Committee Chair
Onyango, Mbakisya
Committee Member
Sartipi, Mina; Osman, Osama A.; Wu, Weidong; Howell, Ashley N.
College
College of Engineering and Computer Science
Publisher
University of Tennessee at Chattanooga
Place of Publication
Chattanooga (Tenn.)
Abstract
Car-following models traditionally focus on vehicle kinematics or dynamics parameters without considering human psychology. However, recent research has attempted to incorporate psychology into car-following models. Despite these efforts, there are limitations in understanding the psychological triggers that influence individual drivers' responses. To address this gap, we propose a new car-following model based on the Theory of Planned Behavior (TPB), which incorporates a human element by utilizing concepts of psychology. To gather the data pertaining to human input a questionnaire was carefully developed utilizing the Theory of Planned Behavior. Data collection and analysis were done through a survey using google forms. The data was used to measure the value of human driving behavior and cluster it into three behavioral profiles namely, defensive, neutral, and offensive. On the other hand, kinematic data was taken from the NGSIM dataset. The measured behavior and relevant kinematic data were then utilized in the new car-following model, which outperformed the baseline model in performance indexes. Therefore, our research presents a new mathematical model that incorporates both kinematics and psychological factors, based on real-world data, and yields better more accurate responses compared to the baseline models.
Acknowledgments
I am thankful to God Almighty for the success of this research, and to everyone who contributed directly and indirectly to it. I want to especially thank the faculty and staff members of the Civil Engineering Department and the College of Engineering and Computer Science. Foremost, I would like to express my sincere gratitude to my first advisor Dr. Osama A Osman for his continuous support throughout my degree and research. I want to thank him for his patience, motivation, enthusiasm, and immense knowledge. His guidance helped me in all the time of research and outside of it. I present my sincere gratitude to my co-advisors, Dr. Mina Sartipi and Dr. Mbakisya Onyango who took care of me and supported me when I needed them. I convey my sincere thanks to Dr. Weidong Wu, who has been of great help thought my school years. And I would like to thank Dr. Joseph Owino and Dr. Ignatius Fomunung for being great mentors and teachers. My sincere gratitude also goes to Dr. Joanne Romagni, Dr. Ethan carver, and the research school for offering me summer internship opportunities abroad and leading me to work on diverse exciting projects. I want to thank my fellow lab mates at the University of Tennessee at Chattanooga: Jibril, Jewel, and Ahmed, for the stimulating discussions, for the help and encouragement they extended, and for all the fun for whatever time we had. Last but not least, I would like to thank my family and friends, especially my mother.
Degree
M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science.
Date
8-2023
Subject
Traffic monitoring--Psychological aspects; Kinematics
Discipline
Transportation Engineering
Document Type
Masters theses
DCMI Type
Text
Extent
xiv, 123 leaves
Language
English
Rights
http://rightsstatements.org/vocab/InC/1.0/
License
http://creativecommons.org/licenses/by/4.0/
Date Available
9-1-2024
Recommended Citation
Khan, Faiza, "Integrating human psychology into car-following models for accurate response prediction: a realistic approach" (2023). Masters Theses and Doctoral Dissertations.
https://scholar.utc.edu/theses/833
Department
Dept. of Civil and Chemical Engineering