Road safety has always been a major concern for governments, city planners, and communities worldwide. Despite decades of advancements in vehicle design and stricter traffic laws, accidents remain a significant global issue.

According to the data from the World Health Organization (WHO), close to 1.2 million people die every year due to road collisions. They are the biggest cause of death for those aged between 5 and 29 years.

This ongoing challenge has prompted researchers and automakers to turn to artificial intelligence (AI). It is the technology that is proving to be a powerful tool in reducing traffic-related injuries and fatalities.

In this article, we will discuss how AI is helping make roads safer for both drivers and pedestrians.

AI in Traffic Management

Beyond vehicles themselves, AI is being applied to traffic management systems in cities worldwide. Intelligent algorithms can analyze traffic flow, predict congestion, and adjust signals dynamically to prevent bottlenecks that often lead to collisions.

California is one of the states experimenting with AI and Internet of Things (IoT) for traffic management. The state’s prime cities, including Los Angeles, San Francisco, and San Jose, are known for traffic congestion. Data from Consumer Affairs suggests that Los Angeles ranked second on the list of cities with the worst traffic in 2025. It was at the very top in 2024.

According to ABC 7, California Governor Gavin Newsom unveiled three AI projects that aim to improve government efficiency and address road traffic congestion. The new deals are supposed to reduce highway congestion, enhance road safety, and improve customer service of a state call center.

By smoothing the flow of traffic and predicting dangerous patterns, these systems reduce the likelihood of accidents before they happen. Importantly, they also gather valuable data that can be used to improve infrastructure design, making roads safer over time.

Reducing Human Error with Machine Learning

The majority of road accidents are still caused by human error. Machine learning (ML) models, however, are being trained to anticipate mistakes that drivers commonly make.

These models learn from millions of driving scenarios, enabling systems to recognize the earliest signs of distracted driving, fatigue, or risky maneuvers. According to an MDPI study, ML can not only monitor drivers, but also analyze their behaviors. This includes risky behaviors like accelerating, braking, or how they react to obstacles.

Some vehicles are even equipped with driver monitoring systems that can prompt an alert if the AI detects signs of drowsiness. Consider the example of an accident in Forsyth, a county near Atlanta, Georgia. According to Fox5 Atlanta, the nurse said that she fell asleep before the fatal crash.

If such an accident occurs, Atlanta personal injury attorneys can be helpful. They can guide the individuals involved in the accident about the legal steps to take. They can also calculate damages and negotiate with insurance agents for the best possible outcome.

According to the Atlanta Personal Injury Law Firm, lawyers have the right expertise and knowledge to help in such cases. However, these accidents can simply be prevented with the use of ML.
By predicting and intervening at the right moment, these technologies reduce the risks associated with human fallibility.

AI and Emergency Response Systems

Artificial intelligence is not only helping prevent accidents but also improving how emergency services respond when crashes occur. AI-powered dispatch systems can analyze accident reports, detect severity levels from incoming calls, and prioritize resources accordingly. Some cities are experimenting with AI tools that integrate with traffic cameras to automatically notify emergency teams about collisions, cutting down response times.

Faster response means injuries are treated sooner, vehicles are cleared quickly, and roads return to safe conditions with minimal delay. This broader use of AI creates a safety net that goes beyond prevention and addresses what happens in the critical minutes after an accident.

In addition to dispatch and monitoring, AI is enhancing communication between vehicles and emergency services. Some connected cars are now equipped with systems that automatically transmit crash data, including impact severity, airbag deployment, location, etc., directly to first responders.

This allows medical teams to arrive better prepared, knowing what equipment or treatment may be necessary before they reach the scene. As this technology becomes more widespread, it could significantly improve survival rates and reduce the long-term consequences of serious accidents.

Smart Infrastructure for Safer Roads

AI is playing a role in designing and maintaining infrastructure as well. Sensors embedded in roadways can send real-time data to AI platforms that detect issues such as potholes, damaged guardrails, or malfunctioning traffic lights. Addressing these hazards quickly can prevent accidents that often result from poor infrastructure.

An example can be seen in Hertfordshire County in England. According to a BBC article, the county has deployed the Autonomous Road Repair System (ARRES). It is a robot that identifies and fills cracks or potholes on public roads.
The idea is also to fill the cracks quickly to prevent the water from seeping into the roads. This will help avoid the freezing and expansion of the water, which will minimize further road damage.

Frequently Asked Questions

Can AI help reduce distracted driving caused by smartphones?

Yes, AI can play a role in reducing smartphone-related distractions. Some systems monitor driver attention through in-car cameras and sensors, detecting when someone looks away from the road for too long. If distraction is identified, the AI system issues warnings or even adjusts driving assistance features.

How does AI impact pedestrian safety on busy roads?

AI systems are increasingly being developed to protect pedestrians as well as drivers. Advanced sensors and computer vision tools can identify crosswalks, pedestrians, and automatically stop the vehicle if the driver fails to respond. Some cities are also testing AI-powered crosswalk lights that adjust timings based on pedestrian flow.

Will AI reduce accidents involving cyclists and motorcyclists?

AI has strong potential to reduce risks for vulnerable road users such as cyclists and motorcyclists. Computer vision technology allows vehicles to detect smaller, fast-moving objects more reliably than human eyes in certain conditions. Predictive algorithms can also anticipate the behavior of cyclists, such as sudden lane shifts or turns.

The promise of AI in road safety is not just about reducing accidents but reshaping how we think about transportation altogether. From self-driving cars to smart traffic lights, the integration of artificial intelligence is moving us closer to a future with safer roads. Although challenges remain, such as ethical considerations and regulatory frameworks, the progress made so far shows that AI is already making a difference.

As the technology matures, its influence will expand beyond the mechanics of driving to the policies, laws, and human behaviors connected to road safety. The end goal is clear: fewer accidents, fewer injuries, and ultimately, more lives saved.