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Autonomous vehicles to increase road use

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Autonomous driving
Autonomous driving

Impact of technology could be complicated by how it changes our relationship with our cars, finds research

Autonomous vehicles could increase car use, reducing or even eliminating promised energy savings and environmental benefits, a study has warned.

Research from scientists from the University of Leeds, University of Washington and Oak Ridge National Laboratory, in the journal Transportation Research Part A, says the impact of the technology could be complicated by how it changes our relationship with our cars.

The study uses analysis of self-driving technology combined with data on car and truck use, driver licenses, and vehicle running costs to model the impact on energy demand of various levels of automation on US roads by 2050.

It identifies several efficiency benefits of self-driving cars and predicts ranges of likely energy impacts, depending on the extent of adoption of the technology and other factors:

•          More efficient computer-directed driving styles (0-20% reduction in energy use)

•          Improved traffic flow because of coordination between vehicles (0-4% reduction)

•          "Platooning" (4-25% reduction)

•          Reduced crash risks mean that cars can be lighter (5-23% reduction)

•          Less emphasis on high performance (5-23% reduction).

However, the study predicts that the very attractiveness of self-driving technology could reduce or even outweigh the efficiency gains. It estimates a 5-60% increase in car energy consumption due to people using to use highly automated cars in situations where they would have previously taken an alternative mode of transportation.

Lead author Dr Zia Wadud, associate professor in the University of Leeds' Faculty of Engineering and a research group leader in the University's Institute for Transport Studies, said: "When you make a decision about transport, you don't just think about the out-of-pocket costs of the train ticket or the car's petrol; you also take into account non-financial costs.

"Car owners might choose to travel by train to relatively distant business meetings because the train allows them to work and relax. The need to drive is part of the cost of choosing the car, just as standing on a cold platform is part of the cost of the train. If you can relax in your car as it safely drives itself to a meeting in another city that changes the whole equation."

The study also predicts that people who currently find it difficult or impossible to drive will have increased access to road transport with the advent of the new systems, resulting in an estimated 2-10% increase in road energy use for personal travel.

Possible higher speed limits because of the improved safety of autonomous cars (7-22%) and demand for heavy extra equipment in driverless cars such as TV screens and computers (0-11%) might also tend to reduce efficiency savings.

A major uncertainty is the effect of autonomous driving technology on car sharing. The technology could allow vehicles to move independently between different users and therefore not only increase sharing but possibly also make it easier for users to match trip types to car types. Instead of using one car for all journeys, users might be able to use a shared, smaller car for a commute and a larger one for family leisure trips, for example. The authors say these factors could reduce energy consumption by 21-45%.

The authors suggest that policymakers could focus less on accelerating the introduction of complete automation and more on promoting aspects of automation with positive environmental outcomes. For instance, regulators could encourage standardisation of car networking protocols to allow vehicles to communicate with each other on the road and therefore deliver benefits such as "platooning".

The researchers warn that, if a high level of automation becomes the norm, it may be necessary to financially intervene in transport decisions. For example, self-driving cars' navigation and communication systems could be used as a basis for road pricing schemes to control congestion and reduce overall travel demand.

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