<![CDATA[The development of autonomous vehicle technology has brought about a revolution in transportation systems, presenting solutions for efficiency, safety, and comfort. One of the main challenges in the development of autonomous vehicles is accurate motion modeling to understand and predict vehicle dynamics in various conditions. This article discusses the application of the Euler Method, a simple but effective numerical method, to model the movement of autonomous vehicles. This method is used to solve differential equations that describe the dynamics of the vehicle, including acceleration, speed, and position based on the input of the control system. Modeling is done through a discrete approach, where changes in variable values are calculated at small time intervals. This study evaluates the performance of the method in various scenarios, such as straight trajectories, sharp turns, and sudden stop situations, which are often encountered by autonomous vehicles in the real world. The simulation was carried out using MATLAB software to visualize the dynamics of movement and analyze the accuracy of the prediction results. The results show that the Euler Method is able to produce fairly accurate modeling on simple scenarios, although there are limitations in dealing with more complex dynamics due to the linear nature of this method. Therefore, further development with more sophisticated numerical methods, such as the Runge-Kutta Method or adaptive algorithms, is needed to improve accuracy on more complex scenarios. This article makes a significant contribution in providing technical and practical references for researchers and developers in optimizing more reliable and efficient autonomous vehicle systems.]]>
