"We are working on a low-cost 'auto drive' navigation system, that doesn't depend on GPS, done with discrete sensors that are getting cheaper all the time," Professor Paul Newman of Oxford University's Department of Engineering Science said (via Clean Technica), describing the project. "It's easy to imagine that this kind of technology could be in a car you could buy."
The Oxford project is aimed at achieving a middle ground between the human-piloted cars that exist today and the futuristic autonomous concepts being worked on by companies like Google. Instead of the cars driving themselves all the time, the driver handles some of the work, but the car occasionally prompts the driver when it knows a route, allowing the driver the option to let the car take over.
That prompt comes by way of Apple's iPad, which is positioned on the dashboard and flashes an "auto-drive" option when the system recognizes an area. Activating auto-drive switches control of the car over to an internal system that relies on cameras and lasers built into the body of the car, as well as an additional computer in the trunk. Newman says the system works due to technological leaps forward in laser mapping.
"Our approach is made possible because of advances in 3D laser mapping that enable an affordable car-based robotic system to rapidly build up a detailed picture of its surroundings," Newman said. "Because our cities don't change very quickly, robotic vehicles will know and look out for familiar structures as they pass by so that they can ask a human driver 'I know this route, do you want me to drive?'"
The iPad remains up front as the human's main means of interacting with the system, though a simple tap on the brakes is also capable of switching back to manual control.
The technology is nowhere near being ready for commercial production. Professor Newman says the group's long-term goal is to produce a system that will cost about ?100. Currently, the prototype navigation system costs ?5,000.
The team will continue testing its iPad-driven system at its base in Begbroke Science Park, near Oxford. The next step will see them teaching the system to understand complex traffic flows and make decisions on its own about routing.