If you had a utopia where every vehicle was autonomous tomorrow it would be a relatively easy sell. But we don’t, the transition needs to account for societal and regulatory perspectives, not just the technology.
Autonomous vehicles aren’t going to become ubiquitous overnight, but cars are increasingly connected and driver assist features are ever more sophisticated. Two decades ago only top of the range cars featured ABS braking, now it is considered essential. Lane control and self-parking are now available from mass market car manufacturers across their entire range.
In fact, according to the Society of Motor Manufacturers & Traders, more than half of new cars sold in the UK now have elements of autonomous control such as collision warning and autonomous emergency braking. We can expect more connectivity and more autonomy, but it is still a big step to fully autonomous urban driving. The transition needs to account for societal and regulatory perspectives, not just the technology. And it is arguably the societal issues where the biggest mismatch may arise.
We need to determine as a society how we want to use the advent of intelligent mobility to shape a better outcome for all of us, rather than for the individual or for the manufacturer. Then we need to understand how we may achieve that. To enable us to do so we will need more fundamental insights into the acceptability of new technology to the population, linked to the changing attitude of, say, millennials to vehicle ownership and use.
Red herrings, white elephants – how do you avoid them?
The emergence of mobility as a service and autonomous vehicles is going to impact not just how people and goods move around, but on the aesthetic and functional design of towns and cities. Planners and modellers need to spot trends, explore whether they are long term and significant, and help clients manage uncertainty.
This approach is quite novel within transport planning. The UK Department for Transport has developed five scenarios for traffic forecasting which consider macroeconomic factors such as GDP, demographics, fuel prices and the correlation between driver behaviours and income. Transport for London has its own set of future scenarios and the government’s National Infrastructure Commission is developing yet another set against which to test infrastructure needs and returns on investment.
Scenarios are very helpful, but there’s a sting in the tail: decision-makers and politicians are not well-equipped to deal with a range of options – they like a single answer.
Planners can ideally help decision-makers by determining which options perform well (but not necessarily best) in all, or a wide range of, scenarios. You might call this ‘no regrets planning’. Rather than finding the optimum option under a single scenario, it spreads and mitigates risk if that scenario doesn’t develop as expected. It is a way of avoiding white elephants.
For local authorities these are key issues. They are having to assess now what the changes in mobility will mean for the streetscape in 10 or 15 years’ time and consider the impact on traditional revenue sources such as parking. Will their streets be overrun by self-driving taxis and will existing assets be fit for purpose? And, of course, who is going to pay for changes and how?
They’re issues were a critical friend, able to bring greater depth and breadth of knowledge, can make all the difference for local authorities – assessing the likely impacts of new technologies on their assets and guiding them towards sound decisions.