BXA VanGuard
Empowering Women with Smart, Safe, and Informed Navigation.
Challenge
How can the safety of women in autonomous public transport be strengthened?
Autonomous driving in local public transport offers great potential for the mobility of the future. What needs to be considered for the objective and/or subjective safety of women* in public transport with a focus on autonomous driving?
Team
Xinjie Jiang, Viswanath Amrutha
About the prototype
VanGuard integrates transport and crime data from institutions into its mobile app and in-vehicle kiosk system. The app, integrated with BVG Muva, uses an AI model for predictive analytics and image-based monitoring. This AI-driven approach enables route planning focused on safety by identifying potential risks through AV sensors and feeding optimized routes into the autonomous vehicle's (AV) navigation system. The system synthesizes commuter feedback and area-based insights gathered through an in-app community, enhancing safety and user experience. Emergency services can also tap into this ecosystem for timely interventions. By collecting and harmonizing diverse data inputs, VanGuard prioritizes safety parameters in route planning, fostering a secure commuting environment. The loop of continuous data gathering, analysis, and feedback creates a robust framework for safer urban mobility.
Outputs
Further information about the progress, milestones, and roadblocks.
Impressions
