Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1132312 | Transportation Research Part B: Methodological | 2011 | 20 Pages |
Path travel time reliability is an essential measure of the quality of service for transportation systems and an important attribute in travelers’ route and departure time scheduling. This paper investigates a fundamental problem of finding the most reliable path under different spatial correlation assumptions, where the path travel time variability is represented by its standard deviation. To handle the non-linear and non-additive cost functions introduced by the quadratic forms of the standard deviation term, a Lagrangian substitution approach is adopted to estimate the lower bound of the most reliable path solution through solving a sequence of standard shortest path problems. A subgradient algorithm is used to iteratively improve the solution quality by reducing the optimality gap. To characterize the link travel time correlation structure associated with the end-to-end trip time reliability measure, this research develops a sampling-based method to dynamically construct a proxy objective function in terms of travel time observations from multiple days. The proposed algorithms are evaluated under a large-scale Bay Area, California network with real-world measurements.
► Develop algorithms for finding the most reliable path with travel time correlations. ► Develop a sampling-based method to characterize spatial correlation structure. ► Adapt a Lagrangian substitution approach to handle non-additive objective functions. ► Quantify solution quality using a large-scale network with real-world measurements.