Driverless cars and Mobility as a Service can improve our world – so long as they're properly regulated

Uber-branded driverless cars in Pittsburgh. Image: Getty.

New technology has the potential to improve public transport and increase mobility – but we won’t reap the benefits without the right intervention by government. If new technologies are not implemented properly they will potentially worsen health outcomes, reduce safety, increase congestion and make it harder for the government to achieve their objectives.

Electric vehicles, autonomous vehicles and Mobility as a Service (MaaS) are intrinsically linked issues that will develop together to provide an on-demand autonomous vehicle service (“Uber without drivers”) alongside other public and private transport modes. This will sit alongside the private ownership of electric and autonomous vehicles which continues the conventional model.

We are already seeing journey planning apps evolve from merely providing travel information to linking through to transport service provision. This will evolve to a full MaaS model, where various public and private transport options are presented alongside each other, with ordering and payment for any services used handled by the app. This will include on-demand autonomous vehicle rides.

MaaS has potential to help achieve the health, wellbeing, air pollution and congestion objectives of government, but only through good user interface design where active and sustainable transport are included and prioritised. But if not planned properly, active travel options, which cannot currently earn revenue for the app providers, could be deprioritised in the app user interface (that is, shown with less prominence, not ‘front-and-centre’).

Citymapper, for example, shows Uber alongside other modes and allows booking from within the app. Government will therefore need to influence third party app design to prioritise walking and public transport use in order to achieve their sustainable transport aims. This could be achieved by restrictions on the supply of transit data – for example, requiring journeys that can be completed on foot in under 20 minutes to have walking as the first or most prominent option. It could also be achieved by purchasing prominence in the user interface in much the same way advertising is purchased.


Autonomous vehicles, arranged on a shared basis, could allow more people to stop owning cars. In a positive scenario walking, cycling and public transport would remain the main public transport modes with autonomous vehicles used on rare occasions for specific reasons, such as visiting places with poor public transport or collecting large items.

However, if the pricing of autonomous vehicle rides is set too close to that of public transport fares there is potential for mode shift away from sustainable transport to autonomous vehicles. If the autonomous vehicle ride cost is too low relative to public transport fares this will also encourage low occupancy levels. This negative scenario would cause increased congestion and have worse health outcomes as active travel stages of journeys decrease.

Electric and autonomous electric vehicles are not zero emission: air pollution is generated in their production and when the electricity for their operation is generated. More significantly, they are responsible for roadside particulate matter (PM) pollution from braking systems and tire wear. Therefore, the introduction of electric vehicles and autonomous electric vehicles should not be permitted to facilitate an increase in private or private hire vehicle trips.

Autonomous vehicles are presented as being safer and requiring less road space because they can drive closer together. However, to achieve these benefits all vehicles on the road will need to be autonomous and coordinated. Complete adoption of autonomous vehicles is unlikely any time soon, without an intervention such as banning conventional vehicles.

The benefits of autonomous vehicles will not appear automatically. As with any technology, we need to ensure it is regulated properly – and we don’t lose sight of the healthier society we were hoping to achieve.

Steve Chambers is policy & research coordinator at Living Streets, the charity for every day walking, on whose blog this article first appeared.

 
 
 
 

“Stop worrying about hairdressers”: The UK government has misdiagnosed its productivity problem

We’re going as fast as we can, here. Image: Getty.

Gonna level with you here, I have mixed feelings about this one. On the one hand, I’m a huge fan of schadenfreude, so learning that it the government has messed up in a previously unsuspected way gives me this sort of warm glow inside. On the other hand, the way it’s been screwing up is probably making the country poorer, and exacerbating the north south divide. So, mixed reviews really.

Here’s the story. This week the Centre for Cities (CfC) published a major report on Britain’s productivity problem. For the last 200 years, ever since the industrial revolution, this country has got steadily richer. Since the financial crash, though, that seems to have stopped.

The standard narrative on this has it that the problem lies in the ‘long tail’ of unproductive businesses – that is, those that produce less value per hour. Get those guys humming, the thinking goes, and the productivity problem is sorted.

But the CfC’s new report says that this is exactly wrong. The wrong tail: Why Britain’s ‘long tail’ is not the cause of its productivity problems (excellent pun, there) delves into the data on productivity in different types of businesses and different cities, to demonstrate two big points.

The first is that the long tail is the wrong place to look for productivity gains. Many low productivity businesses are low productivity for a reason:

The ability of manufacturing to automate certain processes, or the development of ever more sophisticated computer software in information and communications have greatly increased the output that a worker produces in these industries. But while a fitness instructor may use a smartphone today in place of a ghetto blaster in 1990, he or she can still only instruct one class at a time. And a waiter or waitress can only serve so many tables. Of course, improvements such as the introduction of handheld electronic devices allow orders to be sent to the kitchen more efficiently, will bring benefits, but this improvements won’t radically increase the output of the waiter.

I’d add to that: there is only so fast that people want to eat. There’s a physical limit on the number of diners any restaurant can actually feed.

At any rate, the result of this is that it’s stupid to expect local service businesses to make step changes in productivity. If we actually want to improve productivity we should focus on those which are exporting services to a bigger market.  There are fewer of these, but the potential gains are much bigger. Here’s a chart:

The y-axis reflects number of businesses at different productivities, shown on the x-axis. So bigger numbers on the left are bad; bigger numbers on the right are good. 

The question of which exporting businesses are struggling to expand productivity is what leads to the report’s second insight:

Specifically it is the underperformance of exporting businesses in cities outside of the Greater South East that causes not only divergences across the country in wages and standards of living, but also hampers national productivity. These cities in particular should be of greatest concern to policy makers attempting to improve UK productivity overall.

In other words, it turned out, again, to the north-south divide that did it. I’m shocked. Are you shocked? This is my shocked face.

The best way to demonstrate this shocking insight is with some more graphs. This first one shows the distribution of productivity in local services business in four different types of place: cities in the south east (GSE) in light green, cities in the rest of the country (RoGB) in dark green, non-urban areas in the south east in purple, non-urban areas everywhere else in turquoise.

The four lines are fairly consistent. The light green, representing south eastern cities has a lower peak on the left, meaning slightly fewer low productivity businesses, but is slightly higher on the right, meaning slightly more high productivity businesses. In other words, local services businesses in the south eastern cities are more productive than those elsewhere – but the gap is pretty narrow. 

Now check out the same graph for exporting businesses:

The differences are much more pronounced. Areas outside those south eastern cities have many more lower productivity businesses (the peaks on the left) and significantly fewer high productivity ones (the lower numbers on the right).

In fact, outside the south east, cities are actually less productive than non-urban areas. This is really not what you’d expect to see, and no a good sign for the health of the economy:

The report also uses a few specific examples to illustrate this point. Compare Reading, one of Britain’s richest medium sized cities, with Hull, one of its poorest:

Or, looking to bigger cities, here’s Bristol and Sheffield:

In both cases, the poorer northern cities are clearly lacking in high-value exporting businesses. This is a problem because these don’t just provide well-paying jobs now: they’re also the ones that have the potential to make productivity gains that can lead to even better jobs. The report concludes:

This is a major cause for concern for the national economy – the underperformance of these cities goes a long way to explain both why the rest of Britain lags behind the Greater South East and why it performs poorly on a

European level. To illustrate the impact, if all cities were as productive as those in the Greater South East, the British economy would be 15 per cent more productive and £225bn larger. This is equivalent to Britain being home to four extra city economies the size of Birmingham.

In other words, the lesson here is: stop worrying about the productivity of hairdressers. Start worrying about the productivity of Hull.


You can read the Centre for Cities’ full report here.

Jonn Elledge is the editor of CityMetric. He is on Twitter as @jonnelledge and on Facebook as JonnElledgeWrites

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