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OPTIMUM · Project

Big Data Platform That Predicts Traffic Problems Before They Happen

transportPilotedTRL 7
optimumproject.eu

Imagine if your city's transport system could see traffic jams, delays, and breakdowns coming before they actually happen — like a weather forecast, but for roads and buses. OPTIMUM built a platform that pulls together data from sensors, social media, and transport networks, crunches it all in real time, and warns operators so they can act before problems pile up. It was tested in real cities including Vienna and the West Midlands. Think of it as giving transport managers a crystal ball powered by data instead of guesswork.

By the numbers
EUR 5,966,186
EU contribution for R&D
19
consortium partners
9
countries represented
53
total deliverables produced
8
demo deliverables with working software
11
industry partners in consortium
58%
industry ratio in consortium
The business problem

What needed solving

Cities and transport operators lose millions annually to traffic congestion, unpredictable delays, and reactive decision-making that only responds after problems have already caused damage. Current transport management relies on historical patterns and manual monitoring, missing the real-time signals from sensors, social media, and connected vehicles that could prevent disruptions. The result is excessive CO2 emissions, wasted fuel, frustrated passengers, and inefficient freight delivery.

The solution

What was built

OPTIMUM built a complete big data platform with several working components: a traffic forecasting engine for predicting congestion, real-time stream analytics for processing live data feeds, complex event processing for detecting transport disruptions as they emerge, a multi-modal data infrastructure handling video, audio, social media, and sensor data, personalization and recommendation services for travelers, and Car2X communication integration. All components reached final versions and were tested across multiple European pilot sites.

Audience

Who needs this

Public transport authorities managing bus/tram/metro networks in congested citiesFreight and logistics companies losing money to unpredictable urban congestionSmart city solution providers looking for proven predictive transport componentsHighway and motorway operators needing real-time traffic management toolsMobility-as-a-Service (MaaS) platforms wanting to add predictive capabilities
Business applications

Who can put this to work

Urban Public Transport
enterprise
Target: Public transport operators and municipal transit authorities

If you are a public transport operator dealing with unpredictable delays and passenger complaints — this project developed a traffic forecasting engine and real-time stream analytics platform that predicts disruptions before they occur. It was piloted across multiple European cities with 19 consortium partners. The system processes multi-source data streams to recommend proactive route adjustments and service changes.

Freight and Logistics
mid-size
Target: Freight carriers and fleet management companies

If you are a freight company struggling with congestion-related delivery delays and fuel waste — this project built a proactive charging pilot for freight transport that optimizes routing and toll pricing dynamically. The platform fuses sensor data, traffic feeds, and weather information to reroute vehicles before congestion hits. It was tested in real-world conditions as part of a EUR 5,966,186 EU-funded effort.

Smart City Technology
any
Target: ITS solution providers and smart city integrators

If you are a smart city technology provider looking for proven data fusion and predictive analytics components — this project delivered a scalable big data architecture with Car2X communication integration, tested in a 2nd-iteration pilot. The platform includes complex event processing, personalization engines, and multi-modal data infrastructure covering video, audio, social media, and structured transport data.

Frequently asked

Quick answers

What would it cost to implement this kind of predictive transport system?

The full R&D effort behind OPTIMUM was funded with EUR 5,966,186 in EU contribution across 19 partners. Actual deployment costs for a single city or operator would depend on existing infrastructure, but the modular architecture means you could adopt specific components (like the traffic forecasting engine) without the full platform.

Can this scale to a large city or national transport network?

The platform was specifically designed as a 'largely scalable, distributed architecture' for big data management. It was piloted in multiple real-world settings including Vienna and the West Midlands, demonstrating cross-city adaptability. The architecture handles multi-source data streams from sensors, social media, and transport systems simultaneously.

Who owns the intellectual property and can I license the technology?

The consortium of 19 partners across 9 countries jointly developed the platform, with the coordinator NETCOMPANY SA based in Belgium. IP ownership would follow the EU Horizon 2020 grant agreement terms, meaning each partner typically owns what they developed. Licensing discussions would need to go through the relevant consortium members.

How mature is this technology — is it ready for deployment?

OPTIMUM ran real-life pilots across multiple sites including Vienna, West Midlands, LPP, and ADRIA, with at least two iteration cycles. The project produced 8 demo deliverables and 53 total deliverables. Key components like the traffic forecasting engine and stream analytics reached final versions after pilot testing.

Does it integrate with existing transport management systems?

The platform was built for interoperability with modern transport systems, including a dedicated data infrastructure for ITS multi-modal data and social media streams. It includes Car2X communication integration tested in pilot conditions. The architecture is designed to connect with various sensors, systems, and service providers.

What data sources does it actually use?

The platform processes structured transport data, social media streams, video, audio, and sensor feeds. It includes complex event processing for real-time pattern detection and sentiment analysis from social media. All data modalities were integrated through a unified data infrastructure developed and tested during the project.

Are there regulatory considerations for deploying this in my city?

Based on available project data, the platform was deployed in compliance with regulations across 9 European countries during its pilot phase. Transport data privacy and social media processing would need to follow local data protection rules. The project addressed real-world deployment requirements through its multi-city pilot approach.

Consortium

Who built it

The OPTIMUM consortium is strongly industry-oriented with 11 out of 19 partners coming from industry (58% ratio), complemented by 4 research organizations and 2 universities. The partnership spans 9 countries across Europe, coordinated by NETCOMPANY SA from Belgium. With 4 SMEs in the mix alongside larger industry players, the consortium combined commercial deployment capability with research depth. The high industry ratio and multi-city pilot deployments suggest the technology was developed with real-world adoption in mind, not just academic publications.

How to reach the team

NETCOMPANY SA (Belgium) — contact through SciTransfer for a warm introduction to the right technical lead

Order a report on this consortiumSee NETCOMPANY SA profile →
Next steps

Talk to the team behind this work.

Want to know if OPTIMUM's predictive transport platform fits your operations? SciTransfer can arrange a direct conversation with the team that built it.

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