Travel time forecasting and dynamic origin-destination estimation for freeways based on bluetooth traffic monitoring

Transportation Research Record

Volumn , Issue 2175, 2010, Pages 19-27

  Barceló, Jaume ^a   Montero, Lidin ^a   Marqués, Laura ^a   Carmona, Carlos ^a  

^a UNIVERSITAT POLITÈCNICA DE CATALUNYA   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC VEHICLE IDENTIFICATION; LICENSE PLATES (AUTOMOBILE); OPTICAL CHARACTER RECOGNITION; TRAFFIC CONTROL; TRAVEL TIME;

AUTOMATIC VEHICLE LOCATIONS; INDUCTIVE LOOP DETECTORS; LICENSE PLATE DETECTION; LICENSES PLATE RECOGNITION; MEASUREMENTS OF; NEW INFORMATION AND COMMUNICATION TECHNOLOGIES; ORIGIN DESTINATION; REAL-TIME APPLICATION; TRAFFIC MONITORING; TRAVEL TIME FORECASTING;

BLUETOOTH;

EID: 78651267177     PISSN: 03611981     EISSN: None     Source Type: Journal    
DOI: 10.3141/2175-03     Document Type: Article

References (15)

1. Waller, S. T., Y.-C. Chiu, N. Ruiz-Juri, A. Unikrishnan, and B. Bustillos. Short Term Travel Time Prediction on Freeways in Conjunction with Detector Coverage Analysis. Technical Report FHWA/TX-08/0-5141-1. Center for Transportation Research, University of Texas at Austin for Texas Department of Transportation, Austin, 2007.
2. Sanfeliu, A., A. Punsola, Y. Yoshimura, M. R. Llácer, and M. D. Gramunt. Legal Challenges for Networking Robots Deployment in European Urban Areas: The Privacy Issue. Workshop on Network Robot Systems. Presented at IEEE International Conference on Robotics and Automation, Kobe, Japan, 2009.
3. Nanthawichit, C., T. Nakatsuji, and H. Suzuki. Application of Probe-Vehicle Data for Real-Time Traffic-State Estimation and Short-Term Travel-Time Prediction on a Freeway. In Transportation Research Record: Journal of the Transportation Research Board, No. 1855, Transportation Research Board of the National Academies, Washington, D.C., 2003, pp. 49-59.
4. Kuchipudi, C., and S. I. J. Chien. Development of a Hybrid Model for Dynamic Travel Time Prediction. In Transportation Research Record: Journal of the Transportation Research Board, No. 1855, Transportation Research Board of the National Academies, Washington, D.C., 2003, pp. 22-31.
5. Cheng, P., Q. Zhijun, and B. Ran. Particle Filter-Based Traffic State Estimation Using Cell Phone Network Data. Proc., Intelligent Transportation Systems Conference, Toronto, Ontario, Canada, 2006.
6. Kalman, R. E. A New Approach to Linear Filtering and Prediction Problem. Journal of Basic Engineering, Vol. 82, No. 1, 1960, pp. 35-45.
7. Van Der Zijpp, N. J., and R. Hamerslag. Improved Kalman Filtering Approach for Estimating Origin-Destination Matrices for Freeway Corridors. In Transportation Research Record 1443, TRB, National Research Council, Washington, D.C., 1994, pp. 54-64.
8. Chang, G. L., and J. Wu. Recursive Estimation of Time-Varying Origin-Destination Flows from Traffic Counts in Freeway Corridors. Transportation Research B, Vol. 28, No. 2, 1994, pp. 141-160.
9. Chu, L., J.-S. Oh, and W. Recker. Adaptive Kalman-Filter-Based Freeway Travel Time Estimation. Presented at 84th Annual Meeting of the Transportation Research Board, Washington, D.C., 2005.
10. Work, D., O.-P. Toossavainen, S. Blandin, A. Bayen, T. Iwuchukwu, and T. Tracton. An Ensemble Kalman Filtering Approach to Highway Traffic Estimation Using GPS Enabled Mobile Devices. Proc., 47th IEEE Conference on Decision and Control, Cancun, Mexico, Dec. 9-11, 2008, pp. 5062-5068.
11. Bell, M. G. H. The Real Time Estimation of Origin-Destination Flows in the Presence of Platoon Dispersion. Transportation Research Part B, Vol. 25, No. 2-3, 1991, pp. 115-125.
12. Codina, E., and J. Barceló. Adjustment of O-D Matrices from Observed Volumes: An Algorithmic Approach Based on Conjugate Gradients. European Journal of Operations Research, Vol. 155, 2004, pp. 535-557.
13. Ben-Akiva, M., M. Bierlaire, D. Burton, H. N. Kotsopoulos, and R. Mishalani. Network State Estimation and Prediction for Real-Time Traffic Management. Networks and Spatial Economics, Vol. 1, 2001, pp. 293-318.
14. Mahmassani, H. S., and X. Zhou. Transportation System Intelligence: Performance Measurement and Real-Time Traffic Estimation and Prediction in a Day-to-Day Learning Framework. In Advances in Control, Communication Networks, and Transportation Systems (E. Abed, ed.), Birkhauser Boston, Mass., 2005.
15. Theil, H. Applied Economic Forecasting. North-Holland, Netherlands, 1966.