Our projects

PANACEA

PracticAl and Effective tools to moNitor and Assess CommErciAl drivers’ fitness to drive PANACEA has 17 partners from 8 countries coming from multidisciplinary fields. The project will design, develop and test a holistic driving ability assessment system for commercial drivers

RE-ENGAGE

Driver re-engagement in autonomous driving by means of HMI adapted to human activity There are several challenges that need to be researched to create safe transition strategies in future vehicles. For example, it takes time to re-engage in the driving

A-HBM Step 5

The SAFER A-HBM5 project follows on from four previous projects; A-HBM steps I-IV, from 2008 to today. This is state-of-the-art research on car occupant muscle responses and development of active human body models (HBM) and is part of a continuous

Motorcycle rider model for injury prediction

Motorcyclists are one of the most vulnerable road user groups around the world; approximately 375,000 cyclists die riding motorized two and three-wheelers annually. The number of people riding motorcycles is growing worldwide and improving protection could potentially save lives and

Drone Lighting Systems: will it take off

Darkness is a well-known for increasing the risk of accidents for vulnerable road users. Johansson, Wanvik and Elvik (2009) concluded that the risk for cyclists increases by 55% in darkness, compared to daylight. This project aims to investigate how drones

ICV-SAFE

Testing safety of intelligent connected vehicles (ICV) in open and mixed road environment (ICV-Safe) Intelligent connected vehicles (ICV) are expected to bring immense societal benefits. For a safe introduction of such vehicles, a thorough safety assessment is required. Taking advantage

DRIVER

Valid information about the state of the driver will be paramount to enable future safe automated driving. Drivers that are fatigued or sleepy, highly stressed or are struck by a sudden disease, are causing a high proportion of fatal motor

SAFETY CULTURE AND AUTOMATION

This FFI pre-study is a follow-up of our SAFER pre-study Safety Culture For Automation In Transport Companies ( https://www.saferresearch.com/projects/safety-culture-automation-transp… ). Safety culture is the prevailing way of thinking and acting at a workplace in relation to risks and safety, i.e.

Experimental characterization of soft (adipose) tissue rate-dependent response

An important restriction in the current Finite element human body models (FE-HBMs) is the material models implemented, as biofidelity is sacrificed to accommodate computationally stable models. But also, because experimental data on tissue level is much lacking for the development

AI ROAD SIDE - Recommendation for methodology on AI-based Road-side object identification

The project aims to investigate and specify the Swedish Transport Administration’s requirements for Road-side image processing, e.g. what is state of the art and what has already been done, are there existing solutions we can further utilize? Possible data scources,

Cooperative Automated Driving Use Cases for V2X Communication

Advanced Driver Assistance Systems (ADAS) and autonomous driving (AD) are progressing towards higher speeds and more complex dynamic scenarios, where the on-board sensor systems may not be sufficient to provide adequate awareness of traffic situation for accurate and timely situation

HAVOC

Heavy Automated Vehicle Operation Center (HAVOC) - Requirements and HMI design This project addresses a portion of numerous human behavior challenges identified in a recent SAFER-prestudy (Human factors related to remote control of automated heavy vehicles). The aim is to

Virtual reality interactions with autonomous vehicles

Re-SAFE focuses on using virtual reality (VR) to study interactions with connected and automated vehicles (CAVs) from the perspective of a vulnerable road user (VRUs). The project is based in the newly established virtual reality hub on Traffic Safety at

SAFETY DATASET FOR TRAINING AND VALIDATION OF AI PERCEPTION FUNCTIONS IN AD AND ADAS

Project B-0012 within SAFER's Open Research at AstaZero Program. Goals and Purposes The goal of this project is to evaluate crucial experimental properties and data collection configurations for establishing a safety dataset that can be used for AI training and

Evaluation of a fragrance system to counter sleepiness at the wheel

Driver fatigue is a major cause of car accidents, and the prevention of fatigue is a major goal in the automotive industry. To reach the goal of zero traffic-accident fatalities, developing innovative solutions to prevent fatigue is a key objective.

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

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

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