Date of Award

6-2019

Degree Name

Master of City and Regional Planning/MS in Engineering (Transportation Planning Specialization)

Department/Program

Civil and Environmental Engineering

Advisor

Carole Turley Voulgaris

Abstract

Walkability as a concept that captures the ability to walk from one place to another has multiple dimensions. Between traversability to being a proxy for better urban places, there are also numerous measurements of walkability that attempts to quantify certain or all aspects of walkability. It is, however, unclear, through a review of available literature, how these measurements of walkability relate to each other statistically. This methodology focuses on generating a framework for analysts to evaluate and prioritize pedestrian infrastructure. WalkScore™ (WS), HCM Pedestrian Level of Service (PLOS), Average Nodal Degree (AND), and Intersection Density are the four metrics selected for this analysis that focuses on distinctive aspects of walkability (proximity, amenity, network-connectivity, respectively). A sample of 51 street segments from the County of San Luis Obispo is selected according to their respective Average Daily Traffic (ADT) volumes. Pearson’s Correlations between the six combinations of relationships are measured, and the strongest correlation between the six relationships is between WalkScore™ and Intersection Density with an R2 of 0.44.

A regression model that includes external factors such as population and adjacent land use is used to analyze and predict PLOS of the street segment. Although the model is not statistically significant, the goal of this research is to identify gaps in current and potential walkability of street segments in the sample. Therefore, this framework of using established walkability metrics to predict PLOS, and then distinguishing places for improvements is proposed as a result of this research to be used by government agencies to prioritize pedestrian infrastructure.

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