Level 3 driving, which enters full-fledged autonomous driving, is becoming more common. And research on autonomous driving is growing rapidly. Therefore, there is a need for a hardware platform to implement autonomous driving, but the actual vehicle price is too high and the implementation conditions are very limited, so its usability is inevitably reduced. In this study, by providing an easy-to-access hardware platform for anyone to support autonomous driving research, compatibility with software platforms can be increased. As a result of this study, it is possible to conduct hardware platform and software platform education at the same time. Through this, trial and error due to errors in each of the two platforms can be reduced. In addition, various sensors, such as camera sensors and LiDAR sensors, were installed on the hardware platform, and a hardware platform capable of testing autonomous driving for education and R&D was conducted not only outdoors but also indoors with little external environmental impact.

There is a need to reduce fuel consumption in order to reduce GHG emissions from the transport sector, which accounts for large volumes. In this study, the fuel consumption rate can be compared with the method using the CAN communication data in the engine controller through the OBD II interface and the direct measurement method using the fuel flow meter. For this purpose, we measured the fuel consumption rate in the engine controller and the fuel flow meter with the chassis dynamometer, and confirmed the reliable data of the fuel flow meter. As a result, the fuel consumption rate in the engine controller and the fuel consumption rate in the fuel flow meter were directly measured. After that, the running test was carried out using the chassis dynamometer and the reliability of the fuel consumption rate using the flow meter was confirmed.