Numerical and Experimental Investigation of the Optimization of Vehicle Speed and Inter-Vehicle Distance in an Automated Highway Car Platoon to Minimize Fuel Consumption

The development of the technology of automated highways promises the opportunity for the vehicles to travel safely at a closer distance concerning each other. As such, vehicles moving in the wake of others experience a reduction in fuel consumption. This article investigates the effect of longitudinal distance between two passenger cars on drag coefficients numerically and experimentally. For the numerical analysis, the fluid flow at car speeds of 70, 90 and 110 km/h were examined. The Artificial Intelligence coding was applied to train an Artificial Neural Network to extend the calculated data. The optimum values for the inter-vehicle distance and the vehicle speed to assure the least drag coefficient are obtained. To support the numerical results an instrument designed and built particularly to accurately measure the fuel consumption was installed on a midsize sedan car and some field tests were carried out. The results show that the platooning with an optimized longitudinal distance between two cars can reduce the drag coefficient by 7%, the fuel consumption by 12.6% and the CO2eq production by 12.6% per vehicle