Systematic and orchestrated deployment of safety solutions in complex urban environments for ageing and vulnerable societies

Informazioni relative al progetto

SOTERIA

ID dell’accordo di sovvenzione: 101077433

DOI

10.3030/101077433

Progetto chiuso

Data della firma CE 30 Agosto 2022

Data di avvio 1 Novembre 2022

Data di completamento 30 Aprile 2026

Finanziato da

• Climate, Energy and Mobility

Costo totale

€ 3 319 325,01

Contributo UE

€ 3 319 325,00

Coordinato da

NETCOMPANY S.A.
Luxembourg

Periodic Reporting for period 2 - SOTERIA (Systematic and orchestrated deployment of safety solutions in complex urban environments forageing and vulnerable societies)

Periodo di rendicontazione: 2024-05-01 al 2025-06-30

Sintesi del contesto e degli obiettivi generali del progetto

Although the European roads are the safest in the world, 20 634 people lost their lives in 2022 with almost 70% of fatalities in urban areas being vulnerable road users (VRUs). The EC has adopted the Road Safety Policy Framework 2021 – 2030, as part of its efforts to halve the number of fatalities by 2030. However, progress in reducing fatality rates remains below the interim target of 50%, a milestone on the way to achieve close-to fatalities by 2050, the so-called "Vision Zero". At the same time, more and more people opt for active forms of mobility for reasons of personal health and fitness or for environmental considerations. Measures and policies promoting active mobility are considered a game changer in reducing CO2 emissions and congestion in urban areas. But safety needs to be systematically taken into consideration. Improved road infrastructure and lower speeds, for example, have the capacity to reduce the impact of collisions that may occur. SOTERIA aims to accelerate the attainment of “Vision Zero” goals by providing a framework of models, services and tools that enable data-driven urban safety intelligence. Project partners are working towards designing solutions that promote safe and green travelling for VRUs, foster integration of electric micro-mobility in urban environments and enable inclusive transport for all road users. Their aspiration is to achieve road safety equality for the ever-changing urban mobility scene where disruptive services and complex needs necessitate innovative solutions. Project partner’s mission is to uncover unexplored behaviours of VRUs and engage Living Lab (LL) communities in the co-creation of urban safety solutions. Simulation models for the safety of public spaces and accident analysis as well as data-driven routing applications leveraging explainable Artificial Intelligence (XAI) are developed. A platform of interconnected services is designed to determine risk-free routes, improve the visibility of VRUs to motorised vehicles, inform VRUs of potential hazards and nudge them towards safer behaviours.

Lavoro eseguito dall’inizio del progetto fino alla fine del periodo coperto dalla relazione e principali risultati finora ottenuti

During Months 19 to 32, SOTERIA partners advanced the development, testing, and refinement of road safety solutions for VRUs across the four LLs in Germany, Greece, Spain, and the United Kingdom. Building on the co-creation foundations laid in the first phase of the project, targeted stakeholder engagement continued through workshops, surveys, and pilot demonstrations. New user groups such as motorised courier driverss and shared e-bike users were included, and feedback from over 2000 individuals informed refinements to solution specifications and use cases.The integrated SOTERIA platform matured significantly, with enhanced modules for accident analysis, safe routing, and situational awareness. The Safe Mobility Data Space (SMDS) was upgraded with 22 new datasets and 9 smart data models covering accident hotspots, harsh driving events, and travel demand. Comprehensive Knowledge Archive Network (CKAN) and Eclipse connectors were deployed to support secure data sharing. The labelled graph and visualisation dashboard were expanded to include temporal and user-specific safety indicators. Accident prediction capabilities were strengthened through the deployment of deep learning models and generalised linear models (GLMs). These models incorporated connected vehicle data and travel demand segmentation to estimate accident frequency and severity across road sections and intersections. The XAI module was updated to ensure transparency and interpretability of predictions, using techniques such as GNNExplainer and GraphLIME. Two sensor kits were upgraded to capture motion, environmental, and proximity data from micro-vehicles. These kits, along with the REBO dashcam system, were deployed in the SOTERIA netowrk of eight European cities to collect real-world data on near-misses and hazardous conditions. The data supported the development of the speed advisory module, which provides real-time alerts to VRUs based on road and environmental risks. A suite of safety services was implemented, including the micromobility hazard mapper, protective equipment assessment module, and a nudging engine that delivers multilingual, context-aware safety messages. The mobile application was redesigned with improved user interface / user experience, accident hotspot overlays, and journey logging features to support user engagement and impact tracking. The first round of demonstrations was completed in all LLs, validating seven core solutions (measures) and informing improvements for the second round. Dissemination activities expanded the stakeholder network while there were over 10 000 website visitors and 500 social media followers. Two national patents were granted, and an EU patent application was filed. Policy recommendations were drafted through a stakeholder workshop, aligning SOTERIA outcomes with Vision Zero goals and Sustainable Urban Mobility Plans.

Progressi oltre lo stato dell’arte e potenziale impatto previsto (incluso l’impatto socioeconomico e le implicazioni sociali più ampie del progetto fino ad ora)

During Months 19–32, SOTERIA advanced scientific innovation across key domains. In accident analysis, new smart data models and automated pipelines enabled refined hotspot detection and integration of connected vehicle and travel demand data. Deep learning models were enhanced for frequency and severity prediction. In XAI, techniques like GNNExplainer and GraphLIME improved interpretability of risk factors. Safe routing progressed with a dynamic engine combining accident risk, demand, and pollution data. Micro-vehicle safety systems were upgraded with advanced sensor kits capturing motion, proximity, and environmental data. Situational awareness services evolved through a connected mobility platform broadcasting user attributes, supported by infrastructure-based monitoring. These developments laid the groundwork for final testing and impact assessment in the concluding phase of the SOTERIA project.

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