Abstract
In consideration of the constraint of the advanced traveler information systems (ATIS) detecting accuracy and the time delay of information feedback systems, a novel approach named graded- information feedback strategy is proposed and applied into a two-route scenario. The approach adopts the fuzzy C-means clustering algorithm to classify road traffic conditions based on flux, mean velocity, and density. Then, each cluster centre is fixed on. Furthermore, real-time traffic conditions on each route could be judged by the preceding cluster centers. Results of judgment would be displayed on variable message signs to guide the successors at the entrance to make reasonable route-choices. Meanwhile, a cellular automaton model is adopted to investigate the correlation between efficiency of two- route systems, number of clustering, and travelers’ route choice behavior. Compared with the conventional strategies, the simulation shows that the innovative information feedback strategy can evidently improve utilization efficiency of road networks.
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