Development of a Smart Phone App to Warn the Driver of Unintentional Lane Departure using GPS Technology

Principal Investigator(s):

M. Imran Hayee, Dept. Head, Professor, UMD-Electrical Engineering

Project summary:

Unintentional lane departure on a straight or a curved road section is a major safety risk. Currently available commercial lane-departure warning systems either use vision-based technology or GPS technology with lane-level resolution. Both of these techniques have their own performance limitations and are complex and costly to implement, prohibiting their widespread market penetration.

Researchers have previously developed an innovative lane-departure detection and warning algorithm which can also provide an advance curve-speed warning using standard GPS technology. Our team's algorithm acquires trajectory of a moving vehicle in real time using standard GPS receiver and compares it with a reference direction of travel to detect any potential lane departure. The necessary reference direction of travel is obtained from one or more past trajectories of the same vehicle using our innovative algorithm.

Our team's field tests show that our algorithm is robust enough to successfully detect unintentional lane departures on both straight and curved roads. Due to its robustness and simplicity, this technique can be implemented in vehicles at a much lower cost than other currently available options. Alternatively, this technique can also be implemented as an added feature in a navigational device or as a smartphone app for wider and speedier market penetration.

Researchers are developing a smartphone app to implement our technique and make it available to the public free of cost. The app will detect an unintentional lane departure to provide a timely warning to the driver. Our team?s app will be especially useful for long stretches of freeways or highways in rural areas.

Project details: