An exploratory shockwave approach to estimating queue length using probe trajectories

Journal of Intelligent Transportation Systems: Technology, Planning, and Operations

Volumn 16, Issue 1, 2012, Pages 12-23

  Cheng, Yang ^a   Qin, Xiao ^b   Jin, Jing ^c   Ran, Bin ^a,d  

^a University of Wisconsin Madison   (United States)

^b South Dakota State University   (United States)

^c The University of Texas at Austin   (United States)

^d SOUTHEAST UNIVERSITY   (China)

Author keywords

Probe Trajectory; Queue Length Estimation; Signal Detection; Signalized Intersection

Indexed keywords

COMMUNICATION COST; CRITICAL POINTS; DATA COLLECTION; DATA POINTS; IN-VEHICLE; INNOVATIVE APPROACHES; PERFORMANCE MEASUREMENTS; PROBE VEHICLES; QUEUE LENGTHS; REAL-TIME PROBES; SIGNAL TIMING; SIGNALIZED INTERSECTION; SIMULATION PROJECTS; TRAJECTORY-BASED;

ESTIMATION; PROBES; QUEUEING THEORY; SIGNAL DETECTION; TIMING CIRCUITS; TRAFFIC SIGNALS;

TRAJECTORIES;

AUTOMOBILE; DATA ACQUISITION; DETECTION METHOD; ESTIMATION METHOD; INTELLIGENT TRANSPORTATION SYSTEM; PERFORMANCE ASSESSMENT; PROBE; SIGNAL; THRESHOLD; TRAJECTORY;

EID: 84856899743     PISSN: 15472450     EISSN: 15472442     Source Type: Journal    
DOI: 10.1080/15472450.2012.639637     Document Type: Article

References (30)

1. Ahmed, H., El-Darieby, M., Abdulhai, B., & Morgan, Y. (2008). Bluetooth andWi-Fi-based mesh network platform for traffic monitoring. Paper presented at the Transportation Research Board 87th Annual Meeting, Washington, DC, USA.
2. Alexiadis, V., Colyar, J., & Halkias, J. (2004). The Next Generation Simulation Program. ITE Journal, 74(8), 22-26.
3. Balke, K. N., Charara, H., & Parker, R. (2005). Development of a Traffic Signal Performance Measurement System (TSPMS). Texas Transportation Institute, College Station, TX, USA.
4. Ban, X., Herring, R., Hao, P., & Bayen, A. (2009). Delay pattern estimation for signalized intersections using sampled travel times. Transportation Research Record: Journal of the Transportation Research Board, 2130, 109-119.
5. Berkow, M., Monsere, C. M., Koonce, P. J. V., Bertini, R. L., &Wolfe, M. (2009). Prototype for data fusion using stationary and mobile data sources for improved arterial performance measurement. Paper presented at the Transportation Research Board 88th Annual Meeting, Washington, DC, USA.
6. Cheu, R. L., Lee, D. H., & Xie, C. (2001). An arterial speed estimation model fusing data from stationary and mobile sensors. Paper presented at the Intelligent Transportation Systems, 2001. 2001 IEEE Intelligent Transportation Systems Conference Proceedings, Oakland, CA, USA.
7. Claudel, C. G., Hofleitner, A., Mignerey, N., & Bayen, A. M. (2009). Guaranteed bounds on highway travel times using probe and fixed data. Paper presented at the Transportation Research Board 88th Annual Meeting, Washington, DC, USA.
8. Coifman, B. (2002). Estimating travel times and vehicle trajectories on freeways using dual loop detectors. Transportation Research. Part A: Policy and Practice, 36, 351-364.
9. Comert, G., & Cetin, M. (2007). Queue length estimation from probe vehicle location: Undersaturated conditions. Paper presented at the Transportation Research Board 86th Annual Meeting, Washington, DC, USA.
10. Daganzo, C. F. (2005). A variational formulation of kinematic waves: Basic theory and complex boundary conditions. Transportation Research Part B: Methodological, 39, 187-196.
11. Fontaine, M. D., & Smith, B. L. (2007). Investigation of the performance of wireless location technology-based traffic monitoring systems. American Society of Civil Engineers: Journal of Transportation Engineering, 133, 157-165.
12. Geroliminis,N.,&Skabardonis, A. (2005). Prediction of arrival profiles and queue lengths along signalized arterials by using a Markov decision process. Transportation Research Record: Journal of the Transportation Research Board, 1934, 116-124.
13. Izadpanah, P., Hellinga, B., & Fu, L. (2009). Automatic traffic shockwave identification using vehicles' trajectories. Paper presented at the Transportation Research Board 88th Annual Meeting,Washington, DC, USA.
14. Lighthill, M. J., & Whitham, G. B. (1955a). On kinematic waves. I. Flood movement in long rivers. Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences, 229, 281-316.
15. Lighthill, M. J., & Whitham, G. B. (1955b). On kinematic waves. II. A theory of traffic flow on long crowded roads. Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences, 229, 317-345.
16. Liu, H. X., Ma, W., Wu, X., & Hu, H. (2008). Development of a real-time arterial performance monitoring system using traffic data available from existing signal systems. Minneapolis: University of Minnesota, Minnesota Department of Transportation.
17. Liu, H. X., Oh, J. S., Oh, S., Chu, L., & Recker, W. W. (2001). Online traffic signal control scheme with real-time delay estimation technology. Berkeley, CA: California Partners for Advanced Transit and Highways (PATH
18. Lu, X., & Skabardonis, A. (2007). Freeway traffic shockwave analysis: Exploring NGSIM trajectory data. Paper presented at the Transportation Research Board 86th Annual Meeting, Washington, DC, USA.
19. National Transportation Operations Coalition. (2007). 2007 National Traffic Signal Report Card Technical Report. Washington, DC: Institute of Transportation Engineers.
20. Newell, G. F. (1993). A simplified theory of kinematic waves in highway traffic, Part I: General theory. Transportation Research. Part B: Methodological, 27, 281-287.
21. Pan, C., Lu, J., Wang, D., & Ran, B. (2007). Data collection based on Global Positioning System for travel time and delay for arterial roadway network. Transportation Research Record: Journal of the Transportation Research Board, 2024, 35-43.
22. Qiu, Z., & Ran, B. (2008). Kalman filtering applied to network-based cellular probe traffic monitoring. Paper presented at the Transportation Research Board 87th Annual Meeting, Washington, DC, USA.
23. Richards, P. I. (1956). Shock waves on the highway. Operations Research, 4(1), 42-51.
24. Ritchie, S. G., Jeng, S.-T., Tok, Y. C., & Park, S. (2008). Corridor deployment and investigation of anonymous vehicle tracking for real-time traffic performance measurement. Berkeley, CA: California Partners for Advanced Transit and Highways (PATH
25. Robinson, S., & Polak, J. W. (2005). Modeling urban link travel time with inductive loop detector data by using the k-NN method. Transportation Research Record: Journal of the Transportation Research Board, 1935, 47-56.
26. Skabardonis, A., & Geroliminis, N. (2008). Real-time monitoring and control on signalized arterials. Journal of Intelligent Transportation Systems, 12(2), 64-74.
27. Smilowitz, K. R., Daganzo, C. F., Cassidy, M. J., & Bertini, R. L. (1999). Some observations of highway traffic in long queues. Transportation Research Record, 1678, 225-233.
28. Turner, S. M., Eisele, W. L., Benz, R. J., & Holdener, D. J. (1998). Travel time data collection handbook. Texas Transportation Institute, Federal Highway Administration.
29. Viti, F., & van Zuylen, H. J. (2009). The dynamics and the uncertainty of queues at fixed and actuated controls: A probabilistic approach. Journal of Intelligent Transportation Systems, 13(1), 39-51.
30. Wilson, R. E. (2008). From inductance loops to vehicle trajectories. Paper presented at the Symposium on the Fundamental Diagram: 75 Years (Greenshields 75 Symposium), Woods Hole, MA, USA.