VRUdetection

Inspiration

Improve the security and visibility of Vulnerable Road Users.

What it does

Allow data based deep analysis of individual traffic streams to extend the Digital Twin of Ingolstadt with data of Vunerable Road Users with the ability to discern different types.

How we built it

Arduino based collection of ultra-sound distance sensor data. Aggregation based on signal processing algorithms on a Raspberry Pi. Data delivery to the cloud through a LoRa Shield.

Challenges we ran into

Getting reliable sensor data from cheap sensors.

Accomplishments that we're proud of

Stable detection different VRU types (Bike, e-Scooter, Pedestrian).

What we learned

Cool new Team. Coding & Engineering on a LoRa based system

What's next for VRUdetection

Use more sensor types (Lidar, Radar) to improve detection rates Use more sensors on different height levels to distinguish better (i.e. Adults/Children)

Built With

• c
• python