Integrating human psychology into car-following models for accurate response prediction: a realistic approach

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.

Grantor dc:publisher

University of Tennessee at Chattanooga

Year dc:date.available

2024

Author dc:creator

• Khan, Faiza

Contributors dc:contributor

• Onyango, Mbakisya
• Sartipi, Mina; Osman, Osama A.; Wu, Weidong; Howell, Ashley N.
• College of Engineering and Computer Science

• Traffic monitoring--Psychological aspects
• Kinematics

Licence

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language

English, eng

Repository record dc:identifier

https://scholar.utc.edu/theses/833

OAI identifier oai:identifier

oai:scholar.utc.edu:theses-2002