A Fuzzy Timed Petri Net Approach to Modeling Forward Collision Warning Systems Based on the 3-Second Rule

Forward Collision Warning (FCW) systems significantly improve road safety by alerting drivers of potential collisions. This paper presents an FCW system using a Fuzzy Timed Petri Net (FTPN) with a three-second rule timing as a safety distance. Our proposed system is a real-time system in which precision is required as we carefully deal with system timing and uncertainties by integrating Timed Petri Net modeling tools and Fuzzy Logic algorithms as essential classic Artificial intelligence tools. Our proposed approach provides an accurate, real-time interpretation of the safety collision system. The primary purpose of this model is to determine the optimal timing of warnings, taking into account the vehicle speed and the distance between vehicles, using the rules we produced from our database extracted by an expert system. We have simplified the modeling process by moving from Fuzzy Timed Production Rules (FTPR) to FTPN, which makes the modeling process effective. Our modeling results have shown that it is a dynamic system in real time that brilliantly comprehends the environment’s complexity and makes decisions quickly. After the development phase, a rigorous verification process was conducted. After verification, our proposed system achieved highly satisfactory results by using a range of precise scenarios, focusing on the speed of response and accuracy of results while characterizing each model with unique latent variables defined within different periods.