Traffic state identification methods based on cloud computing model
Weining Liu, Qinglu Ma, Dihua Sun, Yu-Fang Dan · 2010
In order to identify the traffic state of urban road network accurately, the traffic state identification methods based on cloud computing model are proposed. The macroscopic and microscopic characteristics of urban road network traffic flow are discussed in detail; and then the identification index systems are proposed. The traffic state identification models are proposed based on cloud computing theory. Numerical results of an arterial road network testified to the effectiveness of the proposed methods. The methods proposed can be applied to traffic state analysis on-line and to extract the traffic information in historical database to provide decision support for traffic management.