An Empirically Validated Adjustment Factor Level of Traffic Stress Framework for Urban Bicycle Network Planning

Author

• Logan Sirbaugh

Date

2026

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Civil Engineering

Committee Chair

Stephanie Ivey

Committee Member

Aaron Robinson

Committee Member

Anzhelika Antipova

Committee Member

Brian Waldron

Committee Member

Martin Lipinski

Abstract

Bicyclist safety remains a critical challenge for transportation agencies seeking to expand bicycle networks while reducing crash severity and risk. To address this need, planners have used a range of evaluation approaches; however, many are costly, time-intensive, difficult to scale, and limited in transferability across jurisdictions. In response, Level of Traffic Stress (LTS) frameworks emerged as a practical tool for evaluating bicycling comfort and identifying low-stress routes using widely available roadway data. Despite widespread adoption, most LTS approaches rely on assumed design thresholds and perception-based criteria rather than observed safety outcomes, limiting their empirical grounding and consistency. This dissertation addresses this gap by developing an empirically grounded Adjustment-Factor LTS Framework that links roadway characteristics to bicyclist crash severity using geocoded bicycle-motor vehicle crash data from six major United States metropolitan regions. Ordered logistic regression was used to quantify relationships between roadway attributes and injury severity, translating them into structured adjustment factors that refine baseline stress classifications using commonly available roadway data. Rather than proposing a fixed model, the framework is designed to remain flexible and scalable across jurisdictions with varying data availability while shifting stress classification from assumption-based thresholds to empirically informed safety relationships. The dissertation consists of three research papers that collectively develop, test, and validate the Adjustment-Factor LTS Framework. Key deliverables include a transferable methodology for empirically adjusting LTS scores using crash data, a transparent framework that accommodates varying levels of data completeness, and validation against existing LTS approaches to highlight areas of alignment and divergence. Results show the framework captures meaningful differences in bicyclist crash-severity risk not consistently reflected in traditional design-based LTS methods. The primary contribution of this research is the introduction of a scalable, data-driven LTS framework that directly links bicyclist safety outcomes to network stress classification. By prioritizing empirical evidence and implementation flexibility, the Adjustment-Factor LTS Framework provides transportation practitioners with a practical tool to support bicycle network planning, infrastructure prioritization, and more defensible, data-driven safety decisions across diverse urban contexts.

Comments

Data is provided by the student.”

Library Comment

Dissertation or thesis originally submitted to ProQuest/Clarivate.

Notes

Open Access

Recommended Citation

Sirbaugh, Logan, "An Empirically Validated Adjustment Factor Level of Traffic Stress Framework for Urban Bicycle Network Planning" (2026). Electronic Theses and Dissertations Archive. 4009.
https://digitalcommons.memphis.edu/etd/4009