Intelligent Vehicle Experimental Test-beds


Human-Centered Driver Assistance Systems


Vision Systems for Occupant Posture Analysis


Vision Systems for Driver Analysis and Interface


Related Research

Research Thrusts

Intelligent Vehicles and Novel Experimental Test beds

This research thrust involves developing the new test beds required to create intelligent vehicles.  By developing an extensive test bed infrastructure, the types of research capable on such systems becomes nearly limitless.  The modular and reconfigurable nature of the test beds allows new research in system design, behavioral studies and human factors, occupant analysis, surround analysis, and driver intent/state analysis as well as research into combining these efforts to create a truly intelligent vehicle.


Human-Centered Driver Assistance Systems

and Full Surround Capture

In order to create a human-centered driver assistance system, a multidisciplinary approach to research must be taken.  In this thrust, we use computer vision research combined with behavioral analysis studies, driver intent studies, and psychological studies to research driver assistance systems that put the driver first.


Real-Time Vision for Occupant Posture Analysis for "Smart" Airbags

Vision-based techniques are employed to model and estimate the occupant posture in a real-time manner for the purpose of safer airbag deployment. Most airbag systems consider a single standard for the occupant's size and the nature of the crash. Vision based technology enables the use of precise information about the occupant's size, position and posture to aid the single standard airbag system in deciding whether the occupant is of the right type for deployment.


Vision Systems for Driver Affect, Intent, and View Estimation and Interfaces

The most important part of any vehicle is its occupants.  Therefore it is important for any intelligent vehicle to be able to interface with the driver to relay information (through any number of feedback channels, e.g. auditory, visual, haptic) or detect situations within the vehicle that might lead to unsafe driving (e.g. driver drowsiness or inattention).


Related Research

Related research from the CVRR Laboratory and collaborations.