Blind Man Test Drives Google's Autonomous Car

Velcroman1 writes "'This is some of the best driving I've ever done,' Steve Mahan said the other day. Mahan was behind the wheel of a Toyota Prius tooling the small California town of Morgan Hill in late January, a routine trip to pick up the dry cleaning and drop by the Taco Bell drive-in for a snack. He also happens to be 95 percent blind. Mahan, head of the Santa Clara Valley Blind Center, 'drove' along a specially programmed route thanks to Google's autonomous driving technology. Google announced the self-driving car project in 2010. It relies upon laser range finders, radar sensors, and video cameras to navigate the road ahead, in order to make driving safer, more enjoyable and more efficient — and clearly more accessible. In a Wednesday afternoon post on Google+, the company noted that it has hundreds of thousands of miles of testing under its belt, letting the company feel confident enough in the system to put Mahan behind the wheel."

Comments

Slowing down

[DrYak]

As explained by other, the car *does* slow down, and even eventually halt when exposed to situation it thinks it can't handle.

Also, the car has much lower reaction times. So in some situations, it doen't really need to slow down, it will react immediatly if needed, whereas a human driver will need to slow down to make room for slower refelexes.
(The distance between autonomous vs human-driven cars on the motorway, for example).

Re:Finally the ATM's will be used!

[audacity242]

Drive-up ATMs have braille for two reasons.

1. It's cheaper and more efficient to make all your ATMs the same, so walk-up and drive-through models are often the same.

2. Blind people need to have access to cash, too, and it's not uncommon for them to be driven to an ATM by a sighted driver. Usually they sit in the rear driver's side seat and the driver just pulls a little more forward than normal so the blind person can access the ATM.

Re:human factor

[ematic]

I am currently enrolled in Sebastian Thrun's robot car course CS373. He's the Stanford professor and Google Fellow that headed the group that WON the DARPA Grand Challenge. My understanding, from taking this course, is that their self-driving car is not only able to navavigate to a goal-destination in unfamiliar territory (as in the Grand Challenge, which took place in a desert), but the car is able to identify urban obstacles: crosswalks, stop signs, traffic lights, and can also predict the motion of potential obstacles around it (i.e. cars and pedestrians). The robot car uses controllers with statistical models, so it is able to identify the probability of an obstacle entering the trajectory of the vehicle and respond accordingly -- slowing down like you would in that situation.

Watch some videos of the Stanford car.

Here's the class at Udacity if you're interested.
http://www.udacity.com/overview/Course/cs373