Date of Completion

12-21-2018

Embargo Period

12-21-2018

Advisors

Norman W. Garrick, Carol M. Atkinson-Palombo, John N. Ivan, P.E.

Field of Study

Civil Engineering

Degree

Master of Science

Open Access

Open Access

Abstract

The Walk Score® (WS) algorithm works by identifying the closest amenities (grocery stores, banks, restaurants, and schools) and awarding points based on the distance to them from a given location. Scores have a range between 0 and 100. In 2011, the Walk Score® (WS) founders and advisory board modified the algorithm to better account for pedestrian friendliness by adding block length and intersection density data into the model to represent roadway characteristics and named it Street Smart Walk Score®.

Modelers attempting to quantify accessibility often focus on two components: a transportation element (or resistance factor) and an activity element (or attraction factor). The transportation element often considers variables such as infrastructure, topography, route directness, as well as distance, travel time, or cost. Activity factors are measured from objective variables such as destination locations, parking availability, land-use density, land-use mix, and subjective variables such as the perceived quality of products at destinations.

It is generally believed that WS and SSWS account for both the land use and the street network elements of accessibility measures. However, the extent to which these metrics accurately represent these variables has not been fully evaluated by research. The goal of this thesis is to determine if Walk WS and SSWS are true measures of accessibility in fully representing both transportation and activity. WS and SSWS are analyzed to understand if they adequately account for street network density, street network connectivity and street design characteristics – all of which are key aspects of the transportation element of accessibility.

Major Advisor

Norman W. Garrick

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