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Schedule-Based Dynamic Transit Modeling : Theory and Applications - Nigel H.M. Wilson

Schedule-Based Dynamic Transit Modeling

Theory and Applications

By: Nigel H.M. Wilson (Editor), Agostino Nuzzolo (Editor)

Hardcover

Published: 1st November 2003
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Schedule-Based Dynamic Transit Modeling: Theory and Applications outlines the new schedule-based dynamic approach to mass transit modeling. In the last ten years the schedule-based dynamic approach has been developed and applied especially for operational planning. It allows time evolution of on-board loads and travel times for each run of each line to be obtained, and uses behavioral hypotheses strictly related to transit systems and user characteristics. It allows us to open new frontiers in transit modelling to support network design, timetable setting, investigation of congestion effects, as well as the assessment of new technologies introduction, such as information to users (ITS technologies).

The contributors and editors of the book are leading researchers in the field of transportation, and in this volume they build a solid foundation for developing still more sophisticated models. These future models of mass transit systems will continue to add higher levels of accuracy and sensitivity desired in forecasting the performance of public transport systems.

Prefacep. ix
General Aspects
The Schedule-Based approach in dynamic transit modelling: a general overviewp. 1
Introductionp. 1
User target time and demand temporal segmentationp. 3
Transit supply modelsp. 5
Schedule-based path choice modelsp. 9
Schedule-based assignment modelsp. 19
Conclusionsp. 22
A dynamic mode transit service choice model to design ex-urban transport service timetablesp. 25
Introductionp. 25
The proposed joint mode-transit service choice model: general structurep. 27
The database and choice set definitionp. 29
Estimation of the modelp. 31
Conclusionp. 38
Finding shortest time-dependent paths in Schedule-Based transit networks: a Label Setting algorithmp. 43
Introductionp. 43
General problem definitionp. 44
The deterministic transit assignment algorithmp. 45
Application issuep. 50
Conclusionsp. 51
A large scale Stochastic Multi-Class Schedule-Based transit model with random coefficientsp. 53
Backroundp. 53
Modelling contextp. 55
Utility functions in the transit assignment modelp. 56
Solution algorithmp. 64
Proposals to optimise MSA-based modelsp. 67
Conclusions and recomendationsp. 73
Schedule-Based Dynamic Assignment models for public transport networksp. 79
Introduction and general definitionsp. 79
Demand modelsp. 81
Supply modelsp. 85
Transit dynamic assignment modelsp. 90
Application to Its
Simulation-Based Evaluation of Advanced Public Transportation Systemsp. 95
Introductionp. 95
Model requirementsp. 96
Modeling frameworkp. 98
Case studyp. 106
Conclusionp. 111
Short-term prediction of vehicle occupancy in Advanced Public Transportation Information Systems (APTIS)p. 113
Introductionp. 113
The case study of the city of Naplesp. 116
The overall modeling frameworkp. 118
Preliminary applications to small scale examples networksp. 128
Conclusion and research perspectivesp. 133
DY-RT: a tool for Schedule-Based planning of regional transit networksp. 135
Introductionp. 135
DY-RT software architecturep. 137
DY-RT: the system of modelsp. 141
Application examplesp. 149
Conclusionsp. 157
A Schedule-Based transit assignment model addressing the passengers' choice among competing connectionsp. 159
Introductionp. 159
Existing approachesp. 160
Connection searchp. 164
Connection choicep. 167
Application and outlookp. 172
Estimation of transit passenger Origin-Destination matrices from passenger counts in congested transit networksp. 175
Introductionp. 175
Some useful concepts for transit networks and notationsp. 177
Model formulationp. 182
Solution algorithmp. 186
Numerical examplep. 188
Conclusionsp. 194
Evaluation of O/D trip matrices by traffic counts in transit systemsp. 197
Introductionp. 197
Notationsp. 200
Estimation of O/D levels by traffic countsp. 203
Estimation of demand model parameters by traffic countsp. 205
Application to a real casep. 207
Conclusionsp. 214
Application for comparing frequency and Schedule-Based approaches in the simulation of a low frequency transit systemp. 217
Introductionp. 218
Assignment models in optimal strategy and schedule-based approachesp. 220
Experimentation in an ex-urban areap. 228
Conclusions and indications for future developmentsp. 235
Minimum path algorithms for a Schedule-Based transit network with a general fare structurep. 241
Introductionp. 241
Cheapest path algorithmp. 243
Optimal path algorithmp. 245
Test networkp. 248
Conclusionp. 250
A Solution to the transit assignment problemp. 263
Introductionp. 263
Problem definitionp. 266
Assignment methodsp. 267
Fail to board probabilitiesp. 269
Capacity constraint transit assignmentp. 272
Examplep. 273
Conclusions and discussionp. 274
Indexp. 281
Table of Contents provided by Ingram. All Rights Reserved.

ISBN: 9781402076879
ISBN-10: 1402076878
Series: Operations Research/Computer Science Interfaces Series
Audience: General
Format: Hardcover
Language: English
Number Of Pages: 282
Published: 1st November 2003
Publisher: Springer-Verlag New York Inc.
Country of Publication: US
Dimensions (cm): 23.5 x 15.5  x 2.54
Weight (kg): 1.32