Some Cities Are Better Suited for Self-Driving Cars Than Others, New Study Finds

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Think about places most synonymous with self-driving vehicles, and you’re bound to call to mind testing hotbeds like Silicon Valley and Detroit.

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But those aren’t necessarily the places where autonomous cars will bring the biggest benefit. A new study from INRIX, a leading provider of traffic analytics, has ranked U.S. cities based on a number of factors to figure out where their deployment in shared fleets could replace the greatest proportion of travel. The top-ranked for autonomous cars include New Orleans, Albuquerque, and Tucson, Arizona—none of which have seen much in the way of whirring sensors affixed atop vehicles. Among other cities in the top ten are Omaha, Nebraska; El Paso, Texas; and Fresno, California. In other words, none of the usual suspects in the realm of cities vying to brand themselves as advanced-transportation hubs.

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While some cities at the forefront of Smart Cities development may already have plans for using autonomous vehicles, the majority do not. This report could spur urban planners and city governments to take a closer look at how the fast-approaching deployment of these vehicles could augment or alter travel on their roads.

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The findings could also prod the private sector to look beyond their current testing centers and figure out where they may want to conduct future pilot projects and early deployment efforts.

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Researchers analyzed data taken from connected cars, parking information, and U.S. Census demographic data. INRIX and partner StreetLight Data developed a scoring system that examined journeys that began and ended within a 25-mile radius of each downtown and compared that against the overall number of trips in the region to establish what percentage of trips were devoted to intracity travel.

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Then researchers looked at the percentage of intracity trips that were 10 miles or less, and they combined both percentages to determine a score for each city.

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Vehicle, parking, and demographic data are weighted equally in INRIX’s calculations. But if a city is interested in solving a particular problem—say, eradicating parking congestion in a commercial zone or providing transportation for senior citizens—the formula can be tailored to reflect those priorities.

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How One City Could Use Data Insights

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To demonstrate how a city can evaluate its optimal deployment areas at a granular level, INRIX researchers constructed heat maps of San Francisco, New York City, and Austin, Texas, that help visualize where fleets of shared vehicles could be optimally deployed.

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For example, in the heat maps of Austin shown above, on which darker blocks depict areas that likely to benefit most from such deployments, the left map unsurprisingly shows downtown areas, but it also shows areas outside downtown including Spicewood Springs Road (BGC1) and Rosedale, north of central Austin (BCG2), that would be strong candidates for autonomous vehicles.

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A stronger emphasis on parking is added for constructing the heat map of the downtown Austin area shown on the right. The map shows several areas, including the southern boundary of the University of Texas campus (BC1), the area south of the capitol building (BC3), and an area adjacent to the Colorado River (BC5), as optimal targets.

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With such information, transportation officials can act.

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“Like a lot of fast-growing cities in the South, Southwest, and West, we have expanded with automobiles as the primary mode of mobility, and in some areas, we have low densities or densities that don’t support high-capacity transit,” said Rob Spillar, transportation director for the city of Austin. “But we absolutely need to offer those people some alternative.”

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• The Parking Garage of the Future: Big Changes in Store for Autonomous Age

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• Ford Plans Expansion of Ride-Sharing Shuttle Service

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• California Revamps Its Rulebook for Autonomous Cars

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Whether it simply helps establish a regulatory framework for autonomous vehicles or specific pickup and dropoff zones for shared self-driving cars, the success of these vehicles in urban environments could depend on whether cities make smart use of data.

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“A lot of cities think about this as ‘Let’s plop these cars downtown,’ and that can be a good position, but maybe it’s not the best place,” he said. “At the end of the day, you want to deploy these strategically to best supply a service to your constituents. Yes, self-driving cars are very cool, but you’re not going to get the benefits unless you strategically plan for them.”

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