一個即時的行車速度預測方法

Abstract

近年來隨著經濟的快速發展及科技的進步，許多傳統的運輸系統透過先進科技的協助，獲得了有效的改善。這正是世界許多國家發展智慧型運輸系統(Intelligent Transportation System, ITS)所帶來的效益。即時交通資訊服務系統的推廣乃屬ITS重要的一環。目前在台灣實際上在運作的即時交通資訊收集有兩種方式：(1) 固定式車輛偵測器、(2) 配備全球定位系統(Global Positioning System, GPS)探針車回報交通資訊。然而，固定式車輛偵測器置的架設及維護需要龐大的費用。而目前現在之GPS探針車僅能回報即時車速資訊，而無法提供完整的交通資訊(例如：交通流量)。並且雖然透過此方法可以收集到即時車速資訊，並可以依此資訊分析出當下最快到達目的地的路徑，但交通路況卻是不斷變化的，當下雖然顯示路況順暢，但當車子行駛到該路段時卻可能已變成壅塞的狀況。因此，在本研究中提出行車速度預測方法(Vehicle Speed Prediction Method, VSPM)，針對GPS探針車回報之即時車速，運用線性迴歸模式(Linear Regression Model, LRM) 計算出即時交通流量並且預測目標路段在下一個時間點之行車速度。 實驗結果顯示，採用線性迴歸模式預測未來的行車速度，其平均車速預測準確度可達98.24%。而利用線性迴歸模式的平均車速誤差比率和交通流量誤差比率分別為4.46%和33.75%，優於其他既有模式。因此，本研究之方法可預測未來的行車速度和提供即時交通流量，予以用路人參考。

For the past few years, with the advance of technology and economic growth, the qualities of traditoional transport systems have improved significantly. Intelligent Transportation System (ITS) has become more and more popular. So far, there are two ways to collect real-time traffic information: (1) stationary Vehicle Detectors (VD) and (2) Global Position System (GPS)-equipped probe cars reporting. However, VD devices need large amounts of money to build and maintain. Therefore, we propose the linear regression model to infer the equation between vehicle speed and traffic flow. The traffic flow can be estimated from the speed which is obtained from GPS-equipped probe cars. For vehicle speed prediction, we propose the regression based methods to predict the future vehicle speed by using the real-time vehicle speed. In experiments, the future traffic information estimation results show that the accuracies of vehicle speed prediction is 98.24%. The Speed Error Ratio and Flow Error Ratio of linear regression model are 4.46% and 33.75% respectively. The estimated speed and traffic flow by using linear regression model is better than by using any other models. Therefore, the linear regression model can be used to estimate traffic flow for ITS. This approach is feasible to estimate the future vehicle speed and the real-time traffic flow for ITS improvement.