Background

Volvo Construction Equipment develops premium equipment with the vision of Building the world we want to live in. We are world leading in autonomous and electrified construction machines. Our machines are used during road building, mining, building schools and hospitals. Developing the best machines and having a global presence makes it possible for us to shape the future of the construction industry.

The operation of heavy-duty vehicles, such as haulers, wheel loaders and excavators, in challenging and dynamic environments like construction sites and quarries, can be demanding on equipment operators. These professionals often face multiple stressors, including environmental factors, extended working hours, and high noise levels, which can significantly affect their performance and decision-making. Understanding how these stressors impact operator behavior is crucial for safety, productivity, and overall efficiency. This project aims to explore these crucial dynamics through advanced simulation technology. 

Description

In Volvo CE Arena[1] at MITC[2], we have a setup of a Volvo Simulator[3] with a control PC that students can use to configure various driving scenarios. The work in this project involves utilizing the simulator to study the behavior of operators when exposed to varying levels of stress, fatigue, and noise. This analysis will include monitoring factors such as decision-making, reaction time, and situational awareness. By designing controlled scenarios that induce stress and fatigue in driving scenarios, such as time pressure, complex tasks, or unexpected events, operator behavior data can be collected and analyzed to identify patterns, correlations, and behavioral changes under different conditions. The result will be the foundation to increase the behavioral variance in the wheel loader driver model used for performance simulation. This work will be done in the context TRUST-SOS project[4].

The project is suitable for 2 students with good knowledge in modeling and simulation.

Some references:

1.  Rahman, H., Ahmed, M. U., & Begum, S. (2019). Non-contact physiological parameters extraction using facial video considering illumination, motion, movement and vibration. IEEE Transactions on Biomedical Engineering, 67(1), 88-98.
2. M. Mariajoseph, B. Gallina, M. Carli and D. Bibbo, "A Physiology-based Driver Readiness Estimation Model for Tuning ISO 26262 Controllability," 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring), Antwerp, Belgium, 2020, pp. 1-5, doi: 10.1109/VTC2020-Spring48590.2020.9129132.
3. Bibbo, D., Mariajoseph, M., Gallina, B., & Carli, M. (2022). A Novel Physiological-Based System to Assess Drivers’ Stress during Earth Moving Simulated Activities. Electronics, 11(24), 4074.

Volvo Construction Equipment in Eskilstuna (Volvo CE)

Mälardalen Industrial Technology Center in Eskilstuna (MITC)

Contact Persons:

Elianne Lindmark (Volvo CE) elianne.lindmark@volvo.com

Abdulkarim Habbab (Volvo CE) abdulkarim.habbab@volvo.com

Anas Fattouh (MDU) anas.fattouh@mdu.se

Sumaia Aldrea (MDU) sumaia.aldrea@mdu.se