|Table of Contents|

Calculation model of intersection capacity based on traffic flow survival function(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2019年04期
Page:
137-150
Research Field:
交通运输规划与管理
Publishing date:

Info

Title:
Calculation model of intersection capacity based on traffic flow survival function
Author(s):
HU Yao12 WEI Wei13 SHANG Ming-ju1 LI Li1 LI Yang1
(1. School of Mathematics and Statistics, Guizhou University, Guiyang 550025, Guizhou, China; 2. Guizhou Provincial Key Laboratory of Public Big Data, Guizhou University, Guiyang 550025, Guizhou, China; 3. School of Data Science and Information Engineering, Guizhou Minzu University, Guiyang 550025, Guizhou, China)
Keywords:
traffic capacity survival function traffic flow product-limit traffic breakdown
PACS:
U491.14
DOI:
-
Abstract:
The concept of stochastic traffic capacity of urban road was proposed for the disadvantage that the basic traffic capacity was unable to fully reflect the road traffic conditions. According to the evaluation system, the traffic breakdown and continuous breakdown were defined to quantify the degree of urban road traffic congestion. The existing estimation methods of traffic capacity were studied, and the product-limit and lifetime distribution were used to construct and estimate the traffic flow distribution function. The parameter model of traditional continuous traffic flow was improved by combining the characteristics of traffic flow data of each intersection entrance, and a calculation model of intersection capacity based on traffic flow survival function was proposed. The estimation result of the calculation model was compared with Highway Capacity Manual 2010 model and practical traffic flow of intersection to analyze the computation errors. Analysis result shows that the mean errors of intersection capacity with traffic breakdown and continuous breakdown calculated by the survival function model and HCM2010 model are 0.162 1 and 0.116 4, respectively, and the variances are 0.029 0 and 0.015 2, respectively, both have small error fluctuation. The relative errors between the results of the proposed calculation model and the measured greater traffic flow are 9.720%, 3.822% and 4.936%, 4.779%, respectively. The relative error of the proposed calculation model in a statistic sense is 5.871%, and the estimation effect is robust. There is a product-limit survival function between the traffic breakdown time, probability of acceptable breakdown, traffic flow, speed and traffic capacity. The traffic capacity of the researched intersection is 7 632 pcu·h-1, so the estimation result of the proposed calculation model is more reliable. Therefore, the proposed calculation model has high practicability, especially in urban road traffic areas with different congestion degrees. By estimating traffic capacity of the acceptable breakdown probability, the optimization objective, scientific decision and acceptable theoretical basis can be provided for urban road traffic organization and management department. 8 tabs, 7 figs, 32 refs.

References:

[1] 孙 剑,郑进炫.城市快速路通行能力再认识与新分析体系构建[J].中国公路学报,2018,31(5):127-135.
SUN Jian, ZHENG Jin-xuan. Revisit of capacity model and reconstruction of capacity analysis framework at urban expressway[J]. China Journal of Highway and Transport, 2018, 31(5): 127-135.(in Chinese)
[2] LORENZ M, ELEFFTERIADOU L. A probabilistic approach to defining freeway capacity and breakdown[C]∥TRB. 4th International Symposium on Highway Capacity. Washington DC: TRB, 2000: 84-95.
[3] BRILON W, GEISTEFELDT J, REGLER M. Reliability of freeway traffic flow: a stochastic concept of capacity[C]∥MAHMASSANI H S. Proceedings of the 16th International Symposium on Transportation and Traffic Theory. Bradford: Emerald Group Publishing, 2005: 125-144.
[4] LAI Yuan-wen, EASA S. Modeling effect of random factors on signalized intersection capacity[J]. China Journal of Highway and Transport, 2016, 29(11): 130-138.
[5] POLUS A, POLLATSCHEK M A. Stochastic nature of
freeway capacity and its estimation[J]. Canadian Journal of Civil Engineering, 2002, 29(6): 842-852.
[6] ELEFTERIADOU L, ROESS R P, MCSHANE W R. Probabilistic nature of breakdown at freeway merge junctions[J]. Transportation Research Record, 1995(1484): 80-89.
[7] OZBAY K, OZGUVEN E E. A comparative methodology for estimating the capacity of a freeway section[C]∥IEEE. 10th International IEEE Conference on Intelligent Transportation Systems. New York: IEEE, 2007: 1034-1039.
[8] 秦严严,王 昊,王 炜,等.自适应巡航控制车辆跟驰模型综述[J].交通运输工程学报,2017,17(3):121-130.
QIN Yan-yan, WANG Hao, WANG Wei, et al. Review of car-following models of adaptive cruise control[J]. Journal of Traffic and Transportation Engineering, 2017, 17(3): 121-130.(in Chinese)
[9] 王晓原,隽志才,贾洪飞,等.交通流突变分析的变点统计方法研究[J].中国公路学报,2002,15(4):69-74.
WANG Xiao-yuan, JUAN Zhi-cai, JIA Hong-fei, et al. Study of a statistical method of change-point to analyze traffic flow breakdown[J]. China Journal of Highway and Transport, 2002, 15(4): 69-74.(in Chinese)
[10] XIAO Qiang, HE Rui-chun, YU Jian-ning, et al. Road traffic flow forewarning and control model with the slope of the change rate[J]. Tehnicki Vjesnik, 2017, 24(S1): 185-191.
[11] JIANG Rui, HU Mao-Bin, JIA Bin, et al. A new mechanism for metastability of under-saturated traffic responsible for time-delayed traffic breakdown at the signal[J]. Computer Physics Communications, 2014, 185(5): 1439-1442.
[12] HAN Y J, AHN S Y. Stochastic modeling of breakdown at freeway merge bottleneck and traffic control method using connected automated vehicle[J]. Transportation Research Part B: Methodological, 2018, 107: 146-166.
[13] YU Zheng-yao, WOOD J S, GAYAH V V. Using survival models to estimate bus travel times and associated uncertainties[J]. Transportation Research Part C: Emerging Technologies, 2017, 74: 366-382.
[14] 孙 剑,胡家琦,孙 杰.城市快速路交织区通行能力估计模型[J].中国公路学报,2016,29(4):114-122.
SUN Jian, HU Jia-qi, SUN Jie. Capacity estimation model on weaving segments of urban expressway[J]. China Journal of Highway and Transport, 2016, 29(4): 114-122.(in Chinese)
[15] ANBAROGLU B, HEYDECKER B, CHENG Tao. Spatio-temporal clustering for non-recurrent traffic congestion detection on urban road networks[J]. Transportation Research Part C: Emerging Technologies, 2014, 48: 47-65.
[16] 郭延永,刘 攀,吴 瑶,等.基于贝叶斯多元泊松-对数正态分布的交通冲突模型[J].中国公路学报,2018,31(1):101-109.
GUO Yan-yong, LIU Pan, WU Yao, et al. Traffic conflict model based on Bayesian multivariate Poisson-lognormal normal distribution[J]. China Journal of Highway and Transport, 2018, 31(1): 101-109.(in Chinese)
[17] 邵长桥,郑加菊,张 可.基于运行效率的通行能力计算方法[J].北京工业大学学报,2016,42(1):107-111.
SHAO Chang-qiao, ZHENG Jia-ju, ZHANG Ke. Freeway capacity estimation method based on traffic operational efficiency[J]. Journal of Beijing University of Technology, 2016, 42(1): 107-111.(in Chinese)
[18] 丁 恒,黄文娟,陈 森,等.拥堵交通网络能耗节约边界信号优化方法[J].系统工程理论与实践,2017,37(3):700-709.
DING Heng, HUANG Wen-juan, CHEN Sen, et al. Boundary signal optimization for congestion network based on energy saving[J]. Systems Engineering—Theory and Practice, 2017, 37(3): 700-709.(in Chinese)
[19] 李瑞敏,唐 瑾.过饱和交叉口交通信号控制动态规划优化模型[J].交通运输工程学报,2015,15(6):101-109.
LI Rui-min, TANG Jin. Traffic signal control optimization model of over-saturated intersection based on dynamic programming[J]. Journal of Traffic and Transportation Engineering, 2015, 15(6): 101-109.(in Chinese)
[20] 胡启洲,孙 煦.基于多维联系数的城市路网交通拥堵态势监控模型[J].中国公路学报,2013,26(6):143-149.
HU Qi-zhou, SUN Xu. Model for traffic congestion state monitor in urban road network based on multi-dimension connection number[J]. China Journal of Highway and Transport, 2013, 26(6): 143-149.(in Chinese)
[21] 胡立伟,杨锦青,何越人,等.城市交通拥塞辐射模型及其对路网服务能力损伤研究[J].中国公路学报,2019,32(3):145-154.
HU Li-wei, YANG Jin-qing, HE Yue-ren, et al. Urban traffic congestion radiation model and damage caused to service capacity of road network[J]. China Journal of Highway and Transport, 2019, 32(3): 145-154.(in Chinese)
[22] BURSA B, GAJIC N, MAILER M. Insights into the congestion patterns on alpine motorways based on separate traffic lane analysis[J]. Transportation Research Procedia, 2019, 37: 441-448.
[23] YAN Qing-long, SUN Zhe, GAN Qi-jian, et al. Automatic identification of near-stationary traffic states based on the PELT changepoint detection[J]. Transportation Research Part B: Methodological, 2018, 108: 39-54.
[24] JIN Wen-long. On the equivalence between continuum and car-following models of traffic flow[J]. Transportation Research Part B: Methodological, 2016, 93: 543-559.
[25] JIN Wen-long. A first-order behavioral model of capacity
drop[J].Transportation Research Part B: Methodological, 2017, 105: 438-457.
[26] KERNER B S. Breakdown minimization principle versus
Wardrop's equilibria for dynamic traffic assignment and control in traffic and transportation networks: a critical mini-review[J]. Physica A: Statistical Mechanics and its Applications, 2017, 466: 626-662.
[27] 董晓芳,张良勇,徐兴忠.随机删失模型下排序集样本的非参数估计与应用[J].统计与决策,2014(22):72-74.
DONG Xiao-fang, ZHANG Liang-yong, XU Xing-zhong. Nonparametric estimation and application of sorting set samples under random deletion model[J]. Statistics and Decision, 2014(22): 72-74.(in Chinese)
[28] 李永明,周 勇.基于右删失宽相依数据的Kaplan-Meier估计和风险率估计的渐近性质[J].应用数学学报,2019,42(1):71-84.
LI Yong-ming, ZHOU Yong. Asymptotic properties of the Kaplan-Meier estimator and hazard rate estimator for right censored and widely orthant dependent data[J]. Acta Mathematicae Applicatae Sinica, 2019, 42(1): 71-84.(in Chinese)
[29] REMPE F, FRANECK P, FASTENRATH U, et al. A phase-based smoothing method for accurate traffic speed estimation with floating car data [J]. Transportation Research Part C: Emerging Technologies, 2017, 85: 644-663.
[30] 杨晓光,赵 靖,马万经,等.信号控制交叉口通行能力计算方法研究综述[J].中国公路学报,2014,27(5):148-157.
YANG Xiao-guang, ZHAO Jing, MA Wan-jing, et al. Review on calculation method for signalized intersection capacity[J]. China Journal of Highway and Transport, 2014, 27(5): 148-157.(in Chinese)
[31] 胡 尧,韦 维,王登梅,等.一种确定信号交叉口拥堵的概率统计预警模型[J].数理统计与管理,2010,29(4):603-614.
HU Yao, WEI Wei, WANG Deng-mei, et al. A probability warning model for traffic jam of signalized intersections[J]. Journal of Applied Statistics and Management, 2010, 29(4): 603-614.(in Chinese)
[32] 徐立群,吴 聪,杨兆升.信号交叉口通行能力计算方法[J].交通运输工程学报,2001,1(1):82-85.
XU Li-qun, WU Cong, YANG Zhao-sheng. The methods of computing the capacity of signalized intersection[J]. Journal of Traffic and Transportation Engineering, 2001, 1(1): 82-85.(in Chinese)

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Last Update: 2019-09-03