| Summary: | 碩士 === 國立交通大學 === 運輸與物流管理學系 === 104 === Providing accurate travel time to travelers could not only make them do proper trip plannings but the decisions of depart time and route choices, achieving the goal of distributing quantity of vehicles and releasing traffic congestions. This research provide a travel time prediction model which improved from k-NN method and applied it on the segment of freeway which without signalize intersections. This proposed dynamic k-NN travel time prediction model get it’s primal k from k-NN method, and adjust the value k base on the situation of current traffic characteristic. Compare with k-NN method, the prediction model this research proposed can make the value k be more suitable for each time segment. This research using the vehicle detectors on the freeway as data source , and test the model with the peak hours of the freeway. Based on the testing results, the performance of the prediction model this research proposed is better than that of using k-NN method only.
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