期刊文献+

Estimation of Incident-Induced Congestion on Signalized Arteries Using Traffic Sensor Data 被引量:2

Estimation of Incident-Induced Congestion on Signalized Arteries Using Traffic Sensor Data
原文传递
导出
摘要 This paper describes how to derive quantitative information about the effect of traffic incidents on urban traffic flow from the raw measurements detected by sectional loop sensors. 3-he two critical parame- ters of the travel delay and queue length, which reflect the temporal and spatial properties of inci- dent-induced congestion, cannot be directly determined from commonly used loop sensors. The modified queuing diagram is used here to quantify incident-induced queues and travel delays on signalized arteries using sensor data from the targeted and upstream links. The method is tested using data generated by the VISSIM simulation model, with results indicating its efficiency and accuracy with an average relative travel delay error of 18.67% for all samples which falls to 8.07% for high volume and very high volume conditions. This paper describes how to derive quantitative information about the effect of traffic incidents on urban traffic flow from the raw measurements detected by sectional loop sensors. 3-he two critical parame- ters of the travel delay and queue length, which reflect the temporal and spatial properties of inci- dent-induced congestion, cannot be directly determined from commonly used loop sensors. The modified queuing diagram is used here to quantify incident-induced queues and travel delays on signalized arteries using sensor data from the targeted and upstream links. The method is tested using data generated by the VISSIM simulation model, with results indicating its efficiency and accuracy with an average relative travel delay error of 18.67% for all samples which falls to 8.07% for high volume and very high volume conditions.
出处 《Tsinghua Science and Technology》 EI CAS 2012年第3期296-303,共8页 清华大学学报(自然科学版(英文版)
基金 Partially supported by the National Natural Science Foundation of China (Nos. 90924002 and 60834001) the National Key Basic Research and Development (973) Program of China (No. 2006CB705506)
关键词 traffic incident signalized intersections travel delay queue length traffic incident signalized intersections travel delay queue length
  • 相关文献

参考文献16

  • 1Cheu R L, Ritchie S G. Automated detection of lane-blocking freeway incidents using artificial neural networks. Transportation Research Part C. Emerging Technologies, 1995, 3(6). 371-388.
  • 2Adeli H, Karim A. Fuzzy-wavelet RBFNN model for freeway incident detection. Journal of Transportation En- gineering-ASCE, 2000, 126(6). 464-471.
  • 3Teng H, Qi Y. Application of wavelet technique to freeway incident detection. Transportation Research Part C. Emerging Technologies, 2003, H(3). 289-308.
  • 4Morales J M, Analytical procedures for estimating freeway traffic coneestion. ITE Journal, 1987, 57(1). 45-52.
  • 5Skabardonis A, Petty K, Noeimi H, et al. 1-880 field ex- periment. Data-base development and incident delay esti- mation procedures. Transportation Research Record." Journal of the Transportation Research Board, 1996, 1554. 204-212.
  • 6Fu L, Rilett L R. Real-time estimation of incident delay in dynamic and stochastic networks. Transportation Research Record, 1997, 1603. 99-105.
  • 7Li J, Lan C J, Gu X. Estimation of incident delay and its uncertainty on freeway networks. Transportation Research Record." Journal of the Transportation Research Board, 2006, 1959. 37-45.
  • 8Newell G F. Delays caused by a queue at a freeway exit ramp. Transportation Research Part B." Methodological, 1999, 33(5). 337-350.
  • 9Gupta A K, Katiyar V K. Analysis of shock waves and jams in traffic flow. Journal of Physics A." Mathematical and General, 2005, 38(19). 4069-4083.
  • 10A1-Deek H, Garib A, Radwan A E. New method for esti- mating freeway incident congestion. Transportation Re- search Record, 1995, 1494. 30-39.

同被引文献12

  • 1Michalopoulos P G,Pishaody V B. Deriation of delays based on improved macroscopic traffic models [J]. Transportation research part B, 1981,15 : 299- 317.
  • 2Morales M J. Analytical procedures for estimating freeway traffic congestion[J]. Public Road, 1986,50 (2) :55-61.
  • 3Newell G F. A simplified theory of kinematic waves in highway traffic, Part Ⅱ: Queueing at freeway bottle- necks[J]. Transportation research part B, 1993, 27 (4) :289-303.
  • 4Lawson T W,et al. Using the input-output diagram to determine the spatial and temporal extents of a queue upstream of a bottleneckFJ]. Transportation Research Record,1997,1572(1) : 140-147.
  • 5Sheu J B, Chou Y H. Stochastic modeling and real-time prediction of incident effects on surface street traffic congestion[J]. Applied Mathematical Model- ing, 2004,28 : 445- 468.
  • 6Sun C, Chilukuri V. Dynamic Incident Progression Curve for Classifying Secondary Traffic Crashes[J]. Journal of Transportation Engineering, 2010,136 (12) : 1153-1158.
  • 7Younshik C, Recker W. A Methodological Approach for Estimating Temporal and Spatial Extent of Delays Caused by Freeway Accidents[J]. IEEE Transactions on Intelligent Transportation Systems, 2012, 13 ( 3 ) : 1454-1461.
  • 8陈茜,李文权.基于CTM的大型活动突发事件交通影响范围确定(英文)[J].Journal of Southeast University(English Edition),2009,25(2):257-261. 被引量:6
  • 9李长城,刘小明,荣建.路面湿滑指数开发及其在交通运行管理中的应用[J].公路交通科技,2010,27(11):132-136. 被引量:7
  • 10Tingting Zhao,Yi Zhang,Bingyan Huang.RMT-Based Urban Traffic Cross-Correlation Analysis and Its Application on Traffic Incident Impact Analyses[J].Tsinghua Science and Technology,2012,17(1):104-112. 被引量:1

引证文献2

二级引证文献10

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部