Distributed Intelligence and Technology for Traffic and Mobility Management

The transport sector is expected to alter shape in the coming decades.

This transition is driven by user-centred mobility services, integrated and intelligent transport networks, pricing and payments, automation, safety and security, as well as public and private innovation.

Next to Big Data and Artificial Intelligence, these developments provide major opportunities, but also increase system complexity.

The overarching aim of DIT4TraM is to develop, implement and test a generic distributed control paradigm, applicable at the level of traffic operations, mobility management, demand-supply synchronisation and shared mobility, including advanced monitoring, estimation and (machine learning) forecasting technology, and associated algorithms for a variety of novel multi-modal management and mobility concepts operating at all urban scales.

A holistic approach to decentralisation, distribution and mechanism design for monitoring and control is proposed aiming to achieve social optimality, yet with only necessary information exchanges, which is further translated into four key application fields corresponding to four interlaced urban scales carefully selected to ensure that all relevant challenges are tackled.

Pilots in several cities across Europe are organised to test DIT4TraM concepts and assess market potential and design business models.

Our vision is to support the transition to seamless and sustainable connected and autonomous mobility by disentangling the system components to the highest extent possible, yet ensuring sufficient cooperation and emergent coordination by smart system design, leading to liveability, safety, resilience, efficiency, as well as privacy, participation, fairness and sustainability on a city scale.

The DIT4TraM partnership (4 Universities, 5 Industrial partners, 2 RTOs, 3 stakeholders), has been formed to address the combination of technical, organisational, and implementation challenges to develop and successfully test the proposed solution.