DriveCap is a low-cost aftermarket in-vehicle system that can measure driver’s capability on common driving tasks in a wide range of vehicles. We apply decades of research onautonomous vehicle and driver assistance systems at Carnegie Mellon’s Robotics Institute for development of prototype DriveCap systems.
One of the key observations to arise during formulation of the Safe Driving projects was that the problems related to driving within both the aging and disabled communities could be decomposed into driver capability within a set of common denominator tasks. The basic fact is that task-specific levels competence are needed in core driver capabilities, regardless of what is leading to unsafe driving.
For example, correct mirror position is an important enabler of safe driving. Successful driver education techniques have been deployed in both the older driver population and for commercial vehicle operators. The basic premise is the same for any population - provide drivers with the knowledge and tools to properly set their mirrors on their own and accelerate uptake through carefully designed policy actions.
Unfortunately, there are only ~400 driver rehabilitation specialists in the United States. This means a large majority of drivers will not be able to access expert assistance for detection of capability decline and identification of suitable remedies. The DriveCap project seeks to extend the reach of these specialists and collect driver capability metrics utilizing low cost sensor technologies. To this end, the team is developing a small footprint package and validating the system's performance. This is a rich area for PST research - most notably issues surrounding acceptance, data rights, licensing, policy barriers and solutions related to how DriveCap is implemented, and payment for the system itself.