A near miss can be defined as a dangerous interaction between at least two road users that could have led to a collision, but didn’t.

Using AI-powered computer vision sensors to collect traffic data on different road user types, Viva has developed a way of automatically detecting near miss interactions. It builds on state of the art research to quantify near misses, analyzing trajectories of road users in time and space and how they relate to each other.

The feature’s first version focuses on near misses between drivers and cyclists, who are one of the most vulnerable road users. Near miss experiences can discourage people from cycling at a time when governments seek to increase active travel levels.

Viva’s Near Miss data is an alternative measure to prevent incidents, create safer environments for vulnerable road users, and promote cycling as a result.

Cyclist's Way Blocked

When a cyclist’s way is blocked by an obstruction e.g - a parked car

Problematic Pass

When a motorist gives too little space when overtaking a cyclist

Vehicle Pulling Out

When a driver pulls out or in across another vehicle's path

Make the right decisions with trusted data

Near Miss provides objective and unbiased data through consistent near miss measurements.

Support evidence-based decision making

Justify expenditure on road safety interventions and prove results to stakeholders.

Discover road safety hazards & intervene early

Understand where, when, why, and how near miss interactions are taking place and proactively intervene.

Post-intervention analysis

Compare near miss counts before and after an intervention to measure effectiveness.