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| The team spent much of its time integrating existing technologies and enabling them to interpret streams of information in real time. |
“Much of the work that went into designing and developing Little Ben was not cutting-edge research,” said Spletzer, “but rather integrating various technologies and applying them to specific tasks.
“A lot of research on autonomous cars had already been done. Our challenge was to integrate and extend these results in a very limited timeframe. Previous work on autonomous cars and highways focused on getting cars to stay in lane. But the task at the Grand Challenge was to enable a robotic car to respond dynamically to its environment. Nothing at that level of difficulty had been done before.
“This was a big software engineering problem. You had to merge information from a lot of sensors, calculating the weight of each input before making a determination. That requires algorithms for making intelligent decisions and acting on input.
“The car had to switch smoothly from one mode to another, from four-way stop to U-turn to passing to merging and so on. The goal was to get all the sensors to communicate to Ben’s central [computer] in real time – while the car is traveling 25 mph, or 37 feet per second.”
The complexity of the challenge provided ample opportunity for failure. Of the 36 cars that made it to the national qualifying event, only 11 were approved to take part in the Grand Challenge; DARPA had expected a final field of 20. And of the final 11 cars, five were disqualified for various infractions during the first two hours of the event.
“I did not think we would do as well as we did,” Spletzer confessed. “A lot of really good teams fell out of the competition. It takes just one mistake.”
A second phone call home
The Grand Challenge had hardly begun when such a mistake almost befell the Ben Franklin Racing Team.
Not 30 minutes into the race, a message flashed on the JumboTron saying that Little Ben had been “retired.” A year’s effort, and countless weeks of working day and night, appeared lost.
“I saw that message and called my wife back in Pennsylvania,” said Spletzer, who was watching the video from bleachers provided for spectators. “I told her, ‘We’re finished, we’re the first one out.’”
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Out on the course, Little Ben, after traversing an unpaved stretch of terrain, had slowly negotiated a steep, bumpy, downhill grade, then stopped atop a small berm overlooking the paved road. The car remained on the berm, leading judges to conclude that the Prius was overwhelmed by the transition from unpaved to paved surface.
But the judges reconsidered, and rescinded their decision to disqualify, when Little Ben finally turned right onto the highway.
“Apparently, the steepness of the incline from the berm to the paved highway made Ben’s lidar think that the asphalt was actually a short wall, an obstacle,” said Spletzer. “We had accounted for this contingency in our programming, but Ben needed time to switch from ‘stop’ to ‘proceed’ modes.
“Sure enough, Ben pulled out, signaled and started to turn onto the highway. When he did, everyone in the JumboTron tent broke into applause. The judges decided to give Ben a break, and I called my wife back.”
What lies ahead for the Ben Franklin Racing Team, and for robotic cars?
If DARPA decides to hold a fourth Urban Challenge, Lee and Spletzer say they would be open to renewing their collaboration. As for autonomous cars, Lee notes that, in some respects, the future is already here.
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“A lot of new technologies are coming to high-end civilian cars, such as adaptive cruise control, crash-avoidance features and lane-departure warning systems that rely on computer vision or sensors instead of a highway rumble strip.”
Spletzer, meanwhile, is confident engineers can go further. Just as computers have been programmed and trained to beat the world’s grand chessmasters, he says, robotic cars may someday navigate roads more ably than humans can.
“Computers can really do well when you focus them on specific tasks,” he says, citing IBM’s “Deep Blue,” the first machine to win a chess tournament against a human.
“Ultimately, we’d like to make robotic cars that can drive better than humans can. That won’t be easy. The driving environment has many complicated aspects. It’s not limited to an eight-by-eight chessboard.
“It’s going to be some time before cars drive themselves – 25 to 50 years, maybe closer to 50.
“I plan to be around then.”
