RobotCycle: Assessing Cycling Safety in Urban Environments

This paper introduces RobotCycle, a novel ongoing project that leverages Autonomous Vehicle (AV) research to investigate how cycling infrastructure influences cyclist behaviour and safety during real-world journeys. The project's requirements were defined in collaboration with key stakeholders (i.e. city planners, cyclists, and policymakers), informing the design of risk and safety metrics and the data collection criteria. We propose a data-driven approach relying on a novel, rich dataset of diverse traffic scenes captured through a custom-designed wearable sensing unit. We extract road-user trajectories and analyse deviations suggesting risk or potentially hazardous interactions in correlation with infrastructural elements in the environment. Driving profiles and trajectory patterns are associated with local road segments, driving conditions, and road-user interactions to predict traffic behaviour and identify critical scenarios. Moreover, leveraging advancements in AV research, the project extracts detailed 3D maps, traffic flow patterns, and trajectory models to provide an in-depth assessment and analysis of the behaviour of all traffic agents. This data can then inform the design of cyclist-friendly road infrastructure, improving road safety and cyclability, as it provides valuable insights for enhancing cyclist protection and promoting sustainable urban mobility.