01089729

Component

https://doi.org/10.3141/2085-13

http://scholar.google.com...+Ran&publication_year=2008

A study of the problem of predicting traffic flows under traffic equilibrium in a stochastic transportation network is presented. Travelers’ risk-taking behaviors are explicitly modeled with respect to probabilistic travel times. Traveling risks are quantified from the travel time distributions directly and are embedded in the route choice conditions. The classification of risk-neutral, risk-averse, and risk-prone travelers is based on their preferred traveling risks. The formulation of the model clarifies that travelers with different risk preferences have the same objective—to save travel time cost—though they may make different route choices. The proposed solution algorithm is applicable for networks with normal distribution link travel times theoretically. Further simulation analysis shows that it can also be applied to approximate the equilibrium network flows for other frequently used travel time distribution families: gamma, Weibull, and log-normal. The proposed model was applied to a test network and a medium-sized transportation network. The results demonstrate that the model captures travelers’ risk-taking behaviors more realistically and flexibly compared with existing stochastic traffic equilibrium models.

01120896

English

pp 111-123

2008

Transportation Research Record: Journal of the Transportation Research Board

9780309125963

Print

Figures (8) ; References (14) ; Tables (3)

Algorithms; Equilibrium (Systems); Gamma distributions; Mathematical models; Normal distributions; Risk taking; Route choice; Stochastic processes; Traffic assignment; Traffic equilibrium; Traffic flow; Travel time; Weibull distributions

Log-normal distributions; Transportation networks

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

TRIS, TRB, ATRI

Jan 29 2008 3:21PM

• Adaptive Route Choice Models in Stochastic Time-Dependent Networks
• Dynamic Network Loading Model with Explicit Traffic Wave Tracking
• Dynamic Origin–Destination Demand Estimation Using Turning Movement Counts
• Effectiveness of Origin–Destination Matrix Correction Procedure Using Traffic Counts
• Enhanced Lagged Cell-Transmission Model for Dynamic Traffic Assignment
• Generalized Wardrop Principle and Its Application in Regional Transportation
• Incorporating Within-Day Transitions in Simultaneous Offline Estimation of Dynamic Origin–Destination Flows Without Assignment Matrices
• Lower-Bound Solution Algorithm for Equilibrium Signal-Setting Problem
• Measurement of Uncertainty Costs with Dynamic Traffic Simulations
• Modeling User Responses to Pricing: Simultaneous Route and Departure Time Network Equilibrium with Heterogeneous Users
• Probit-Based Time-Dependent Stochastic User Equilibrium Traffic Assignment Model
• Robust Pricing of Transportation Networks Under Uncertain Demand
• Simultaneous Perturbation Stochastic Approximation Algorithm for Solving Stochastic Problems of Transportation Network Analysis: Performance Evaluation
• Stochastic User Equilibrium Model with Implicit Travel Time Budget Constraint