A Study on the Evaluation Method of Highway Driving Assist System Using Monocular Camera

• Published in: Applied sciences Vol. 10; no. 18; p. 6443
• Main Authors: Bae, Geon Hwan, Lee, Seon Bong
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2020
• Subjects: Automotive parts; autonomous vehicle; Autonomous vehicles; Cameras; Control algorithms; Data acquisition; Deep learning; Differential global positioning system; Global positioning systems; GPS; highway driving assist (HDA); monocular camera; Neural networks; real vehicle test; Roads & highways; Sensors; Simulation; Systems analysis; test scenario; Test vehicles; Tires
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app10186443

In this paper, we propose a method to evaluate Highway Driving Assist (HDA) systems, a type of Advanced Driver Assistance System (ADAS), using a monocular camera, which eliminates the need of experts or expensive equipment and reduces the time, effort, and cost required in such tests. We use the information from the images captured by the monocular camera, such as the lane and rear tires of the lead vehicle, and from the geometrical composition, including the heading angle and the distance of the camera from the front bumper of the test vehicle. To verify the evaluation method, we used the image and geometric information to calculate the distances of the lead vehicle and the lane center from the test vehicle. We compared and analyzed the method using DGPS (Differential Global Positioning System), Data Acquisition(DAQ) and the method using monocular camera. Therefore, it was determined that the proposed method of evaluating HDA systems using a monocular camera is reliable because of the small margin of error between the theoretical with monocular camera and real vehicle test with DAQ and DGPS.