由於現代都市化與人口密度提高的趨勢，都會區交通壅塞成為世界各大都市的問題。而隨著無線網路通訊與全球衛星定位系統的快速發展，車用智慧型導航系統逐漸普及。都會區因停車造成的堵塞、耗時、與空氣污染問題，可由車用智慧型導航系統提供停車建議服務來達成紓解交通、節省用車人時間、以及都市環境保護等目標。本研究提出一個應用於智慧型導航系統之有效率停車建議服務，提供即時的停車場建議與導航。此服務對需要停車的使用者提供一個建議停車場序列，根據使用者的目前地理位置與目標地理位置，在一定範圍內依序排列推薦度最高至最低的停車場，供使用者自行選擇並前往停車。我們蒐集台北市、高雄市、與桃園縣共260個公有停車場的實際資料，觀察停車場的停車行為，進行統計分析，發展出停車建議演算法，並使用實際資料進行驗證測試與比較。 In this paper, an effective parking recommendation service for vehicular intelligent guiding system is provided with real-time parking lot guiding service for future green city. The system shows drivers a best parking lot recommendation sequence and saves drivers’ time circling around by the accurate prediction of parking probability in each parking lot. The cost model containing parking probability as a factor for the best recommendation sequence is constructed according to the main conditions for parking. Through the collection and analysis of real data from parking lots in Taipei city, an integrated algorithm is developed to estimate the parking probability by the condition of current available spaces and parking popularity. Comparative experiments are performed to verify the improvement of prediction algorithm.
