基于城市综合体分类的停车收费政策预评估

为有效评估停车收费政策在不同类型城市综合体中产生的效果差异,基于辐射范围、居民出行距离及公共交通服务水平三项特征指标,利用K-Means聚类算法将城市综合体分成市域型和区域型两类。与区域型综合体相比,市域型综合体辐射范围更广、所吸引的人群活动出行距离更长、公共交通服务水平更具竞争力。构建城市综合体居民行为选择模型,利用RP/SP融合数据标定模型参数,以消除意愿调查产生的偏差。该模型综合考虑停车收费政策和公共交通服务水平的关联性,能有效分析停车收费价格上涨幅度和公共交通服务水平改善对市域型和区域型城市综合体居民方式选择行为影响的贡献程度,为区域差别化停车收费政策制定提供参考依据。

Pre-Evaluation of Parking Charge Policy Based on the Classification of Urban Complex

In order to evaluate the effect of parking charge policy in different types of urban complex, this paper categorizes the surveyed urban complexes into two types: metropolitan and regional, based on im-pact range, travel distance, and level of service of public transit using K-Means clustering algorithm. Com-pared with regional complex, metropolitan complexes have larger impact range, longer travel distance and higher level of service of public transit. This paper develops a traveler behavior choice model for urban complex, using SP/RP survey data for model calibration so as to eliminate the deviations caused by survey bias. Considering the relationship between parking charge policy and level of service of public transit, the model can effectively describe the contributions of increasing parking fee and improving level of service of public transit to travel choice behavior. The findings are expected to be reference of differentiating park-ing charge policy by areas.