An extended model and procedural framework for planning multi-modal passenger journeys

Transportation Research Part B: Methodological

Volumn 37, Issue 7, 2003, Pages 641-660

  Horn, Mark E T ^a  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

Author keywords

Demand responsive; Journey planning; Modelling; Multi modal; Optimisation; Public transport; Shortest path; Simulation; Traveller information

Indexed keywords

ALGORITHMS; COMPUTATIONAL METHODS; PLANNING;

PUBLIC TRANSPORT SERVICES;

TRANSPORTATION;

OPTIMIZATION; PLANNING METHOD; PUBLIC TRANSPORT; SERVICE PROVISION; TRANSPORTATION PLANNING;

EID: 0037616266     PISSN: 01912615     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0191-2615(02)00043-7     Document Type: Article

References (18)

1. Cormen, T. H., Leiserson, C. E., & Rivest, R. L. (1990). Introduction to algorithms. : MIT Press and McGraw-Hill.
2. DFT, 2002. A review of the effectiveness of personalised journey planning techniques, http://www.localtransport.dft.gov.uk/travelplans/pjourney/.
3. Dial, R.B., 1967. Transit pathfinder algorithm. Highway Research Record, vol. 205. National Research Council (USA). Highway Research Board, pp. 67-85
4. Dijkstra, E. W. (1959). A note on two problems in connection with graphs. Numerische Mathematik, 1 269-271.
5. Hickman, M. D., & Wilson, N. H. M. (1995). Passenger travel time and path choice implications of real-time transit information. Transportation Research-C, 3(4), 211-226.
6. Horn, M.E.T., Procedures for planning multi-leg journeys with fixed-route and demand-responsive passenger transport services. Transportation Research Part C, in press
7. Horn, M.E.T., 2000. A framework for modelling passenger movement in urban public transport systems. 22nd Conference of the Australian Institutes of Transport Research, Canberra 2000
8. Horn, M.E.T., 2001. An extended journey-planning framework for passenger transport modelling, CSIRO Mathematical and Information Sciences Technical Report 01/48
9. Horn, M. E. T. (2002). Multi-modal and demand-responsive passenger transport systems: a modelling framework with embedded control systems. Transportation Research A, 36 167-188.
10. Infopolis, 2000. http://www.ul.ie/~infopolis.
11. Lee, F., 2001. Twenty-first century journey-planning, Operational Research Society Newsletter 365, and at http://www.uk.cgey.com/services/or/docs/21ņturyurnℏan.pdf.
12. MVA, 2002. http://www.mva-group.com/tech/dss/ojps.htm.
13. Opcom, 2002. http://www.opcom.com.au/iptis/index.html.
14. Peng, Z. -R, & Huang, R. (2000). Design and development of interactive trip planning for web-based transit information systems. Transportation Research C, 8(1-6), 409-425.
15. Spiess, H., & Florian, M. (1989). Optimal strategies: a new network assignment model for transit networks. Transportation Research B, 23(2), 83-102.
16. Tong, C. O., & Richardson, A. J. (1984). A computer model for finding the time-dependent minimum path in a transit system with fixed schedules. Journal of Advanced Transportation, 18(2), 145-161.
17. Tong, C. O., & Wong, S. C. (1999). A stochastic transit assignment model using a dynamic schedule-based network. Transportation Research-B, 33(2), 107-121.
18. Wu, J. H., Florian, M., & Marcotte, P. (1994). Transit equilibrium assignment: a model and solution algorithm. Transportation Science, 28(3), 193-203.