GeSI Member Spotlight: Google Green Light

From Traffic Congestion to Smarter, Lower-Emission Cities

What if cities could reduce congestion and emissions without building anything new? Project Green Light shows that with AI and data, existing infrastructure can be transformed into a smarter, lower-emission system—turning digital innovation into immediate climate action.

Google’s Project Green Light uses AI and Google Maps data to optimise traffic signals, reducing stop-and-go traffic. Already deployed in 20+ cities globally, the solution has achieved up to 30% fewer stops and 10% lower emissions, demonstrating scalable digital impact in urban mobility.

The Challenge

Urban transport is one of the largest contributors to global greenhouse gas emissions, with road traffic accounting for a significant share of urban pollution.

A key driver of inefficiency is stop-and-go traffic at intersections, where:

vehicles idle unnecessarily

repeated acceleration increases fuel consumption

congestion compounds across interconnected roads

Stop-and-go driving generates significantly higher emissions than smooth-flow traffic, making traffic signal optimisation a critical—yet often underutilised—lever for decarbonisation.

Despite this, many cities still rely on static or outdated traffic light systems, which:

are not responsive to real-time conditions

require manual optimisation

lack data-driven insights at scale

Cities therefore face a structural challenge: how to improve traffic flow and reduce emissions without costly infrastructure upgrades.

The Solution

Google developed Project Green Light, an AI-powered solution that optimises traffic signal timing using insights from Google Maps driving data.

How it works:

Data Analysis:
The system analyses large-scale, anonymised traffic patterns from Google Maps to identify congestion hotspots.

AI Modelling:
Machine learning models simulate traffic flows and detect inefficiencies at intersections.

Optimisation Recommendations:
The system generates actionable recommendations—such as adjusting signal timing or coordinating intersections to create “green waves”.

Easy Deployment:
Cities can implement these changes in minutes, using existing infrastructure—no new hardware required.

Continuous Improvement:
Performance is monitored and refined through ongoing data analysis and feedback loops.

Global deployment

Project Green Light is already deployed in 20+ cities across Europe, Asia, the Middle East, and the Americas, demonstrating its scalability across diverse urban environments.

Cities include:

Europe: Hamburg, Budapest, Manchester

Middle East: Abu Dhabi, Haifa

Asia: Bangalore, Hyderabad, Kolkata, Jakarta, Bali

Americas: Rio de Janeiro, Seattle, Boston, Québec City

The solution is already influencing tens of millions of car journeys per month, highlighting its ability to deliver impact at scale.

Quantified Benefits

Early deployments show measurable and scalable impact:

Up to 30% reduction in vehicle stops at intersections

Up to 10% reduction in emissions at optimised intersections

Reduced fuel consumption and congestion across urban networks

No need for new infrastructure investments

Additional benefits include:

improved travel time and traffic flow

lower operational costs for cities

rapid scalability across regions

Why This Matters

This use case demonstrates how digital technologies can unlock system-level efficiency gains in infrastructure-heavy sectors.

Key insights:

AI enables real-time optimisation of complex urban systems

Data-driven solutions can deliver immediate emissions reductions

Scalable, low-cost deployment accelerates adoption globally

Most importantly, it shows how digital innovation can translate into measurable, real-world impact, aligning with the Digital with Purpose approach of moving from ambition to implementation.