M. Imran Hayee
, Dept. Head, Professor, UMD-Electrical Engineering
A Lane-Departure Warning System (LDWS) and Advance Curve-Warning System (ACWS) are critical among several Advanced Driver-Assistance Systems (ADAS) functions, with significant potential to reduce crashes. Generally, LDWS use different image processing or optical scanning techniques to detect a lane departure. Such LDWS have some limitations--such as harsh weather or irregular lane markings--that can influence their performance. Other LDWS use a GPS receiver with access to digital maps with lane-level resolution to improve the system's efficiency but make the overall system more complex and expensive. In this project, researchers proposed a lane-departure detection method that uses a standard GPS receiver to determine the lateral shift of a vehicle by comparing a vehicle's trajectory to a reference road direction without the need of any digital maps with lane-level resolution. This method only needs road-level information from a standard digital mapping database. Furthermore, the system estimates the road curvature and provides advisory speed for a given curve simultaneously. The field test results showed 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 about 10% of the time when the vehicle did not actually depart its lane. Furthermore, the system always issues the curve warning with an advisory speed at a safe distance well ahead of time.
- Project number: 2017002
- Start date: 05/2016
- Project status: Completed
- Research area: Transportation Safety and Traffic Flow