The Study of Travel Time Prediction for Freeway by Using Dynamic k-NN Method
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...
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ndltd-TW-104NCTU54230222017-09-06T04:22:12Z http://ndltd.ncl.edu.tw/handle/18336628090492600377 The Study of Travel Time Prediction for Freeway by Using Dynamic k-NN Method 變動k值之k-NN法應用於高速公路旅行時間預測之研究 Liu, Hsuan-Ning 劉軒寧 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. Wang, Jin-Yuan 王晉元 2016 學位論文 ; thesis 32 zh-TW |
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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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author2 |
Wang, Jin-Yuan |
author_facet |
Wang, Jin-Yuan Liu, Hsuan-Ning 劉軒寧 |
author |
Liu, Hsuan-Ning 劉軒寧 |
spellingShingle |
Liu, Hsuan-Ning 劉軒寧 The Study of Travel Time Prediction for Freeway by Using Dynamic k-NN Method |
author_sort |
Liu, Hsuan-Ning |
title |
The Study of Travel Time Prediction for Freeway by Using Dynamic k-NN Method |
title_short |
The Study of Travel Time Prediction for Freeway by Using Dynamic k-NN Method |
title_full |
The Study of Travel Time Prediction for Freeway by Using Dynamic k-NN Method |
title_fullStr |
The Study of Travel Time Prediction for Freeway by Using Dynamic k-NN Method |
title_full_unstemmed |
The Study of Travel Time Prediction for Freeway by Using Dynamic k-NN Method |
title_sort |
study of travel time prediction for freeway by using dynamic k-nn method |
publishDate |
2016 |
url |
http://ndltd.ncl.edu.tw/handle/18336628090492600377 |
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