Article ID: | iaor19991339 |
Country: | United Kingdom |
Volume: | 32B |
Issue: | 7 |
Start Page Number: | 499 |
End Page Number: | 516 |
Publication Date: | Sep 1998 |
Journal: | Transportation Research. Part B: Methodological |
Authors: | Rilett L.R., Fu Liping |
Keywords: | networks: path |
The dynamic and stochastic shortest path problem (DSSPP) is defined as finding the expected shortest path in a traffic network where the link travel times are modeled as a continuous-time stochastic process. The objective of this paper is to examine the properties of the problem and to identify a technique that can be used to solve the DSSPP given information that will be available in networks with Intelligent Transportation System (ITS) capabilities. The paper first identifies a set of relationships between the mean and variance of the travel time of a given path and the mean and variance of the dynamic and stochastic link travel times on these networks. Based on these relationships it is shown that the DSSPP is computationally intractable and traditonal shortest path algorithms cannot guarantee an optimal soluton. A heuristic algorithm based on the