Authors: George Kamiya, Kate Palmer and Jacob Teter
The future of self-driving cars remains highly uncertain. But visions of fully autonomous vehicles have captured the public imagination, with academics, technologists, and cultural commentators speculating on what a self-driving future might mean.
Building on our first comprehensive report on Digitalization & Energy, the IEA is setting out to explore the important and intriguing possibilities of emerging mobility technologies and services – defined here as automation, sharing, and electrification. Working at the intersection of energy, transport, and digital technologies, the IEA aims to assess how automation could impact long-term energy and emission trends and to advise on policies that could help to steer technology and business developments toward achieving environmental, energy, and other social goals.
To inform our modelling and policy analysis, we are tapping into expertise in multiple realms, consulting and exchanging ideas with researchers, technologists, legal experts, designers, investors, visionaries, and policy makers. The IEA recently convened a two-day workshop to bring together international experts and decision-makers from across these communities. This commentary summarises the lively debate and discussion at the workshop, and previews some of the key questions we will address in the coming months.
How and when will robots hit the road?
The future of highly automated and connected vehicles is decidedly uncertain; questions remain around technologies, regulations, and public acceptance. Experts predict a range of possible development and deployment pathways.
One possible trajectory continues down the long road of incremental progress. Technologies are first introduced in the luxury vehicle market, and then gradually diffuse down to other segments, bringing greater comfort and convenience, performance, and safety. Blind spot monitors, lane keeping, and collision warning and avoidance follow the route of adaptive cruise control to become standard features in more and more new cars.
Or we could leap directly to fully autonomous vehicles (AVs), deploying them in limited contexts and expanding the range and conditions of their use. Given the major challenge of putting human and robot-driven vehicles on a single road network, many see the best way forward to be designing separate “geofenced” spaces, effectively cordoned off roadways, for self-driving cars.
The most likely early adopters of AVs are commercial applications, particularly where labour costs are high or where automation could enable higher vehicle utilisation (such as trucks, buses, taxis and ride hailing). High-cost automated driving technologies also represent a lower proportional cost on larger, more expensive vehicles like buses and heavy trucks. Testing and trials in a variety of use cases are well underway, with over sixty cities hosting AV tests or committing to doing so in the near future.
Differing consumer preferences and demographics, regulatory regimes, and built environments will likely drive differences in adoption among regions. For instance, the aging population in Japan is a driver of its ambitious plans for AV deployment. High consumer acceptance and a favourable regulatory environment in Singapore could mean they will be among the first to deploy AVs widely. Some of these regional differences are already evident in the differences in how ride-hailing services are used in cities and suburbs and among countries. For instance, short-distance ride-hailing in the U.S. versus long-distance carpooling in Western Europe versus app-based motorcycle taxis in Indonesia. Finland is looking to integrate ride-hailing services into a multimodal Mobility-as-a-Service (MaaS) ecosystem.
Heaven, hell, or something in between
The consequences of automation on global energy demand and emissions are highly uncertain, depending on the combined effect of changes in consumer behaviour, policy intervention, technological progress and vehicle technology. Analyses of a range of scenarios in the U.S. context show a wide range of possible outcomes. For example, under a best-case scenario of improved efficiency through automation and ride-sharing, road transport energy use could halve compared with current levels. Conversely, if efficiency improvements do not materialise and rebound effects from automation result in substantially more travel, energy use could more than double.
In the rosiest of model scenarios, citizen-agents dutifully forgo private car ownership and instead use a mix of driverless shuttle services, shared bikes and e-scooters to connect to high quality rapid transit. On-street parking is eliminated, freeing up space for bikes, pedestrians, commerce, and green space. Trip costs and commute times drop. More universal and affordable mobility enhance equality of opportunity and access to jobs and services.
In the dystopian reading, AVs reduce driver stress and allow for more productive use of travel time, making private car travel more attractive. Living further outside city centres becomes more attractive and property values adjust accordingly, exacerbating sprawl. New demand from non-drivers (such as children and the elderly) contribute to greater overall travel. Costs for taxi services fall dramatically, encouraging a shift from public transit to low-occupancy AVs. Road freight also becomes much cheaper, encouraging more goods shipment. All these factors encourage more road travel activity and energy demand.
Sharing, electrification, and multi-modal integration
So how might we steer these new developments away from a 21st century reboot of car-centric cityscapes, and away from the noise, congestion and tailpipe emissions that are plaguing cities today?
Perhaps by focusing on the destination – a safe and comfortable city with many clean and convenient ways to get around – some design principles can be formulated. Policy and planning principles that focus on how sharing, electrification, and automation contribute to a multi-modal mobility ecosystem can help get us where we want to go.
Sharing of vehicles and rides could be key to making the most of scarce road space and dampening potential rebound effects in travel activity. Pricing signals based on footprint or passenger throughput can incentivise active modes, pooled rides, and transit. On the most heavily trafficked routes, supply-side measures, like converting lanes into dedicated priority bus networks, could help deploy automation sooner.
Electrification could help to reduce the energy use and emissions impacts of AVs. With high utilisation rates, commercial fleets – the most likely early adopters of AVs – will favour powertrains with low operational costs and higher efficiencies such as EVs. Automated driving technologies may be easier to implement in EVs due to the greater number of drive-by-wire components. While the outlook for electrification of AVs seems promising, commercial services will demand greater utilisation and range, requiring larger and more expensive battery packs or more frequent recharging. On-board computers and electronics may draw significant power, reducing the range of an electric AV. Ensuring suitability and synergies between automation and electrification requires a more deliberate design of EV-related policies and charging infrastructure buildout to prepare for an automated and shared future.
Early evidence from several major U.S. cities, including Boston and New York, show that ride-hailing services may be adding to congestion and substituting for public transit. While low-cost autonomous taxis could accelerate this trend and displace public transit, the right policies could instead ensure that they serve as first- and last-mile feeders to transit services and as substitutes to single occupancy vehicles. If cities and countries can compel corporate providers of mobility services to disclose certain key data, urban and transport planners may be able to better target infrastructure investments and services to ensure more efficient and equitable access.
Policies for a sustainable and equitable mobility future
Governments at all levels can play a critical role in enabling emerging mobility technologies and ensuring that they help to solve (rather than exacerbate) existing challenges. Crucially, efforts to limit the use of single-occupancy vehicles must be complemented with policies to encourage and promote sharing, interoperability, and integration across different modes and mobility service providers.
At the national level, regulations should seek to support rather than impede, but also steer AV development, while ensuring safety of road users and pedestrians. National strategy and policy can empower cities to adopt smarter mobility practices across all transport modes. Clear policy intent and implementation at this level can have long-term ripple effects, like shaping more efficient car designs of the future.
Adoption of AVs has the potential to make cities more sustainable, inclusive, prosperous, and resilient. Fair user fees across all modes can encourage more efficient use of our city streets. So far, more than 100 cities and companies have committed to supporting this idea through the Shared Mobility Principles for Liveable Cities. With automation likely to reduce the need for parking, cities will face key decisions on how to repurpose these spaces to ensure safer, more sustainable and productive neighbourhoods and cities.
Dynamic congestion pricing could be a simple and effective policy tool to mitigate some of the negative externalities of AVs, like greater vehicle travel and empty vehicle miles. But congestion pricing has been politically difficult to date, with only a few cities worldwide implementing it effectively. Rising gridlock and new technology options could drive greater public appetite for pricing; otherwise, governments will need to look at developing creative policy packages to achieve similar outcomes.
The impacts of vehicle automation are likely to extend into many facets of the economy, the physical landscape, and our daily lives. In this introductory commentary, we have only touched on some of the critical issues and questions that we aim to explore further in future posts.
*Kate Palmer, former Transport Analyst (Trainee); Jacob Teter, Transport Analyst.