Many advocates argue that illegal discrimination pays blatant racial disparities In traffic stops – the police simply stop more black drivers than white drivers who behave similarly. Other observers claim that the patterns come from different baseline rates of traffic violations. It’s hard to separate out these potential causes, because we usually only know if someone broke the traffic law when they were stopped by the police.
In a new studyWe and our co-authors – Justin Kashuk, Lisa Benalls and Samuel Madden – investigated this question using data about drivers’ movements collected from mobile phones. We found that drivers spent the same amount of time speeding in neighborhoods where the majority of the population was white as in neighborhoods where the majority of the population was not. But in all of the 10 cities we looked at, fast-enforcement officers focused on geographically small – and often racially unrepresented – areas. Individual cities varied, but on average across all 10 cities, accelerators were stopped more often in communities of color than in white neighborhoods.
Police don’t always stop drivers where they are speeding
To understand who the police issued a ticket for speeding, we used the traffic stop records we collected as part of Open Police Project. We restricted the data to cities that were large enough and detailed enough traffic stop data for us to compare the number of times police pulled over drivers for speed in different neighborhoods. This gave us 10 cities: Aurora, Colorado; Chicago; Houston. Madison, Wisconsin; Mesa, Arizona; Oklahoma City Plano, Tex. San Antonio; Tulsa. And Wichita.
We then crossed our police stop data with real-time driving data from drivers in those 10 cities. We used anonymous and aggregated information from Cambridge Mobile Telematics about the second-by-second speed and location of hundreds of thousands of drivers who, in total, made tens of millions of car trips in 2019 and early 2020, before the pandemic reduced driving. This unique data set allows us to determine where and how fast the drivers in our sample are, regardless of whether the ticket was hit by the police.
Combining these data sources allows us to compare the places where people were speeding and where the police stopped the speeding drivers.
In Mesa, for example, police stopped speeding drivers in the city’s western neighborhood, where 50 percent of the population is white, about three times more than the eastern part of the city, where 75 percent of the population is white. You can see this in the figure below, where the red neighborhoods represent the places where the police stopped more speeding drivers relative to the amount of time the drivers actually spent there at speed. These highly-enforced neighborhoods are concentrated in the western part of the city, where many of the Mesa minority live.
More of the cities we examined looked more like a mesa than none. For example, despite the fact that speeding rates were roughly the same across Chicago, police there pulled out more speed drivers on the city’s south and west sides, where most residents are black or Hispanic, than on the north side of the city, Where there is a larger population. She is white.
But the stricter accelerated enforcement pattern in neighborhoods with more ethnic minorities was not found everywhere. In some cities, such as Houston, police have enforced speeding tickets more stringently in White neighborhoods.
Why does Houston look so different from Mesa and Chicago? When we looked closely at where the police stopped the motorists, we found that the speed stops were concentrated in small geographic areas. Across the 10 cities we studied, more than 50 percent, and in some cases more than 75 percent, of the speed stops occurred in areas where only 10 percent of the population lived.
Police departments have focused on a relatively small number of locations to catch speeding drivers. Because American cities tend to be quite separate, focusing enforcement on a handful of speed traps can lead to racial inequality, even if officers aren’t intentionally discriminating.
Our approach helps us connect behavior and execution in ways that were not possible even a few years ago. But our results have limits. The 10 cities we looked at may differ from other American cities in important ways. And the triggers in our sample may be safer than average.
In particular, our sample came from drivers who chose to share their driving data with their car insurance companies as a way to measure their safety on the road – and may not want to share their data unless they think they are good drivers. Fortunately, we find that our results are quite similar if we use the driving data collected from different mobile tools such as map apps you will likely not encounter this self-selection problem.
Speed radars and speed bumps
Researchers have suggested several possible strategies to reduce racial disparities in traffic enforcement. For example, rather than relying on a small number of speed traps, the police could spread enforcement efforts more evenly across the city, or even adopt Random Police Strategies. Or, cities can reduce the control of traffic violations — and the social and financial costs that come with them — by deterring unsafe driving with speed bumps, roundabouts and other physical infrastructure that Slow driver speeds and save lives.
Our research shows that speed is largely unrelated to race. Policy makers may want to ensure that the ways in which their officers are prevented from speeding do not have a disproportionate racial impact, either.
Johann Geibler (@jgaeb1) is a PhD student at Harvard University.
William Kaye (iamwillcai) is a PhD student at Stanford University.
Sharad Joel (@5harad) Professor of Public Policy at Harvard Kennedy School.