Predictive ApproacHes fOr SafEr UrBan Environments

Project Information

PHOEBE

Grant agreement ID: 101076963

DOI

10.3030/101076963

EC signature date 5 August 2022

Start date 1 November 2022

End date 31 July 2026

Funded under

• Climate, Energy and Mobility

Total cost

€ 3 368 933,75

EU contribution

€ 3 368 933,75

Coordinated by

EVROPSKI INSTITUT ZA OCENJEVANJE CEST - EURORAP
Slovenia

Periodic Reporting for period 2 - PHOEBE (Predictive ApproacHes fOr SafEr UrBan Environments)

Reporting period: 2024-05-01 to 2025-04-30

Summary of the context and overall objectives of the project

The EU-funded ‘Predictive Approaches for Safer Urban Environment’ (PHOEBE) project brings together the interdisciplinary power of traffic simulation and road safety assessment to increase road safety, focusing on those more vulnerable in traffic using active and micromobility. The PHOEBE framework combines research, data, and innovative tools and models to simulate and forecast the safety impact of disruptive changes, transitions or scenarios across urban transport networks. The 3.5-year- long PHOEBE project will apply and refine the framework in real-world scenarios across three pilot sites: Athens (GR), Valencia (ES) and West Midlands (UK).

The challenge: Recent European Union statistics on urban road fatalities suggest that even though road fatalities are constantly declining, still nearly 7500 fatalities were recorded in the EU27 in 2020. This number of urban fatalities represents around 40% of all road fatalities.The predominantly car-centric mobility planning of past decades create passenger car congestion in urban environments across the continent. Furthermore, lacking speed limit compliance, car-centric spatial design and reckless driving create a precarious or even dangerous urban landscape for pedestrians, cyclists, users of emerging mobility solutions and vulnerable road users. The latter group is facing significant challenges, as traffic flows might be too fast in urban environments or street spaces are too crowded. Therefore, the PHOEBE project is following the ambitious ‘Vision Zero’ goal that was formulated by the European Commission with the aim to halve the number of road fatalities by 2020 and a long term-goal to move close to zero fatalities by 2050.THE

The plan: PHOEBE is developing an integrated, dynamic human-centred predictive safety assessment framework for all road user types in urban areas. This will be achieved by bringing together traffic simulation, road safety assessment, data concerning human behaviour and mode shift, as well as demand modelling of new and emerging mobility data. The unique PHOEBE plan to develop integrated modelling and simulation tools to help cities to plan urban road safety measures. PHOEBE will be able to predict and assess safety impacts at the transport system level without the need for detailed simulation of the entire network by applying a simple Select - Simulate - Evaluate - Extrapolate approach. Overall, the results of PHOEBE can be used as a blueprint by other European cities to developed their own knowledge products, such as socioeconomic analysis model, urban road safety assessment, human behaviour and choice modelling. It will show how cities can establish and apply the predictive safety assessment framework in an efficient and cost-effective way, providing a theoretical guide on how it works, and how to implement it and knowledge products.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The PHOEBE project successfully developed a replicable methodological framework to simulate and forecast the safety impact of changes in urban transport networks. This framework integrates traffic simulation, road safety assessment, and behavioural and demand models to better predict safety impact of urban changes. During this review period, the project enhanced various components, including mode shift and human behavioural models, and integrated them into the Aimsun traffic simulation. Additionally, risk prediction safety models for urban networks were improved as well as the traffic simulation models and environment. This components was posterior integrated to apply and refine the Framework in real-world scenarios across three use cases: Athens, Valencia, and West Midlands. The results of the model developments and demonstrations can be seen in Deliverable D3.2 These demonstrations were supported by strong data foundations and innovative data sources mapped and gathered as part of WP2 and documented in Deliverable2.1 c and 2.2. The work allow the completion of several key objectives, including the development of a new methodology for dynamic safety prediction, harmonisation of safety definitions, and the integration of social components into risk assessments.

The project actively facilitated knowledge sharing through workshops, conferences, and dedicated events. These efforts aimed to disseminate the methodologies and tools developed to a broad range of stakeholders/ PHOEBE partners also engaged local stakeholders and collected feedback through workshops and reflection sessions, which contributed to the refinement and reapplication of models

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

The PHOEBE project is advancing beyond the state of the art in several key areas. A major innovation lies in the integration of risk assessments and social components into traffic simulation, enabling decision-makers to more straightforwardly assess safety performance indicators when simulating urban interventions that will later be implemented in European cities.
During the review period, the project team focused on integrating these components—an area that has traditionally been fragmented in current methodologies. Each component was also individually enhanced using innovative modelling techniques, such as the establishment of the crash × conflict relationship, and by leveraging emerging data sources like crowdsourced mobility data and AI/ML-derived features. This approach not only fills critical data gaps but also ensures the global applicability of data manipulation techniques.
The project introduced dynamic safety indicators that reflect how road safety risks fluctuate throughout the day. This allows for granular safety analysis, helping decision-makers identify and address specific concerns at different times, leading to more targeted, effective and innovative interventions.
An important part of this integrated framework is creating a set of common safety indicators across all components and harmonising them so that the links between the components are seamless, something that, from the best of our knowledge, was never done before. In addition and during the development of this framework, special attention is given to the vulnerable road users (VRUs) and new emerging modes of transport (e.g. micro-mobility), something still not well explored in the road safety literature.