A Robust and Efficient Method for Fusing Heterogeneous Data from Traffic Sensors on Freeways

Computer-Aided Civil and Infrastructure Engineering

Volumn 25, Issue 8, 2010, Pages 596-612

  Van Lint, J W C ^a   Hoogendoorn, Serge P ^a  

^a DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATED VEHICLE IDENTIFICATIONS; CONGESTED TRAFFIC; CRITICAL TASKS; DATA ARCHIVAL; DATA CORRUPTION; DATA FUSION ALGORITHM; DATA SOURCE; EFFICIENT METHOD; FREE FLOWING; FREEWAY TRAFFIC; GROUND TRUTH; HETEROGENEOUS DATA; MICROSIMULATION; ON-LINE TRAFFIC; SPATIOTEMPORAL SEMANTICS; TEMPORAL RESOLUTION; TRAFFIC CONDITIONS; TRAFFIC DATA; TRAFFIC FLOW THEORY; TRAFFIC SENSORS; TRAVEL TIME;

DATA FUSION; HIGHWAY PLANNING; HIGHWAY TRAFFIC CONTROL; LICENSE PLATES (AUTOMOBILE); ONLINE SYSTEMS; SEMANTICS; TRAFFIC SURVEYS;

SENSORS;

COMPUTER SIMULATION; SENSOR; SPATIAL RESOLUTION; SPATIOTEMPORAL ANALYSIS; TRAFFIC CONGESTION; TRAFFIC MANAGEMENT; TRAVEL TIME;

EID: 78651473768     PISSN: 10939687     EISSN: 14678667     Source Type: Journal    
DOI: 10.1111/j.1467-8667.2009.00617.x     Document Type: Article

References (38)

1. Castillo, A. E., Conejo, A. J., Menéndez, J. M. & Jiménez, P. (2008), The observability problem in traffic network models, Computer-Aided Civil and Infrastructure Engineering, 23(3), 208-22.
2. Castillo, A. E., Menéndez, J. M. & Sánchez-Cambronero, S. (2008), Traffic estimation and optimal counting location without path enumeration using Bayesian networks, Computer-Aided Civil and Infrastructure Engineering, 23(3), 189-207.
3. Dailey, D. J., Harn, P. & Lin, P.-J. (1996), ITS data fusion, Technical Report Research Project T9903, Task 9, Washington State Transportation Commission, Department of Transportation and the U.S. Department of Transportation, Federal Highway Administration
4. Dharia, A. & Adeli, H. (2003), Neural network model for rapid forecasting of freeway link travel time, Engineering Applications of Artificial Intelligence, 16(7-8), 607-13.
5. FOSIM (Freeway Operations SIMulation) (2008).
6. Hegyi, A., De Schutter, B. & Hellendoorn, H. (2005), Model predictive control for optimal coordination of ramp metering and variable speed limits, Transportation Research Part C: Emerging Technologies, 13(3), 185.
7. Helbing, D. & Treiber, M. (2002), Critical discussion of synchronized flow, Cooperative Transportation Dynamics, 1, 2.1-2.24.
8. Hellinga, B. R. (2002), Improving freeway speed estimates from single-loop detectors, Journal of Transportation Engineering, 128(1), 58-67.
9. Herrera, J. C. & Bayen, A. M. (2008), Traffic flow reconstruction using mobile sensors and loop detector data, Transportation Research Board 87th Annual Meeting, Transportation Research Board, p. 18, 08-1868.
10. Hoogendoorn, S. P. & Bovy, P. H. L. (2001), State-of-the-art of vehicular traffic flow modeling, Proc. Institution of Mechanical Engineers, 215(1), 283-303.
11. Ivan, J. N. & Sethi, V. (1998), Data fusion of fixed detector and probe vehicle data for incident detection, Computer-Aided Civil and Infrastructure Engineering, 13, 329-37.
12. Karim, A. & Adeli, H. (2003), Fast automatic incident detection on urban and rural freeways using wavelet energy algorithm, Journal of Transportation Engineering, ASCE, 129(1), 57-68.
13. Kerner, B. S. (2004), The Physics of Traffic: Empirical Freeway Pattern Features, Engineering Applications, and Theory, Springer, Berlin, New York
14. Kesting, A. & Treiber, M. (2008), How reaction time, update time, and adaptation time influence the stability of traffic flow, Computer-Aided Civil and Infrastructure Engineering, 23, 125-37.
15. Kikuchi, S., Miljkovitc, D. & Van Zuylen, H. (2000), Examination of methods that adjust observed traffic volumes on a network, Transport Research Record, 1717, 109-19.
16. Lighthill, M. & Whitham, G. (1955), On kinematic waves ii: a theory of traffic flow on long crowded roads, Proceedings of the Royal Society of London Series A, 229(1178), 317-45.
17. Linn, R. J. & Hall, D. L. (1991), A survey of multi-sensor data fusion systems, Proceedings of the SPIE - The International Society for Optical Engineering, Orlando, Florida, 13-29.
18. Luo, R., Yih, C.-C. & Su, K. L. (2002), Multisensor fusion and integration: approaches, applications, and future research directions, Sensors Journal, IEEE, 2(2), 107-19.
19. Newell, G. (1993a), A simplified theory of kinematic waves in highway traffic: part i. General theory, Transportation Research Part B: Methodological, 27(4), 281-87.
20. Newell, G. (1993b), A simplified theory of kinematic waves in highway traffic: part ii. Queueing at freeway bottlenecks, Transportation Research B: Methodological, 27(4), 289-303.
21. Ni, D. & Wang, H. (2008), Trajectory reconstruction for travel time estimation, Journal of Intelligent Transportation Systems, 12(3), 113-25.
22. Ou, Q., Van Lint, J. & Hoogendoorn, S. (2008), Piecewise inverse speed correction by using individual travel times, Transportation Research Record: Journal of the Transportation Research Board, 2049(-1), 92-102. 10.3141/2049-11.
23. Papageorgiou, M. & Vigos, G. (2008), Relating time-occupancy measurements to space-occupancy and link vehicle-count, Transportation Research Part C: Emerging Technologies, 16(1), 1-17.
24. Piella, G. (2003), A general framework for multiresolution image fusion: from pixels to regions, Information Fusion, 4(4), 259-80.
25. Richards, P. (1956), Shock waves on the highway, Operations Research, 4, 42-51.
26. Simon, D. (2006), Optimal State Estimation: Kalman, H-infinity, and Nonlinear Approaches, John Wiley & Sons, New York
27. Treiber, M. & Helbing, D. (2002), Reconstructing the spatio-temporal traffic dynamics from stationary detector data, Cooper@tive Transport@tion Dyn@mics, 1, 3.1-3.24.
28. Van Lint, J. & Hoogendoorn, S. P. (2007), The technical and economic benefits of data fusion for real-time monitoring of freeway traffic, World Congress of Transportation Research, WCTRS, Berkely, California
29. Van Lint, J. W. C. (2004), Reliable travel time prediction for freeways, TRAIL Thesis series, TUD Technische Universiteit Delft, Delft
30. Van Lint, J. W. C., Hoogendoorn, S. P. & Hegyi, A. (2008), Dual ekf state and parameter estimation in multi-class first-order traffic flow models, Proceedings of the 17th IFAC (International Federation of Automatic Control) World Congress, Seoul, Korea
31. Van Lint, J. W. C., Hoogendoorn, S. P. & Van Zuylen, H. J. (2005), Accurate travel time prediction with state-space neural networks under missing data, Transportation Research Part C: Emerging Technologies, 13(5-6), 347-69.
32. Van Lint, J. W. C. & Van der Zijpp, N. J. (2003), Improving a travel time estimation algorithm by using dual loop detectors, Transportation Research Record, 1855, 41-48.
33. Varshney, P. K. (1997), Multisensor data fusion, Electronics and Communications Engineering Journal (December), 245-53.
34. Vermijs, R. G. M. M. & Schuurman, H. (1994), Evaluating capacity of freeway weaving sections and on-ramps using the microscopic simulation model fosim, Proceedings of the second international symposium on highway capacity, Vol. 2, Sydney, Australia, 651-70.
35. Wang, Y. & Papageorgiou, M. (2005), Real-time freeway traffic state estimation based on extended Kalman filter: a general approach, Transportation Research Part B, 39, 141-67.
36. Wang, Y., Papageorgiou, M. & Messmer, A. (2006), A real time freeway network traffic surveillance tool, IEEE Transactions on Control Systems Technology, 14(1).
37. Xiong, N. & Svensson, P. (2002), Multi-sensor management for information fusion: issues and approaches, Information Fusion, 3(2), 163-86.
38. Yager, R. R. (2004), A framework for multi-source data fusion, Information Sciences, 163(1-3), 175-200.