HighlightsA generalized statistical traffic assignment (GESTA) model is developed to estimate the probability distributions of link and path flows.Route choice models are consistent with the settings of random O-D demands and random path/link flow and costs.GESTA has a clear multi-level structure based on three types of variations: demand variation, route choice variation and measurement errors.The theory of variance analysis for path/link flow is established.The atomic and non-atomic games in statistical traffic equilibrium are differentiatedGESTA is tested on a large-scale real network to gain insights; numerical experiments are also used to discuss the non-uniqueness of path flow distributions in GESTA.
AbstractThis paper generalizes and extends classical traffic assignment models to characterize the statistical features of Origin-Destination (O-D) demands, link/path flow and link/path costs, all of which vary from day to day. The generalized statistical traffic assignment (GESTA) model has a clear multi-level variance structure. Flow variance is analytically decomposed into three sources, O-D demands, route choices and measurement errors. Consequently, optimal decisions on roadway design, maintenance, operations and planning can be made using estimated probability distributions of link/path flow and system performance. The statistical equilibrium in GESTA is mathematically defined. Its multi-level statistical structure well fits large-scale data mining techniques. The embedded route choice model is consistent with the settings of O-D demands considering link costs that vary from day to day. We propose a Method of Successive Averages (MSA) based solution algorithm to solve for GESTA. Its convergence and computational complexity are analyzed. Three example networks including a large-scale network are solved to provide insights for decision making and to demonstrate computational efficiency.
On the variance of recurrent traffic flow for statistical traffic assignment
2017-05-14
26 pages
Article (Journal)
Electronic Resource
English
Estimation of Link Flow Variance by Stochastic Traffic Assignment
British Library Conference Proceedings | 1997
|Engineering Index Backfile | 1952
Some statistical problems in connection with traffic assignment
Elsevier | 1976
|Traffic : an equilibrium traffic assignment program
TIBKAT | 1978
|NTIS | 1968
|