Short-Term Prediction of Vehicle Occupancy in Advanced Public Transportation Information Systems (APTIS)

  • P. Coppola
  • L. Rosati
Part of the Operations Research/Computer Science Interfaces Series book series (ORCS, volume 28)

Abstract

Most ITS applications to transit systems are oriented to the efficient management of Public Transportation (PT) operator’s resources, that is crew and fleet of vehicles. However, the potential of ITS application to transit system goes further than the efficient management of the fleet of vehicles. In fact, information on the real-time actual network state, if communicated to travelers, may be an effective tool for improving quality and effectiveness of services and, hence, for diverting people to PT modes. In this paper, we focus on Advanced Public Transportation Information System (APTIS) deploying shared en-route descriptive information. The case study of the city of Naples (Italy) is analyzed. Here PT travelers have reacted positively to being provided information on waiting time at stops and have expressed great interest in receiving additional information such as passenger occupancy of future vehicles. The latter information can be efficiently obtained by means of a modeling framework simulating travelers path choice and the way in which they propagate over the network, as well as Origin-Destination (OD) travel demand pattern. Such a modeling framework is described in this paper. This is based on the schedule based approach and simulates within-day dynamics in transit networks, on both the demand and supply side. Preliminary applications to a small-scale example network are also presented in the paper.

Keywords

Public Transportation Transit System Transit Network Short Term Prediction Random Utility Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Bibliography

  1. [1]
    Azienda Napoletana di Mobilità - ANM (2002). Sistema di Ausilio all’Esercizio paline informative: algoritmo di previsione. ANM Internal ReportGoogle Scholar
  2. [2]
    Cascetta, E., Inaudi, D., and Marquis, G. (1993) Dynamic estimators of origin-destination matrices using traffic counts. Transportation Science, 27, 363–373.CrossRefGoogle Scholar
  3. [3]
    Casey, R. F. et al. (1998) Advanced Public Transportation Systems: The State of the Art. Report of Federal Transit Administration - U.S. Dept. of TransportationGoogle Scholar
  4. [4]
    Miyata, A., Muroaka, K., Akiyama, T. and Abe, A. (1997) The Correction of the Forecasting Travel Time by Using AVI Data. Proceedings of 4th ITS World Congress, Berlin (Germany).Google Scholar
  5. [5]
    Nguyen, S. and Pallottino, S. (1988) Equilibration Traffic Assignment for Large Scale Transit Networks. European Journal of Operational Research, 37, 176–186.CrossRefGoogle Scholar
  6. [6]
    Nuzzolo, A. and Coppola, P. (2002) Real-time information to Public Transportation users: why what when ? Proceeding of Hong Kong Society of Transportation Studies, Hong Kong.Google Scholar
  7. [7]
    Nuzzolo, A., Russo, F., and Crisalli, U. (2002) The schedule-based approach in dynamic transit modeling: a general overview. Preprints of the 1st Workshop on the Schedule-Based Approach in Dynamic Transit Modeling, Ischia (Italy).Google Scholar
  8. [8]
    Nuzzolo, A., and Russo, F. (1994) Departure time and path choice models for intercity transit assignment. Proceedings of the 7th IATBR Conference, Valle Nevado, Cile.Google Scholar
  9. [9]
    Nuzzolo, A., Russo, F., and Crisalli, U. (2001) A doubly dynamic schedule-based assignment model for transit networks. Transportation Science, 35, 268–285.CrossRefGoogle Scholar
  10. [10]
    Nuzzolo, A., and Crisalli U. (2001) Estimation of transit origin/destination matrices from traffic counts using a schedule-based approach. Proceedings of AET Conference, Cambridge (UK).Google Scholar
  11. [11]
    Spiess, H. and Florian, M. (1989) Optimal strategies: a new assignment model for transit networks. Transportation Research, 23B, 83–102.Google Scholar

Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • P. Coppola
    • 1
  • L. Rosati
    • 1
  1. 1.Department of Civil Engineering“Tor Vergata ” University of RomeRomeItaly

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