School of Transportation Science and Engineering, Beijing Key Laboratory for Cooperative Vehicle Infrastructure System and Safety Control, Beihang University, Beijing, China.
School of Architecture and Urban Planning, Harbin Institute of Technology Shenzhen Campus, Shenzhen, China.
Accid Anal Prev. 2018 Mar;112:116-126. doi: 10.1016/j.aap.2017.12.026.
Although a growing body of literature focuses on the relationship between the built environment and pedestrian crashes, limited evidence is provided about the relative importance of many built environment attributes by accounting for their mutual interaction effects and their non-linear effects on automobile-involved pedestrian crashes. This study adopts the approach of Multiple Additive Poisson Regression Trees (MAPRT) to fill such gaps using pedestrian collision data collected from Seattle, Washington. Traffic analysis zones are chosen as the analytical unit. The effects of various factors on pedestrian crash frequency investigated include characteristics the of road network, street elements, land use patterns, and traffic demand. Density and the degree of mixed land use have major effects on pedestrian crash frequency, accounting for approximately 66% of the effects in total. More importantly, some factors show clear non-linear relationships with pedestrian crash frequency, challenging the linearity assumption commonly used in existing studies which employ statistical models. With various accurately identified non-linear relationships between the built environment and pedestrian crashes, this study suggests local agencies to adopt geo-spatial differentiated policies to establish a safe walking environment. These findings, especially the effective ranges of the built environment, provide evidence to support for transport and land use planning, policy recommendations, and road safety programs.
尽管越来越多的文献关注建成环境与行人碰撞事故之间的关系，但考虑到许多建成环境属性的相互作用效应及其对涉及汽车的行人碰撞事故的非线性效应，关于这些属性的相对重要性的证据有限。本研究采用多加法泊松回归树（MAPRT）的方法，利用从华盛顿西雅图收集的行人碰撞数据来填补这一空白。选择交通分析区作为分析单元。研究调查了各种因素对行人碰撞频率的影响，包括路网特征、街道元素、土地利用模式和交通需求。密度和混合土地利用程度对行人碰撞频率有重大影响，约占总影响的 66%。更重要的是，一些因素与行人碰撞频率呈明显的非线性关系，这对现有研究中常用的统计模型的线性假设提出了挑战。本研究通过各种精确识别出的建成环境与行人碰撞之间的非线性关系，建议地方机构采取地理空间差异化政策，建立安全的步行环境。这些发现，尤其是建成环境的有效范围，为交通和土地利用规划、政策建议和道路安全计划提供了支持证据。
