Farecard passenger flow model at chicago transit authority, Illinois

Transportation Research Record

Volumn , Issue 2072, 2008, Pages 3-9

  Rahbee, Adam B ^a,b  

^a Chicago Transit Authority   (United States)

^b London Underground Modernisation Programme   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

LIGHT RAIL TRANSIT; MASS TRANSPORTATION;

ALGORITHMICS; CHICAGO; CHICAGO TRANSIT AUTHORITIES; ILLINOIS; NEW YORK CITY TRANSITS; ORIGIN DESTINATION; PASSENGER FLOWS; PASSENGERS' FLOW MODELING; RAIL PASSENGERS; TRANSIT NETWORKS;

RAPID TRANSIT;

EID: 61349144962     PISSN: 03611981     EISSN: None     Source Type: Journal    
DOI: 10.3141/2072-01     Document Type: Article

References (11)

1. Rahbee, A., and D. Czerwinski. Using Entry-Only Automatic Fare Collection Data to Estimate Rail Transit Passenger Flows at CTA. Proc., 2002 Transport Chicago Conference, Chicago, Ill., 2002.
2. Rahbee, A. Path Assignment for the CTA Farecard-Based Rail Passenger Flow Model. Chicago Transit Authority, Chicago, Ill., 2003.
3. Barry, J. J., R. Newhouser, A. Rahbee, and S. Sayeda. Origin and Destination Estimation in New York City Using Automated Fare System Data. In Transportation Research Record: Journal of the Transportation Research Board, No. 1817, Transportation Research Board of the National Academies, Washington, D.C., 2002, pp. 183-187.
4. Hofmann, M. Hybrid Rule Based Architecture for Origin/Destination Extraction from Electronic Fare Collection Data. Proc., Annual Universities' Transport Study Group, Leeds, U.K., 2005.
5. Zhao, J. The Planning and Analysis Implications of Automated Data Collection Systems: Rail Transit OD Matrix Inference and Path Choice Modeling Examples. MS thesis. Massachusetts Institute of Technology, Cambridge, 2004.
6. Farzin, J. Constructing an Automated Bus Origin-Destination Matrix Using Farecard and Global Positioning System Data in São Paulo, Brazil. In Transportation Research Record: Journal of the Transportation Research Board, No. 2072, Transportation Research Board of the National Academies, Washington, D.C. 2008, pp. 30-37.
7. Buneman, K. Automated and Passenger-Based Transit Performance Measures. In Transportation Research Record 992, TRB, National Research Council, Washington, D.C., 1984, pp. 23-28.
8. Gordilla, F. The Value of Automated Fare Collection Data for Transit Planning: An Example of Rail Transit OD Matrix Estimation. MS thesis. Massachusetts Institute of Technology, Cambridge, 2006.
9. Utsunomiya, M. Possible Benefits of Increased Data Availability After Implementing Smart Card in Public Transportation Systems. MS thesis. Massachusetts Institute of Technology, Cambridge, 2004.
10. Cui, A. Bus Passenger Origin-Destination Matrix Estimation Using Automated Data Collection Systems. MS thesis. Massachusetts Institute of Technology, Cambridge, 2006.
11. CTA Rail Passenger Mile Estimates for NTD Reporting. TransInfo, LLC, Chicago, Ill., 2004.