Designing an Experimental Platform to Assess Ergonomic Factors and Distraction Index in Law Enforcement Vehicles...

Area of Science:

• Human Factors Engineering
• Occupational Safety
• Transportation Safety

Background:

• Mission-based driving presents unique safety challenges for law enforcement officers.
• Poorly designed Driver-Vehicle Interfaces (DVIs) in police vehicles contribute to driver distraction.
• Aftermarket equipment often exacerbates DVI issues, leading to operational errors.

Purpose of the Study:

• To develop and evaluate a system for optimizing the Driver-Vehicle Interface (DVI) to reduce distraction in law enforcement vehicles.
• To enhance occupational driver safety during mission-based operations.
• To create a data-driven approach for monitoring and mitigating driver distraction.

Main Methods:

• Development of a specialized driving simulation platform for law enforcement vehicles.
• Strategic selection and placement of sensors (dashboard, steering wheel, controls) for monitoring driver behavior.
• Integration of sensors with existing vehicle systems, prioritizing accuracy and reliability.
• Implementation of a supervised machine learning model to predict driver distraction levels.

Main Results:

• The system successfully integrates sensors to capture real-time driver interaction data.
• A machine learning model was devised to evaluate driver distraction.
• The sensor placement aims to provide comprehensive monitoring without compromising ergonomics.

Conclusions:

• Optimizing the Driver-Vehicle Interface (DVI) is critical for reducing law enforcement driver distraction.
• The developed sensor system and machine learning model offer a promising approach to enhance safety.
• Further research on sensor configuration and integration is recommended to validate DVI improvements for safer mission-based driving.