Audi Canada

Winner on points: Team FAUtonOHM wins Audi Autonomous Driving Cup 2016

“We are really intentionally augmenting a grade of problem from year to year, generally in a final round,” pronounced Dr. (Engineering) Lars Mesow, member of a foe committee, about a opening of a 8 college teams. “This new era of gifted students showed well-developed creativity and came adult with singular solutions.” The Audi Q5 indication cars versed with ultrasonic sensors and video camera had to autonomously equivocate obstacles, negotiate intersections and cranky trade and expostulate during a protected stretch to issuing trade ahead. The hurdles also embody executing a left spin opposite approaching traffic, pointing parking maneuvers and protected puncture braking when obstructions unexpected appeared.

The group FAUtonOHM tender a jury with a altogether performance. The students quietly mastered a pushing tasks on a exam march and presented their growth work with sound systematic explanations. Second place, with a financial endowment of 5,000 euros, went to a group KACADU of a Research Center Informatics Karlsruhe. The group MomenTUM of a Technical University Munich took third place and received, 1,000 euros in esteem money. Andreas Reich, Head of Electronics Pre-Development during AUDI AG, congratulated a 3 tip placed teams and presented a awards. “I wish to demonstrate my good honour to all participants,” pronounced Reich. “Anyone who already shows such unrestrained for destiny issues such as piloted pushing during their studies can design some sparkling career prospects.”

On a final day, Ricky Hudi, Head of Development Electrics/Electronics during AUDI AG, explained a advantages of rarely accurate digital maps and a destiny of Car-to-X communication. Audi demonstrated a standard use box in team-work with experts from HERE. A indication automobile detects an barrier to trade and stores this information on a real-time map. The information is afterwards sent to a automobile that is following behind, that is means to pass by a jeopardy section safely and easily. “Here we are showing, on a indication scale, how overflow comprehension can work,” explained Dr. Stefan Knirsch, Audi Board Member for Technical Development during AUDI AG. “Real-time jeopardy warnings about glisten ice, car breakdowns and building trade jams give drivers profitable supplemental information and raise trade reserve significantly.”

Today, immobile HD maps by HERE yield 3D models of a road, travel infrastructure and sourroundings that are accurate to a inch. The subsequent step is to couple a maps with real-time information from genuine trade events. Cars acquire this information with their cameras, sensors and control systems and track a data, anonymized, to secure servers for estimate and evaluation. From there, a information is immediately common with other highway users.

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