Little Ben, a Toyota Prius fitted with laser and camera sensors by a Penn-Lehigh-Lockheed team of engineers, navigated 58 miles of urban landscape with as much savvy (and as much or more patience) as many human drivers at DARPA’s Grand Challenge for robotic vehicles in California in November.
A thousand spectators held their breath as a Toyota Prius named Little Ben slowed down, activated its right-turn signal and approached a cluttered intersection in the California desert.
At this premier competition of the world’s smartest robotic vehicles, the 2007 DARPA Urban Challenge, the scene awaiting Little Ben looked like an accident waiting to happen. It would have daunted a human driver, requiring steady nerves and navigational skills, and precise peripheral and depth-of-field vision.
Three other driverless cars – three of the 11 finalists in the Challenge – were blocking the route Little Ben needed to take to reach its goal.
Knight Rider, a Subaru Outback fielded by the University of Central Florida team, had arrived first on the spot. But Knight Rider had inexplicably stopped at the intersection on Ben’s right, and the robot’s human-operated DARPA “chase vehicle” had then stopped two car lengths behind the Outback.
Skynet, a Chevy Tahoe entered by Cornell University, had halted behind Knight Rider’s chase vehicle, pulled around to pass, then stopped again – in the wrong lane.
Further complicating matters, Talos, a Land Rover belonging to the MIT team, had also stopped and was facing Little Ben from across the intersection.
Meanwhile, several other chase vehicles idled nearby, their drivers poised to use remote control if Little Ben careened toward one of the stalled robots in an ill-advised attempt to get through.
Little Ben, product of the Ben Franklin Racing Team of Lehigh, the University of Pennsylvania and Lockheed Martin, began executing its right turn. Shouts of “Oh, no!” rose from the crowd watching the race on a Sony JumboTron.
A single question, says John Spletzer, seemed to be going through everyone’s mind: Could a robotic car evaluate this little slice of chaos and respond as deftly as an experienced human driver would?
“There were already three robotic cars at the intersection that didn’t know what to do,” says Spletzer, an assistant professor of computer science and engineering and lead Lehigh member of the Ben Franklin Racing Team. “Adding a fourth robot was a recipe for disaster.”
But Little Ben, with an elaborate system of laser and camera sensors, had already seen what it needed to make its decision. There was daylight separating Knight Rider, Skynet and the chase vehicles. As the Prius eased between its stationary rivals and continued on its way, the JumboTron viewers stood and cheered.
“That was the highlight of the race,” says Spletzer. “Ben didn’t know why the other robots had stopped. But he did what any human driver would try to do and what we all take for granted. He was the only one of the four robots that knew how to react and do the correct thing in that situation.”
Designing and outfitting a car to drive itself, to size up real-life traffic situations, and to determine and execute the optimum responses to those events – that was the goal of the 89 teams that entered the Urban Challenge. DARPA, the Defense Advanced Research Projects Agency, is seeking to develop driverless, ground-combat vehicles for the U.S. military and to meet a congressional mandate that one-third of those vehicles be unmanned by 2015.
A rigorous, yearlong winnowing process narrowed the field of 89 original entrants to 11 for the final event – the Grand Challenge, which was held Nov. 3 on an urban course at the former George Air Force Base in Victorville, Calif.
The 2007 Challenge was the third in three years and the first to require that cars interact with moving as well as stationary objects. (This was the first Challenge for Lehigh; Penn entered a team in the 2005 Urban Challenge but did not make it to the final event.)
To qualify for the 2007 Grand Challenge, cars had to show they could change route plans in the event of a blocked road, stop and wait their turn at a four-way stop sign, merge into moving traffic, navigate a traffic circle, park in a specific parking spot, and obey all California traffic laws.
To have a shot at winning, the finalists had to complete the 58-mile Victorville course in six hours or less. Cars were also judged by how well they drove – as DARPA director Tony Tether said, “the vehicles must perform as well as someone with a California driver’s license.”
The stakes were high, as DARPA was offering $2 million, $1 million and $500,000 to the teams fielding the first-, second- and third-place cars.