Skip to content AI MOVE
Current public transport prioritisation relies on vehicle-installed transponders communicating with traffic lights, a system limited to municipal transport. This project proposes an innovative solution using CCTV cameras at intersections and transit zones to recognise and prioritise all high-occupancy vehicles, expanding efficiency across diverse transport providers. Our approach leverages advanced image recognition technology, enhancing traffic flow and pedestrian safety by dynamically managing urban crossings. By utilising existing infrastructure, this cost-effective method reduces complexity and broadens prioritisation benefits, contributing to smarter, more inclusive cities. This initiative significantly enhances public transport efficiency, aligns with intelligent mobility management goals, and promotes a more sustainable urban environment.
Project start:
Project end:
Budget:
Countries
Urban congestion costs the EU billions of euros a year; smarter and more inclusive transport management tackles inefficiencies and improves sustainability. It also makes public transport safer and faster, enhancing uptake as users have more favourable impressions.
The project implements AI-enhanced CCTV systems to dynamically prioritise public transport vehicles (including DRT providers), leveraging existing infrastructure for cost-effective, inclusive traffic management, reducing congestion, and improving urban mobility efficiency.
The project anticipates improved traffic flow, enhanced public transport efficiency, reduced emissions, cost-effective urban mobility, and equitable prioritisation, fostering sustainable, inclusive, and smarter city transport ecosystems.
Avigdor Luttinger
avigdor@itc.city
Updates
Subscribe to our newsletter to receive the latest news and insights.
