由於車輛在近20年當中成長的速度相當驚人，相對於道路的擴展速度卻是趨於緩慢，因此塞車已經是世界各大都會區所需要面對的問題。駕駛遇到塞車時會浪費許多時間和燃料，也會造成環境上的污染。根據日本政府單位的研究報告日本每年因為塞車所造成經濟上的損失高達1千億美金。若是駕駛可以提早知道哪些路段現階段是屬於塞車的情況，則可以避開此路段，藉此減緩塞車問題。 由於都會區紅綠燈交通管制為一種人為障礙，在相同的路況之中，會因為紅綠燈影響到其旅行時間，因此無法只靠旅行時間去判斷此路段的交通狀況。此篇論文透過實際在台北市開車記錄GPS所收集位置與時間的資訊，將其轉換成時間與空間的平均速度兩個值，評估是否能夠利用前面車輛傳達的經驗資訊有供後來者參考，協助有效地選擇花費時間最短的路線。此外將時間與空間的平均速度結合上一個行經此路線的旅行時間，更能準確地預估所需要的旅行時間。 As the vehicles in the past 20 years the pace of growth was quite startling, as opposed to the expansion of the road tends to slow the speed of it is, so traffic is already the world's urban areas need to face. Traffic congestion will be consumed drivers a lot of time and fuel, may also result in environmental pollution. According to the Japanese government study in Japan because of traffic congestion caused by the economic loss of up to 1 billion U.S. dollars every year. If drivers know which roads is serious traffic congestion, they can make a detour, so that the problem of traffic congestion can mitigate. In urban area, traffic light is a contrived obstacle, in the same traffic state, traffic lights will affect the travel time and therefore can not rely on the travel time to determine the traffic conditions. This paper to drive through the actual record in Taipei collected GPS location and time information to be converted to temporal mean speed and spatial mean speed. Assess whether the use of the vehicle in front of information to convey the experience to choose the shortest route. In addition to the temporal mean speed and spatial mean speed combined with the travel time of the vehicle in front, a more accurate estimate of travel time required.
