David Levinson is an engineering professor at the University of Minnesota who attended this month’s conference. He explained to me that the key for autonomous vehicles is that they can react far more quickly and precisely to their surroundings.
“We could go down from 33,000 to a few hundred deaths per year by car,” Levinson told me. “In mixed environments, speeds can be regulated so that cars go much slower. People might be more wiling to travel at slower speeds in neighborhoods when they don’t have to stop at stupid traffic lights. And we won’t have the option to be more aggressive, like we can right now.”
Unlike many harried urban drivers today, robot cars would always stop for a child crossing the street or give plenty of room to a bicyclist. Saving tens of thousands of lives, while making cities safe again, is an inspiring vision.
Impeccably driven robot cars would also greatly expand our road capacity. Compared to mistake-prone humans, over twice as many robot cars might fit onto a lane of highway, which could make traffic jams (and freeway expansions) obsolete.
At the same time, the ability to daydream while driving is appealing to stressed-out commuters. As Levinson explained to me, robot cars might lead to even more driving than we see today.
“Autonomous cars will be faster on average, and as a result they’ll increase the distance people are willing to travel, “ Levinson told me. “They will also reduce the cognitive burden of drivers, and so people will be willing to spend more time driving. Both things would lead to further suburbanization.”
Even so, changes like slower growth in the amount of driving are poised to reshape the region’s transportation needs, said David Levinson, a U of M professor and chair in transportation engineering for the university’s Department of Civil Engineering. Data from countries with older populations than the United States’ suggest the country is likely to see demand slow further as baby boomers age.
“We need to be thinking about not that we need to be adding capacity but maintaining what we have and what we need [and] thinking about strategic reductions in our capacity,” Levinson said. “That’s not a conversation that’s going on anywhere.”
The downtown should become denser as driverless cars become more widespread, said David Levinson, a University of Minnesota professor and chair in transportation engineering for the university’s Department of Civil Engineering.
But residents outside the downtown will also choose to live farther away from the core because driverless technology will make their commutes more efficient and they’ll be able to do something besides driving during the commute.
“We know that the more people have to think about their trips, the more they overestimate the time they are actually taking,” Levinson said. “So if they don’t think about their trips, they’re going to tend to underestimate how much time they’re taking and they’ll be more willing to be traveling.”
Karlyn Stanley, RAND Corporation senior researcher, who will discuss the opportunities and challenges that lay ahead for autonomous and automated vehicles and the legal, regulatory, and policy frameworks responsible for their oversight and governance.
Bryant Walker Smith, University of South Carolina law professor, who will address the legal, ethical, and policy issues surrounding automated driving.
A panel discussion led by Senator Scott Dibble, Santa Clara University law professor Dorothy Glancy, and University of Minnesota professor David Levinson. The panel will explore the impacts and implications of autonomous vehicles for society.
Minnesota Secretary of State Mark Ritchie, who will close the conference by addressing opportunities and visions for Minnesota.
Breakout sessions exploring industry and design perspectives, civil liability and insurance, criminal liability, regional and city planning perspectives, and ethics, equity, and access.
For a detailed event program and speaker information, please visit the event website.
With frequent press attention on traffic congestion and “gridlock,” it may be surprising that work trip travel times in US cities are better than those of high income competitors in other nations …. Indeed, the University of Minnesota’s David Levinson, found that the typical employee can reach two-thirds of jobs in major US metropolitan areas within 30 minutes.
Census Bureau data indicates that the average work trip travel time in US cities of more than 5 million population was approximately 29 minutes each way. Western European cities of more than 5 million population have an average travel time of 32 minutes. Toronto, Canada’s only city of this size, has a travel time of 33 minutes. East Asian cities with more than 5 million residents (Tokyo, Osaka-Kobe-Kyoto, Nagoya, Seoul, Hong Kong and Singapore) have far longer average travel times — at 42 minutes. Australia’s two largest cities (Sydney and Melbourne), which are yet to reach 5 million, have an average travel times of 35 minutes.
Time is important, of course. What you can do with that time (the quality of the experience) also matters. If you can work while traveling, the value of saving time is less than if you must focus on the driving task. This is one reason why autonomous vehicles may be such a game-changer. It may also explain in part the premium people are willing to pay for high quality transit and intercity rail service.
Google has been secretly working on a car. We knew that they were working on autonomous vehicles, but they have also been redesigning the car for an autonomous world and came up with a pod car. The design will be familiar with those who have been following Personal Rapid Transit, though an important difference is that it is in principle trackless (or rather the entire road network has been sufficiently mapped in detail so the whole world is track, rather than bespoke track).
The promotional video is below:
The newest vehicle is designed for slow speed (25 MPH) on campuses, and is especially light. The low mass is important as it saves energy but also causes less damage when it accidentally hits something or someone. Combining the low mass with the lower likelihood of a crash at low speed will magnify its safety advantage for non-occupants in this environment compared with faster heavier vehicles (which privilege the safety of the vehicle occupants).
While I had been assuming the first market for autonomous or semi-autonomous vehicles would be the relatively controlled environment of the freeway, the relatively controlled environment of low-speed places makes sense as well. These are two different types of vehicles (high speed freeway vs. low speed neighborhood), and though they may converge, there is no guarantee they will, and perhaps today’s converged multi-purpose vehicle will instead diverge.
There has long been discussion of Neighborhood Electric Vehicles, ranging from golf carts to something larger, which are in use in some communities, particularly southwestern US retirement complexes. In Sun City, Arizona, for instance, people use the golf cart not just for golfing, but for going to the clubhouse or local stores.
They can do this because local streets are set with low speed limits, and there are special paths where they are not.
How many places already fit this bill:
Neighborhoods in master planned communities
Note that many of these places have gotten a bad rap from the current flavor of urban planning which decries non-gridded networks. However keep in mind that non-grids have the advantage of discourage through traffic. Perhaps roads are too wide or too fast in these places, but that is much easier to fix through traffic calming than a too connected network.
We will not only be able to deal with such ideal places. We will also need to do retrofits.
How many places could fit this bill:
Cities designed before the automobile, where the grid can be retrofitted to disallow high-speed traffic
Anywhere there is space to retrofit a slow network in parallel with the existing fast network
So will people buy such cars with limited speed? Many will as a second or third vehicle, as they already do with golf carts. The arguments are very similar to those about electric vehicles.
The opportunity arises with Cloud Commuting, when such cars, as they are autonomous, come to you. They will be dispatched when they are practical for the trip at hand, which may either be a short distance within a `slow space place’, or can travel along a `slow path’ between nearby places.
This slow path is of course faster than bike paths and sidewalks, but slower than Principal Arterials and freeways.
Retrofitting cities for transportation has a long history, cities and transportation co-evolve. We redesigned our cities, which had originally emerged with human and animal powered transportation, first for streetcars, and then for the automobile, and in some larger cities for subways. We have also redesigned our taller buildings for escalators and elevators.
We have already differentiated speed on links, and setting speed limits is one of the key jobs of the traffic engineer in ensuring safety. This is not only on the link in question, but important for other links as well. Travelers shifted away from freeways and onto less safe rural roads when the speed limit was set to 55 MPH in the 1970s, and back when it was raised in the 1980s, improving overall safety, though not necessarily safety on the freeways themselves (See Lave and Elias 1994).
As part of an expansive budget bill signed into law last week, state lawmakers nudged transportation officials to boost the speed limit to 60 miles per hour on lane miles where it can “reasonably and safely” be done. By 2019, traffic engineers must examine every mile of road with a 55 mph limit and determine if it is prudent to go higher.
It’s an enormous undertaking. There are 6,771 miles on two-lane/two-way state highways now covered by a 55 mph limit. Officials figure they’ll get through about one-fifth per year, starting as soon as next month. They will analyze each stretch’s crash history, design, lane width, sight lines and ditch slope.
“The fact we’re studying the roads does not mean you can jump to the conclusion that all roads will be raised to 60 miles per hour,” said Peter Buchen, assistant state traffic engineer at the Minnesota Department of Transportation.
But the agency has been moving in that direction. In 2005, the department bumped the limit to 60 mph on 791 miles of two-lane highways and added another 750 miles last year. Buchen said those were prime candidates — straight, wide-open stretches with clear sight lines and low incidence of crashes. He said limits on hillier, curvier highways probably won’t budge.
So I will posit several Axioms about transportation
Axiom 1: Some roads should be fast – The aim of transportation is connecting people with destinations. They can connect with more destinations if they can do so in less time. Ceteris paribus, faster roads will take less time.
Axiom 2: Some roads should be slow – Some roads serve neighborhoods and have traffic that is not just motor vehicles. Ceteris paribus, slower roads are more likely to ensure safety, a high quality of life, and increased interaction within the neighborhood. Without loss of generality, let’s call these roads streets.
Axiom 3: Fast roads attract traffic from slow roads – In general, people prefer to spend less time traveling, and will spend less time on faster roads. These roads will attract more people. There will be net reductions in traffic on streets that are made slower and net increases in traffic on roads that are made faster.
We thus should redesign our road hierarchy with these axioms and the possibility of slow vehicles becoming mainstream, developing a slow network so that these neighborhood vehicles cannot not only travel within neighborhoods or on campuses, but between them.
One of the classic questions in Artificial Intelligence is when will a computer beat a master human in some game (Chess, Jeopardy). Well, the next test is not a simple board game, but something involving control of a physical device at high speeds. So the next test is when will a self-driving autonomous vehicle without a human in the drivers seat (at all or via remote control) beat the humans in a NASCAR, Indy, or Formula One car race?
My best guess is 2025, though I am fairly confident before 2029 (the bicentennial of the Rainhill Trials and a year before the bicentennial of the Tom Thumb on the B&O), but this is without a lot of basis. We don’t have enough data points of cars vs. humans in a race. The automakers are not going to be too keen on this, since it sends the wrong message perhaps, and their is a great deal of risk, so it will be after robo-cars are already somewhat widely deployed.
Obviously if you took the safeties off, and didn’t worry about crashing, a robo-car could drive faster than humans now on an empty track. But with other drivers, this would affect the computer, how would/should it respond?