Preface | p. ix |
Origin-Based Network Assignment | p. 1 |
Introduction | p. 1 |
Problem statement | p. 2 |
Review of solution methods for TAP | p. 4 |
An origin-based method for TAP | p. 6 |
Experimental results | p. 7 |
Discussion | p. 13 |
Conclusions | p. 14 |
On Traffic Equilibrium Models with a Nonlinear Time/Money Relation | p. 19 |
Introduction | p. 20 |
The time-based traffic equilibrium problem | p. 21 |
Solution approaches | p. 23 |
A route generation algorithm | p. 26 |
Numerical tests | p. 27 |
Stochastic Network Equilibrium Under Stochastic Demand | p. 33 |
Introduction | p. 33 |
Notation | p. 35 |
Critique of SUE in the context of day-to-day variability | p. 37 |
Equilibrium conditions: fixed demand | p. 40 |
Equilibrium conditions: stochastic demand | p. 44 |
Solution algorithm | p. 45 |
Numerical tests | p. 46 |
Conclusion | p. 49 |
Stochastic Assignment with Gammit Path Choice Models | p. 53 |
Introduction | p. 53 |
Review of stochastic assignment | p. 55 |
Probabilistic path choice models | p. 59 |
Numerical examples | p. 63 |
Conclusions | p. 66 |
Estimation of Travel Time Reliability | p. 69 |
Introduction | p. 69 |
Logit SUE model | p. 72 |
Logit SUE sensitivity analysis | p. 72 |
Approximation of travel times variances | p. 77 |
Example | p. 77 |
Conclusion | p. 83 |
A Joint Model of Mode/Parking Choice with Elastic Parking Demand | p. 85 |
Background and objectives | p. 85 |
The parking choice sub-model | p. 88 |
The mode choice sub-model | p. 95 |
Simulation of realistic parking policies | p. 97 |
A New General Equilibrium Model | p. 105 |
Introduction | p. 106 |
DREAM--The general equilibrium model | p. 108 |
An outline of the DREAM model | p. 109 |
Features of the general equilibrium model | p. 113 |
Test Results | p. 116 |
Macroscopic Flow Models | p. 119 |
Introduction | p. 119 |
The basic model LWR model for a link | p. 120 |
Partial flow models for links | p. 122 |
Intersection modeling | p. 126 |
Intersection models as solutions of optimization problems | p. 133 |
An experimental validation | p. 136 |
Conclusion | p. 137 |
AIMSUN 2 Simulation of a Congested Auckland Freeway | p. 141 |
Introduction and objectives | p. 141 |
Simulation model | p. 142 |
AIMSUN 2 simulation process | p. 144 |
Study area and scope | p. 144 |
Model development | p. 146 |
Geometric information | p. 146 |
Traffic flow information | p. 147 |
Trip matrices | p. 147 |
Driver and vehicle information | p. 147 |
Maximum vehicle acceleration | p. 149 |
Motorway model | p. 151 |
Model outputs | p. 153 |
Lane utilisation | p. 153 |
Motorway speeds | p. 154 |
Greenlane Northbound on-ramp | p. 155 |
Calibration parameters | p. 156 |
Run times | p. 159 |
Conclusion | p. 159 |
Postscript | p. 160 |
Fuzzy Traffic Signal Control | p. 163 |
Introduction | p. 163 |
Fuzzy traffic signal control | p. 163 |
Fuzzification interface | p. 166 |
Defuzzification of outputs | p. 170 |
Conclusions | p. 174 |
An Urban Bus Network Design Procedure | p. 177 |
Introduction | p. 177 |
The main transit network (MTN) | p. 178 |
The main transit lines (MTL) | p. 181 |
Feeder lines | p. 185 |
Model application and results | p. 186 |
Conclusions | p. 193 |
The Cone Projection Method | p. 197 |
Introduction | p. 198 |
Achieving the complementarity formulation | p. 198 |
A cone field method of calculating equilibria | p. 203 |
The cone projection method | p. 205 |
A simple method | p. 207 |
Conclusion | p. 209 |
A Park & Ride Integrated System | p. 213 |
Introduction | p. 214 |
A Park & Ride Integrated system | p. 215 |
Routing model | p. 217 |
Travel time prediction | p. 221 |
Computational results | p. 225 |
Conclusion | p. 227 |
Longitudinal Analysis of Car Ownership in Different Countries | p. 229 |
Introduction | p. 229 |
An age-cohort-period model | p. 230 |
A multinational comparison | p. 233 |
A comparative analysis for homogeneous zones | p. 239 |
Long term forecasting using the demographic approach | p. 241 |
Summary and conclusions | p. 242 |
Index | p. 247 |
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