Does the thought of brake-by-wire and steer-by-wire driving petrify you? If so, how do you feel about handing over total control of your vehicle to a robotic system? This nerve-jangling scenario may not be far off. Oxford University’s Mobile Robotics Group has developed and implemented a robotic system that enables an electric Nissan Leaf to partially drive itself over stretches of road especially constructed to evaluate the system (Fig. 1).
If that isn’t enough to unnerve drivers, researchers at Universidad Carlos III de Madrid have developed a system that improves GPS accuracy by up to 90%. The system also could be involved in feeding information from intelligent road systems into a car’s onboard computer, which in turn could provide a driver, or the vehicle’s robotic driving system, with data regarding oncoming highway conditions and regulations.
1. Oxford University has developed and implemented a robotic system that enables a Nissan Leaf to partially drive itself over stretches of road especially constructed to evaluate the system
Oxford’s vehicle uses navigation systems that can recognise its surroundings. Cameras and lasers in the adapted car’s body are linked to an onboard computer. An iPad mounted on the dashboard controls the technology and prompts the driver to let the car take over the driving for a portion of a familiar route (Fig. 2). The driver enables this by touch control, and just like automatic cruise control, the driver can regain control of the vehicle by tapping the brake pedal.
2. Cameras and lasers integrated in the car body are linked to an onboard computer. An iPad mounted on the dashboard controls the technology and prompts the driver to let the car drive a portion of a familiar route. The driver can cancel the car’s control by tapping the foot brake.
Automated technology that can park a car or react to changing road conditions is already available in some production road cars. Autonomous navigation systems like Oxford’s are likely to be the next big step in revolutionising the driving experience.
The robotic system is based on sensorial fusion theory. Whilst human drivers might use current GPS to find their way around, today’s GPS systems cannot provide anything like the coverage, precision, and reliability that robotic cars need to operate safely.
“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,” explained Paul Newman an EPSRC Leadership Fellow with Oxford University’s Department of Engineering Science who is leading the research alongside Oxford’s Ingmar Posner.
“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?’ And the driver can choose to let the technology take over,” Newman said.
The prototype navigation system costs around £5000. “Long-term, our goal is to produce a system costing around £100,” said Newman.
The technology is currently being tested at Begbroke Science Park near Oxford. The next stage of the research led by Posner will involve enabling the new robotic system to understand complex traffic flows and make decisions on its own about which routes to take.
GPS Accuracy Gets A Boost
The work at Universidad Carlos III de Madrid will ensure that the GPS system will accurately pinpoint vehicle position regardless of location. The margin of error of current GPS is about 15 metres in open countryside where the receiver has good visibility from the satellites. This changes dramatically when a vehicle enters a city environment, where the determination of its position can be inaccurate by up to 50 metres. In certain cases, such as tunnels, communication is lost.
The Madrid system can guarantee the position of the vehicle to within 2 metres in urban settings. To achieve this accuracy, the system uses a GPS and a low-cost inertial measurement unit. This device integrates three accelerometers and three gyroscopes to measure changes in velocity and the maneuvers performed by the vehicle. This information is fed to a computer that merges the data and corrects errors in the geographic coordinates.
The system software is based on an architecture that uses context information and an algorithm called the Unscented Kalman Filter. It eliminates the instantaneous deviations caused by the degradation of the signals received by the GPS receiver or the total or partial loss of satellite contact.
The researchers have a prototype that can be installed in any type of vehicle. They already are working a car that has become a platform for research and experimentation for professors and students at Universidad Carlos III de Madrid. The future target for the university researchers is to be able to capture and interpret all of the information that is available on the road.
The researchers also will work on developing a system that uses the sensors in a driver’s smart phone, since intelligent phones are equipped with more than 10 sensors, such as an accelerometer, a gyroscope, a magnetometer, GPS, and cameras, in addition to Wi-Fi, Bluetooth, or GSM communications.