Abstract:

Optimizing commuting behavior by optimizing the built environment of communities is an important measure to alleviate traffic pressure in big cities. Implementing regionally differentiated policies for community built environment may be more conducive to optimizing commuting behavior. By using mobile phone signaling data to construct the OD database of the job-housing contact among residents' committees and to calculate the average commuting distance of committees' residents, this paper analyzes the impact of community built environment ("5D" indicator) on residents' commuting distance based on the geographically weighted regression model (GWR). It shows that multiple indicators of the built environment of community including density, diversity, accessibility, distance and other dimensions have a significant impact on residents' average commuting distance. High population density areas can reduce the average commuting distance of residents, but the regional differences are obvious. Residents in suburban villages with higher population density bear long-distance commuting. Mixed land use can reduce the average commuting distance of residents, especially an important means to reduce commuting demand in suburbs. The accessibility of the subway has increased the average commuting distance in the area to a certain extent. Regionally differentiated policies for the community built environment, such as improving the difference in housing costs between the central city and the suburbs, increasing the local function of the central city relative to a single area and the land use mix of the suburbs, and increasing the construction of rail transit in the central city, are beneficial to optimize residents. Commuting behavior and reducing regional commuting.

Key words: mobile signaling data, built environment, commuting behavior, spatial heterogeneity, Guangzhou

摘要：

通过优化社区建成环境来优化通勤行为是缓解大城市交通压力的重要举措，实施差异化的社区建成环境政策可能更有助于优化通勤行为。在利用手机信令数据构建居委会之间的职住联系OD数据库并计算居委会的居民平均通勤距离的基础上，构建社区建成环境“5D”指标体系，利用地理加权回归模型（GWR）来分析社区建成环境对居民通勤距离的影响。研究表明，包括密度、多样性、通达性、距离等维度的多项指标对居民平均通勤距离有显著影响。人口密度提高能减少居民平均通勤距离，但区域差异明显，人口密度较高的城郊村居民承受着长距离通勤。混合的土地利用能减少居民平均通勤距离，尤其是减少郊区居民平均通勤距离。地铁通达性在一定程度上增加了区域居民平均通勤距离。通过调控改善中心城区与郊区的居住成本差异，增加中心城区局部功能相对单一区域和郊区的土地利用混合度，增加中心城区局部区域轨道交通建设力度，皆有利于优化居民通勤行为和减少区域通勤距离。

关键词: 手机信令数据, 建成环境, 通勤行为, 空间异质性, 广州市