Abstract

Problem, research strategy, and findings

City governments and planners alike commonly seek to increase pedestrian activity on city streets as part of broader sustainability, community building, and economic development strategies. Though walkability has received ample attention in planning literature, most planners still lack practical methods for predicting how development proposals could affect pedestrian activity on specific streets or public spaces at different times of the day. Cities typically require traffic impact assessments (TIAs) but not pedestrian impact assessments. In this study I present a methodology for estimating pedestrian trip generation and distribution between detailed origins and destinations in both existing and proposed built environments. Using the betweenness index from network analysis, I introduce a number of methodological improvements that allow the index to model pedestrian trips with parameters and constraints to account for pedestrian behavior in different settings. I demonstrate its application in the Kendall Square area of Cambridge (MA), where estimated foot traffic is compared during lunch and evening peak periods with observed pedestrian counts.

Takeaway for practice

The proposed approach can be particularly useful for TIAs, neighborhood plans, and large-scale development projects, where pedestrian flow estimates can be used to guide pedestrian infrastructure and safety improvements and public space investments or for locating pedestrian priority streets during the COVID-19 pandemic.

中文翻译：

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估计街道网络上的行人流量

摘要

问题、研究策略和发现

作为更广泛的可持续性、社区建设和经济发展战略的一部分，市政府和规划者通常寻求增加城市街道上的行人活动。尽管步行性在规划文献中得到了充分的关注，但大多数规划者仍然缺乏实用的方法来预测开发建议如何影响一天中不同时间特定街道或公共空间的行人活动。城市通常需要交通影响评估 (TIA)，但不需要行人影响评估。在这项研究中，我提出了一种方法，用于估计现有和拟建建筑环境中详细起点和目的地之间的步行出行生成和分布。使用网络分析的介数指数，我介绍了许多方法上的改进，使指数能够使用参数和约束对行人旅行进行建模，以解释不同环境中的行人行为。我在剑桥（马萨诸塞州）的肯德尔广场地区演示了它的应用，将午餐和晚上高峰时段的估计人流量与观察到的行人数量进行比较。

外卖练习

提议的方法对于 TIA、社区规划和大型开发项目特别有用，在这些项目中，人流量估计可用于指导行人基础设施和安全改进以及公共空间投资，或在 COVID-19 大流行期间定位行人优先街道.