A Real-Life-Data-Based Transit Accessibility and Equity Analysis: A Case Study on the Fresno City

Tuesday, June 10, 2025

4:45 PM – 6:00 PM MT

Primary Author(s)

Pratham Aggarwal

Undergraduate Student Assistant
Fresno State Transportation Institute
Fresno, CA, United States

Presenter(s)

Pratham Aggarwal

Undergraduate Student Assistant
Fresno State Transportation Institute
Fresno, CA, United States

Co-Author(s)

RG

Ritvik Gaur

Graduate Research Assistant
Fresno State Transportation Institute
Fresno, CA, United States
Saugat Paudel

Graduate Fellow
Fresno State Transportation Institute
Fresno, CA, United States
Amneek Chalotra, Student

Student Fellow
Fresno State Transportation Institute
Hanford, CA, United States
Aly M. Tawfik, PTP

Associate Professor
California State University, Fresno
Fresno, CA, United States
Kent Klann

Research Assistant
Fresno State Transportation Institute
Fresno, CA, United States

Submitter(s)

Pratham Aggarwal

Undergraduate Student Assistant
Fresno State Transportation Institute
Fresno, CA, United States

Abstract: Public transportation plays a vital role in ensuring access to essential services for some critical groups of the population; however, sometimes, not all communities benefit equally from the provided services. Sometimes, transit accessibility in different communities suffers from disparities based on socioeconomic factors like income, race, and population density. This research project aims to understand the transit accessibility equity gaps, particularly how accessible public transport is for different communities and in different areas. A case study of Fresno City, CA is presented. We use transit accessibility data for 338 census block groups within Fresno city and fuse this data with equity data from census sources, focusing on factors such as income, race, car ownership, and population density. Various transit metrics- e.g. percent of the population with access to transit services, transit travel times, transit walking distances, and transit to driving travel time ratio- are analyzed and compared across these equity measures. Python libraries are used to process the data and create visual comparisons to represent the transit accessibility equity gaps. The results demonstrate transit accessibility inequities in Fresno that are in line with similar findings from other studies in the literature, indicating that lower-income and minority communities may be suffering from limited access to needed transit services. The research findings provide public transportation engineers, planners, and policy-makers with a potentially valuable tool that can help uncover and address transit accessibility inequities and make data-driven decisions to enhance public transit, contributing to a more inclusive and equitable system.

Learning Objectives:

Attendees can expect to learn the following from this session:

analyze Fresno City transit accessibility data with visuals, getting metrics such as travel times and transit-to-driving ratios.
compare transit accessibility across income, race, and population density, identifying equity gaps in Fresno City’s transportation system.
conclude data-driven solutions for addressing transit accessibility inequities, offering recommendations for more inclusive public transportation policies.