Lane Detection

The lab is being designed to focus on three main topics, sensors and sensor fusion, intelligent vehicles, and preventing vehicle crashes. One example of current work is determining the precise location of the host vehicle relative to the road via lane markers and “potential in-path targets” before taking any active or passive actions. Such actions could consist of prompting the driver of changes in road conditions, warning of a potentially dangerous situation down the road, or going so far as to autonomously control the vehicle by interacting with the steering, braking, or powertrain to help prevent an accident. Again, a high level of enthusiasm occurs because synergistic Intelligent Vehicle System (IVS) capabilities will allow for the “tuning” of the advanced mathematical algorithms executing in simulated real-world vehicles (i.e., specify powertrain, chassis, etc.) and scripted road surfaces (i.e., specify μ) and driving maneuvers. A vehicle’s performance (i.e., stability, deceleration, etc.) can be studied via a comprehensive vehicle dynamics model in commercial research caliber software – CarSim. CarSim will allow for the integration of other standard design tools such as Matlab/Simulink, or LabView to design architectures that utilize realistic representations of vehicle dynamics model(s). Results from simulation and real-time data collection can then be utilized to initiate commercial product development for the open market. The research areas that would be investigated through this lab are:

  • Simulation and analysis of vehicle crash scenarios.
  • Study of vehicle dynamics with respect to stability and control.
  • Sensor characterization like LIDAR, RADAR etc.
  • Development and study of Collision Warning system.
  • Lane detection and tracking.