A lane departure warning system is a critical element among advanced driver-assistance systems functions, which has significant potential to reduce crashes. Generally, lane departure warning systems use image processing or optical scanning techniques to detect a lane departure. These systems have some limitations, however, such as harsh weather or irregular lane markings having a negative influence on their performance. Integrating global positioning system (GPS) and digital maps of lane-level resolution with an image processing based lane detection system can improve its efficiency but make the overall system more complex and expensive. In this paper, a lane detection method is proposed which uses a standard GPS receiver without any lane-level resolution maps. The proposed algorithm determines the lateral shift of a vehicle by comparing the vehicle’s trajectory acquired by standard GPS receiver to the reference road direction. The reference road direction is extracted from a standard digital mapping database commonly available in any navigational device containing maps with only road-level information. Extensive field tests were performed to evaluate the efficiency of the proposed system. The field test results show that the proposed system can detect a true lane departure with an accuracy of almost 100%. Although no true lane departure was left undetected, occasional false lane departures were detected when the vehicle did not actually depart its lane. Furthermore, a modification in the proposed algorithm was also tested which has significant potential to reduce the frequency of false alarms.
Using ADAS to Future-Proof Roads—Comparison of Fog Line Detection from an In-Vehicle Camera and Mobile Retroreflectometer
