Traffic AI Cameras Expand to Seatbelt, Phone Use, and Impaired Driving Detection
The New Frontier of Traffic Enforcement
For decades, automated traffic enforcement was limited to speed cameras and red-light cameras. While controversial, these tools became a fixture in cities across the United States, the European Union, and Australia. Now, advances in artificial intelligence (AI) and computer vision are pushing traffic enforcement into new territory. Modern AI-powered traffic cameras can detect far more than speeding—they can identify whether a driver is wearing a seatbelt, using a handheld phone, or even showing signs of impairment behind the wheel.
This rapid expansion of capabilities marks a turning point in road safety and civil liberties debates. Proponents argue the technology saves lives, while critics warn about privacy, accuracy, and the potential for overreach.
From Speeding to Seatbelts: What’s Changing
The traditional traffic camera captured a simple infraction—speeding above a posted limit or running through a red light. AI cameras, however, can analyze subtle behaviors inside the vehicle cabin:
-
Seatbelt Detection – Cameras can spot whether a driver or passenger is buckled up. In Australia, New South Wales launched widespread seatbelt camera programs in 2021, issuing hundreds of thousands of fines in the first year. Similar pilots are now underway in Europe.
-
Phone Use Monitoring – Distracted driving caused by texting or calling is one of the top causes of crashes worldwide. AI cameras can identify drivers holding phones near their faces or laps, capturing evidence even at highway speeds.
-
Impaired Driving Indicators – Researchers in the EU and U.S. are training AI systems to detect erratic lane changes, delayed reaction times, and abnormal eye or head movements, raising the possibility of real-time impaired driving alerts.
The U.S. Approach: State-Level Pilots and Pushback
In the United States, traffic enforcement has traditionally been a patchwork of local laws. Some states fully embrace cameras, while others ban them. With AI technology, the split is becoming more pronounced:
-
New York is testing distracted driving detection systems along select corridors. Cameras capture drivers texting and issue automated citations.
-
California passed legislation in 2023 allowing pilot programs for phone-use detection, though strong privacy rules limit how long images can be stored.
-
Texas and Florida, meanwhile, continue to ban most automated enforcement technologies, arguing that they violate constitutional due process rights.
Civil liberties groups in the U.S. argue that these cameras create “mass surveillance highways,” but road safety advocates counter with crash data showing lives saved.
Europe Leads in Deployment
The European Union has taken a more unified approach. The EU’s 2022 Road Safety Charter called for cutting road deaths by half by 2030, and AI enforcement plays a big role.
-
The Netherlands has deployed phone-use cameras nationwide, issuing thousands of fines for drivers caught holding devices.
-
Spain and France are expanding seatbelt cameras across highways, often coupled with existing speed enforcement systems.
-
Germany, historically cautious on privacy issues, is still debating the scope of AI enforcement, balancing GDPR requirements with road safety goals.
The EU’s coordinated strategy may serve as a global model, demonstrating how member states can adopt common technology standards while maintaining oversight.
Australia: A Pioneer in AI Enforcement
Australia is perhaps the most aggressive adopter of AI traffic cameras. New South Wales pioneered large-scale distracted driving detection in 2019, installing cameras that scan millions of vehicles per year. The state reported a 22% reduction in road fatalities attributed to phone use after the rollout.
Victoria and Queensland followed suit with combined seatbelt and phone detection systems. Unlike the U.S., where courts often block such programs, Australia has widespread public acceptance, driven by strong road safety campaigns.
How the Technology Works
Modern AI traffic cameras use a blend of hardware and software innovations:
-
High-Resolution Lenses capture detailed images of drivers even in low light or high-speed conditions.
-
Infrared Sensors allow seatbelt and phone detection regardless of sunlight glare or window tint.
-
Machine Learning Models analyze images in milliseconds, distinguishing between safe and unsafe behaviors.
-
Data Integration connects violations to license plates, allowing automated ticketing or real-time alerts.
Importantly, most systems are designed to blur passenger faces and only store images when an infraction is detected. Still, concerns remain over potential misuse.
Benefits of AI Traffic Cameras
Supporters of these new systems point to measurable benefits:
-
Lives Saved – Distracted driving accounts for thousands of deaths annually. Automated enforcement can reduce incidents by changing driver behavior.
-
Efficiency – AI cameras operate 24/7, reducing the need for costly police patrols.
-
Fairness – Unlike officer-based stops, automated systems apply rules consistently, avoiding racial profiling concerns.
-
Revenue – While controversial, fines generate funds for infrastructure and safety programs.
Controversies and Criticisms
Despite benefits, expansion beyond speed and red-light enforcement raises serious concerns:
-
Privacy – Continuous surveillance of drivers may feel invasive. Who owns the data, and how long is it stored?
-
Accuracy – False positives remain a risk. A driver scratching their face could be misread as holding a phone.
-
Equity – Critics argue fines disproportionately impact low-income drivers.
-
Scope Creep – If cameras detect seatbelts today, will they monitor other personal behaviors tomorrow?
Civil liberties groups in the U.S. and Europe continue to file lawsuits, while technology vendors stress transparency and limited data retention.
Market Growth and Major Vendors
The global market for AI traffic cameras is growing rapidly. Analysts project the sector will exceed $20 billion by 2030, driven by government contracts and public-private partnerships.
-
Verra Mobility (U.S.) supplies red-light and speed systems and is now adding AI features for distracted driving detection.
-
Acusensus (Australia) is a leader in phone and seatbelt detection, exporting its technology to Europe and North America.
-
Jenoptik (Germany) focuses on multi-functional enforcement systems, integrating speed, seatbelt, and phone use detection.
Competition among vendors is intense, with AI startups entering alongside long-established traffic camera companies.
Public Opinion: Divided but Shifting
Polls show mixed public support. In Australia, over 70% of residents support phone-use cameras. In the U.S., support is split by state, with higher acceptance in urban areas suffering from distracted driving crashes. In Europe, acceptance tends to rise once data shows reductions in fatalities.
Generational attitudes also play a role. Younger drivers often view cameras as normal parts of digital life, while older generations raise stronger civil liberties concerns.
The Road Ahead
The expansion of AI traffic cameras is unlikely to slow. As technology becomes more precise and affordable, governments around the world will test and adopt new use cases. Potential next steps include:
-
Fatigue Detection – Identifying drowsy drivers before accidents occur.
-
Aggressive Driving Monitoring – Tracking tailgating, swerving, and sudden braking.
-
Insurance Integration – Sharing anonymized violation data with insurers, potentially affecting premiums.
The challenge for policymakers will be balancing safety benefits with civil liberties, ensuring transparency, accuracy, and fair enforcement.
Conclusion
AI-powered traffic cameras represent the next evolution of road safety enforcement. No longer confined to speed and red-light violations, these systems now target distracted driving, seatbelt use, and even impaired driving indicators. The U.S., EU, and Australia are leading testbeds, each with unique political, cultural, and legal approaches.
As the technology matures, societies must answer hard questions: How much surveillance is acceptable for safety? How do we prevent misuse while saving lives? These debates will shape the future of transportation enforcement—and perhaps the balance between technology and civil liberty itself.