Volume 41 Issue 1
Feb.  2023
Turn off MathJax
Article Contents
Article Navigation >  Journal of Transport Information and Safety  > 2023  >  41(1): 23-33
ZHANG Chi, ZHOU Yuming, ZHANG Min, LUO Yuwei, CHEN Jiale. A Method for Identifying Traffic Congestion Resulting from Accidents on Freeways[J]. Journal of Transport Information and Safety, 2023, 41(1): 23-33. doi: 10.3963/j.jssn.1674-4861.2023.01.003
Citation: ZHANG Chi, ZHOU Yuming, ZHANG Min, LUO Yuwei, CHEN Jiale. A Method for Identifying Traffic Congestion Resulting from Accidents on Freeways[J]. Journal of Transport Information and Safety, 2023, 41(1): 23-33. doi: 10.3963/j.jssn.1674-4861.2023.01.003
shu

A Method for Identifying Traffic Congestion Resulting from Accidents on Freeways

doi: 10.3963/j.jssn.1674-4861.2023.01.003
  • 1.

    School of Highway, Chang'an University, Xi'an 710064, China

  • 2.

    School of Transportation Engineering, Chang'an University, Xi'an 710064, China

  • 3.

    Shenzhen Expressway Corporation Limited, Shenzhen 518057, Guangdong, China

  • Received Date: 2022-05-10
    Available Online: 2023-05-13
    Abstract
  • Based on the reliability of travel time, a method for identifying traffic congestion resulting from accidents is proposed, in order to quantitatively study how random congestion takes place on freeway sections and how congestion evolves under various traffic accidents. A model based on the method for studying the reliability of travel-time outlined in the Highway Capacity Manual is developed, which is calibrated based on observed data from a section of a freeway in Southwest China. A Monte Carlo simulation method is adopted to simulate various traffic accident scenarios. These traffic accidents are featured by four characteristics: location, severity, duration, and frequency. The mechanism that traffic congestion takes place and evolves is investigated and travel time index is used to represent the level of congestion on freeway sections under different traffic accidents. Study results show that ①The method presented in the Highway Capacity Manual is portable. ②When traffic volume is closed to saturation, the impact of traffic accidents taking place at the off-ramp sections is higher than those occur in the basic and on-ramp sections, and their impact is much higher under the single-lane closure scenario than that under the shoulder-closure scenario. ③When the traffic flow is close to free flow, the congestion is not sensitive to the accident severity. ④ Congestion would increase dramatically under the single-lane closure scenario when the accident lasts for more than 15 minutes at any traffic volume level. The proposed method for identifying traffic congestion can contribute to detailed exploration of the congestion patterns resulting from traffic accidents as well as classification of the congestion of freeway sections, which shall provide theoretical support to the accident management of relevant highway and transportation departments.

     

    • FullText(HTML)
  • loading
    • References(31)
  • [1]
    李淑庆, 彭囿朗, 肖莉英, 等. 道路交通事故发生机理研究现状与趋势分析[J]. 安全与环境学报, 2014, 14(3): 14-19. https://www.cnki.com.cn/Article/CJFDTOTAL-AQHJ201403005.htm

    LI S Q, PENG Y L, XIAO L Y, et al. Analysis of mechanism of the road traffic accidents in-situ and the future research trends[J]. Journal of Safety and Environment, 2014, 14(3): 14-19. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-AQHJ201403005.htm
    [2]
    国家统计局. 2021年交通事故数据[EB/OL]. (2022-1)[2022-1-17]. https://data.stats.gov.cn/search.htm?s=%E4%BA%A4%E9%80%9A%E4%BA%8B%E6%95%85.

    NATIONAL BUREAU OF STATISTICS. Traffic accident data for 2021[EB/OL]. (2022-1)[2022-1-17]. https://data.stats.gov.cn/search.htm?s=%E4%BA%A4%E9%80%9A%E4%BA%8B%E6%95%85. (in Chinese)
    [3]
    LOMAX T, TURNER S, SHUNK G, et al. Quantifying congestion. Volume 1: final report[R]. Texas: Texas Transportation Institute, 1997.
    [4]
    KOUKIS D, ANTONATOS S, ANTONIADES D, et al. A generic anonymization framework for network traffic[J]. IEEE International Conference on Communications, 2006, 19(3): 2302-2309.
    [5]
    庄斌, 杨晓光, 李克平. 道路交通拥挤事件判别准则与检测算法[J]. 中国公路学报, 2006, 19(3): 82-86. doi: 10.19721/j.cnki.1001-7372.2006.03.015

    ZHUANG B, YANG X G, LI K P. Criteria and detection algorithm of road traffic congestion events[J]. China Journal of Highway and Transport, 2006, 19(3): 82-86. (in Chinese) doi: 10.19721/j.cnki.1001-7372.2006.03.015
    [6]
    LAM T. The effect of variability of travel time on route and time-of-day choice[D]. California: University of California, 2000.
    [7]
    RAFFERTY P. Practical benefits analysis of travel time reliability from automated detection[J]. Transportation Research Record, 2009(2115): 119-126.
    [8]
    ELIASSON J. The relationship between travel time variability and road congestion[C]. 11th World Conference on Transport Research, Berkeley CA, Unites States: TRB, 2007.
    [9]
    YANG M L, LIU Y G, YOU Z S. The reliability of travel time forecasting[J]. IEEE Transactions on Intelligent Transportation Systems, 2010, 11(1): 162-171. doi: 10.1109/TITS.2009.2037136
    [10]
    黄帅凤. 基于手机数据的高速公路行程时间可靠性评估方法研究[D]. 南京: 东南大学, 2018.

    HUANG S F. Research on freeway travel time reliability evaluation method based on mobile phone data[D]. Nanjing: Southeast University, 2018. (in Chinese)
    [11]
    WOODARD D, NOGIN G, KOCH P, et al. Predicting travel time reliability using mobile phone GPS data[J]. Transportation Research Part C: Emerging Technologies, 2017(75): 30-44.
    [12]
    ASAKURA A. Reliability measures of an origin and destination pair in a deteriorated road network with variable flows[C]. 4th EURO Transportation Meeting on Transportation Networks, Newcastle, Australia: Elsevier Science BV, 1998.
    [13]
    薛晓姣, 杨宏志, 任楠. 应急条件下区域路网行程时间可靠性研究[J]. 交通信息与安全, 2019, 37(2): 25-32. doi: 10.3963/j.issn.1674-4861.2019.02.004

    XUE X J, YANG H Z, REN N. Travel time reliability of regional road network under emergency conditions[J]. Journal of Transport Information and Safety, 2019, 37(2): 25-32. (in Chinese) doi: 10.3963/j.issn.1674-4861.2019.02.004
    [14]
    冷军强. 冰雪条件下城市路网行程时间可靠性研究[D]. 哈尔滨: 哈尔滨工业大学, 2010.

    LENG J Q. Travel time reliability of urban road network under ice and snowfall conditions[D]. Harbin: Harbin Institute of Technology, 2010. (in Chinese)
    [15]
    王婧, 何杰, 吴炼. 雨天高速公路网行程时间可靠性评价方法[J]. 交通运输系统工程与信息, 2011, 11(6): 117-123.

    WANG J, HE J, WU L. Evaluating approach of travel time reliability for highway network under rain environment[J]. Journal of Transportation Systems Engineering and Information Technology, 2011, 11(6): 117-123. (in Chinese)
    [16]
    张琦, 陈红, 刘至真, 等. 降雨量对OD行程时间可靠性影响分析[J]. 交通运输系统工程与信息, 2019, 19(6): 243-249.

    ZHANG Q, CHEN H, LIU Z Z, et al. Analysis of effects of rainfall on origin-destination-based travel time reliability[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(6): 243-249. (in Chinese)
    [17]
    刘永红, 李进龙, 陈欣, 等. 先进出行信息下交通事故对行程时间可靠性的影响[J]. 交通运输系统工程与信息, 2018, 18(3): 36-41. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201803006.htm

    LIU Y H, LI J L, CHEN X, et al. Impact of incident on travel time reliability in advanced traveler information systems[J]. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(3): 36-41. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201803006.htm
    [18]
    陈玲娟, 刘海旭, 蒲云. 交通事故持续期内行程时间的可靠性研究[J]. 西南交通大学学报, 2013, 48(2): 376-382. https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT201302029.htm

    CHEN L J, LIU H X, PU Y. Travel time reliability during incident duration time[J]. Journal of Southwest Jiaotong University, 2013, 48(2): 376-382. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-XNJT201302029.htm
    [19]
    CISZEWSKAK E, ROMANOWSKAA, KUSTRAW. Analysing the impact of traffic incidents on express road traffic flow using FREEVAL[C]. 12th International Road Safety Conference GAMBIT 2018, Gdansk, Poland: EDP Sciences, 2018.
    [20]
    ASAKURA Y, KASHIWADANI M. Road network reliability caused by daily fluctuation of traffic flow[C]. 19th PTRC Summer Annual Meeting, University of Sussex, United Kingdom: TRB, 1991.
    [21]
    BHATTACHARYA M, MAZUMDER P, LOMAX R J. FD-TLM electromagnetic field simulation of high-speed Ⅲ-Ⅴ heterojunction bipolar transistor digital logic gates[C]. 14th International Conference on VLSI Design, Bangalore, India: IEEE, 2001.
    [22]
    Transportation Research Board. Highway Capacity Manual[M]. Washington, D.C. : NationalAcademy of Sciences, 2016.
    [23]
    FHWA. Travel time reliability: making it there on time, all the time[EB/OL].[2022-4-18]. http://ops.fhwa.dot.gov/publications/tt_reliability/TTR_Report.htm.
    [24]
    PU W J. Analytic relationships between travel time reliability measures[J]. Transportation Research Record, 2011(2254): 122-130.
    [25]
    LAM T C, SMALL K A. The value of time and reliability: measurement from a value pricing experiment[J]. Transportation Research Part E: Logistics and Transportation Review, 2001, 37(2-3): 231-251.
    [26]
    SCHROEDER B J, ROUPHAIL N M, AGHDASHI S. Deterministic framework and methodology for evaluating travel time reliability on freeway facilities[J]. Transportation Research Record, 2013, 2396(1): 61-70.
    [27]
    CHEN H, YOU Y S, ZHOU J B, et al. A simplified approach to estimate the urban expressway capacity after traffic accidents using a micro-simulation model[J]. Advances in Mechanical Engineering, 2013(5): 656345.
    [28]
    郑来, 顾鹏, 卢健. 基于T-S模糊故障树和贝叶斯网络的重特大交通事故成因分析[J]. 交通信息与安全, 2021, 39 (4): 43-51. doi: 10.3963/j.jssn.1674-4861.2021.04.006

    ZHENG L, GU P, LU J. A cause analysis of extraordinarily severe traffic crashesbased on T-S fuzzy fault tree and bayesiannetwork[J]. Journal of Transport Information and Safety, 2021, 39(4): 43-51. (in Chinese) doi: 10.3963/j.jssn.1674-4861.2021.04.006
    [29]
    胡骥, 闫章存, 卢小钊, 等. 基于有序Logit与Probit模型的交通事故严重性影响因素分析[J]. 安全与环境学报, 2018, 18(3): 836-843.

    HU J, YAN Z C, LU X Z, et al. Analysis for the influential factors of the accident severity based on the ordinal logit and probit models[J]. Journal of Safety and Environment, 2018, 18(3): 836-843. (in Chinese)
    [30]
    刘伟铭, 管丽萍, 尹湘源. 基于决策树的高速公路事件持续时间预测[J]. 中国公路学报, 2005, 18(1): 99-103. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL200501022.htm

    LIU W M, GUAN L P, YIN X Y. Prediction offreeway incident duration based on the decision tree[J]. China Journal Highway and Transport, 2005, 18(1): 99-103. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL200501022.htm
    [31]
    蓝岚, 路峰, 王军. 城市交通事故现场处理时间及影响因素分析[J]. 安全与环境学报, 2021, 21(3): 1173-1181. https://www.cnki.com.cn/Article/CJFDTOTAL-AQHJ202103037.htm

    LAN L, LU F, WANG J. Analysis of the on-site processing time and the influential factors of the urban traffic accidents[J]. Journal of Safety and Environment, 2021, 21(3): 1173-1181. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-AQHJ202103037.htm
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 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(12)  / Tables(8)

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (1096) PDF downloads(88) Cited by()
    Proportional views
    Related

    Copyright Editorial Office of Transport Information and Safety鄂ICP备05003336号-2

    Address：No. 1178，Heping Avenue, Wuchang, Wuhan, CHINA (430063)

    Tel：027-86580355 Email：jtjsj@vip.163.com

    Supported by: Beijing Renhe Information Technology Co. Ltd  

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return