Object-Oriented Geographic Information System Data Model for Transit Trip-Planning Systems

Abstract

Efficiency is essential to Internet transit trip-planning systems. High-quality data models of transit networks hold the key to efficiency of data querying and network analysis. Because of the schedule control and dynamic nature of the transit network, highway-based generic network models cannot be directly implemented by transit systems. In the process of developing an Internet transit trip-planning system, an object-oriented geographic information system data model, which handles the dynamic nature of transit systems, was developed. In this data model, the entire transit network and its components are modeled as space–time entities (objects) that have start times, end times, and spans of lifetime. A time map object controls the creation and destruction of these objects. Therefore, in the process of network search, only active components of the system (i.e., with transit services available) are built into the network topology. This has greatly reduced data redundancy and enhanced network search efficiency. The data model showed good performance when it was implemented in an online trip-planning service for Waukesha Metro Transit, Wisconsin.

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References

Vonderohe

A. P.

, Chou

C. L.

, Sun

, and Adams

. Results of a Workshop on a Generic Data Model for Linear Referencing System. Proc., Geographic Information System for Transportation Symposium, Sparks, Nev., 1995, pp. 23–56.

Vonderohe

A. P.

, and Hepworth

T. D.

. Analysis and Adjustment of Measurement Systems for Linear Referencing. URISA Journal, Vol. 10, No. 1, 1998, pp. 37–47.

Vonderohe

A. P.

, and Hepworth

T. D.

. A Methodology for Design of Measurement Systems for Linear Referencing. URISA Journal, Vol. 10, No. 1, 1998, pp. 48–57.

Dueker

K. J.

, and Butler

J. A.

. GIS-T Enterprise Data Model with Suggested Implementation Choices. URISA Journal, Vol. 10, No. 1, 1998, pp. 12–36.

Fletcher

, Espinoza

, Mackoy

R. D.

, Gordon

, Spear

, and Vonderohe

. The Case for a Unified Linear Reference System. URISA Journal, Vol. 10, No. 1, 1998, pp. 7–11.

Sutton

J. C.

, and Wyman

M. M.

. Dynamic Location: An Iconic Model to Synchronize Temporal and Spatial Transportation Data. Transportation Research Part C, Vol. 8, 2000, pp. 37–52.

Peng

Z. R.

, and Huang

. Design and Development of Interactive Trip-Planning for Web-Based Transit Information Systems. Transportation Research C, Vol. 8, 2000, pp. 409–425.

Huang

, and Peng

Z. R.

. An Integration of Network Data Model and Routing Algorithms for Online Transit Trip Planning. Presented at 80th Annual Meeting of the Transportation Research Board, Washington, D.C., 2001.

Eiselt

H. A.

, and Sandblom

C.-L.

. Integer Programming and Network Models. Springer, New York, 2000.

10.

Friedrich

, Hofsäß

, and Wekeck

. Timetable-Based Transit Assignment Using Branch and Bound. Presented at 80th Annual Meeting of Transportation Research Board, Washington, D.C., 2001.

11.

Wachowicz

Object-Oriented Design for Temporal GIS. Taylor & Francis, London, 1999.

12.

Huang

, and Peng

Z. R.

. Schedule-Based Path Finding Algorithms for Online Transit Trip Planning. Presented at 81st Annual Meeting of Transportation Research Board, Washington, D.C., 2002.