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access icon free Dynamic traffic diversion model based on dynamic traffic demand estimation and prediction

© The Institution of Engineering and Technology
Received 26/01/2018, Accepted 09/07/2018, Revised 10/06/2018, Published 26/07/2018

Traffic diversion is an effective measure to solve the incidental traffic congestion in urban expressway traffic system. By adopting the macroscopic traffic flow model METANET, this study analyses the state change of traffic flow on the road network and establishes the dynamic traffic diversion model, inducing the redistribution of traffic demand. Considering the changes in the amount of origin–destination (O–D) demand, diversion rate is introduced into the basic theory of dynamic O–D model, and then established a dynamic traffic flow model based on dynamic demand change. The genetic algorithm is used to solve the non-linearity problem of the objective function in the traffic diversion model. This study sets up five cases for numerical analyses, and gets the optimal diversion scheme.

Inspec keywords: numerical analysis; road traffic; genetic algorithms

Other keywords: optimal diversion scheme; dynamic demand change; dynamic traffic flow model; macroscopic traffic flow model; origin-destination demand; dynamic traffic demand prediction; O-D demand; METANET; traffic demand redistribution; dynamic O-D model; dynamic traffic demand estimation; nonlinearity problem; state change analysis; numerical analysis; dynamic traffic diversion model; incidental traffic congestion; road network; genetic algorithm; diversion rate; urban expressway traffic system

Subjects: Systems theory applications in transportation; Optimisation techniques; Other numerical methods

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