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AI Planning for Integrated Urban Traffic Control

An AI planning system will be used for urban traffic control, leveraging the opportunities arising from connected autonomous vehicles.

Categories

Business Category
Transportation
Technical Category
Planning and scheduling

What is the challenge that is being addressed?

Current urban traffic control techniques are restricted to operational tools such as traffic lights management and variable message signs.

The advent of Connected Autonomous Vehicles (CAVs) presents a unique opportunity for a fundamental change in urban traffic control. CAVs hold the promise of significant benefits in terms of accident prevention, decreased carbon emissions, time savings, and better traffic control. Vehicle to infrastructure communication (V2I) capabilities of CAVs can provide a new range of tools for urban traffic controllers to affect traffic conditions: CAVs can provide information about traffic conditions, and can receive information about the best route to be followed to reach their destination.

In this context, we are looking to extend the capabilities of the smart AI-based approaches for traffic light optimisation, by including the management of CAVs as part of the management of planned and unplanned incidents in urban areas. The AI-based management combining traffic lights and CAVs route can allow to exploit the synergies between the two intervention tools, and support a more encompassing control of traffic in urban regions.

What is the AI solution the project plans to implement?

In the considered Urban Traffic Control scenario AI planning is used in response to unexpected traffic conditions. The idea is that a planning system is in charge of controlling a urban network, and has the possibility to communicate with traffic lights and CAVs in the region. The overall architecture would be based on the principle of exploiting as much as possible the existing traffic control infrastructure, to provide a complete knowledge model on which the AI planning engine can reason to generate solutions that can improve mobility in the controlled region by exploiting the synergies between traffic light optimisation and CAVs routing.

Who will help implement this solution?

This work is partly supported by the UKRI Future Leaders Fellowship AI4UTMC and the AIPlan4EU project, and will be developed in collaboration with Simplifai Systems limited and the Kirklees Council traffic authority.

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