ORCID Identifier(s)


Graduation Semester and Year




Document Type


Degree Name

Doctor of Philosophy in Industrial Engineering


Industrial and Manufacturing Systems Engineering

First Advisor

Shuchisnigdha Deb


ABSTRACT: Bicycling is beneficial for health, the environment, road users’ flexibility, and personal expenses. Compared to motor vehicles, they are an active mode of transport, cause minimum pollution, are affordable, and can easily navigate through the increasing traffic all over the world. This increase in traffic, however, also increases the possibility of crashes with motor vehicles. Bicyclists, being more exposed to traffic than drivers, suffer fatal consequences from a crash. Therefore, a standard tool is required to understand bicyclist behavior on the road. This tool can provide insights into bicyclists’ behavior so that appropriate infrastructure or policy changes can be implemented. Furthermore, affordable technology can be utilized to assist bicyclists by alerting them of imminent danger ahead of time. The objectives of this research are to 1) develop and validate a Cyclist Behavior Questionnaire (CBQ) for the US population and 2) identify an effective warning system for a smartphone-based app to alert bicyclists. To accomplish the first objective, a CBQ was developed and administered online. A Principal Component Analysis (PCA) determined the 11-item 4 factorial structure of CBQ, which was later verified using a Confirmatory Factor Analysis (CFA). An innovative methodology was developed and implemented to validate self-reported responses of CBQ with bicyclists’ actual responses from a bike-simulator study. For the second objective, a focus group study with experts was conducted. Experts identified a list of potential warning signals including red/yellow flashing signals, and tone/speech audible signals. A bike-simulator experiment further investigated the efficacy of these signals under different environmental factors. The results were analyzed using cyclists’ response to the warnings, as well as their physiological and emotional reaction. Results identified a multimodal combination of red visual and tone audible warning to be the most efficient at alerting cyclists. The findings of these studies will improve the understanding of bicyclists’ behavior and their interaction with technologies while riding. Future research should focus on how the adoption of these technologies would affect bicycling skills and behavior (for example, situation awareness).


Cyclists, Simulator, Assistance system, Questionnaire


Engineering | Operations Research, Systems Engineering and Industrial Engineering


Degree granted by The University of Texas at Arlington

Available for download on Friday, August 01, 2025