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Optimization of a Traffic Control Scheme for a Post-Disaster Urban Road Network
Traffic control of urban road networks during emergency rescues is conducive to rapid rescue in the affected areas. However, excessive control will lead to negative impacts on the normal traffic order. We propose a novel model to optimize the traffic control scheme during the post-disaster emergency rescue period named PD-TCM (post-disaster traffic control model). In this model, the vertex and edge betweenness indexes of urban road networks are introduced to evaluate the controllability of the road sections. The gravity field model is also used to adjust the travel time function of different road sections in the control and diverging domains. Experimental results demonstrate that the proposed model can obtain the optimal traffic control scheme efficiently, which gives it the ability to meet the demand of emergency rescues as well as reducing the disturbances caused by controls.
Optimization of a Traffic Control Scheme for a Post-Disaster Urban Road Network
Traffic control of urban road networks during emergency rescues is conducive to rapid rescue in the affected areas. However, excessive control will lead to negative impacts on the normal traffic order. We propose a novel model to optimize the traffic control scheme during the post-disaster emergency rescue period named PD-TCM (post-disaster traffic control model). In this model, the vertex and edge betweenness indexes of urban road networks are introduced to evaluate the controllability of the road sections. The gravity field model is also used to adjust the travel time function of different road sections in the control and diverging domains. Experimental results demonstrate that the proposed model can obtain the optimal traffic control scheme efficiently, which gives it the ability to meet the demand of emergency rescues as well as reducing the disturbances caused by controls.
Optimization of a Traffic Control Scheme for a Post-Disaster Urban Road Network
Zengzhen Shao (Autor:in) / Zujun Ma (Autor:in) / Shulei Liu (Autor:in) / Tongshuang Lv (Autor:in)
2017
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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