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Real-time demand-based traffic diversion

Real-time demand-based traffic diversion

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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.

Chapter Contents:

  • 6.1 Model of path choice behavior of driver under guidance information
  • 6.1.1 Discrete probability selection model
  • 6.1.2 Prospect theory model
  • 6.1.3 Fuzzy logic model
  • 6.1.4 Other models
  • 6.2 Optimization of traffic diversion strategy
  • 6.2.1 Responsive strategy
  • 6.2.2 Iterative strategy
  • 6.3 Research on dynamic O–D estimation
  • 6.3.1 Intersection model
  • 6.3.2 Expressway model
  • 6.3.3 Network model
  • 6.4 Dynamic traffic diversion model based on dynamic traffic demand estimation and prediction
  • 6.4.1 DODE model of urban expressway
  • 6.4.1.1 The module of METANET model
  • 6.4.1.2 The module of DODE model
  • 6.4.2 Traffic diversion model of urban expressway
  • 6.4.2.1 Simulation of driver's diversion behavior
  • 6.4.2.2 Influence of diversion on the traffic flow of exit ramp
  • 6.4.2.3 Evaluation index of road network performance
  • 6.4.3 Dynamic traffic diversion model based on DODE
  • 6.4.4 Model solution
  • 6.4.5 Case study
  • 6.4.5.1 Experimental design
  • 6.4.5.2 Experimental analysis and results of traffic diversion
  • 6.4.5.3 Experimental analysis and results of DODE
  • 6.5 Conclusion
  • References

Inspec keywords: traffic engineering computing; genetic algorithms

Other keywords: incidental traffic congestion; urban expressway traffic system; origin-destination demand; road network; genetic algorithm; dynamic traffic flow model; demand-based traffic diversion; METANET; macroscopic traffic flow model

Subjects: Optimisation techniques; Traffic engineering computing

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