We are delighted to let you know that our recent study entitled “Assessing Utility Theory and Logistic Regression Models to Predict Drivers’ Stop/Go Behavior Considering Random Taste Variations” is now available online. This research investigates drivers’ decisions at yellow lights, including stopping, yellow-light running (YLR), and red-light running (RLR), and compares the predictive capabilities of logistic regression and utility theory models while considering behavioral heterogeneity. The study provides insights that can guide practitioners in selecting appropriate modeling approaches for traffic safety and driver-assistive systems.
https://doi.org/10.1007/s41060-025-00803-1
SpringerLink
Assessing utility theory and logistic regression models to predict drivers’ stop/go behavior considering random taste variations
International Journal of Data Science and Analytics - Modeling drivers' stop/go decisions when facing yellow traffic lights is crucial for dilemma protection, driver-assistive, and warning...
February 15, 2026 555 1
