摘要
城市投入建立公共自行车系统,用以解决公共交通出行"最后1km"的问题,每个租赁点需投放自行车数目的确定过于经验化,造成部分租赁点的自行车数目无法满足需求,而另一些租赁点自行车数量供大于求.针对如何确定租赁点投入公共自行车数量的问题,研究分析了目前常用的几种确定公共自行车投放数量的方法的缺点,依据可靠的自行车借用统计数据,结合公共自行车需求与用地类型,居住人口和建筑面积等变量相关,建立了迭代回归模型.模型可靠性分析表明,迭代回归模型在没有详细历史数据的情况下,能够充分利用短期调查数据,更准确的确定新设置的租赁点投放自行车的数目,为初次建立公共自行车系统的城市提供了投放依据.
Many cities try to solve ＂the last kilometer＂ of public transportation by setting up the public bicycle systems. Due to the fact that the number of bicycle input in the rental stations are too empiri- cal, it makes that part of the rental stations cannot meet the requirements while other rentals are over-supplied. Aiming at how to determine the input numbers for the rental stations exactly, here an itera-tive regression model is proposed. After analyzing several commonly methods used in forecasting the input number of bicycle, as well as the shortages of these methods, an iterative regression model is es- tablished based on the reliable bicycle use statistics, together with the land-use type, the residents population, building areas and other related variables. The model reliability analysis shows that the it- erative regression model can make full use of the short term survey data in the absence of detailed his-torical data. It is much more accurate in determining the input number, and provides a basis of estab-lishing the public bicycle system for the cities first time. The model meets the requirement of residents and save resources at the same time. It has certain practical value and practical significance.
出处
《武汉理工大学学报（交通科学与工程版）》
2014年第2期245-248,共4页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
国家自然科学基金项目资助(批准号:50978106)
关键词
慢行交通
公共自行车
需求预测
回归分析法
non-motorized traffic
public bicycle
demand forecasting
regression analysis method
