Proof of Concept for Hazard Prediction and Risky Decision Making Tests

Thu, 05/12/2022 - 14:13
Tests de predicción de peligros y toma de decisiones arriesgadas

The ability to predict road hazards allows us to respond to traffic events more effectively. Drivers with higher Hazard Perception skills are less likely to have an accident. Decision Making depends on how we self-assess our driving ability and how we measure risk while driving.

Cándida Castro Ramírez, researcher at CIMCYC, together with her team have constructed Danger Prediction and Decision Making tests. To do so, they have used realistic video recordings of traffic scenes. In these tests, the driver can play a passive role, such as when a pedestrian suddenly crosses the road, or an active role by making risky decisions such as running an amber light.

Hazard Perception and Decision Making were evaluated independently, using different 3D-dynamic environments to evaluate and train vehicle drivers. In this way, inexperienced drivers can learn to explore the road like an experienced driver without being exposed to real hazards.

This project also aims to analyze how drivers underestimate risk, with the help of the Decision Making Test in these immersive reality contexts.

90% of traffic collisions are due to human error, so virtual reality training programs allow drivers to expose themselves to risky situations but in a controlled environment, learning to detect them and acquiring skills so that when it happens in reality they can respond in the safest way.


-Cándida Castro Ramírez: @email

More information

Link to explanatory video