While the driverless future has been touted as way for humanity to combat roadway accidents and diminish energy expenditure and greenhouse gas emissions, a new study from University of Leeds, University of Washington, and Oak Ridge National Laboratory claims the actual impact may be both positive and negative due to how it will change humanity’s relationship with vehicles.
“There is no doubt that vehicle automation offers several efficiency benefits, but if you can work, relax and even hold a meeting in your car that changes how you use it,” said the study’s lead author Zia Wadud, of the Univ. of Leeds, in a prepared statement. “That, in turn, may change the transport equation and the energy and environmental impact of road transport.”
Among the possible benefits, the researchers report that computer-directed driving styles may reduce energy usage up to 20 percent, traffic jams may be reduced up to 4 percent, and autonomous vehicles driving close to one another (known as platooning) can create aerodynamic savings up to 25 percent.
“There is a lot of hype around self-driving cars, much of it somewhat utopian in nature. But there are likely to be positives and negatives,” said co-author Don MacKenzie, of Univ. of Washington, in a prepared statement. “By taking a clear-eyed view, we can design and implement policies to maximize the benefits and minimalize the downsides of automated vehicles.”
The study estimated that there may be a 60 percent increase in car energy consumption due to automated vehicles. This may occur due to people opting to use cars, whereas before they may have utilized trains or planes. Additionally, people with limited road access, such as the elderly or disabled, will increase road energy usage up to 10 percent for personal travel.
“Vehicle automation presents a paradox: it may encourage people to travel much more, but at the same time it makes it practical to implement tools such as road pricing that can offset those effects,” said MacKenzie. “Ultimately, however, it’s up to the government to set appropriate policies to manage these impacts.”
The research, which was published in Transportation Research Part A, used analysis of self-driving technology and data from automobile usage, vehicle running costs, and other datasets to model energy demands for US roads by 2050.
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