Smarter Roads Ahead: How Smartphones and AI Reduce Crashes

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In an age of constant innovation, few technologies shape modern life as deeply as artificial intelligence. Its ability to gather vast data and uncover behavioral trends is unmatched. What determines its impact, however, is how people interpret and apply the insights it reveals.

A Massachusetts-based firm, Cambridge Mobile Telematics (CMT), is putting this power to work through its platform, StreetVision. Using data collected from drivers’ smartphones, the company analyzes patterns in road use and risky behavior. Much of this data comes from motorists who share their driving information in exchange for insurance discounts.

Earlier this year, CMT examined distracted driving patterns across Georgia. Their findings revealed that the state still trails others with comparable hands-free driving laws. This analysis was part of a broader look into how smartphones and AI can identify dangerous road habits before they lead to collisions.

Ryan McMahon, CMT’s senior vice president of strategy, explained that smartphones serve as rich sources of driving behavior data. He said their sensors detect sudden braking, sharp turns, and high-impact movements, all of which help paint a full picture of road risk. The data also reveals when drivers exceed speed limits or accelerate too abruptly.

Through these patterns, experts can identify hazardous stretches of road and potential accident zones. McMahon shared that the company processes over a trillion data points daily, which are then visualized on an interactive map for traffic engineers and safety officials. These maps reveal how driving conditions change over time, helping agencies take preventive action.

One striking example is an off-ramp in East Point, Georgia, connecting Highway 166 Eastbound to Main Street. Vehicles there must decelerate sharply from freeway speeds to a full stop while navigating a tight curve. According to StreetVision’s analytics, this area shows unusually high levels of harsh braking and phone movement—clear signs of distracted and risky driving.

Using AI, CMT’s systems interpret this data to forecast crash-prone locations. The program divides roads into small sections and ranks them based on risk intensity. On this particular ramp, the highest risk lies right at the curve’s midpoint, where drivers struggle most to control their vehicles.

McMahon noted that increased phone motion along this route suggests widespread distraction, further elevating crash probabilities. CMT’s technology now assists safety organizations across 32 U.S. states and 10 other nations. During a demonstration in Washington, D.C., the team used similar data to locate an intersection where a stop sign was obscured by tree branches—a factor that forced drivers into sudden stops.

Telematics data, which merges telecommunications with vehicle analytics, has also highlighted the alarming scale of distracted driving nationwide. McMahon shared that in over a third of crashes the company tracked, drivers had been holding their phones just a minute before impact.

The combination of speeding, inattentiveness, and flawed infrastructure creates a recipe for disaster. However, McMahon believes that better urban planning and data-informed policy can drastically reduce such risks. He suggested that by studying risky behavior early, transportation leaders can prevent tragic outcomes later.

The Georgia Department of Transportation has partnered with CMT before, although it now uses another firm providing similar technology. Still, the goal remains the same—to make driving safer through predictive insights.

Ultimately, the responsibility for road safety rests with drivers themselves. Yet smartphones and AI are giving policymakers and engineers the tools to redesign roads, refine regulations, and create safer environments for everyone on the move.

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