Estimation of Scaling Factors for Traffic Counts Based on Stationary and Mobile Sources of Data

International Journal of Intelligent Transportation Systems Research

Volumn 15, Issue 3, 2017, Pages 180-191

  Meng, Fanyu ^a   Wong, S C ^a   Wong, W ^a   Li, Y C ^a  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

GPS; Mobile data sources; Scaling factors; Stationary data sources; Taxi; Traffic counts

Indexed keywords

GLOBAL POSITIONING SYSTEM; LINEAR REGRESSION; MEAN SQUARE ERROR; MOBILE POWER PLANTS; REGRESSION ANALYSIS; TAXICABS; TRAFFIC SURVEYS;

DATA-SOURCES; MOBILE DATA; SCALING FACTORS; TAXI; TRAFFIC COUNTS;

INTELLIGENT CONTROL;

EID: 85024932779     PISSN: None     EISSN: 18688659     Source Type: Journal    
DOI: 10.1007/s13177-016-0131-1     Document Type: Article

References (27)

1. Herrera J.C., Work D.B., Herring R., Ban X., Jacobson Q., Bayen A.M.: Evaluation of traffic data obtained via GPS-enabled mobile phones: The Mobile Century field experiment. Transp. Res. C Emerg. Techno. 18(4), 568–583 (2010)
2. Wong W., Wong S.C.: Systematic bias in transport model calibration arising from the variability of linear data projection. Transp. Res. B Methodol. 75, 1–18 (2015)
3. Bachmann C., Abdulhai B., Roorda M.J., Moshiri B.: A comparative assessment of multi-sensor data fusion techniques for freeway traffic speed estimation using microsimulation modeling. Transp. Res. C Emerg. Technol. 26, 33–48 (2013)
4. Faouzi N.-E.E., Leung H., Kurian A.: Data fusion in intelligent transportation systems: progress and challenges – A survey. Inf. Fusion. 12(1), 4–10 (2011)
5. Cao J., Hadiuzzaman M., Qiu T.Z., Hu D.: Real-time queue estimation model development for uninterrupted freeway flow based on shockwave analysis. Can. J. Civ. Eng. 42(3), 153–163 (2015)
6. Strub I.S., Bayen A.M.: Weak formulation of boundary conditions for scalar conservation laws: an application to highway traffic modelling. Int. J. Robust Nonlinear Control. 16(16), 733–748 (2006)
7. Kwong K., Kavaler R., Rajagopal R., Varaiya P.: Arterial travel time estimation based on vehicle re-identification using wireless magnetic sensors. Transp. Res. C Emerg. Technol. 17(6), 586–606 (2009)
8. Chowdhurya D., Desaib R.C.: Steady-states and kinetics of ordering in bus-route models: connection with the Nagel-Schreckenberg model. Eur. Phys. J. B. 15, 375–384 (2000)
9. Ma D., Wang D., Bie Y., Jin S., Mei Z.: Identification of spillovers in urban street networks based on upstream fixed traffic data. KSCE J. Civ. Eng. 18(5), 1539–1547 (2014)
10. Hofleitner A., Herring R., Abbeel P., Bayen A.: Learning the dynamics of arterial traffic from probe data using a dynamic Bayesian network. IEEE Trans. Intell. Transp. Syst. 13(4), 1679–1693 (2012)
11. Jenelius E., Koutsopoulos H.N.: Travel time estimation for urban road networks using low frequency probe vehicle data. Transp. Res. B Methodol. 53, 64–81 (2013)
12. Zhan X., Hasan S., Ukkusuri S.V., Kamga C.: Urban link travel time estimation using large-scale taxi data with partial information. Transp. Res. C Emerg. Technol. 33, 37–49 (2013)
13. Zheng F., Van Zuylen H.: Urban link travel time estimation based on sparse probe vehicle data. Transp. Res. C Emerg. Technol. 31, 145–157 (2013)
14. Bhaskar A., Chung E.: Fundamental understanding on the use of Bluetooth scanner as a complementary transport data. Transp. Res. C Emerg. Technol. 37, 42–72 (2013)
15. Caceres N., Romero L.M., Benitez F.G., del J.M.: Traffic Flow Estimation Models Using Cellular Phone Data. IEEE Trans. Intell. Transp. Syst. 13(3), 1430–1441 (2012)
16. Jie L., van Zuylen H., Chunhua L., Shoufeng L.: Monitoring travel times in an urban network using video, GPS and Bluetooth. Procedia Soc. Behav. Sci. 20, 630–637 (2011)
17. 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. TRB 2003 Annual Meeting, 2003
18. Herrera J.C., Bayen A.M.: Incorporation of Lagrangian measurements in freeway traffic state estimation. Transp. Res. B Methodol. 44(4), 460–481 (2010)
19. Xie, C., Cheu, R., and Lee, D.: Improving arterial link travel time estimation by data fusion. TRB 2004 Annual Meeting, 2004
20. Yager R.R.: On ordered weighted averaging aggregation operators in multicriteria decisionmaking. IEEE Trans. Syst. Man Cybern. 18(1), 183–190 (1988)
21. Canaud M., Nabavi A., Bécarie C., Villegas D., Faouzi N.E.E.: A realistic case study for comparison of data fusion and assimilation on an urban network – the archipel platform. Trans. Res. Procedia. 6, 28–49 (2015)
22. Choi K., Chung Y.: A data fusion algorithm for estimating link travel time. ITS J. 7(3–4), 235–260 (2002)
23. Bhaskar A., Chung E., Dumont A.-G.: Fusing loop detector and probe vehicle data to estimate travel time statistics on signalized urban networks. Comput.-Aided Civ. Infrastruct. Eng. 26(6), 433–450 (2011)
24. Geroliminis N., Daganzo C.F.: Existence of urban-scale macroscopic fundamental diagrams: Some experimental findings. Transp. Res. B Methodol. 42(9), 759–770 (2008)
25. Transport Department, H. K. The annual traffic census 2011. Transport department, Hong Kong, Hong Kong special Adiministrative Region, 2012
26. Travel Characteristics Survey 2011 Final Report. Hong Kong Special Administrative Region, 2014
27. Akaike H.: A New Look at the Statistical Model Identification. IEEE Trans. Autom. Control. AC-19(6), 716–723 (1974)