Analyzing the Effect of Passenger-Requested Unscheduled Stops on Demand

  • Dejan Paliska
  • Jurij Kolenc
Keywords: public transit, reliability measures, statistical models, unscheduled stops


This paper discusses the effect of unscheduled stops requestedby passengers on bus transit demand and presents theresults of its study. In the research a set of regression modelsthat estimate the route-level demand were developed using datacollected with Automatic Passenger Counters and AutomaticVehicle Location systems installed on buses, and demographic,socio-economic and land use information from other sources.The results obtained indicate that the number of rider-requestedunscheduled stops have no significant effect on demand,suggesting that the company policy which tolerates unscheduledstops is inadequate for attracting new riders.


Kemp, M. A.: A Simultaneous Equations Analysis of

Route Demand and Supply, and its Application to the San

Diego Bus System, Washington, DC: UMTA, Report

DTUM-60-80-71001, 1981.

Horowitz, A. J,: Simplifications for Single-Route Transit

Ridership Forecasts Transportation 12, pp. 261-275,

Azar, K. T., and J, F. Ferreira: Integrating Geographic

Information Systems into Transit Ridership Forecast Models,

Journal of Advanced Transportation 29(3), pp.

-279, 1994.

Hartgen, D., and M. W. Horner: A Route-Level Transit

Ridership Forecasting Model for Lane Transit District,

Oregon. NC, Center for Interdisciplinary Transportation

Studies, Report No. 170, 1997.

Peng, Z.:A Simultaneous Route-Level Transit Patronage

Model: Demand, Supply, and Inter-Route Relationships.

Unpublished doctoral dissertation, Portland State University,

Portland, OR, 1994.

Kimpel, T. J.: Time Point-Level Analysis of Transit Service

Reliability and Passenger Demand. Portland, OR:

Unpublished Doctor of Philosophy in Urban Studies,

Portland State University, 2001.

Furth, P. G., B. Hemily, T. H. Mueller, and f. G. Strathman:

Uses of Archived A VL-APC Data to Improve Transit

Performance and Management: Review and Potential,

Washington DC: Transportation Research Board,

TRCP Report No. 23 (Project H-28),

h ttp://gulliver.

tcrp webdoc 23. pdf, 2003.

Vaziri, M., Hutchinson, J., and M. Kermanshah: Short-

Term Demand for Specialized Transportation: Time-

-Series Model, Journal of Transportation Engineering

, pp. 6105-121, 1990.

Arrowhead Space & Telecommunications, Inc: Bus

Driver Fatigue and Stress Issues Study, Final Report No.

DTGH61-99-Z-00027, Washington DC.


Peng, Z., and K. J, Dueker: Spatial Data Integration in

Route-Level Transit Demand Modeling, Journal of the

Urban and Regional Information Systems Association

, pp. 26-37, 1995.

Pendyala, R. M.: Integrated Transit Demand and Supply

Model User Manual. ITSUP Version 0.50, Public Transit

Office, Florida Department of Transportation, Tallahassee,

Zhao, F., L. Chow, M. Li, Gan, A., and L. D. Shen:

FSUTMS Mode Choice Modeling: Factors Affecting

Transit Use and Access, Report No. NCTR 392-07,

-03, National Center For Transit Research

(NCTR), University of South Florida, 2002.

Zhao, F: GIS Analysis of the Impact of Community

Design on Transit Accessibility, Proceedings of the

ASCE South Florida Section 1998 Annual Meeting,

Sanibel Island, FL., pp. 1-12, 1998.

Brinckerhoff, P.: Tour and Trip Mode Choice Models,

Draft Technical Report, Prepared for Sacramento

Area Council of Governments, Sacramento, California,

Sun, X., Wilmont, C. G., and T. Kasturi: Household

Travel, Household Characteristics, and Land Use: An

Empirical Study from the I994 Portland Travel Survey,

Transportation Research Record 1617, Transportation

Research Board, National Research Council, Washington,

D. C. , 1998.

Loutzenheiser, D. R.: Pedestrian Access to Transit: Model

of Walk Trips and Their Design and Urban Form

Determinants around Bay Area Rapid Transit Stations,

Transportation Research Record 1604, Transportation

Research Board, National Research Council, Washington,

D. C., pp. 40-49, 1997.

Dargay, J., and M. Hanly: The Demand for Local Bus

Service in England, Journal of Transport Economics

and Policy 36, pp. 73-91, 2002.

Preslar, D. A.: Transit Ridership Forecasting Using a

GIS, Proceedings of the ASCE Conference on Transportation,

Land Use, and Air Quality - Making the

Connection pp. 595- 605, 1998.

Zhao, F., L. Chow, M. Li, I. Ubaka, and A. Gan: Forecasting

Transit Walk Accessibility: Regression Model Alternative

to Buffer. Transportation Research Record


How to Cite
Paliska D, Kolenc J. Analyzing the Effect of Passenger-Requested Unscheduled Stops on Demand. Promet [Internet]. 1 [cited 2024Jul.19];19(4):213-20. Available from:
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