Year

2025

Season

Fall

Paper Type

Master's Thesis

College

College of Computing, Engineering & Construction

Degree Name

Master of Science in Civil Engineering (MSCE)

Department

Engineering

NACO controlled Corporate Body

University of North Florida. School of Engineering

Committee Chairperson

Dr. Thobias Sando

Second Advisor

Dr. Pruthvi Manjunatha

Third Advisor

Dr. Ryan Shamet

Department Chair

Dr. Alan Harris

Abstract

This research develops a comprehensive, data-driven framework for assessing multimodal bicycle accessibility using open-source technologies and real-time routing data. Traditional active transportation studies often depend on proprietary GIS tools and static network datasets, which limit scalability, reproducibility, and integration with live mobility systems. In contrast, this study introduces a Python-based approach that leverages GeoPandas, the Google Maps Directions API, and General Transit Feed Specification (GTFS) data to dynamically evaluate infrastructure quality, operational stress, and multimodal connectivity. The framework was applied to Duval County, Florida, to examine how roadway design, facility type, and transit availability jointly influence bicycle network performance and accessibility.

The analytical framework consists of three major components: (1) facility-level scoring, (2) traffic-stress evaluation, and (3) route-level multimodal analysis. The facility-scoring model quantifies roadway suitability for cycling using composite indicators of comfort, safety, and speed. Each roadway segment was assigned a Facility Score derived from geometric, operational, and protection-level attributes such as facility type, posted speed, and lane configuration. These metrics were normalized and weighted to produce a unified score reflecting overall bicycling comfort. A complementary Bicycle Level of Traffic Stress (LTS) classification was then implemented to assess operational comfort under varying speed and traffic conditions. The LTS analysis categorized segments into four stress levels, ranging from “LTS 1” (low-stress, suitable for all ages) to “LTS 4” (very high-stress, suitable only for expert cyclists).

Results from the facility and LTS analyses show that Duval County’s existing bicycle network remains largely characterized by discontinuous, high-stress corridors. More than 80 percent of the network operates at LTS 3 or 4, indicating that most streets are unsuitable for casual cyclists. Planned and funded projects, however, are expected to significantly improve comfort and safety, nearly tripling the share of low-stress (LTS 1–2) corridors. The greatest improvements occur along downtown, Riverside–Avondale, and the University of North Florida–Town Center corridors, where multiple protected and shared-use facilities intersect with high-frequency transit routes.

At the route level, the study analyzed twenty representative trips using the integrated Bike–Bus–Bike (B–B–B) routing engine. This module automatically identified first- and last-mile bicycle connections to the nearest bus stops and evaluated total travel times, distances, and composite comfort scores. Comparisons between direct bicycle routes and multimodal alternatives revealed clear trade-offs between speed and comfort. Direct cycling offered shorter travel times but exposed riders to higher stress, while multimodal routes reduced stress exposure by leveraging transit to bypass unsafe segments. Although total travel time increased modestly, perceived safety and accessibility improved substantially, particularly for trips exceeding ten miles. These findings highlight the potential of combining transit and bicycle infrastructure to achieve equitable, low-stress mobility for all user groups.

Overall, the study demonstrates that integrating infrastructure scoring, traffic-stress assessment, and multimodal routing provides a powerful, transferable tool for transportation planning. The developed framework enables continuous, GIS-independent evaluation of bicycle network performance and supports data-driven investment prioritization. By combining open-source technologies with real-time routing APIs, this research advances a replicable model for equitable and sustainable active transportation planning applicable to other urban regions.

Download

Share

COinS