AI-Driven Tech Systems Can Help Reduce Car Accidents. Here's How

AI-Driven Tech Systems

Improving traffic safety is a collective goal and one that could potentially benefit all of us, not just drivers. As we well know, car accident fatalities have skyrocketed during the Covid-19 pandemic. Recent findings hint that drivers in all 50 states were actually at higher risk of dying in a car accident during the early months of the pandemic. 

However, a switch to autonomous vehicles could provide our drivers with the biggest change to driving habits since vehicles were first created. In an effort to reduce car accidents and fatalities, many local, state, and federal government companies are introducing programs that aim to increase awareness and improve driving habits. 

Los Angeles was among the first U.S cities to adopt its Vision Zero plan, the city's proposal to eliminate traffic fatalities by 2025. The program emphasises the fact that more than 200 citizens in Los Angeles are killed each year while crossing the city, and more than half of those accidents involve bicyclists and pedestrians. AI-driven programs like One Vision reduce vehicle speed because, as the developers note, eliminating speed is "fundamental to safe streets." 

Although Los Angeles ranks as the most dangerous place for traffic accidents – with 3,563 deadly accidents in 2018 alone – the issue of traffic safety impacts drivers worldwide, and AI-driven programs are here to reduce accidents if not prevent them.  

AI systems Claim to Prevent More than 90% of crashes 

Novel behavioural AI system claims to prevent over 90% of car accidents by predicting the actions of pedestrians and other road users and notifying motorists of a potential incident.

These systems come as dashcam after-fit solutions; however, the creators behind it hope they will be offered as standard fit within the next three years, linked to advanced driver-assistance systems (ADAS). 

The AI application will help autonomous systems "better understand people," predict other motorists' behaviors and alert the driver. It can also offer trucking fleets data about any near-miss (as well as any accident), which helps with the driver training. 

The system was first installed on London's buses for more than a year, while trials have just started with van-based fleet operators. 

A Behavioral AI system scans the highway for vulnerable motorists and predicts their next movement, managing to detect objects up to 80 metres ahead at 40mph, twice the distance of the industry average, with 99% precision. 

According to Behaviour AI developers, the system is capable of predicting where they are moving on the road and if they're going to cross the road. Recent data shows that the AI-based system can predict two seconds before the motorists realize the gravity of the situation and send them an alert. 
However, little is known about behavioral AI, which means it should continuously learn, not just from one driver but from an entire fleet. 

AI in Driverless Cars 

The switch to self-driving cars with no human driver could offer us a significant change to our driving habits since motorized vehicles were first created. These vehicles are equipped with a variety of cameras, sensors, and radars, to be aware of what is going on, but they call for a higher degree of AI to make sense of it all. Since autonomous vehicles don't require human input once they set off for a destination, they need to be able to recognize images like other vehicles, people, and lights.

This can not only impact the way we deal with accidents as a society but also the number of accidents. According to, you're eligible for a compensation claim if you're involved in an accident where someone else has been negligent. In that case, the claimant files the claim while the defendant is the other part, who is accused of causing the injury. The implementation of autonomous driving could make this process slightly more complex, although it is hoped that the number of accidents will be decreased.

AI Can Be Used to Detect Unsafe Driving 

AI dash cams are all the rage right now and with the right reason. These systems use advanced algorithms that can precisely detect any safety issues, like fatigue, distracted driving, or mobile phone use, in a matter of seconds. 

Once the system works out a score for the current driving against benchmarked numbers, a real-time alert is sent to the motorist, if necessary. The developers suggest that AI-powered dash cams could help reduce the number of accidents in fleets up to 30%. 

Easily Recognizing Traffic Patterns 

Another key piece of research has been carried out on the importance of AI in road safety, but this time in Spain. The Universitat Oberta de Catalunya's researchers wanted to identify any recurring patterns in road traffic accidents, examining hours of video footage of traffic in Barcelona and Madrid to do this. 

For efficiency, the researchers used artificial neural networks and machine learning to locate patterns in areas with high rates of road accidents. Not long after, the team concluded that traffic accidents are more likely to happen on highly agglomerated streets with features like public art displays and benches that could distract motorists. 

There's also a good chance that the rate of traffic collisions will ultimately decrease thanks to AI technology used in ways like this. While artificial intelligence provides crucial insights, the team believes city streets can only be made safer if the studies are combined with the expertise of engineers, architects, transport authorities, and city planners.  

AI-powered systems strike us as a very powerful tool for finding out where issues might appear, but they are not going to solve them independently. 


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