Bolten Nicholas, Caspi Anat
Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington, United States of America.
PLoS One. 2021 Mar 19;16(3):e0248399. doi: 10.1371/journal.pone.0248399. eCollection 2021.
A wide range of analytical methods applied to urban systems address the modeling of pedestrian behavior. These include methods for multimodal trip service areas, access to businesses and public services, diverse metrics of "walkability", and the interpretation of location data. Infrastructure performance metrics in particular are an increasingly important means by which to understand and provide services to an urbanizing population. In contrast to traditional one-size-fits all analyses of street networks, as more detailed pedestrian-specific transportation network data becomes available, the opportunity arises to model the pedestrian network in terms of individual experiences. Here, we present a formalized and city-scale framework, personalized pedestrian network analysis (PPNA), for embedding and retrieving pedestrian experiences. PPNA enables evaluation of new, detailed, and open pedestrian transportation network data using a quantitative parameterization of a pedestrian's preferences and requirements, producing one or more weighted network(s) that provide a basis for posing varied urban pedestrian experience research questions, with four approaches provided as examples. We introduce normalized sidewalk reach (NSR), a walkshed-based metric of individual pedestrian access to the sidewalk network, and sidewalk reach quotient (SRQ), an estimate of inequity based on comparing the normalized sidewalk reach values for different pedestrian profiles at the same location. Next, we investigate a higher-order and combinatorial research question that enumerates pedestrian network-based amenity access between pedestrians. Finally, we present city-scale betweenness centrality calculations between unique pedestrian experiences, highlighting disagreement between pedestrians on the "importance" of various pedestrian network corridors. Taken together, this framework and examples represent a significant emerging opportunity to promote the embedding of more explicit and inclusive hypotheses of pedestrian experience into research on urban pedestrian accessibility, multimodal transportation modeling, urban network analysis, and a broader range of research questions.
应用于城市系统的一系列广泛分析方法涉及行人行为建模。这些方法包括多模式出行服务区域、商业和公共服务可达性、各种“步行适宜性”指标以及位置数据解读等方面的方法。特别是基础设施性能指标，正日益成为理解城市化人口并为其提供服务的重要手段。与传统的一刀切式街道网络分析不同，随着更详细的特定行人交通网络数据的出现，就有机会根据个人体验对行人网络进行建模。在此，我们提出一个形式化的城市尺度框架——个性化行人网络分析（PPNA），用于嵌入和检索行人体验。PPNA能够利用行人偏好和需求的定量参数化来评估新的、详细的和开放的行人交通网络数据，生成一个或多个加权网络，为提出各种城市行人体验研究问题提供基础，并给出了四种方法作为示例。我们引入归一化人行道可达性（NSR），这是一种基于步行范围的个体行人进入人行道网络的指标，以及人行道可达性商数（SRQ），它是通过比较同一位置不同行人特征的归一化人行道可达性值来估计不平等程度。接下来，我们研究一个更高阶的组合研究问题，即枚举行人之间基于行人网络的便利设施可达性。最后，我们展示了独特行人体验之间城市尺度的中介中心性计算，突出了行人在各种行人网络走廊“重要性”上的分歧。总体而言，这个框架和示例代表了一个重大的新机遇，可促进将更明确和包容的行人体验假设嵌入到城市行人可达性、多模式交通建模及城市网络分析等研究以及更广泛的研究问题中。
