QUADRAE

Project manager
Mats Petersson
Period
2016-01-01 - 2020-12-31

As technologies for active safety and vehicle automation grow ever more complex, it becomes increasingly important to complement traditional methods for testing these systems with virtual tests, based on computer simulations.

The FFI QUADRA project (2010-2014) addressed this general topic, with a focus on driver behaviour models. QUADRÆ (Quantitative Driver Behaviour Modelling for Active Safety Assessment Expansion), will expand beyond QUADRA by (1) developing and validating driver models for a more complete coverage of prioritised pre-crash scenarios and support systems, including scenarios with transitions from semiautomated driving, (2) carrying out selected virtual tests, including safety benefit assessments and system parameter tunings, and (3) advancing the general knowledge on how to best do virtual testing. To achieve these goals, QUADRÆ will focus on well-defined test-cases, cooperate with industrial function developers and testers, adopt proven models from psychology and neuroscience, conduct experiments with human drivers, and use state-of-theart databases of actual crashes.

Short facts

Project title: QUADRAE
Project type:
Research area:
Road user behaviour
Financier(s):
Period:
-

Project publications

An existing modelling framework is leveraged to create a driver braking model for use in simulations of critical longitudinal scenarios with a slower or braking lead vehicle. The model applies intermittent brake adjustments to minimize accumulated
Author(s)
Svärd, M., Markkula, G., Engström, J., Granum, F., & Bärgman, J.
Published in
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Year of publication
2017
Although an automated vehicle may operate for an extended time, it may suddenly request a user's intervention in critical situations-those beyond the system's operational design domain. Despite the proliferation of studies to understand how users resume
Author(s)
Morando, A., Victor, T., Bengler, K., & Dozza, M.
Published in
Manuscript in preparation for journal submission
Year of publication
2019
Visual time-sharing (VTS) behavior characterizes an inattentive driver. Because inattention has been identified as the major contributing factor in traffic crashes, understanding the relation between VTS and crash risk could help reduce crash risk through the
Author(s)
Morando, A., Victor, T., & Dozza, M.
Published in
IEEE Transactions on Intelligent Transportation Systems
Year of publication
2019
This paper introduces a reference model of glance behavior for driving safety assessment. This model can improve the design of automated and assistive systems. Technological limitations have previously hindered the use of unobtrusive eye trackers to
Author(s)
Morando, A., Victor, T., & Dozza, M.
Published in
IEEE Transactions on Intelligent Transportation Systems
Year of publication
2018
Author(s)
Bianchi Piccinini, G.F., Lehtonen, E., Forcolin, F., Engström, J., Albers, D., Markkula, G., Lodin, J., & Sandin, J.
Published in
Human Factors (submitted)
Year of publication
2018

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