Implications of autonomous ride-sharing

Managing the transition to a self-driving future (Part 2)

ITF. Shared Mobility — Innovation for Liveable Cities (link)

This is Part 2 of our three-part series looking at the impact of autonomous and ride-share vehicles on cities and communities. Before you read on, we recommend that you read Part 1 which provides some of the background information used to formulate the policy implications we discuss below.


Policy Implications

Most of the policy discussion revolves around removing the existing legislative, regulatory and legal impediments to autonomous vehicles on public roads and to identify further regulation to address safety issues and community expectations. While this enabling legislation is required, a more robust policy discussion is needed about the impact of self-driving cars on the transport network, social-economic impacts on the community, changes to the way cities are planned and function — the practical realities of self-driving impacts on each and every one of us.

While this enabling legislation is required, a more robust policy discussion is needed about the impact of self-driving cars on the transport network…

In this light, most of the policy debate at the moment has not been based on empirical data, there is very little primary research that has been undertaken on these impacts. The study undertaken by the ITF provided empirical data, which could indicate what may happen in a city with self-driving cars, both in transition and at full adoption. This data provides a good starting point for a discussion of what we could expect to occur and the policy development that will be needed to ensure informed decisions are made.

Where should we focus the policy debate?

Below are some areas (in no particular order) that should be considered for more policy development work, based on the empirical data from the self-driving vehicle model put together for Lisbon.

1. Enabling Self-driving Regulation. The focus of existing reviews into autonomous vehicle regulation and policy is entered on enabling legislation that will create a framework for approving a wide range of autonomous vehicles. Existing regulation only allows their use with specific case-by-case relaxation of existing regulation — usually to test the system in a controlled environment. In Australia, regulation of the transport system is managed at all level’s of government. Significant cooperation will be required to ensure harmonised regulations are developed across Australia, there is little to gain from differing regulations on each side of state borders.

2. During the Transition to Self-driving Vehicles. The impact of autonomous vehicles will be especially dependent on the market structure and how that changes over time. The modelling undertaken for Lisbon highlights that transition analysis will be key to understanding the introduction of the autonomous systems, various business models, interaction with mass transit systems and changing consumer choice behaviours. Over time self-driving and ride-sharing systems will decreases in cost becoming more competitive with existing services. As these costs decrease, the community will use these services more, increasing the overall network travel — this is consistent with a lower generalised cost of travel.

Uber. Left: SF without uberPOOL experiences traffic congestion downtown. Right: POOL moves the same number of people in a smarter way. (link)

By virtue, ride-pooling is able to reduce traffic volumes through higher vehicle utilisation. In practical terms, this reduces traffic volumes, especially at key nodes and thoroughfare. Recent data from Uber highlights that UberPool significantly decreases congestion in downtown San Fransisco (see above). Ride-pooling has the potential to counterbalance the forecast increase in traffic, resulting in fewer vehicle kilometres as they require fewer trips to move the same number of people. The impact on the community will largely depend on how governments approach the issue of transition , their subsequent policy response and the various market forces and competing business models.

3. Leaving Behind Stranded Assets. The decreasing cost curve of new autonomous vehicle technologies and business models will change the way that different types of infrastructure will be utilised. The future is unknowable, but what is known is that, as consumer preferences changes there will be stranded or underutilised assets; These are likely to include roads, intelligent transport systems (ITS) and/or public transit. The government has traditionally been the main source of ownership and funding of these assets. The high-level of public sector involvement provides two differing outcomes, either government will act in its own interest and protect its existing investment or use its balance sheet as a means to absorb any short-term financial costs while prosecuting market reform to maximise societal welfare.

4. Greater Environmental Impacts. The impact of the transport sector is almost wholly dependent on the total distance of travel taken, largely because of the dependence on fossil fuels. The Australian Department of Environment estimates that the transport sector contributed 17% of Australia’s emissions in 2013–14. Both Industry and government expect that autonomous vehicles will lead to increases in the distance travelled by vehicles, which will further exacerbate the forecast 25% increase in transport sector emissions to 2030. Electric vehicles provide one possible mitigation to increased emissions, but only if energy generators move away from high-intensity carbon emissions. The changes to the transport sector will be larger than previously estimated, so more government policy making will be required to manage the transition in the transport sector, along with requirements under ratified national and global environmental agreements.

5. New Approaches to Transport Planning. Like most infrastructure, the current approach to transport planning is to ensure that there is sufficient capacity to take people where they want to go when they want to go. However, the tools that are used today don’t allow us to easily assess the shift from private car and public transit, to what may happen in the future. Companies like Uber are in a great position to know where people live, where they want to go to and when they want to go — where people largely have not allowed the government to collect this information in the past.

ITF. Visualisation of shared self-driving car simulation for Lisbon. (link)

Planners need access to more detailed information and tools (i.e. Agent-based Models, Land Use Transport Integration Models) to really understand complex interactions in the same way that private companies are now able to do. The community has been willing to trade away access to some of their data so they can access things like Uber, perhaps it is time the government started a conversation with the public about what they expect from a modern transport system and how they can help make it a reality.

6. Active Transport. It is a well-known fact that those people who use public transport have to walk more, for some it is a daily frustration, but it is also a much-lauded health intervention and an important benefit to society, which results in more healthy people and fewer visits to the hospital. As more and more people choose to use point-to-point transit, we need to ask ourselves, how should we incentivise people to be more active?

7. Changes to how the city works. Marchetti’s constant is little known outside of professionals who plan cities. Cesare Marchetti observed that although cities, urban form and transport modes change throughout history, the length of time people are willing to travel from home to their workplace stays relatively constant. If autonomous vehicles reduce travel time, will we travel less or just live further from the city? Recent analysis by David Metz at the UK Department of Transport concluded that recent infrastructure projects, rather than saving time, have just allowed people to travel longer distances[1]. Autonomous vehicles are likely to substantially affect where people want to live, and possibly where they work.

8. New Business Models. Many pundits are already predicting that autonomous and ride-sharing vehicles will fundamentally change the current business models of car companies, they will also really impact government as well. Recently, in 2015–16, the City of Melbourne in Australia received over AUD$100m in revenue for parking fines and fees alone. Governments and the private sector alike will need to invest time to understand how they can continue to remain financially and economically balances into the future, and adjust accordingly.

9. Industry Structure. I want to talk to you about Monopoly, no not the game but rather the potential for new entrants to monopolise new industries. While I totally support innovation and market players gaining market share, the community just needs to be aware of the risks that the internet plays in establishing oligopolies and monopolies. The internet makes it so much easier than in other industries to economies of scale, barriers to entry, network effects and technological barriers (through patents). Equally important is making sure that market participants don’t become monopsony suppliers. There is no evidence that monopoly suppliers are using their market power anti-competitively, but history shows that sometimes what starts off as innovation ends up sub-optimal for society.

10. Should Data be shared with Government? This is a very tricky problem, how to strike the right balance between private entities and the public good. There are too many nuances to discuss here, but policymakers need to balance a number of things, including:

  • What information do we need to ensure a level playing field and ensure that monopolies or market power aren’t abused
  • Are there benefits for mandating shared data between services providers, so they don’t need to provide parallel service offerings, which will double (or more) the number of vehicles on the road
  • Ensure that community expectations around privacy and security are met, both for data on providers servers and if that data is shared with government

These are just some of the complex policy issues requiring attention before the benefits of self-driving cars can be fully realised. We are entering the fourth great transport revolution and need to plan for the future before it is too late and we’re playing catch-up.

What’s next?

Part 3 — How soon is the revolution — when can we expect to ride in autonomous vehicles?


Footnotes

  1. The point is also made in a 2009 paper by Yves Crozet: ‘Economic Development and the Role of Travel time: The key concept of accessibility’ published in Commissioned Papers for the 4th International Future Urban Transport Conference of the Volvo Research and Educational Foundations, Gothenburg, Sweden, April 19–21, 2009.

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Chris is currently challenging the way cities are planned by understanding the link between transport accessibility and how cities evolve. Feel free to reach out to him on Twitter or Linkedin if you are interested in talking about the boundaries between society, technology and the built environment.