01024723

Component

https://doi.org/10.3141/1964-04

http://scholar.google.com...mans&publication_year=2006

Existing learning and adaptive behavior models are typically derived from reinforcement learning from actual experiences in dynamic nonstationary environments. When the dynamics involve uncertainty with respect to the choice behavior of other travelers, travelers might make particular choice options by taking into account their expectations about the behavior of other travelers. Consequently, they will learn not only from their own experiences but also from the extent to which their conjectures about the behavior of other travelers are consistent with actual choices. A general model of interactive learning behavior that evolves toward equilibrium in such strategic situations is described. The properties of the model are examined by using numerical computer simulations. The results of the simulations support the face validity of the formulated model.

01037567

English

pp 27-34

2006

Transportation Research Record: Journal of the Transportation Research Board

0309099730

Print

Figures (6) ; References (14)

Behavior; Learning; Networks; Numerical analysis; Psychological adaptation; Route choice; Simulation; Strategic planning; Travel behavior; Travelers; Uncertainty

Bounded rationality framework; Expectations; Quantal response model

Highways; Planning and Forecasting; Society; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Mar 3 2006 10:22AM

• Arriving-on-Time Problem: Discrete Algorithm That Ensures Convergence
• Cell-Based Network Optimization Model for Staged Evacuation Planning Under Emergencies
• Combined Model for Intermodal Networks with Variable Transit Frequencies
• Decomposition Scheme for Continuous Network Design Problem with Asymmetric User Equilibria
• Derivation of Origin–Destination Distributions from Traffic Counts: Implications for Freeway Simulation
• Difference Between Area-Based and Cordon-Based Congestion Pricing: Investigation by Trip-Chain-Based Network Equilibrium Model with Nonadditive Path Costs
• Doubly Uncertain Transport Network: Degradable Link Capacity and Perception Variations in Traffic Conditions
• Dynamic Continuous Network Design Problem: Linear Bilevel Programming and Metaheuristic Approaches
• Dynamic Origin-Destination Trip Demand Estimation for Subarea Analysis
• Heuristic Priority Ranking of Emergency Evacuation Staging to Reduce Clearance Time
• Interactive Heuristic for Practical Vehicle Routing Problem with Solution Shape Constraints
• Modeling Impact of Technological Changes on Urban Commercial Trips by Commercial Activity Routing Type
• New Reserve Capacity Model of Signal-Controlled Road Network
• Noniterative Approach to Dynamic Traffic Origin-Destination Estimation with Parallel Evolutionary Algorithms
• Number and Location of Sensors for Real-Time Network Traffic Estimation and Prediction: Sensitivity Analysis
• Optimal Scheduling of Evacuation Operations
• Proposed Framework for Simultaneous Optimization of Evacuation Traffic Destination and Route Assignment
• Quantifying Opportunity Costs in Sequential Transportation Auctions for Truckload Acquisition
• Real-Time Mass Passenger Transport Network Optimization Problems
• Real-Time Traffic Volatility Forecasting in Urban Arterial Networks
• Reliable Network Design Problem: Case with Uncertain Demand and Total Travel Time Reliability
• Reverse Supply Chain Network Design Problem
• Selectorecombinative Genetic Algorithm to Relax Computational Complexity of Discrete Network Design Problem
• Single-Point Approximations for Traffic Equilibrium Problem Under Uncertain Demand
• Stochastic Heuristic Dynamic Assignment Based on AIMSUN Microscopic Traffic Simulator
• Survival Analysis-Based Dynamic Travel Demand Models for Hurricane Evacuation
• Tabu-Based Heuristic Approach for Optimization of Network Evacuation Contraflow
• Variable Toll Pricing and Heterogeneous Users: Model and Solution Algorithm for Bicriterion Dynamic Traffic Assignment Problem