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ABOUT THE PROJECTS 

Improved Quantitative Driver Behavior Models and Safety Assessment Methods for ADAS and AD (QUADRIS)
QUADRIS is following the projects QUADRA and QUADRAE. This four-year project, running from April 1, 2021, to March 31, 2025, aims to enhance the development of advanced driver support systems and self-driving cars by refining safety assessment methods.

The project focuses on three main areas: developing methods to ensure simulated collisions are representative, creating validated driver models for run-off-road accidents, and expanding driver modeling to include self-driving cars through reference-driver models. These improvements will enable safer, faster, and more accurate safety benefit assessments during the development of ADAS and AD systems. QUADRIS will play a crucial role in maintaining the competitiveness of the Swedish automotive industry, especially as automated driving becomes a key factor in brand success.

V4Safety
The V4SAFETY method aims to enhance road safety by providing a reliable framework for evaluating various safety measures within Connected, Cooperative, and Automated Mobility (CCAM). By integrating driver models in virtual safety assessment, this framework will allow for a more detailed analysis of how different human behaviors and safety measures, including in-vehicle technologies and infrastructure changes, impact traffic safety. However, the inclusion of computational driver models does not ensure that the evaluation process can accurately simulate driving, crashing and the safety impact of new safety measures. That said, there are large benefits with behavior-model based virtual safety assessment, if it is done correctly and transparently. Simulation-based pre-crash safety assessment has the potential to save lives – helping us to move towards Vision Zero – by supporting the decision-making for a variety of stakeholders, from system developers, via policy makers, to consumers.

Car Passenger Protection – To the Next Level
This project aimed to advance the safety of car passengers by developing new knowledge and assessment tools for real-world seatbelt interactions. This initiative addressed the challenges posed by a diverse population, increased car automation, and shared mobility, which resulted in various seating positions and postures. The project focused on passengers aged 4 and older, using real-world crash data, virtual human body models, and international collaboration. Two doctoral students have been contributing to research on seating postures and crash safety. One PhD student has developed a family of human models, and the other PhD student has been developing methods to assess sitting comfort and postures. This project supported SAFER’s HBM platform and aimed to enhance Sweden's leadership in road safety research by linking human factors with injury protection in vehicle crashes.

Emergency vehicle approaching system
Emergency vehicles face risks from surrounding traffic. To support drivers' move-over behavior, this study, including a simulator experiment with 75 participant, tested an Emergency Vehicle Approaching (EVA) warning. This in-car alert notified drivers about 15 seconds in advance, giving them more time to move over safely. Eye tracking, combined with vehicle speed and placement measurements, examined the effects of EVA warnings on driver behavior. Previous studies only measured vehicle position and speed, but eye-tracking revealed how drivers' glance behavior changed with EVA warnings. Also, this study prepared for a naturalistic study in real traffic.

Cycling on rural roads – Removing barriers
This project aimed to enhance cycling safety and comfort on rural roads to support a sustainable transportation system. It focused on identifying barriers that make rural cycling unpleasant and proposed measures to improve the experience. The study used empirical data and workshops with relevant stakeholders to identify traffic environment barriers, such as difficult road crossings and high traffic intensity. Proposed measures were tested in a cycling simulator to capture cyclists' sensations, and a GIS-based tool quantified the effects of these measures. The project's long-term goal was to incorporate active travelers' experiences into transport system design, promoting increased cycling in rural areas, benefiting climate, public health, inclusion, and the ecosystem.

Belt use by pregnant women
The project aimed to enhance traffic safety for pregnant women by addressing the improper use of safety belts and evaluating the impact of comfort products on crash performance. Approximately 16% of pregnant women incorrectly used seatbelts, often relying on unregulated comfort products. The study, "Pregnant Women's Seatbelt Use: Impact of Comfort Products in Collisions," assessed the safety and efficacy of these products. Previous crash tests showed that most comfort products reduced seatbelt performance, with only one product maintaining safety standards. The project included creating virtual models of pregnant women and comfort products to improve understanding and recommendations. The results highlighted the need to re-evaluate and potentially regulate comfort products for pregnant women to ensure their safety.

Driver physiological monitoring for vehicle Emergency Response
The DrivER project aimed to enhance driver safety by developing physiological monitoring systems for emergency response in vehicles. The project focused on using unobtrusive sensors to detect driver sleepiness, stress levels, and sudden illnesses such as heart-related complications. Utilizing smart wearables, radar sensors, and sensors integrated into vehicle components, the study targeted both private and professional drivers. Conducted as part of the Connected Occupant Physiological Evaluation (COPE) concept, the project demonstrated proof-of-concept for these detection systems.

Safety performances of instrumented micro-mobility modes
The project aimed to enhance safety performance in shared micro-mobility services, particularly e-scooters, addressing public safety concerns and high insurance premiums. It sought to develop new methods and digital solutions to improve user safety by evaluating alternative safety measures beyond accident statistics, such as monitoring near misses using surrogate safety metrics. The main research question targeted in this pre-study was how to assess the safety performance of a trip using a shared micromobility mode. This included performing a review of the literature and the state-of-the-art and adopting a multi-disciplinary approach with experts from industry and research institutes to identify the research gaps and develop a practical and structured approach to address them. The findings intended to inform a larger project aimed at developing business models that incentivize safe behavior and implementing C-ITS services to promote safer riding practices.

RemoSafe
The project aimed to understand the needs, feasibility, and development of a remote monitoring system (RMS) adapted from driver monitoring systems, enhancing traffic safety in future transportation. Several workshops were held to explore current systems, map future remote operator work, analyze gaps, and disseminate results. The project supported enhanced collaboration in this field, identified needs, assessed feasibility, and produced a report summarizing workshop findings, contributing to a proposal for a larger subsequent project.