Designing heterogeneous sensor networks for estimating and predicting path travel time dynamics: An information-theoretic modeling approach

Transportation Research Part B: Methodological

Volumn 57, Issue , 2013, Pages 66-90

  Xing, Tao ^a   Zhou, Xuesong ^b   Taylor, Jeffrey ^a  

^a Department of Electrical and Computer Engineering   (United States)

^b Arizona State University   (United States)

Author keywords

Automatic vehicle identification sensors; Automatic vehicle location sensors; Sensor network design; Travel time prediction

Indexed keywords

AUTOMATIC VEHICLE IDENTIFICATION; ERRORS; FORECASTING; IMPORTANCE SAMPLING; INFORMATION THEORY; LOCATION; SENSOR NETWORKS; TIME VARYING CONTROL SYSTEMS; TRAFFIC CONTROL; UNCERTAINTY ANALYSIS;

AUTOMATIC VEHICLE LOCATIONS; DETERMINANT MAXIMIZATION; HETEROGENEOUS SENSOR NETWORKS; SENSOR NETWORK DESIGN; SENSOR SELECTION PROBLEM; TRAVEL TIME PREDICTION; TRAVEL TIME UNCERTAINTY; UNCERTAINTY QUANTIFICATIONS;

TRAVEL TIME;

ALGORITHM; ERROR ANALYSIS; ESTIMATION METHOD; KALMAN FILTER; MODELING; PREDICTION; SENSOR; TRAVEL TIME;

EID: 84885081923     PISSN: 01912615     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trb.2013.09.007     Document Type: Article

References (43)

1. Ban X., Herring R., Margulici J.D., Bayen A. Optimal sensor placement for freeway travel time estimation. Transportation and Traffic Theory 2009, 97-721. Springer, (Chapter 34). W.H.K. Lam, S.C. Wong, H.K. Lo (Eds.).
2. Chen A., Chootinan P., Pravinvongvuth S. Multiobjective model for locating automatic vehicle identification readers. Transportation Research Record 2004, 1886:49-58.
3. Coifman B., Beymer D., Mc Lauchlan P., Malik J. A real-time computer vision system for vehicle tracking and traffic surveillance. Transportation Research Part C 1998, 6(4):271-288.
4. Danczyk A., Liu H. A mixed-integer linear program for optimizing sensor locations along freeway corridors. Transportation Research Part B 2011, 45(1):208-217.
5. Eisenman S.M., Fei X., Zhou X., Mahmassani H.S. Number and location of sensors for real-time network traffic estimation and prediction: a sensitivity analysis. Transportation Research Record 2006, 1964:260-269.
6. Evensen G. The ensemble Kalman filter: theoretical formulation and practical implementation. Ocean Dynamics 2003, 53(4):343-367.
7. Fei X., Mahmassani H.S. Structural analysis of near-optimal sensor locations for a stochastic large-scale network. Transportation Research Part C 2011, 19(3):440-453.
8. Fei X., Mahmassani H.S., Murray-Tuite P. Vehicular network sensor placement optimization under uncertainty. Transportation Research Part C 2013, 29:14-31.
9. Fei X., Lu C.-C., Liu K. A Bayesian dynamic linear model approach for real-time short-term freeway travel time prediction. Transportation Research Part C 2011, 19(6):1306-1318.
10. Haas, C., Mahmassani, H.S., Khoury, J., Haynes, M., Rioux, T., Logman, H., 2001. Evaluation of Automatic Vehicle Identification for San Antonio's Transguide for Incident Detection and Advanced Traveler Information Systems. Center for Transportation Research, University of Texas at Austin, Research Report No. 4957-1.
11. Gentili M., Mirchandani P.B. Locating sensors on traffic networks: models, challenges and research opportunities. Transportation Research Part C 2012, 24:227-255.
12. Haghani A., Hamedi M., Sadabadi K.F., Young S., Tarnoff P. Data collection of freeway travel time ground truth with Bluetooth sensors. Transportation Research Record 2010, 2160:60-68.
13. Herrera J.-C., Bayen A. Incorporation of Lagrangian measurements in freeway traffic state estimation. Transportation Research Part B 2010, 44(4):160-481.
14. Hintz K.J., McVey E.S. Multi-process constrained estimation. IEEE Transactions on Systems, Man and Cybernetics 1991, 21(1):237-244.
15. Hurdle V.F., Son B. Road test of a freeway model. Transportation Research Part A 2000, 34(7):537-564.
16. Lam W.H.K., Lo H.P. Accuracy of O-D estimates from traffic counts. Traffic Engineering and Control 1990, 31(6):358-367.
17. Leow W.L., Ni D., Pishro-Nik H. A sampling theorem approach to traffic sensor optimization. IEEE Transactions on Intelligent Transportation Systems 2008, 9(2):369-374.
18. Li X., Ouyang Y. Reliable sensor deployment for network traffic surveillance. Transportation Research Part B 2011, 45(1):218-231.
19. Lindveld Ch.D.R., Thijs R., Bovy P.H.L., Van der Zijpp N.J. Evaluation of on-line travel time estimators and predictors. Transportation Research Record 2000, 1719:45-53.
20. Liu H., Danczyk A. Optimal sensor locations for freeway bottleneck identification. Computer-Aided Civil and Infrastructure Engineering 2009, 24(8):535-550.
21. Löfberg, J., 2004. YALMIP: a toolbox for modeling and optimization in Matlab. In: Proceedings of the CACSD Conference, Taipei, Taiwan, September 2004, pp. 284-289.
22. Lu, J., Tang, H., Lu, S., Ran, B., 2006. Locating roadside servers for advanced traveler information systems. In: Transportation Research Board 85th Annual Meeting, CD 06-1544, Washington, DC, USA, January 2006.
23. Min W., Wynter L. Real-time road traffic prediction with spatio-temporal correlations. Transportation Research Part C 2011, 19(4):606-616.
24. Mirchandani P.B., Gentili M., He Y. Location of vehicle identification sensors to monitor travel-time performance. IET Intelligent Transport Systems 2009, 3(3):289-303.
25. Newell G.F. A simplified theory on kinematic waves in highway traffic, part I: general theory. Transportation Research Part B 1993, 27(4):281-287.
26. Ni D., Leonard J.D., Williams B.M. The network kinematic waves model: a simplified approach to network traffic. Journal of Intelligent Transportation Systems: Technology, Planning, and Operations 2006, 10(1):1-14.
27. Okutani I., Stephanedes Y. Dynamic prediction of traffic volume through Kalman filtering theory. Transportation Research Part B 1984, 18(1):1-11.
28. Rakha H., Zhang W. Estimating traffic stream space-mean speed and reliability from dual and single loop detectors. Transportation Research Record 2005, 1925:38-47.
29. Shannon C.E. A mathematical theory of communication. Bell System Technical Journal 1948, 27:379-423.
30. Sherali H.D., Desai J., Rakha H. A discrete optimization approach for locating automatic vehicle identification readers for the provision of roadway travel times. Transportation Research Part B 2006, 40(10):857-871.
31. Stathopoulos A., Karlaftis M.G. A multivariate state space approach for urban traffic flow modeling and prediction. Transportation Research Part C 2003, 11(2):121-135.
32. Toh K.C., Todd M.J., Tutuncu R.H. SDPT3 - a Matlab software package for semidefinite programming. Optimization Methods and Software 1999, 11:545-581.
33. Turner, S.M., Eisele, W.L., Benz, R.J., Holdener, D.J., 1998. Travel Time Data Collection Handbook. Federal Highway Administration, Office of Highway Information Management, Washington, DC, Report FHWA-PL-98-035.
34. Vandenberghe L., Boyd S., Wu S.-P. Determinant maximization with linear matrix inequality constraints. SIAM Journal on Matrix Analysis and Applications 1998, 19(2):499-533.
35. Van Lint, J.W.C., 2004. Reliable Travel Time Prediction for Freeways. Ph.D. Dissertation. Delft University of Technology, Netherland.
36. Van Lint J.W.C., Van der Zijpp N.J. Improving a travel-time estimation algorithm by using dual loop detectors. Transportation Research Record 2003, 1855:41-48.
37. Wasson J.S., Sturdevant J.R., Bullock D.M. Real-time travel time estimates using MAC address matching. Institute of Transportation Engineers Journal 2008, 78(6):20-23.
38. Work, D., Tossavainen, O.-P., Blandin, S., Bayen, A., Iwuchukwu, T., Tracton, K., 2008. An ensemble Kalman filtering approach to highway traffic estimation using GPS enabled mobile devices. In: Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mexico, December 9-11, 2008, pp. 5062-5068.
39. Yang H., Iida Y., Sasaki T. An analysis of the reliability of an origin-destination trip matrix estimated from traffic counts. Transportation Research Part B 1991, 25(5):351-363.
40. Yperman, I., Logghe, S., Immers, B., 2005. The link transmission model: an efficient implementation of the kinematic wave theory in traffic networks. In: Proceedings of the 10th EWGT Meeting and 16th Mini-Euro Conference, Poznan, Poland, September 2005, pp. 122-127.
41. Zhang X., Rice J.A. Short-term travel time prediction. Transportation Research Part C 2003, 11(3-4):187-210.
42. Zhou X., List G.F. An information-theoretic sensor location model for traffic origin-destination demand estimation applications. Transportation Science 2010, 44(2):254-273.
43. Zhou X., Mahmassani H.S. A structural state space model for real-time origin-destination demand estimation and prediction in a day-to-day updating framework. Transportation Research Part B 2007, 41(8):823-840.