It is widely accepted that travel times in urban road networks can vary greatly within a short period as well as from period to period in a single day. One important cause for this variability in urban travel times is the delay that drivers experience at intersections, particularly signalized intersections. This delay can be due to the time a driver needs to wait for a red light or the time needed for a queue of waiting vehicles at an intersection to dissolve, or both. As a result, the ability to capture the characteristics of delay at signalized intersections is a critical, yet challenging, step in estimating and predicting urban link travel times. The uncertainties in these experienced delays are caused by traffic conditions and traffic control at the intersections. In this paper a delay distribution model is developed for an urban trip over a route with two consecutive fixed-time controlled intersections. The proposed model captures the stochasticity in the arrival and departure process at the first intersection. An example illustrates how these stochastic factors influence the realized delay distribution for the two consecutive signalized intersections. Delay distributions are analyzed for different levels of mismatch of the two controlled intersections (from well coordinated to badly coordinated) under different degrees of saturation. Finally, the predicted delay distributions are validated with the VISSIM simulation model and show that the proposed (analytical) model can represent the VISSIM simulation data.
Modeling Variability of Urban Travel Times by Analyzing Delay Distribution for Multiple Signalized Intersections
Transportation Research Record: Journal of the Transportation Research Board
Transportation Research Record: Journal of the Transportation Research Board ; 2259 , 1 ; 80-95
2011-01-01
Article (Journal)
Electronic Resource
English
Delay Variability at Signalized Intersections
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|Delay Variability at Signalized Intersections
Online Contents | 2000
|Delay Pattern Estimation for Signalized Intersections Using Sampled Travel Times
Transportation Research Record | 2009
|