The AI Journal: AI data analysis could make roads safer
Ryan McMahon, Cambridge Mobile Telematics (CMT) senior vice president of strategy and corporate development, explains how AI can accelerate road safety in an article recently published in The AI Journal
Traffic deaths in the U.S. have fallen for 15 consecutive quarters and in 2024, dropped to 39,345 for the first time below 40,000 since 2020, McMahon writes.
Preliminary data from the National Highway Traffic Safety Administration (NHTSA) estimates 2025 traffic deaths will fall to 36,640, a 6.7% decrease.
“That is thousands of people alive today who, on the 2022 trendline, would not be,” McMahon says.
The decrease follows stronger laws, better feedback, and the ability to measure changes in driving behavior, he writes.
“AI’s role is in what comes next: helping safety professionals connect risks conventional analysis cannot, intervene earlier, and accelerate a decline still far too slow,” the article states.
Phone use while driving dropped before the deaths did, according to the article. It adds that CMT found 37% of 54 million trips involved drivers distracted by their phones in 2019. This number continued to increase until it started reversing in 2023 and eventually dropped by 8.6% in 2024. CMT estimates the 8.6% decrease included avoiding 105,000 crashes and 480 deaths.
Drivers using phones are 240% more likely to crash, and collision claims analysis has found that distracted drivers are 3.5 times the crash risk, McMahon writes.
“Safer vehicles and calmer post-pandemic roads deserve a share of the credit; no national trend has a single cause,” he writes. “But distraction is the one major risk behavior that has verifiably fallen, year after year, wherever it is measured.”
State laws, such as hands-free laws, help reduce the behavior. He points to data from four states that went hands-free in 2023. Ohio, Michigan, Missouri, and Alabama have averaged an 11.8% reduction in distraction, preventing an estimated 31,000 crashes and 140 deaths, he says.
Insurance programs also reinforce the laws, according to the article. Voluntary programs such as Nationwide’s SmartRide and Focused Driving Rewards use trip feedback and discounts to reward focused driving. A University of Pennsylvania trial found weekly goals and friendly competition built on trip feedback decreased handheld phone use by 20.5% and modest financial incentives dropped it by 27.6%.
McMahon writes, “If the tide is turning, why has almost no one noticed? Partly because the roads are still dangerous. More than 36,000 deaths a year does not feel like progress, and it should not; less bad is not good. And partly because the official instruments cannot show the change.”
The article highlights blind spots in current data collection. For example, the National Occupant Protection Use Survey uses standing daytime observers at intersections and records phone use. Observers only record drivers who are stopped with their phones visible to them.
NHTSA data on distracted driving is also likely under-recorded because the distraction must be proven by a police report, the article notes.
“The turn is visible because measurement no longer depends on the roadside,” the article states. “For drivers who choose to participate in safe-driving programs, a smartphone’s motion sensors generate rich signals about each trip. Privacy is a design requirement here: for public-safety analyses such as these, telematics measurements are anonymized and aggregated to show how a population’s driving changes, never to follow an individual.”
The data shows the entire trip, not just daytime, according to the article. The instrument is telematics. AI can validate it.
AI can understand risk by combining information. It can look at the conditions a crash occurred in, the behaviors observed, where they cluster, and which interventions work, the article states.
“For drivers, this future should feel like help, not homework,” McMahon writes. “AI can make the feedback more personal and timely: a heads-up that the road ahead is where distraction and speeding tend to mix, or encouragement after a week of focused trips. Separately, voluntary programs can recognize and reward measured improvement. The driver stays in charge, opts in, and collects the benefit twice, in safety and in savings.”
AI’s data analysis can help people act earlier, he writes.
For example, AI could help flag a potentially obscured sign from an overgrown tree limb after noting aggregated driving data showing a pattern of late braking, the article notes. It adds that AI could give humans the data it has collected for review before a crash is recorded at the intersection.
“The problem can be solved with a chainsaw, not a citation,” McMahon says.
He points to CMT’s StreetVision as an AI behavioral platform that can help road safety.
“This is what a turning tide looks like: laws grounded in measurement, education aimed where it matters, feedback that builds habits, a death toll falling quarter after quarter,” he writes. “It is a turn, not a victory. More than 36,000 people will still die on American roads this year, and nearly a third of states have no hands-free law. But for the first time, we are working with information worthy of the problem. We no longer have to wonder whether we are saving lives. We can count them, and what we do next decides how many more.”
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