A Stochastic Traffic Assignment Model for Transportation Network

Traffic information in the future is likely to be available to all parts of a transportation network, and there will be various futuristic optimization models for traffic engineering. Assuming that the system can access statistical information of the aggregated traffic demands between source-destination pairs or zones in the transportation network, traffic congestion can be reduced by using the total travel time of the system as a measure in a traffic assignment model. This paper focuses on a traffic or route assignment problem that incorporates stochastic traffic demand, which can be solved with a Genetic Algorithm.