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.

 
 
 
 

What does the Greater Manchester Spatial Plan mean for the region’s housing supply and green belt?

Manchester. Image: Getty.

We’re not even halfway through January and we’ve already seen one of the biggest urban stories of the year – the release of Greater Manchester’s new spatial plan for the city-region. The Greater Manchester Spatial Framework (GMSF) sets an ambitious target to build more than 200,000 homes over the next 18 years.

Despite previous statements indicating greenbelt development was off the table, the plan allows for some moderate easing of greenbelt, combined with denser city centre development. This is sensible, pragmatic and to be welcomed but a question remains: will it be enough to keep Manchester affordable over the long-term?

First, some history on Manchester’s housing strategy: This is not the first iteration of the controversial GMSF. The first draft was released by Greater Manchester’s council leaders back in October 2016 (before Andy Burnham was in post), and aimed to build 227,000 houses by 2037. Originally, it proposed releasing 8.2 per cent of the green belt to provide land for housing. Many campaigners opposed this, and the newly elected mayor, Andy Burnham, sent the plan back to the drawing board in 2017.

The latest draft published this week contains two important changes. First, it releases slightly less greenbelt land than the original plan, 4.1 per cent of the total, but more than Andy Burnham previously indicated he would. Second, while the latest document is still ambitious, it plans for 26,000 fewer homes over the same period than the original.

To build up or to build out?

In many cities, the housing supply challenge is often painted as a battle-ground between building high-density homes in the city centre or encroaching on the green belt. Greater Manchester is fortunate in that it lacks the density of cities such as London – suggesting less of a confrontation between people who what to build up and people who want to build out.

Prioritising building on Greater Manchester’s plentiful high-density city centre brownfield land first is right and will further incentivise investment in public transport to reduce the dependence of the city on cars. It makes the goal in the mayor’s new transport plan of 50 per cent of all journeys in Greater Manchester be made on foot, bikes or public transport by 2040 easier to realise.

However, unlike Greater London’s greenbelt which surrounds the capital, Greater Manchester’s green belt extends deep into the city-region, making development on large amounts of land between already urbanised parts of the city-region more difficult. This limits the options to build more housing in parts of Greater Manchester close to the city centre and transport nodes. The worry is that without medium-term reform to the shape of Manchester’s green belt, it may tighten housing supply in Manchester even more than the green belt already does in places such as London and York. In the future, when looking to undertake moderate development on greenbelt land, the mayor should look to develop in these areas of ‘interior greenbelt’ first.

Greater Manchester’s Green Belt and Local Authority Boundaries, 2019.

Despite the scale of its ambition, the GMSF cannot avoid the sheer size of the green belt forever: it covers 47 per cent of the total metropolitan area). In all likelihood, plans to reduce the size of the green belt by 2 per cent will need to be looked at again once the existing supply of brownfield land runs low – particularly if housing demand over the next 18 years is higher than the GMSF expects, which should be the case if the city region’s economy continues to grow.

An example of a successful political collaboration

The GMSF was a politically pragmatic compromise achieved through the cooperation of the metropolitan councils and the mayoral authority to boost the supply of homes. It happened because Greater Manchester’s mayor has an elected mandate to implement and integrate the GMSF and the new transport plan.

Other cities and the government should learn from this. The other metro mayors currently lacking spatial planning powers, in Tees Valley and the West Midlands, should be gifted Greater Manchester-style planning powers by the government so they too can plan and deliver the housing and transport their city-regions need.

Long-term housing strategies that are both sustainable and achievable need to build both up and out. In the short-term Greater Manchester has achieved this, but in the future, if its economic success is maintained, it will need to be bolder on the green belt than the proposals in the current plan. By 2037 Manchester will not face a trade-off between high-density flats in the city centre or green belt reform – it will need to do both.  If the city region is to avoid the housing problems that bedevil London and other successful cities, policy makers need to be ready for this.

Anthony Breach is an economic analyst at the Centre for Cities, on whose blog this post first appeared.