01336716

Component

In this study, a non-linear optimization-based conceptual framework is proposed along with related modeling components pertaining to stochastic capacity, travel time performance functions and different degrees of traveler knowledge in an advanced traveler information provision environment. This proposed method categorizes commuters into two classes: (1) travelers with access to perfect traffic information every day, and (2) travelers with some degree of knowledge of average traffic conditions across different days. Within a gap function framework (for describing the user equilibrium under different information availability), a mathematical programming model is formulated to describe the route choice behavior of the perfect information (PI) and expected travel time (ETT) user classes under stochastic day-dependent travel time. Based on an operational algorithm for large-scale networks, the model was applied to a simple corridor to illustrate the effectiveness of traveler information under stochastic capacity.

01329018

11-3002

English

19p

2011

Transportation Research Board 90th Annual Meeting

DVD

Figures (7) ; References (16) ; Tables (1)

Advanced traveler information systems; Commuters; Highway capacity; Highway operations; Optimization; Programming (Mathematics); Real time information; Route choice; Stochastic processes; Travel time

Traffic conditions; User equilibrium

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

Transportation Research Board Annual Meeting 2011 Paper #11-3002

TRIS, TRB

Feb 17 2011 6:22PM