Traffic nightmare in Lagos: The case for AI-driven planning

The recent closure of the Independence Bridge in Lagos for maintenance work has once again exposed the glaring lack of systematic planning in Nigeria’s infrastructure management. The decision, taken without a comprehensive traffic diversion strategy, resulted in citywide gridlock, bringing Lagos to a standstill. Commuters were stranded for hours, businesses suffered delays, and the government’s response to the chaos was an afterthought rather than a proactive measure.

In a world driven by data, statistics, and artificial intelligence, such an avoidable disaster is inexcusable. The fundamental question remains: why was there no detailed analysis of vehicular movement before executing the closure? Proper planning could have mitigated the chaos and ensured a seamless transition without disrupting daily life.

What should have been done?

Traffic volume assessment and AI modelling

A well-planned infrastructure maintenance project should begin with a thorough assessment of traffic patterns. This would include:

· Hourly monitoring of vehicular movement on the affected road for at least 3–4 months before initiating repairs.

· Data-driven estimates of the volume of vehicles that would be displaced.

· AI-powered predictive models to simulate potential traffic congestion on alternative routes.

Optimised traffic diversion strategies

Once data is collected, a well-structured traffic diversion plan should be implemented, considering:

· The capacity of arterial roads to handle additional load.

· Real-time monitoring of congestion on alternative routes using smart cameras and IoT sensors.

· Public advisories to reduce traffic density by staggering work hours or enforcing work-from-home orders where feasible.

Work scheduling and public awareness

Infrastructure maintenance must be aligned with minimising public inconvenience. Best practices include:

· Conducting repairs at night or during off-peak hours.

· Declaring specific maintenance days (e.g., once or twice a week) instead of an unplanned complete shutdown.

· Issuing clear public notices weeks in advance, supported by digital alerts and AI-driven traffic rerouting recommendations.

A smarter future for Lagos: AI in public infrastructure management

Lagos aspires to be a smart city, yet events like this expose its shortcomings in adopting modern governance tools. The use of AI-driven analytics, predictive modelling, and IoT-enabled traffic monitoring can revolutionize how the city manages infrastructure projects. Implementing a Smart Traffic Control Centre would allow:

· Automated congestion detection and dynamic rerouting suggestions.

· AI-driven decision-making for optimal maintenance timing.

· Data-informed expansion of road networks to prevent future bottlenecks.

The way forward

This crisis should serve as a wake-up call for the Lagos State Government and the Federal Ministry of Works. Future road maintenance projects must integrate AI, big data, and machine learning to prevent similar disruptions. Investing in smart infrastructure management is not an option—it is a necessity for a rapidly growing metropolis.

Lagosians deserve a city that plans ahead, not one that reacts in distress. It is time for the authorities to embrace technology-driven governance and ensure that never again will the closure of a single bridge bring an entire city to its knees.

About the author:
Colonel Manish Kochhar is the CEO of Telenoetica Digital Innovation Africa Ltd (TDIAL) and former Head of Optical Networks at Globacom. With a master’s in telecommunications and IT and a PG diploma in AI-ML, he is a technology enthusiast who writes on technical and business matters.