Could self-driving cars make crossings or traffic lights redundant?

Decisions made by engineers today will determine how all cars drive. Image: Grendelkhan/Flickr/creative commons.

A lot of discussion and ethical thought about self-driving cars have focused on tragic dilemmas, like hypotheticals in which a car has to decide whether to run over a group of schoolchildren or plunge off a cliff, killing its own occupants. But those sorts of situations are extreme cases.

As the most recent crash – in which a self-driving car killed a pedestrian in Tempe, Arizona – demonstrates, the mundane, everyday situations at every crosswalk, turn and intersection present much harder and broader ethical quandaries.

Ethics of extremes

As a philosopher working with engineers in Stanford’s Center for Automotive Research, I was initially surprised that we spent our lab meetings discussing what I thought was an easy question: How should a self-driving car approach a crosswalk?

My assumption had been that we would think about how a car should decide between the lives of its passengers and the lives of pedestrians. I knew how to think about such dilemmas because these crash scenarios resemble a famous philosophical brainteaser called the “trolley problem”. Imagine a runaway trolley is hurling down the tracks and is bound to hit either a group of five or a single person – would you kill one to save five?

However, many philosophers nowadays doubt that investigating such questions is a fruitful avenue of research. Barbara Fried, a colleague at Stanford, for example, has argued that tragic dilemmas make people believe ethical quandaries mostly arise in extreme and dire circumstances.

In fact, ethical quandaries are ubiquitous. Everyday, mundane situations are surprisingly messy and complex, often in subtle ways. For example: Should your city spend money on a diabetes prevention program or on more social workers? Should your local Department of Public Health hire another inspector for restaurant hygiene standards, or continue a program providing free needles and injection supplies?

These questions are extremely difficult to answer because of uncertainties about the consequences – such as who will be affected and to what degree. The solutions philosophers have proposed for extreme and desperate situations are of little help here.

The problem is similar with self-driving cars. Thinking through extreme situations and crash scenarios cannot help answer questions that arise in mundane situations.

A challenge at crosswalks

One could ask, what can be so hard about mundane traffic situations like approaching a crosswalk, driving through an intersection, or making a left turn? Even if visibility at the crosswalk is limited and it is sometimes hard to tell whether a nearby pedestrian actually wants to cross the street, drivers cope with this every day.

But for self-driving cars, such mundane situations pose a challenge in two ways.

First, there is the fact that what is easy for humans is often hard for machines. Whether it is recognising faces or riding bicycles, we are good at perception and mechanical tasks because evolution built these skills for us. That, however, makes these skills hard to teach or engineer. This is known as “Moravec’s Paradox.”

Second, in a future where all cars are self-driving cars, small changes to driving behavior would make a big difference in the aggregate. Decisions made by engineers today, in other words, will determine not how one car drives but how all cars drive. Algorithms become policy.

Engineers teach computers how to recognise faces and objects using methods of machine learning. They can use machine learning also to help self-driving cars imitate how humans drive. But this isn’t a solution: It doesn’t solve the problem that wide-ranging decisions about safety and mobility are made by engineers.

Furthermore, self-driving cars shouldn’t drive like people. Humans aren’t actually very good drivers. And they drive in ethically troubling ways, deciding whether to yield at crosswalks, based on pedestrians’ age, race and income. For example, researchers in Portland have found that black pedestrians are passed by twice as many cars and had to wait a third longer than white pedestrians before they can cross.

Self-driving cars should drive more safely, and more fairly than people do.


Mundane ethics

The ethical problems deepen when you attend to the conflicts of interest that surface in mundane situations such as crosswalks, turns and intersections.

For example, the design of self-driving cars needs to balance the safety of others – pedestrians or cyclists – with the interests of cars’ passengers. As soon as a car goes faster than walking pace, it is unable to prevent from crashing into a child that might run onto the road in the last second. But walking pace is, of course, way too slow. Everyone needs to get to places. So how should engineers strike the balance between safety and mobility? And what speed is safe enough?

There are other ethical questions that come up as well. Engineers need to make trade-offs between mobility and environmental impacts. When they’re applied across all the cars in the country, small changes in computer-controlled acceleration, cornering and braking can have huge effects on energy use and pollution emissions. How should engineers trade off travel efficiency with environmental impact?

What should the future of traffic be?

Mundane situations pose novel engineering and ethical problems, but they also lead people to question basic assumptions of the traffic system.

For myself, I began to question whether we need places called “crosswalks” at all? After all, self-driving cars can potentially make it safe to cross a road anywhere.

And it is not only crosswalks that become unnecessary. Traffic lights at intersections could be a thing of the past as well. Humans need traffic lights to make sure everyone gets to cross the intersection without crash and chaos. But self-driving cars could coordinate among themselves smoothly.

Traffic control for the future.

The bigger question here is this: given that self-driving cars are better than human drivers, why should the cars be subject to rules that were designed for human fallibility and human errors? And to extend this thought experiment, consider also the more general question: if we, as a society, could design our traffic system from scratch, what would we want it to look like?

Because these hard questions concern everyone in a city or in a society, they require a city or society to agree on answers. That means balancing competing interests in a way that works for everybody – whether people think only about crosswalks or about the traffic system as a whole.

With self-driving cars, societies can redesign their traffic systems. From the crosswalk to overall traffic design – it is mundane situations that raise really hard questions. Extreme situations are a distraction.

The ConversationThe trolley problem does not answer these hard questions.

Johannes Himmelreich, Interdisciplinary Ethics Fellow, Stanford University McCoy Family Center for Ethics in Society.

This article was originally published on The Conversation. Read the original article.

 
 
 
 

To build its emerging “megaregions”, the USA should turn to trains

Under construction: high speed rail in California. Image: Getty.

An extract from “Designing the Megaregion: Meeting Urban Challenges at a New Scale”, out now from Island Press.

A regional transportation system does not become balanced until all its parts are operating effectively. Highways, arterial streets, and local streets are essential, and every megaregion has them, although there is often a big backlog of needed repairs, especially for bridges. Airports for long-distance travel are also recognized as essential, and there are major airports in all the evolving megaregions. Both highways and airports are overloaded at peak periods in the megaregions because of gaps in the rest of the transportation system. Predictions for 2040, when the megaregions will be far more developed than they are today, show that there will be much worse traffic congestion and more airport delays.

What is needed to create a better balance? Passenger rail service that is fast enough to be competitive with driving and with some short airplane trips, commuter rail to major employment centers to take some travelers off highways, and improved local transit systems, especially those that make use of exclusive transit rights-of-way, again to reduce the number of cars on highways and arterial roads. Bicycle paths, sidewalks, and pedestrian paths are also important for reducing car trips in neighborhoods and business centers.

Implementing “fast enough” passenger rail

Long-distance Amtrak trains and commuter rail on conventional, unelectrified tracks are powered by diesel locomotives that can attain a maximum permitted speed of 79 miles per hour, which works out to average operating speeds of 30 to 50 miles per hour. At these speeds, trains are not competitive with driving or even short airline flights.

Trains that can attain 110 miles per hour and can operate at average speeds of 70 miles per hour are fast enough to help balance transportation in megaregions. A trip that takes two to three hours by rail can be competitive with a one-hour flight because of the need to allow an hour and a half or more to get to the boarding area through security, plus the time needed to pick up checked baggage. A two-to-three-hour train trip can be competitive with driving when the distance between destinations is more than two hundred miles – particularly for business travelers who want to sit and work on the train. Of course, the trains also have to be frequent enough, and the traveler’s destination needs to be easily reachable from a train station.

An important factor in reaching higher railway speeds is the recent federal law requiring all trains to have a positive train control safety system, where automated devices manage train separation to avoid collisions, as well as to prevent excessive speeds and deal with track repairs and other temporary situations. What are called high-speed trains in the United States, averaging 70 miles per hour, need gate controls at grade crossings, upgraded tracks, and trains with tilt technology – as on the Acela trains – to permit faster speeds around curves. The Virgin Trains in Florida have diesel-electric locomotives with an electrical generator on board that drives the train but is powered by a diesel engine. 

The faster the train needs to operate, the larger, and heavier, these diesel-electric locomotives have to be, setting an effective speed limit on this technology. The faster speeds possible on the portion of Amtrak’s Acela service north of New Haven, Connecticut, came after the entire line was electrified, as engines that get their power from lines along the track can be smaller and much lighter, and thus go faster. Catenary or third-rail electric trains, like Amtrak’s Acela, can attain speeds of 150 miles per hour, but only a few portions of the tracks now permit this, and average operating speeds are much lower.

Possible alternatives to fast enough trains

True electric high-speed rail can attain maximum operating speeds of 150 to 220 miles per hour, with average operating speeds from 120 to 200 miles per hour. These trains need their own grade-separated track structure, which means new alignments, which are expensive to build. In some places the property-acquisition problem may make a new alignment impossible, unless tunnels are used. True high speeds may be attained by the proposed Texas Central train from Dallas to Houston, and on some portions of the California High-Speed Rail line, should it ever be completed. All of the California line is to be electrified, but some sections will be conventional tracks so that average operating speeds will be lower.


Maglev technology is sometimes mentioned as the ultimate solution to attaining high-speed rail travel. A maglev train travels just above a guideway using magnetic levitation and is propelled by electromagnetic energy. There is an operating maglev train connecting the center of Shanghai to its Pudong International Airport. It can reach a top speed of 267 miles per hour, although its average speed is much lower, as the distance is short and most of the trip is spent getting up to speed or decelerating. The Chinese government has not, so far, used this technology in any other application while building a national system of long-distance, high-speed electric trains. However, there has been a recent announcement of a proposed Chinese maglev train that can attain speeds of 375 miles per hour.

The Hyperloop is a proposed technology that would, in theory, permit passenger trains to travel through large tubes from which all air has been evacuated, and would be even faster than today’s highest-speed trains. Elon Musk has formed a company to develop this virtually frictionless mode of travel, which would have speeds to make it competitive with medium- and even long-distance airplane travel. However, the Hyperloop technology is not yet ready to be applied to real travel situations, and the infrastructure to support it, whether an elevated system or a tunnel, will have all the problems of building conventional high-speed rail on separate guideways, and will also be even more expensive, as a tube has to be constructed as well as the train.

Megaregions need fast enough trains now

Even if new technology someday creates long-distance passenger trains with travel times competitive with airplanes, passenger traffic will still benefit from upgrading rail service to fast-enough trains for many of the trips within a megaregion, now and in the future. States already have the responsibility of financing passenger trains in megaregion rail corridors. Section 209 of the federal Passenger Rail Investment and Improvement Act of 2008 requires states to pay 85 percent of operating costs for all Amtrak routes of less than 750 miles (the legislation exempts the Northeast Corridor) as well as capital maintenance costs of the Amtrak equipment they use, plus support costs for such programs as safety and marketing. 

California’s Caltrans and Capitol Corridor Joint Powers Authority, Connecticut, Indiana, Illinois, Maine’s Northern New England Passenger Rail Authority, Massachusetts, Michigan, Missouri, New York, North Carolina, Oklahoma, Oregon, Pennsylvania, Texas, Vermont, Virginia, Washington, and Wisconsin all have agreements with Amtrak to operate their state corridor services. Amtrak has agreements with the freight railroads that own the tracks, and by law, its operations have priority over freight trains.

At present it appears that upgrading these corridor services to fast-enough trains will also be primarily the responsibility of the states, although they may be able to receive federal grants and loans. The track improvements being financed by the State of Michigan are an example of the way a state can take control over rail service. These tracks will eventually be part of 110-mile-per-hour service between Chicago and Detroit, with commitments from not just Michigan but also Illinois and Indiana. Fast-enough service between Chicago and Detroit could become a major organizer in an evolving megaregion, with stops at key cities along the way, including Kalamazoo, Battle Creek, and Ann Arbor. 

Cooperation among states for faster train service requires formal agreements, in this case, the Midwest Interstate Passenger Rail Compact. The participants are Illinois, Indiana, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, and Wisconsin. There is also an advocacy organization to support the objectives of the compact, the Midwest Interstate Passenger Rail Commission.

States could, in future, reach operating agreements with a private company such as Virgin Trains USA, but the private company would have to negotiate its own agreement with the freight railroads, and also negotiate its own dispatching priorities. Virgin Trains says in its prospectus that it can finance track improvements itself. If the Virgin Trains service in Florida proves to be profitable, it could lead to other private investments in fast-enough trains.

Jonathan Barnett is an emeritus Professor of Practice in City and Regional Planning, and former director of the Urban Design Program, at the University of Pennsylvania. 

This is an extract from “Designing the Megaregion: Meeting Urban Challenges at a New Scale”, published now by Island Press. You can find out more here.