A Graded-Information Feedback Strategy in Two-Route Systems under ATIS

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. Real-time traffic conditions on each route could be evaluated by the preceding cluster centers. Results of the evaluation 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 the 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.