2017 ~ Present | U.S. Department of Energy, General Motors, MathWorks, dSPACE, Freescale

Advanced Driver Assistance System (ADAS)

Goals

To design an advanced driver assistance system (ADAS) for automobiles to enhance driver safety, e.g., by tracking lane markers to keep the driver in the correct lane and alerting the driver to other cars and pedestrians. While image processing algorithms exist to track lanes, cars, and pedestrians, the challenge in this project is to implement these algorithms on an embedded board (with CPUs and GPUs) and a very limited power budget.

Issues Involved or Addressed

Image processing, real-time object recognition, embedded systems, low-power design, parallel programming, graphics, user interface design, sensors, assistive technologies

Methods and Technologies

  • Low-overhead and accurate real-time object recognition
  • Parallel software implementations of image processing algorithms on GPUs
  • Real-time sensing and tracking
  • Low-power optimizations
  • Driver user-interface design

Academic Majors of Interest

  • Electrical & Computer Engineering
  • Computer Science
  • Mechanical Engineering

Preferred Interests and Preparation

Embedded systems, parallel programming, low-power design, sensors, CPU/GPU computing, image processing, real-time object recognition, HCI/User-interface design, GPU programming, automotive electronics, control systems, driver assistance systems

Sponsor(s)

U.S. Department of Energy, General Motors, MathWorks, dSPACE, Freescale