Inclusive Mobility Mapping: Enhancing Safety for Vulnerable Road Users (VRUs) with Reduced Mobility

Important results from the project

We first compiled literature on AI and safety research related to road users with reduced mobility. It then analyzed their motion patterns through interviews, video, and sensor data with 20 participants, highlighting diverse mobility challenges. A multi-sensor dataset was created to benchmark AI-based detection and tracking. Finally, a clear roadmap was developed to develop an inclusive, AI-driven traffic and infrastructure monitoring system to address real-world accessibility needs.

Expected long term effects

The project is expected to have long-term effects, including safer and more accessible urban environments for all. The inclusive AI-driven traffic and infrastructure monitoring system will help policymakers address infrastructure gaps and optimize mobility solutions. The crowdsourcing feature will amplify marginalized voices, fostering collaboration between citizens and decision-makers. These advancements promote equitable mobility, sustainable urban planning, and inclusive technology.

Approach and implementation

The project was implemented through four work packages. WP1 compiled AI and safety research related to road users with reduced mobility. WP2 collected and analyzed motion patterns and challenges of road users with varying abilities using interviews, video, and sensor data. WP3 developed a multi-sensor dataset to benchmark AI-based detection and tracking. WP4 created a roadmap for an inclusive, AI-driven traffic monitoring system. The team fostered strong collaboration throughout the project.