城市中心区停车场短时车辆到达与离去特性研究  

Research on the Vehicle Short Interval Arrivaing and Departing Character in Urban Center Area

作　　者：黎冬平[1] 董瑞娟[2] 陈峻[1] 

机构地区：[1]东南大学交通学院,江苏南京210096 [2]合肥工业大学机械与汽车工程学院,安徽合肥230009

出　　处：《现代交通技术》2007年第2期70-73,共4页Modern Transportation Technology

摘　　要：缓解城市中心区的停车供需矛盾首先要把握中心区停车的供应与需求之间的特征关系。通过对南京市新街口商业区停车场短时车辆到达率与离去率的调查和分析,用BP神经网络算法对其进行短时预测,得出小区所有停车场车辆总到达率特性比单个停车场更为稳定和显著,而车辆离去率特性在两者之间的差异则不明显。本研究为中心区停车场的管理和停车诱导提供了理论依据。It is necessary to hold the relationship between the parking supply and the demand to resolve the parking problem in urban center area.Through investigating and analyzing the vehicle arrivals and leaving of the parking lots in Nanjing Xinjiekou shopping center,the paper adopts the BP neural network to forecast the short interval arriving and departing flow.Then it summarizes that the arriving rate character of all parking lots in the zone is more stable and obvious than that of single parking lot, and both of the departing rate characters are similar.The result affords the basis to the parking management and guidance in the center area.

关 键 词：车辆到达率 车辆离去率 停车 BP神经网络 停车诱导 

分 类 号：U491[交通运输工程—交通运输规划与管理]