Cost-Minimizing Choice Behavior in Transportation Planning; Preface; Contents; 1 Logit Models for Spatial Interaction: Background; 1.1 Introduction; 1.2 Cost-Minimizing Behavior; 1.3 Intuitive Gravity Models and Most Probable State Approach; 1.4 User Equilibrium in a Network; 1.5 Econometric Models of Probabilistic Choice; 1.6 Luce's Axiomatic Derivation; 1.7 ARUM -- Additive Random Utility Maximization -- Approach; 1.8 Structured or Nested Logit Models; 1.9 Transportation Problem in Linear Programming; 1.10 Lagrangian Methods of Deriving Logit Models; 1.11 Welfare Measures
Summary
This book stems from a desire to understand the underlying assumptions and structure of the choice probability models most often used in transportation planning. The book investigates how far a new way of defining cost minimizing behavior can take us. All commonly used choice probability distributions of the logit type - log linear probability functions - follow from cost minimizing behavior defined in the new way; some new nested models also appear. The new approach provides a deeper understanding of what is at work in the models. The new way of defining cost minimizing behavior is as follows
Bibliography
Includes bibliographical references (pages 149-153)
