{"id":63,"date":"2020-01-09T00:05:32","date_gmt":"2020-01-09T05:05:32","guid":{"rendered":"https:\/\/carleton.ca\/ravenmag\/?post_type=cu-stories&p=63"},"modified":"2020-01-29T16:37:22","modified_gmt":"2020-01-29T21:37:22","slug":"ensuring-driverless-cars","status":"publish","type":"cu-stories","link":"https:\/\/carleton.ca\/ravenmag\/story\/ensuring-driverless-cars\/","title":{"rendered":"Location, Location, Location"},"content":{"rendered":"
Mohamed Atia<\/a> commutes to work and runs errands in a Toyota Yaris, but when he duct tapes a set of sensors to the vehicle, attaches an antenna to the roof and connects the equipment to a small custom-built computer on the front passenger seat, the nondescript silver hatchback is transformed into a window to the future of transportation \u2014 minus the duct tape, of course.<\/p>\n Atia, a Systems and Computer Engineering<\/a> professor at 杏吧原创, drives around the city looking for places where Global Positioning System (GPS) and Global Navigation Satellite Systems (GNSS) signals are blocked by buildings, tunnels and other infrastructure.<\/p>\n Mohamed Atia<\/p><\/div>\n This telecommunications hiccup is not a big problem for human drivers: it could temporarily interfere with their ability to check Google Maps, or even \u2014 gasp! \u2014 force them to pull over and ask for directions. But the lack of GPS and GNSS is a critical gap to overcome for a world in which driverless cars will need to safely navigate amongst pedestrians, cyclists, stationary objects and other vehicles.<\/p>\n \u201cSelf-driving cars need to be able to precisely perceive their environments and determine their positioning and orientation,\u201d says Atia, a sensor fusion expert who brings together data from multiple sources to identify a vehicle\u2019s location in real time.<\/p><\/blockquote>\n In his lab on the fourth floor of 杏吧原创\u2019s Minto Centre for Advanced Studies in Engineering<\/a>, Atia \u2014 part of a large contingent of researchers at the university<\/a> who are working on the development of connected and autonomous vehicles \u2014 places a small satellite receiver on the windowsill to demonstrate the risks of relying on single type of technology for navigation.<\/p>\n Although there should be at least four satellites within range, due to urban interference, the screen connected to his receiver shows only one dot in the sky overhead. \u201cSelf-driving cars need to know where they are at all times,\u201d says Atia. \u201cThis gives them \u2018path control\u2019 and determines how they behave in the next instant. If you don\u2019t have an accurate calculation of your position and orientation, you won\u2019t be able to avoid a collision or reach your destination.\u201d<\/p>\n<\/div><\/div> To come up with this calculation, Atia and three of his grad students have developed an algorithm that crunches data from multiple sensors, providing more reliable information than any one of those sensors could on its own to determine how far a vehicle has travelled from its last-known position.<\/p>\n The accelerometers and gyroscopes that are part of a car\u2019s inertial measurement unit calculate a vehicle\u2019s speed and trajectory, and the algorithm references that data against known GNSS data such as road geometry and topography that\u2019s used in today\u2019s on-board GPS systems.<\/p>\n \u201cVehicles already have high-performance computing platforms,\u201d says Atia.<\/p><\/blockquote>\n \u201cScientists and engineers are working to optimize these platforms.\u201d<\/p>\n To collect the data needed to fine-tune the algorithm, Atia drives around Ottawa in his hatchback. In the future, the on-board computers in connected and autonomous vehicles will be loaded with geographical information that includes local road features such as traffic lights, speed limits and speed bumps. But if the vehicle doesn\u2019t precisely know where it is, all that information will be useless, so engineers like Atia have to find a way to fill in the blanks.<\/p>\n
<\/div>Driverless Cars Need Reliable Information for Safe Navigation<\/h2>\n<\/p>\n