|Table of Contents|

Prediction method of OD travel time based on driver’s route choice preference(PDF)

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

Issue:
2016年02期
Page:
143-149
Research Field:
交通信息工程及控制
Publishing date:

Info

Title:
Prediction method of OD travel time based on driver’s route choice preference
Author(s):
SUN Jian12 ZHANG Ying12 ZHANG Chun2
1. State Key Laboratory of Ocean Engineering, Shanghai Jiaotong University, Shanghai 200240, China; 2. Transportation Research Center, Shanghai Jiaotong University, Shanghai 200240, China
Keywords:
prediction method of OD travel time route choice preference GIS map matching floating car data
PACS:
U491.1
DOI:
-
Abstract:
Based on about three million data of more than 3 000 floating cars in Shenzhen City of Guangzhou Province, geographic information system(GIS)technology was used as main tool, the representative Futian and Luohu Districts were used as study areas, and the expansion radii of different OD pairs were determined. Map matching was processed by using the unique number of floating car, the OD path and travel time of floating car were obtained according to the determined study area and expansion radius. The driver’s temporal and spatial preferences during route choice were determined, and the OD travel time prediction method based on the route choice preference was established. Using the mean absolute percentage error(MAPE), the root mean square relative error(RMSRE), and the maximum relative error(MRE)as indicators, the travel time prediction methods based on the shortest route, the fastest route and the preference route were compared. Comparison result indicates that compared to the prediction method based on the shortest route, the values of MAPE, RMSRE, and MRE of proposed method decrease by 66.51%, 61.24%, and 61.47% respectively, compared to the prediction method based on the fastest route, the values of MAPE, RMSRE, and MRE of proposed method decrease by 63.64%, 59.70%, and 58.99% respectively, so the prediction precision of OD travel time is significantly improved by using the prediction method of OD travel time based on driver’s route choice preference. 3 tabs, 8 figs, 21 refs.

References:

[1] 苏永云,晏克非,杨晓光,等.VNS中动态行程时间与多端动态最短路算法[J].中国公路学报,2001,14(1):97-99,103.SU Yong-yun, YAN Ke-fei, YANG Xiao-guang, et al. Study of the algorithm of dynamic travel time and multi-end shortest path in VNS[J]. China Journal of Highway and Transport, 2001, 14(1): 97-99, 103.(in Chinese)
[2] MIWA T, SAKAI T, MORIKAWA T. Route identification and travel time prediction using probe-car data[J]. International Journal of ITS Research, 2004, 2(1): 1-9.
[3] 姚丽亚,关宏志,魏连雨,等.基于实时交通信息的行程时间估算及路径选择分析[J].公路交通科技,2006,23(11):86-89.YAO Li-ya, GUAN Hong-zhi, WEI Lian-yu, et al. Study on link travel time estimation and route selection method based on real-time traffic information[J]. Journal of Highway and Transportation Research and Development, 2006, 23(11): 86-89.(in Chinese)
[4] KWON J, COIFMAN B, BICKEL P. Day-to-day travel time trends and travel time prediction from loop detector data[J]. Transportation Research Record, 2000(1717): 120-129.
[5] YGNACE J L, DRANE C, YIM Y B, et al. Travel time estimation on the San Francisco Bay Area network using cellular phones as probes[R]. Berkeley: University of California, 2000.
[6] BERRY D S, GREEN F H. Techniques for measuring over-all speeds in urban areas[C]∥CRUM R W, BURGGRAF F, JR W N C. Proceedings of the Twenty-Ninth Annual Meeting of the Highway Research Board. Washington DC: TRB, 1950: 311-318.
[7] 陈小鸿,冯均佳,杨 超.基于浮动车数据的行程时间可靠度特征研究[J].城市交通,2007,5(5):42-45,37.CHEN Xiao-hong, FENG Jun-jia, YANG Chao. Research on travel time reliability characteristics based on floating car data[J]. Urban Transport of China, 2007, 5(5): 42-45, 37.(in Chinese)
[8] LI Yan-ying, MCDONALD M. Link travel time estimation using single GPS equipped probe vehicle[C]∥IEEE. The IEEE 5th International Conference on Intelligent Transportation Systems. New York: IEEE, 2002: 932-937.
[9] NANTHAWICHIT C, NAKATSUJI T, SUZUKI H. Application of probe vehicle data for real-time traffic state estimation and short-term travel time prediction on a freeway[J]. Transportation Research Record, 2003(1855): 1-16.
[10] 张和生,张 毅,温慧敏,等.利用GPS 数据估计路段的平均行程时间[J].吉林大学学报:工学版,2007,37(3):533-537.ZHANG He-sheng, ZHANG Yi, WEN Hui-min, et al. Estimation approaches of average link travel time using GPS data[J]. Journal of Jilin University: Engineering and Technology Edition, 2007, 37(3): 533-537.(in Chinese)
[11] 李慧兵,杨晓光,罗莉华.路段行程时间估计的浮动车数据挖掘方法[J].交通运输工程学报,2014,14(6):100-109,116.LI Hui-bing, YANG Xiao-guang, LUO Li-hua. Mining method of floating car data based on link travel time estimation[J]. Journal of Traffic and Transportation Engineering, 2014, 14(6): 100-109, 116.(in Chinese)
[12] RICE J, ZWET E V. A simple and effective method for predicting travel times on freeways[C]∥IEEE. Proceedings of the 2001 IEEE Intelligent Transportation Systems. New York: IEEE, 2001: 227-232.
[13] 方路平,陈仕骁,赵飞帆.基于小样本浮动车系统的平均行程时间估计[J].计算机仿真,2012,29(9):367-370.FANG Lu-ping, CHEN Shi-xiao, ZHAO Fei-fan. Average link travel time estimation based on floating car of small sample size[J]. Computer Simulation, 2012, 29(9): 367-370.(in Chinese)
[14] 杨兆升,于 悦,杨 薇.基于固定型检测器和浮动车的路段行程时间获取技术[J].吉林大学学报:工学版,2009,39(增2):168-171.YANG Zhao-sheng, YU Yue, YANG Wei. Acquisition of travel time based on inductive coil detector and probe vehicle[J]. Journal of Jilin University: Engineering and Technology Edition, 2009, 39(S2): 168-171.(in Chinese)
[15] HAYNES R, JONES A P, SAUERZAPF V, et al. Validation of travel times to hospital estimated by GIS[J]. International Journal of Health Geographics, 2006, 5(12): 1-8.
[16] SUN Jian, ZHANG Chun, ZHANG Li-hui, et al. Urban travel behavior analyses and route prediction based on floating car data[J]. Transportation Letters, 2014, 6(3): 118-125.
[17] 陈宇飞,智 明,秦国锋.基于GIS的最优路径自适应规划算法[J].计算机工程,2007,33(1):53-55,58.CHEN Yu-fei, ZHI Ming, QIN Guo-feng. Optimal shortest-path and auto-adapted plan algorithm based on GIS[J]. Computer Engineering, 2007, 33(1): 53-55, 58.(in Chinese)
[18] 孙 健,刘 琼,彭仲仁.城市交通拥挤成因及时空演化规律分析——以深圳市为例[J].交通运输系统工程与信息,2011,11(5):86-93.SUN Jian, LIU Qiong, PENG Zhong-ren. Research and analysis on causality and spatial-temporal evolution of urban traffic congestions—a case study on Shenzhen of China[J]. Journal of Transportation Systems Engineering and Information Technology, 2011, 11(5): 86-93.(in Chinese)
[19] MINELLI S, IZADPANAH P, RAZAVI S. Evaluation of connected vehicle impact on mobility and mode choice[J]. Journal of Traffic and Transportation Engineering: English Edition, 2015, 2(5): 301-312.
[20] QIN Xiao, SHEN Zhao, WEHBE N, et al. Evaluation of truck impact hazards for interstate overpasses[J]. Transportation Research Record, 2014(2402): 1-17.
[21] 孙 健,张 纯,陈书恺,等.基于季节模型及Kalman滤波的道路行程时间预测[J].长安大学学报:自然科学版,2014,34(6):145-151.SUN Jian, ZHANG Chun, CHEN Shu-kai, et al. Route travel time estimation based on seasonal model and Kalman filtering algorithm[J]. Journal of Chang’an University: Natural Science Edition, 2014, 34(6): 145-151.(in Chinese)

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Last Update: 2016-04-20