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Predicting and avoiding road crashes based on Artificial Intelligence (AI) and big data

This call aims to develop AI-enabled methods and tools to predict safety-critical traffic situations at quantifiable risk levels based on real-time and historical data. Projects should create an AI-enabled digital twin of traffic and infrastructure, analyze technical challenges associated with data acquisition and processing, develop methods to predict safety-critical situations, and demonstrate the feasibility of risk predictions and targeted interventions. The objective is to enable proactive road safety management by identifying high-risk locations and situations before crashes occur, allowing road authorities to deploy appropriate countermeasures proactively.

Opening Date: 16 September 2025
Deadline: 13 January 2026

Data provided by Sciencebusiness.net

This funding opportunity represents a pre-agreed draft that has not yet been officially approved by the European Commission. The final, approved version is expected to be published in the first quarter of 2025. This draft is provided for informational purposes and may be used to preliminarily form consortia and develop project ideas, but it is offered without any guarantees or warranties.

Expected Outcome

Projects are expected to provide knowledge of high-risk locations before crashes occur, enable predictive identification of safety-critical situations, enhance monitoring of traffic flows, and develop methods for real-time crash prediction and prevention.

Scope

The call focuses on leveraging AI and big data to predict and prevent road crashes. Proposals should develop an AI-enabled digital twin integrating various data sources, address challenges in data acquisition and processing, develop methods to predict safety-critical situations, analyze biases in datasets, and explore real-time countermeasures. Collaboration with stakeholders to build consensus on deployment routes is encouraged.

Partner Requests

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