公共自行車租借系統選擇行為之研究

Abstract

為發展永續運輸（Sustainable Transportation），減少機動車輛使用對自然生態環境之破壞，近幾年來許多國家開始推廣「綠色運具」自行車之使用，公共自行車租借服務即屬其中之一。鑑於目前國內市區接駁型公共自行車租借服務仍屬試辦階段尚未普及，為了解民眾對公共自行車租借服務之選擇偏好，本研究應用敍述性偏好法進行二階段問卷設計與調查，據以構建臺北市公共自行車個體選擇行為模式，並應用所構建的多項羅吉特運具選擇模式預測在不同租借收費水準及車外接駁時間等組合情境下之使用機率與政策分析，期能提供未來市區公共自行車租借服務推廣辦理之參考。 本研究所校估檢定之公共自行車效用函數包含以下解釋變數：方案特定常數、車外接駁時間（代表設站密度及車輛調度能力）、公共自行車基本費、公共自行車每次租借逾半小時後加收之費率、天氣、旅次目的及使用者性別等，各參數正負符號均符合先驗知識且具顯著性，其中又以天氣之影響最大。 經由模式應用之分析結果，可推論民眾對於公共自行車使用成本之重視程度高於車外接駁時間，低價之公共自行車租借服務確實有助於提高其使用率並減緩機動車輛使用需求。另推論目前臺北市公共自行車租借站平均站間距離應尚可滿足使用者需求，惟需擴大設站範圍及增加設置地點，以提高租借可及性與使用意願。

In order to develop Sustainable Transportation and to reduce the damage to ecological environment by motor vehicles, many countries have started to promote the usage of green vehicles, and the public rental bicycle service is one of them. In view of Taipei City Government was just to initiate a demonstration project of public rental bicycle service system, of which the acceptance is not well known, it is important to understand the choice behavior of people for the public rental bicycle service. This research designs and conducts a two-stage questionnaire survey, using the stated preference method, to collect data for the development of a disaggregate choice behavior model of Taipei public rental bicycle system, with the form of Multinomial Logit. The model is then used to forecast the probability of choosing public rental bicycle system under different conditions, like different rental cost levels and the out-of-vehicle travel time etc. The proposed model and the results of analysis may be provided as good reference for the promotion of the urban public rental bicycle service in the future. The utility function of the public rental bicycle obtained from this study consists of the following explained variables：alternative specific constants(ASC), out-of-vehicle travel time (represents the density of station setting and the ability of vehicle arrangement), basic rental fee, the extra pay rate over half hours, weather, the trip purpose, gender and so on. The positive and negative signs of the calibrated parameters all fit prior knowledge and are statistically significant. Among all the variables, weather is found to be the most important one with the greatest influence on the choice behavior. Based on the results of model applications, it could be deduced that the influence of public bicycle usage cost is greater than out-of-vehicle travel time. Lower cost is indeed helpful to rise up the bicycle usage rate and slow down the demand for motor vehicles. Besides, the average distance between rental sites of the Taipei city public rental bicycle system is acceptable by the users in general. It’s suggested to broaden the area scope of the rental system and to increase the site number, in order to enhance the accessibility and utilization of the system.