GUO Yan-yong, LIU Pan, WU Yao, ZHOU Ji-biao. Design approach of channelized island based on traffic conflict models at signalized intersection[J]. Journal of Traffic and Transportation Engineering, 2017, 17(4): 140-148.
Citation: GUO Yan-yong, LIU Pan, WU Yao, ZHOU Ji-biao. Design approach of channelized island based on traffic conflict models at signalized intersection[J]. Journal of Traffic and Transportation Engineering, 2017, 17(4): 140-148.

Design approach of channelized island based on traffic conflict models at signalized intersection

More Information
  • Author Bio:

    GUO Yan-yong(1985-), male, postdoctoral fellow, +86-25-83791816, yanyong.guo@ubc.ca

    LIU Pan(1979-), male, professor, PhD, +86-25-83791816, liupan@seu.edu.cn

  • Received Date: 2016-03-15
  • Publish Date: 2017-08-25
  • In order to optimize the channelized island design at signalized intersection, a design approach of channelized island based on traffic conflict models was proposed. Traffic conflict data, traffic flow data, traffic control data, and geometric design data were collected at twenty signalized intersections in Kunming. Adopting Bayesian method, Bayesian fix parameter traffic conflict model and Bayesian random parameter traffic conflict model were constructed. The fitting goodnesses and significant influencing factors of the models were analyzed. Based on the random parameter traffic conflict model, the formula of calculating the expected number of traffic conflicts was determined. The design standard curves of channelized islands at signalized intersections were drawn, and the type selection procedure of channelized islands was proposed. Analysis result shows that the random parameter traffic conflict model yields better fitting result than the fixed parameter model. The variable coefficients of traffic volumes (crossing through traffic volume and right-turn traffic volume), channelized island types, and right-turn design elements (right-turn yielding sign and right-turn radius) obey normal distributions. When the crossing through traffic volume increases by 1%, the traffic conflict frequency increases by 0.56%. When the right-turn traffic volume increases by 1%, the traffic conflict frequency increases by 0.53%. The four types of channelized islands can reduce the traffic conflict frequency by 12.75%, 23.37%, 16.18% and 33.64%, respectively. The right-turn yielding sign can reduce the traffic conflict by 15.03%. When the right-turn radius increases by 1%, the right-turn traffic conflict frequency reduces by 1.72%. The research conclusion indicates that the design approach of channelized islands based on the traffic conflict models is feasible.

     

  • loading
  • [1]
    Editorial Department of China Journal of Highway and Transport. Review on China's traffic engineering research progress[J]. China Journal of Highway and Transport, 2016, 29 (6): 1-161. (in Chinese). doi: 10.3969/j.issn.1001-7372.2016.06.001
    [2]
    GUO Yan-yong, LIU Pan, BAI Lu, et al. Red light running behavior of electric bicycles at signalized intersections in China[J]. Transportation Research Record, 2014 (2468): 28-37.
    [3]
    ZHAO Jing, FU Jing-yan, YANG Xiao-guang. Optimization model of dynamic lane assignment for isolated signalized intersections[J]. Journal of Tongji University: Natural Science, 2013, 41 (7): 996-1001. (in Chinese). doi: 10.3969/j.issn.0253-374x.2013.07.006
    [4]
    AUTEY J, SAYED T, ZAKI M H. Safety evaluation of rightturn smart channels using automated traffic conflict analysis[J]. Accident Analysis and Prevention, 2012, 45: 120-130. doi: 10.1016/j.aap.2011.11.015
    [5]
    MENG Qiang, QU Xiao-bo. Estimation of rear-end vehicle crash frequencies in urban road tunnels[J]. Accident Analysis and Prevention, 2012, 48: 254-263. doi: 10.1016/j.aap.2012.01.025
    [6]
    GB 50674—2011, code for planning of intersections on urban roads[S]. (in Chinese).
    [7]
    CJJ 152—2010, specification for design of intersection on urban roads[S]. (in Chinese).
    [8]
    AL-KAISY A, ROEFARO S. Channelized right-turn lanes at signalized intersections: a review of practice[C]//TRB. Proceedings of the Fourth International Symposium on Highway Geometric Design. Washington DC: Transportation Research Board, 2010: 2-5.
    [9]
    YANG Jing, SHI Yu-qian, YANG Xiao-guang. Research on the application for right turn channeling island design patterns in signalized intersections[J]. Traffic and Transportation: Academic Version, 2011, 27 (12): 124-128. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JTYH201102034.htm
    [10]
    LIANG Xiao. Research on signal intersection channeling area variable lane design theorem[D]. Changchun: Jilin University, 2008. (in Chinese).
    [11]
    DIXON K K, HIBBARD J L, NYMAN H. Right-turn treatment for signalized intersections[C]//TRB. 1999 Proceedings of Transportation Research Circular E-C019: Urban Street Symposium. Washington DC: Transportation Research Board, 1999: 1-11.
    [12]
    HAN Yin, XING Bing, YAO Jiao, et al. Optimal model of regional traffic signal control under mixed traffic condition[J]. Journal of Traffic and Transportation Engineering, 2015, 15 (1): 119-126. (in Chinese). doi: 10.3969/j.issn.1671-1637.2015.01.016
    [13]
    WU Yao. Study on optimization and evaluation of signalized intersection[D]. Xi'an: Chang'an University, 2013. (in Chinese).
    [14]
    SAYED T, ZEIN S. Traffic conflict standards for intersections[J]. Transportation Planning and Technology, 1999, 22 (4): 309-323. doi: 10.1080/03081069908717634
    [15]
    EI-BASYOUNY K, SAYED T. Safety performance functions using traffic conflicts[J]. Safety Science, 2013, 51 (1): 160-164. doi: 10.1016/j.ssci.2012.04.015
    [16]
    SACCHI E, SAYED T. Bayesian estimation of conflict-based safety performance functions[J]. Journal of Transportation Safety and Security, 2016, 8 (3): 266-279. doi: 10.1080/19439962.2015.1030807
    [17]
    ZHANG Xin, LIU Pan, CHEN Yu-guang, et al. Modeling the frequency of opposing left-turn conflicts at signalized intersections using generalized linear regression models[J]. Traffic Injury Prevention, 2014, 15 (6): 645-651. doi: 10.1080/15389588.2013.860526
    [18]
    GUO Yan-yong, LIU Pan, XU Cheng-cheng, et al, Safety analysis of right-turn facility at signalized intersection using traffic conflict model[J]. China Journal of Highway and Transport, 2016, 29 (11): 139-146. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL201611020.htm
    [19]
    HAYWARD J C. Near-miss determination through use of a scale of danger[J]. Highway Research Record, 1972, 384 (1): 24-34.
    [20]
    GUO Yan-yong, SAYED T, ZAKI M H. Automated analysis of pedestrian walking behaviour at a signalised intersection in China[J]. IET Intelligent Transport Systems, 2016, 11 (1): 28-36.
    [21]
    CHIN H C, QUEK S T. Measurement of traffic conflict[J]. Safety Science, 1997, 26 (3): 169-185.
    [22]
    GUO Yan-yong, SAYED T, ZAKI M H, et al. Safety evaluation of unconventional outside left-turn lane using automated traffic conflict techniques[J]. Canadian Journal of Civil Engineering, 2016, 43 (7): 631-642.
    [23]
    ANASTASOPOULOS P C, MANNERING F L. A note on modeling vehicle accident frequencies with random-parameters count models[J]. Accident Analysis and Prevention, 2009, 41 (1): 153-159.
    [24]
    GUO Yan-yong, LIU Pan, LIANG Qi-yu, et al. Effects of parallelogram-shaped pavement markings on vehicle speed and safety of pedestrian crosswalks on urban roads in China[J]. Accident Analysis and Prevention, 2016, 95: 438-447.
    [25]
    SPEIGELHALTER D J, BEST N G, GARLIN B P, et al. Bayesian measures of model complexity and fit[J]. Journal of the Royal Statistical Society Series B, 2003, 64 (4): 583.

Catalog

    Article Metrics

    Article views (1083) PDF downloads(651) Cited by()
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return