Predictive ApproacHes fOr SafEr UrBan Environments

Safer urban environments are needed for all road users to ensure the European targets to halve road deaths and injuries by 2030 are met. Vulnerable road users require specific attention in an urban environment that is subject to constant change as new forms of transport and micro-mobility enter the system.

Existing traffic simulation models allow changes in traffic conditions to be tested but are often vehicle and travel time focused and do not measure detailed outcomes specific to vulnerable road users and road safety. City administrations and transport managers will benefit from predictive tools that allow these changes and their implications for road safety, mobility, and sustainable transport to be anticipated, and support the associated policy, regulatory and consumer response.

The Predictive Approaches for Safer Urban Environments project (PHOEBE) will move beyond the state of the art and deliver an interdisciplinary solution that will integrate traffic simulation, road safety assessment, human behaviour, mode shift and induced demand modelling and new and emerging mobility and telematics data into a harmonised, prospective assessment framework for road safety. New conditions and mobility solutions will be able to be assessed and safe system solutions tested. The PHOEBE framework, software module and knowledge products will allow dynamic safety prediction and socioeconomic evaluation that is evidence-based and simulates future scenarios and impacts. Simple and effective visualisation and socioeconomic modelling will provide the confidence for policy decisions and investment.

City administrations across EU will be consulted as the framework is developed and deployed. The feasibility of the framework will be demonstrated in three use cases in Athens (GR), Valencia (ES) and West Midlands (UK), which have been selected to maximise the use of existing base traffic models, potential impact and to ensure the future scalability and transferability of the solution.