Quantifying driver's field-of-view in tractors: methodology and case study

Area of Science:

• Ergonomics and Human Factors
• Agricultural Engineering
• Human-Computer Interaction

Background:

• Visual awareness is critical for vehicle operation, especially in complex tasks like tractor driving.
• Tractor operation involves dynamic body postures to maintain adequate Field-of-View (FoV) during tasks like ploughing.
• Current FoV analysis relies on Digital Human Model (DHM) simulations, providing only a qualitative 'eye view'.

Purpose of the Study:

• To introduce a novel approach for quantitative analysis of driver Field-of-View (FoV) in tractor cockpits.
• To enhance the evaluation and comparison of tractor cockpit designs based on driver needs.
• To provide engineers with tools for improving tractor design for optimal driver visibility.

Main Methods:

• Development of a new quantitative analysis method for Field-of-View (FoV).
• Application of the method to three distinct tractor models as case studies.
• Integration of quantitative data into existing Digital Human Model (DHM) simulation outputs.

Main Results:

• The new method provides quantitative data to supplement traditional 'eye view' simulations.
• Demonstrated the applicability and effectiveness of the approach across different tractor models.
• Identified potential areas for design modification to improve driver FoV and ergonomics.

Conclusions:

• The proposed quantitative analysis method offers significant improvements over current FoV assessment techniques.
• This approach aids engineers in making data-driven design decisions for tractor cockpits.
• Enhanced cockpit design can lead to improved driver performance, safety, and comfort.