“There is also the risk of turning enforcement into an end in itself. Automated challans can quickly become a revenue-generating exercise rather than a safety-driven one. When violations are detected by machines with little human discretion, even minor errors or unavoidable situations can lead to penalties. Without a strong and accessible grievance redressal mechanism, ordinary citizens may feel trapped in an impersonal system where contesting a wrong fine becomes harder than paying it.
Technology is only as good as the ecosystem it operates in. AI cameras require clear lane markings, visible signage, standardised junction layouts and regular maintenance.”
The Goa government’s plan to install AI-enabled traffic signals and surveillance systems at 92 locations is being presented as a major step towards enforcing discipline on the state’s roads. Cameras that automatically detect violations, issue challans and reduce dependence on human enforcement sound efficient and modern. But the question Goa must ask is simple. Will technology alone succeed where years of weak planning, poor infrastructure and inconsistent enforcement have failed?
There is no denying that traffic discipline in Goa is a serious problem. Red light jumping, wrong side driving, triple riding and disregard for pedestrian safety are common sights. Traffic police are overstretched, junctions are chaotic, and enforcement is often selective. In this context, automated systems promise objectivity and round-the-clock vigilance. The appeal is obvious. Machines do not take bribes, do not get tired and do not look the other way.
Yet the belief that AI signals will automatically create safer roads rests on a shallow understanding of how traffic behaviour actually changes. Discipline is not produced by surveillance alone. It is shaped by road design, clarity of rules, predictability of signals and the sense that the system is fair. Goa’s roads fail on many of these counts.
Across the state, traffic signals often malfunction, remain poorly synchronised or are placed at junctions that are badly designed to begin with. Drivers routinely complain of excessively long red lights on empty roads and confusing signal phases that worsen congestion. Pedestrians are left guessing when it is safe to cross. If basic signal management remains unreliable, adding a layer of artificial intelligence will only automate frustration, not resolve it.
There is also the risk of turning enforcement into an end in itself. Automated challans can quickly become a revenue-generating exercise rather than a safety-driven one. When violations are detected by machines with little human discretion, even minor errors or unavoidable situations can lead to penalties. Without a strong and accessible grievance redressal mechanism, ordinary citizens may feel trapped in an impersonal system where contesting a wrong fine becomes harder than paying it.
Technology is only as good as the ecosystem it operates in. AI cameras require clear lane markings, visible signage, standardised junction layouts and regular maintenance. Goa struggles with all of these. Roads change abruptly, markings fade, and signage is inconsistent. Expecting software to accurately interpret such a chaotic physical environment is unrealistic. In such conditions, errors will not be exceptions. They will be routine.
More importantly, an obsession with enforcement distracts from deeper structural failures. Many accidents occur not because drivers are wilfully reckless, but because roads are poorly engineered. Narrow lanes suddenly widen, curves are unmarked, pedestrian crossings are missing, and lighting is inadequate. No camera can compensate for bad design. Penalising drivers for speeding on roads that invite speeding through their very layout reflects a failure of planning, not discipline.
Public trust is another fragile element. Goa has seen enforcement initiatives in the past that began with promise and ended in controversy or quiet abandonment. Citizens are wary of systems that feel punitive, opaque or disconnected from everyday realities. Rolling out AI-based enforcement without sustained public engagement risks reinforcing the perception that the state is more interested in policing citizens than fixing roads.
None of this is an argument against using technology. Smart traffic management can play a meaningful role if it is part of a broader, integrated strategy. That strategy must prioritise road engineering, consistent signal timing, pedestrian safety, public transport and sustained awareness campaigns. Enforcement should support these goals, not replace them.
If AI traffic signals become another standalone project announced with enthusiasm but implemented without groundwork, they will fail to deliver safer roads. Goa does not need smarter machines alone. It needs smarter planning, accountability and the political will to address the basics first. Until then, artificial intelligence may end up exposing very human failures rather than correcting them.

