Project

Multimodal Data for Road User Behavior Analysis to Support Safe Driving Patterns

Period
1 January–30 September 2021
Project manager
Yacine Atif

Human-operated vehicles with Advanced Driver-Assistance Systems (or ADAS) are projected to
prevent human-failures at the wheels. To support this purpose, driver state is estimated using
both internal factors such as fatigue, inattention and drowsiness levels, as well as external
roadway factors such as traffic volume and roadway configuration. The objective is to
formulate a predicted safety score based on the data at hands, to support automotive safety
solutions for car manufacturers and OEM providers, as well road safety at large, for
infrastructure authorities.
New synthetic information resulting from fusing authentic in-cabin and infrastructure data
contribute to a holistic safety score. The project builds a conceptual framework of risk
prediction involving driver behaviours under different road condition settings. This framework
could also augment mobility simulators to assess traffic under realistic safety settings.

Short facts

Research area
Road user behaviour
Financier(s)
SAFER Pre-Studies Phase 5
Partners
University of Skövde
Smart Eye
Project type
SAFER Pre-study