Assessment Possibilities for Trajectory Fusion of Two Vehicles in the Case of Automated Vehicles

Abstract

Because of the increasing integration of automation and cutting-edge technology into modern transportation systems, the development of efficient and dependable Automated Vehicles (AVs) has become an important area of research. One of the most important characteristics of AVs is their ability to perceive and navigate complex environments safely. The process of combining trajectory data from multiple vehicles, known as trajectory fusion, has the potential to improve AV perception. The feasibility of implementing trajectory fusion in the context of two autonomous vehicles coexisting in the same operational environment is investigated in this study. The primary goal of this research is to investigate the effectiveness of trajectory fusion in increasing the environmental awareness of Automated Vehicles (AVs), while also investigating its implications for the decision-making mechanisms that govern these vehicles. The MATLAB Simulink simulation platform was essential in carrying out this investigation. The intricate dynamics of trajectory fusion within the context of dual AVs were meticulously analyzed and evaluated using this software.