中文摘要：

郊区化导致的汽车出行增加及相关的城市环境与社会问题日益成为城市研究关注的焦点，但目前国内对建成环境与汽车出行行为的研究刚刚起步。基于GPS与活动日志相结合的居民一周活动与出行数据，利用GIS空间分析分别以居住地、工作地和活动空间作为地理背景，分析建成环境对于郊区居民汽车出行距离的影响因素。研究发现，建成环境对工作日汽车出行的影响因地理背景的选择而有不同。整日出行受到工作地和活动空间的影响，工作地与活动空间建设密度增高汽车出行减少，但是居住空间的影响不显著；通勤出行受到居住地、工作地和活动空间的影响，居住地商业密度提高和建设密度降低、工作地和活动空间建设密度提高，汽车出行减少；非工作活动出行也受到居住地、工作地和活动空间的影响，居住地、工作地和活动空间的公交密度低、工作地和活动空间建设密度高，汽车出行少。基于研究结果，本文对地理背景不确定性问题进行了探讨，提出出行行为的研究需要考虑居住地以外其他地理背景的影响。并对控制汽车使用的公共政策提出了建议。

英文摘要：

Car use has changed daily activity travel patterns, which cause serious urban problems including air pollution, traffic congestion, road accidents, and community severance. Particularly in China＇s rapid suburbanization, car use and related social and environmental issues are attracting great attention. Previous research has illustrated the importance Of the built environment and car ownership on daily car travel distance. However, it is still not clear how car ownership and car use impact individual behavior, and the ways researchers measure the contextual influence of the built environment are not consistent. Most of the existing literature only uses residential area as the geographic context to study the impact of built environment, and only a few studies focus on workplaces or other destinations. In recent years, the uncertain geographic context problem has come under intense scrutiny by geographers seeking to elucidate the interaction between urban space and individual behavior. According to this phenomenon of the uncertain geographic context, travel behavior is influenced not only by the origin and destinations of trips, but also by the travel routes and the surrounding activity spaces. However, so far few studies have been conducted on the impact of activity space. Based on a GPS-facilitated activity-travel survey dataset collected in the Shangdi-Qinghe area in Beijing in 2012, the present paper studies the relationship between the built environment and car travel behavior of suburban residents on weekdays. To understand the importance of geographic context, three types of geographic context are used： residential area, work location and activity space. The impact of the built environment on car travel distance in daily travel, commuting travel and non-work travel is analyzed using three sets in a linear regression model. The study finds that the impact of the built environment on car travel behavior depends on travel mode and geographic context, and the built environment .in work locations and activity