Abstract
This paper formulates a scenario-based stochastic programming model to optimize the timing of pretimed signals along arterials under day-to-day demand variations or future uncertain traffic growth. Demand scenarios and their corresponding probabilities of occurrence are introduced to represent the demand uncertainty. On the basis of a cell-transmission representation of traffic dynamics, cycle length, green splits, phase sequences, and offsets are determined to minimize the expected delay incurred by high-consequence demand scenarios. A simulation-based genetic algorithm is proposed to solve the model, and a numerical example is presented to verify and validate the model.
Original language | English (US) |
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Pages (from-to) | 156-166 |
Number of pages | 11 |
Journal | Transportation Research Record |
Issue number | 2192 |
DOIs | |
State | Published - Dec 1 2010 |
Externally published | Yes |
ASJC Scopus subject areas
- Civil and Structural Engineering
- Mechanical Engineering