Where do riders stop, crash and break? And what can we learn from it?

Using data gathered from this summer's pilots, that is the exact question RouBack is setting out to answer. By turning real race data into actionable safety intelligence, we are transforming how the cycling world understands road hazards—helping protect riders and anticipate danger zones before the peloton arrives.

Phase 1: Mapping Hazards & Peloton Dynamics

Building on our summer pilot data, we are actively optimizing our automatic screening tool for upcoming races and try to understand the dynamics and behavior of the peloton. We are learning to pinpoint:

•  Which road features trigger heavy, unexpected braking
•  Which specific segments present the highest risk
•  The impact of positions in the group and the impact of the course on group dynamics
•  Which race situations and events lead to increased stress and risky behavior in the peloton
•  Where/when to strategically use warnings and/or place protection measures

Phase 2: Refining Crash Detection

Parallel to mapping the course, we are retraining and improving our core crash detection algorithms. Our goal is simple yet critical: eliminate false positives so the system only alarms when a rider truly hits the ground.

How can better data analytics improve race safety in your view?
Share your thoughts by emailing us at info@rouback.com!