## 1 Introduction  
Autonomous driving is a key technology for achieving future mobility. Autonomous driving refers to the technology that enables a vehicle to operate on its own, even without direct inputs from the driver. Rapid advances in data processing and communication techniques, facilitated by the fourth industrial revolution, have improved the applicability of autonomous driving technology. Currently, many global automobile companies are attempting to accelerate the commercialization of autonomous vehicles. Apart from ensuring driver convenience, autonomous driving should reduce unnecessary power consumption by regulating vehicle operation based on the traffic environment, thus, it improves the energy efficiency of the vehicle.  
Medium to large-sized commercial vehicle manufacturers use \"platooning\" to reduce the front resistance of the following vehicle, which is generated due to the eddy currents generated at the rear side of the leading vehicle. Furthermore, significant efforts have been devoted toward developing related technologies to improve the fuel economy by reducing the induced pressure resistance of the leading vehicle by under high pressures, thereby reducing the rear side vortex of the leading vehicle [1, 2].  
In vehicle platooning, vehicles are driven with short distances between them by using \"vehicle gap control\" technology. Therefore, the characteristics of platooning with respect to the separation between vehicles should be studied. However, in the study of platooning technology, studies on various vehicle types have not been conducted much, except for the algebraic study of vehicles and simple vehicle speed analysis.  
[PERSON] et al. [3] studied the effect of reducing the average air resistance of clustered vehicles depending on the distance between vehicles during platooning and the number of vehicles and they estimated that the resistance of four vehicles in a cluster was approximately 55% of the resistance of a single vehicle. [PERSON] et al. [4] undertook measurements on test tracks and highways and demonstrated a reduction of 14% in fuel consumption when three trucks were clustered at intervals of 10 m. [PERSON] et al. [5] reported an air force improvement of approximately 7% depending on the reduction in the induced pressure resistance at the rear for different rear structures of the vehicles. [PERSON] et al. [6] reported that the drag coefficient of the leading vehicle varied from \(-2.6\%\) to \(3.4\%\) when the separation between vehicles was 5-30 m and the same type of vehicle was used. The drag coefficient for following vehicles varied from \(-49.1\%\) to \(-25.4\%\), as compared to that for a single vehicle.  
These prior studies show that the drag coefficient increases with the separation distance and that the drag coefficient increases continuously on moving away from the eddy currents of the leading vehicle. Consequently, realizing platooning with appropriate separation between vehicles can reduce the overall drag coefficient, thereby enabling more efficient operation than that when using individual vehicles.  
Therefore, in this study, considering the future developments in platooning technology and the different models, we analyzed the eddy current impact of platooning force using SolidWorks Flow Simulation (version 2015, Dassault Systems, Waltham, France) and the changes in the drag coefficient.