Investigation of Following Vehicles’ Driving Patterns Using Spectral Analysis Techniques

Despite the potential benefits of autonomous vehicles (AVs) reducing human driver errors and enhancing traffic safety, a comprehensive evaluation recent AV collision data reveals concerning trend rear-end collisions caused by following vehicles. This study aimed to address this issue developing methodology that identifies relationship between driving patterns risk leading using spectral analysis. Specifically, we propose process for computing three indices: reaction time, stimulus compliance index, collision-risk aversion index. These indices consistently produced reliable results under various conditions. Our findings align with existing research on Given consistency robustness these indices, they can be effectively utilized in advanced assistance systems or incorporated into AVs assess likelihood posed develop safer strategies accordingly.