From TFA:

"It looks like a palace for Jabba the Hutt."

Does that mean Chicago is a wretched hive of scum and villainy?

Here's the levels. Most high-functioning systems on the market, like the Tesla version, are in the Level 1-2 range.

U.S. Department of Transportation Releases Policy on Automated Vehicle Development

It is also quite straightforward to make your app VoiceOver friendly. The tricky part is managing some of the VoiceOver gestures. Aside from the equivalent of alt tags on images, the most important part is getting the step forward/backward and continuous scroll gestures working right in your app. Turn on VoiceOver, swipe down with two fingers and see what happens. Then swipe one finger left or right. If you've done your job right, the cursor will move in the order you expect. Scrolling on lists that go below the fold are also subtle, yet important.

This actually isn't that big of a leap from a technical difficulty level. A pair of Carnegie Mellon researchers drove across the country in 1995 using a forward camera based system. 98.2% of the trip was autonomous. The non-autonomous parts of the NHAA drive are the same which would be needed under this approach.

ITNAmerica has already sorted this out. It is possible to load your parent's ride account with credits from cash or your own driving contributions. For example, you can drive people around your area and the credits are used by your parents who live halfway across the country. If you fall short one month, just fill up the credits with cash.

In many US States, the local Departments of Transportation want nothing to do with enforcement actions. They will let the police/town/etc install red light cameras, but they don't want to be involved beyond that. In fact many red light cameras are operated by private companies under contract with local municipalities.

Here's an example of why DOTs don't want to be involved in enforcement. A while back some politician in New Jersey, not part of the local DOT, floated the idea of using EZPass toll data to automatically issue speeding tickets. This was almost certainly a money grab. Massive amounts of drivers started asking how to get rid of their EZPass accounts and turn in their transponders. DOT knew lower market penetration would negatively impact congestion at toll booths. They, thankfully, squashed the idea quickly.

From my perspective in the trenches, the reduction is not as big as most people might think for CS and the sciences. If you worked like crazy while building your credentials, either for tenure or to a senior position in a non-tenure research track, you can't really slack off too much. You still need to bring in the cash to cover your team, grad student tuitions, and your own salary, which are now more expensive too. This means just as much research effort and proposal writing. This is exacerbated when research funding is cut at a large scale (sequestration). The reduction really comes from i) having established robust lab practices, methods, and management skills and ii) improved proposal writing skills combined with a track record. Junior faculty expend a lot of time finding and developing the right models, processes, and skills.

Another problem is that you spend your early career developing and reinforcing workaholic habits. It is very hard to step away from work, even for a regular weekend. Unlike most high intensity jobs, the flexible time is great for scheduling around family so they actually see you. You can insulate them from the worst of it.

Um, no. It has been in living rooms for over a decade. TiVo runs linux. Now get off my lawn!

V2V is peer-to-peer and really focused on reducing reaction times. It allows the car ahead to instantly tell the car behind it is braking. This means less latency for corrective action. This also helps non-autonomous cars since V2V equipped vehicles could, theoretically, suck up some of the shockwaves present in current highway driving.

The main advance is the progression towards real-world sensor selection and packaging. If you look at all the cars which completed the Urban Challenge, and the Google cars, you'll notice the spinning Velodyne laser sensor on the roof. It is a great sensor and makes autonomous driving much easier. Unfortunately, that sucker costs more than most luxury cars and would never be deployed the real-world since nobody wants a spinning can on their roof.

Carnegie Mellon would not have won the Urban Challenge without that sensor or the others littered all over the exterior of the car. The major advance for this new Carnegie Mellon car is comparable performance with cheaper sensors fully packaged within the car. This is a big deal since (a) economics limits which sensors you can buy and (b) the car body and shape limit the size and location of sensors. These obviously limit your overall sensing capability.

The new car also has better computer packaging. Most autonomous vehicles have no trunk space and frequently have no back seat room. For a historical perspective, Carnegie Mellon's Navlab 1, which found a spot and parallel parked autonomously in 1992, had racks of computers and an extra air conditioning system to handle the heat load. Urban Challenge vehicles also had racks in their trunk areas. The Cadillac SRX team was able to cram all the computational gear out of sight. This is really Moore's Law, etc but it is still a respectable achievement.

Actually, Google built the All-Star team from the Urban Grand Challenge. The Google group has lots of CMU (winner) and Stanford (2nd place) team members, including the technical lead from CMU.

It's not that simple. A lot of groundbreaking work is the result of side project within a larger research effort. Google is a good example of this. The ideas and approach had their origins in the NSF project Larry and Sergey were working on. While the SDLP project probably had an impact on digital libraries, the stated goal of the work, the larger impact was the creation of a technology behemoth with thousands of US jobs and a major influence on the digital economy. Using your model, would Google have happened? Probably not.

Also, the way you posed the question is interesting for other reasons. Whether a person changes their behavior is often based on far more than just basic science and technology advancements. Issues like federal policy (political science) can have a huge impact. For example, I'm working on technology research related to the aging of the population. This is a very real societal need and it is easy to justify the work from a financial perspective (take a look at nursing home and caregiver costs). However, many health and independence technologies are intertwined with privacy, whether Medicare will pay, and other non-technical issues. We rely on the insights of our colleagues doing research in the social sciences to help us understand the interplay between functionality and barriers to acceptance and commercialization. Without their research, we'd probably make very expensive paperweights.

Exactly. If the researchers didn't account for traveling behavior (i.e., check to see if the person was posting from their typical geographical region) then the results would be heavily skewed by vacations. Hawaii, Maine, Nevada, Utah and Vermont are all popular vacation locations.

It won't stop them, but it gives you the ability to get the plagiarized material pulled. Remember, plagiarism is antithetical to academia. Mashups are fine, as long as you give appropriate credit.