Autonomous driving and passenger injury risk: experiment and simulation (Adires)

Postdoc Project

Project Description

Neck injury, commonly known as whiplash, is common and costly: whiplash is the most commonly reported automobile-related injury, affects women more often than men, and can result in long-term chronic pain. New types of whiplash injuries are likely to occur in autonomously driven cars because passengers may not be facing forwards, nor looking at the road. The risk posed by these new types of whiplash injury is unknown.

Predicting whiplash injury is essential to protect passengers yet is challenging because a mechanical crash dummy's neck is a poor analogue for a human neck. The movement of the head and neck are highly dependent on the activity of the neck muscles: active muscles can generate vastly more force than passive muscles during the lengthening. Since a mechanical crash dummy cannot be endowed with biological muscle, we are left using computer simulation to predict the risk of injury posed by novel crash scenarios. Unfortunately, contemporary muscles models lack the mechanisms required to produce enhanced forces during active lengthening.

We plan to address these two problems using a novel in-vivo experiment of head and neck movement, and by developing a new muscle model that can reproduce forces during active lengthening. In Europe's largest driving simulator, we will measure the kinematics and electrical muscle activity as participants are accelerated forwards, backwards, and, most importantly, to the side. This will not only allow us to measure the movements of the head and neck during strong accelerations, but will also allow us to measure the activity, and reflexes of the muscles throughout these movements. Next, we will improve the accuracy of the muscle model's response during active lengthening by including a model of cross-bridge viscoelasticity and an elastic model of titin. This muscle model will be used to simulate our experiments to assess the accuracy of our simulations. Finally, we will use this model to assess the risk of whiplash injury in crash scenarios that are realistic, and too dangerous to attempt in an in-vivo experiment.

To help others extend our work, we will make the data from the measurements and the models we develop available through DaRUS. These resources will provide a valuable link to the Innovation Campus Mobility as well as the automobile industry around Stuttgart.

Project Information

Project Name Autonomous driving and passenger injury risk: experiment and simulation (Adires)
Project Duration December 2021 - May 2024
Project Leader Tobias Siebert
Norman Stutzig
Jörg Fehr
Project Members Matthew Millard, PostDoc Researcher
Project Partners Christian Holzapfel, Research Institute for Automotive Engineering and Vehicle Engines Stuttgart (FKFS)


F. Kempter, L. Lantella, N. Stutzig, J. Fehr, and T. Siebert. Potential to volunteer testing using a driving simulator with motion capture and emg data acquisition. In Proceedings of the IRCOBI Conference, Munich, Germany, 2021.
Short communication: Potential to Volunteer Testing Using a Driving Simulator with Motion Capture and EMG Data Acquisition (

F. Kempter, J. Fehr, N. Stutzig, and T. Siebert. In The 5th Joint Int. Conference on Multibody System Dynamics (IMSD 2018) , Lisboa, Portugal, 2018.
IMSD2018_Full_Paper_15.pdf (

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