and Road Research Laboratory, 1969. https://trid.trb.org/view/115048
    HILLIER J A, ROTHERY R. The synchronization of traffic signals for minimum delay[J]. Transportation Science, 1967, 1(2):81-94. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=10.1177/1545968308323779
    SEDDON P A. Another look at platoon dispersion 3:the recurrence relationship[J]. Traffic Engineering and Control, 1972, 13(10):442-444.
    HUNT P, ROBERTSON D, BRETHERTON R, et al. SCOOT: a traffic responsive method of coordinating signals[R]. London: Transport and Road Research Laboratory, 1981. https://trid.trb.org/view/179439
    HALL M, WILLUMSEN L G. SATURN:a simulation-assignment model for the evaluation of traffic management schemes[J]. Traffic Engineering & Control, 1980, 21(4):81-94. http://d.old.wanfangdata.com.cn/NSTLQK/NSTL_QKJJ0227422397/
    LIEBERMAN E B, ANDREWS B. TRAFLO:a new tool to evaluate transportation system management strategies[J]. Transportation Research Record:Journal of the Transportation Research Board, 1980, 772:9-15. http://trid.trb.org/view/167530
    TRACZ M. The prediction of platoon dispersion based on rectangular distribution of journey time[J]. Traffic Engineering & Control, 1975, 16(11):25-36. https://trid.trb.org/view.aspx?id=45341
    POLUS A. A study of travel time and reliability on arterial routes[J]. Transportation, 1979, 8(2):141-151. doi: 10.1007/BF00167196
    YU Lei. Calibration of platoon dispersion parameters on the basis of link travel time statistics[J]. Transportation Research Record:Journal of the Transportation Research Board, 2000, 1727:89-94. doi: 10.3141/1727-11
    BIE Yiming, LIU Zhiyuan, MA Dongfang, et al. Calibration of platoon dispersion parameter considering the impact of the number of lanes[J]. Journal of Transportation Engineering, 2013, 139(2):200-207. doi: 10.1061/(ASCE)TE.1943-5436.0000443
    PAUL B, MITRA S, MAITRA B. Calibration of Robertson's platoon dispersion model in non-lane based mixed traffic operation[J]. Transportation in Developing Economies, 2016, 2(2):1-14. doi: 10.1007/s40890-016-0016-7
    姚志洪, 蒋阳升, 吴云霞, 等.基于速度服从混合PH分布的车队离散模型[J].交通运输系统工程与信息, 2016, 16(3):133-140. doi: 10.3969/j.issn.1009-6744.2016.03.020

    YAO Zhihong, JIANG Yangsheng, WU Yunxia, et al. Platoon dispersion model based on mixed phase distribution of speed[J]. Journal of Transportation Systems Engineering and Information Technology, 2016, 16(3):133-140. doi: 10.3969/j.issn.1009-6744.2016.03.020
    姚志洪, 沈旅欧, 巫威眺, 等.基于行程时间分布的异质交通流车队离散模型[J].中国公路学报, 2016, 29(8):134-142, 151. doi: 10.3969/j.issn.1001-7372.2016.08.016

    YAO Zhihong, SHEN Lüou, WU Weitiao, et al. Heterogeneous traffic flow platoon dispersion model based on travel time distribution[J]. China Journal of Highway and Transport, 2016, 29(8):134-142, 151. doi: 10.3969/j.issn.1001-7372.2016.08.016
    巫威眺, 沈旅欧, 靳文舟.基于速度截断分布和流量的车队离散模型[J].西南交通大学学报, 2014, 49(1):126-133. doi: 10.3969/j.issn.0258-2724.2014.01.020

    WU Weitiao, SHEN Lüou, JIN Wenzhou. Platoon flow dispersion model based on truncated normal distribution of speed[J]. Journal of Southwest Jiaotong University, 2014, 49(1):126-133. doi: 10.3969/j.issn.0258-2724.2014.01.020
    LEE J, PARK B. Development and evaluation of a cooperative vehicle intersection control algorithm under the connected vehicles environment[J]. IEEE Transactions on Intelligent Transportation Systems, 2012, 13(1):81-90. doi: 10.1109/TITS.2011.2178836
    FENG Yiheng. Intelligent traffic control in a connected vehicle environment[D]. Arizona: The University of Arizona, 2015.
    TIAPRAPRASERT K, ZHANG Yunlong, WANG Xiubin, et al. Queue length estimation using connected vehicle technology for adaptive signal control[J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 16(4):2129-2140. doi: 10.1109/TITS.2015.2401007
    FENG Yiheng, HEAD K L, KHOSHMAGHAM S, et al. A real-time adaptive signal control in a connected vehicle environment[J]. Transportation Research Part C Emerging Technologies, 2015, 55:460-473. doi: 10.1016/j.trc.2015.01.007
    YU Lei. Real-time calibration of platoon dispersion model to optimizethe coordinated traffic signal timings in ATMS networks[R]. Houston: Center for TransportationTraining and Research, Texas Southern University, Houston, 1999.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(4)  / Tables(3)

    Article views(436) PDF downloads(218) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return