| Summary: | 碩士 === 國立交通大學 === 運輸科技與管理學系 === 90 === Real-time travel information is becoming increasingly important in many intelligent transportation system (ITS) applications. There are many approaches used to collect real-time travel information. One of them relies on instrumented vehicles traveling in the traffic stream, also known as probe vehicles. Consider the situations of Taiwan, using probe vehicles to collect real-time travel information is an effective and efficient approach.
This thesis proposes a data processing model to process the real-time travel data collected by the buses instrumented with GPS, and estimate the average speed in a link. However the buses have their main missions to do, such as carrying passengers, we must filter out the unneeded data to provide accurate travel information. The data processing model includes two parts. One is the data filtering model to filter out the un-normal low speeds resulted from stops for collecting passengers or red light. The other is the data-cutting model. This model using the change point analysis of statistic theory to find a cutting point where the data has significant difference.
In order to evaluate the model, a case study concerning the Guang-Fu Rd. a major road in Hsin-Chu is performed. The result shows that the data filtering model and the data-cutting model can work well.
|
|---|
