| Summary: | 碩士 === 國立交通大學 === 運輸科技與管理學系 === 97 === The travel time prediction is a part of Advanced Traffic Information Systems, ATIS. It is using the instant speed and flow information to predict the travel time on certain the path. It helps the road user and traffic manager to survey or strategy analysis. Using the travel time information, it is useful for road user to do the trip planning by minimizing the travel time. Without travel time information, it is hard to gather enough information doing the efficient trip planning, nor estimating the travel time. Therefore, travel time prediction is the important issue in intelligent transportation system. It help trip planning and decrease the uncertainty of the trip.
The study uses the historical electronic toll collection, ETC, information and historical and real-time vehicle detector, VD, information, speed and flow, on the freeway. Using the comparison method find out the familiar traffic information between historical data and real-time data. Then, estimate the travel time of the historical time by ETC data. With the familiar period and estimated travel time predict the real-time travel time.
The study adopts the k-nearest neighbor method, k-NN method, in data comparison. For decreasing the rate of error, instead of comparing each time period compares the traffic information trend to find out the similar data. Besides, we consider the difference between different VDs, and weight the VD data to adjust. Finally, discussing different data classification increases the performance of prediction.
Finally, the study took the third freeway in Taiwan for example. Figure out if the method got enough predicting ability.
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