Reducing Power Consumption through Effective Data Sharing in Platooning Scenarios

Platooning occurs when vehicles travel closely together to benefit from multi- vehicle movement, increased road capacity and reduced fuel consumption. This study focuses on the optimization of energy consumption under different driving scenarios and road conditions. To quantify the energy consumption, we first consider dynamic events that can affect driving, such as braking and sudden acceleration. In our experiments, we focused on modelling and analyzing the power consumption of autonomous platoons in a simulated environment. The main goal of experiments in a simulated environment is to develop a clear understanding of the different driving and road factors influencing power consumption and to identify optimization parameters. By simulating multiple driving scenarios under different road conditions, the key elements that influence energy consumption can be identified. The initial findings from the simulations suggest that by optimizing the inter- vehicle distances and keeping the vehicle movements concurrent, the power consumption of each vehicle within the platoon can be reduced. Moreover, we explored the influence and impact of vehicle-to-vehicle coordination and communication delays on power consumption. Additionally, controlling speed changes and reducing unnecessary braking can enhance the energy efficiency within the platoon, resulting in significant cost savings over a long period of time. This research focuses on understanding the importance of including detailed power consumption models in the design of a collaborative vehicular environment via information exchange. Incorporating these models can allow platoons to reduce overall power consumption through efficiently designed data sharing and control strategies. The results of this study can help advance automotive technologies in terms of vehicle data exchange and communication, thereby providing a stronger foundation for future transportation.