| Summary: | 碩士 === 國立交通大學 === 運輸與物流管理學系 === 101 === Providing real-time traffic information is a very important and fundamental service in ATIS. Based on this information, travelers can change their departure time or route to decrease travel cost and/or improve travel efficiency. Probe Vehicle is one of the major means to obtain traffic situation. But there are some data filtering issues need to be addressed for the non-dedicated probe vehicles, such as bus and taxi. The data generated while service is ongoing, such as passengers are getting on and off, need to be filtered out since these data do not reflect the real situation. Moreover, when the traffic is severely jammed and having the stop-and-go traffic pattern, special cares are required to rule out the unnecessary data. We proposed a Fuzzy C-Means based method to address the above mentioned issues. Our testing results show that when the average travel speed is higher than 30 km/hr, we suggest dividing the data into two or three groups and take the average of high-speed group. When the average speed is lower than 30km/hr, categorizing data into three groups and takes the middle-speed group is recommended.
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