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Safety and Mobility Optimization via Virtual Environments Lab

Project description

Rolling out an accident prediction framework

As automated vehicles become more common, tackling road safety is more important than ever. The ERC-funded SafeMoVE project aims to improve how we assess road safety in environments where connected vehicles share the road with more vulnerable users, such as cyclists and pedestrians. SafeMoVE will test a forward-looking approach that estimates the risk of accidents without past crash data. The project involves collecting data through cameras and drones, studying how different road users interact, and creating a reliable accident prediction model. It also plans to bring this system to market, targeting groups such as car manufacturers and policymakers. All of this supports the EU’s Vision Zero goal of ending road deaths by 2050.

Objective

SafeMoVE addresses critical gaps in road safety assessment methods, particularly as they pertain to mixed traffic scenarios involving connected and automated vehicles, vulnerable road users, and conventional road users. Building on the scientific advancements of SUperSAFE, SafeMoVE aims to validate and commercialize a universal, proactive methodology for traffic safety analysis. Unlike traditional approaches reliant on historical accident data, the proposed framework employs Extreme Value Theory and Surrogate Measures of Safety to analyse road user interactions, enabling predictions of accident risk without requiring prior crash data. The project encompasses four integrated phases: Data Collection (A1): Using stationary cameras, drones, and simulations to gather detailed exposure and interaction data in real-world and virtual environments; Data Analysis (A2): Extracting and analysing trajectories and interactions to compute SMoS, facilitating safety assessments for both existing and future infrastructures; Framework Development (A3): Validating a proactive methodology for accident prediction and road safety assessment in diverse traffic compositions and automation levels; and Exploitation and Market Exploration (A4): Commercializing the validated methodology through spinouts, targeting stakeholders such as car manufacturers, road authorities, and policymakers. SafeMoVE’s innovative framework aligns with the EU’s Vision Zero target to eliminate road fatalities by 2050. Its proactive approach enables timely safety evaluations, mitigating risks before accidents occur. The project introduces scalable solutions for infrastructure and vehicle safety assessments, fostering advancements in traffic safety research, policy, and industry practices. By integrating multidisciplinary expertise and addressing the challenges of mixed traffic systems, SafeMoVE aspires to revolutionise road safety methodologies and contribute to safer, more efficient transportation systems globally.

Fields of science (EuroSciVoc)

Programme(s)

Topic(s)

Funding Scheme

HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

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Call for proposal

(opens in new window) ERC-2025-POC

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Host institution

LUNDS UNIVERSITET
Net EU contribution
€ 150 000,00
Address
Paradisgatan 5c
22100 Lund
Sweden
Region
Södra Sverige Sydsverige Skåne län
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data

Beneficiaries (1)