A traffic flow wave model applicable to urban road incident congestion is proposed in this paper, based on Traffic-Flow Wave Theory. The model is based on the discrete characteristics of urban congestion traffic flow and is derived from a Velocity-Density linear model. The queuing and dissipation of incident congestion is analyzed based on the new model, both on the existence of traffic controlling measures and on situations without traffic controlling measures. In which, the influence from traffic controlling measures is described as interference wave. The results showed that the correct traffic controlling measures could avoid "Domino" phenomenon, prevent the congestion drifting, and reduce the queuing and delay-time.
This study, based on principle of bus priority, uses complementary doctrines to create mixed traffic flow intersection signal-planning model under effective green time. By discussing the objective function of optimization model, we ensure and take advantage of nonlinear equivalence feature. After that, this study refers to Newton algorithm to solve this model. Considering the mixed characteristic of traffic flow, we put forward to adoption of traffic capacity, delay time and parking number together to evaluate operation effect. Through the example analysis, it was shown that this model and solution algorithm responded well and indications increased remarkably.
This study, based on principle of bus priority, uses complementary doctrines to create mixed traffic flow intersection signal-planning model under effective green time. By discussing the objective function of optimization model, we ensure and take advantage of nonlinear equivalence feature. After that, this study refers to Newton algorithm to solve this model. Considering the mixed characteristic of traffic flow, we put forward to adoption of traffic capacity, delay time and parking number together to evaluate operation effect. Through the example analysis, it was shown that this model and solution algorithm responded well and indications increased remarkably.
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