Researches

We developed an ATV safety test station for experimental evaluations of ATV stability and the performance of various roll bar designs on agricultural ATVs. CDC/NIOSH funded this project as part of the Western Center for Agricultural Safety and Health (WCAHS)'s five-year competitive renewal.

The study includes extensive infrastructure development, including a tilt table, autonomous ATVs, crash test terrain, crash tests, and extensive fieldwork to evaluate different models of ATVs and roll bars. The study includes four sections:

Static Stability

• Static stability is measured using wireless scales and digital inclinometers to determine ATV stability under different types, locations, and amounts of loads.

• This helps identify potential tipping points before an ATV becomes unstable.

Dynamic Stability

• Dynamic stability is measured using a sensing setup that includes IMU, and optical encoder under several tests, including J-turn, bump, and circular driving tests. 

• This helps identify potential tipping points before an ATV becomes unstable.
   

Rollover Simulation (Experimental)

• Use real ATVs in controlled environments to test rollover risks under different conditions (e.g., speed, load, terrain).

• Helps in evaluating the effectiveness of protective devices and rider safety techniques.
   

Rollover Simulation (Computational)

• Used computer simulations to predict the rollover risk

• Helps in providing recommendations for safer operational conditions for agricultural ATV users
   

Many agricultural ATVs are designed for adult male riders, creating reachability, strength, and control challenges for youth and female operators. Our research aims to identify mismatches between rider capabilities and ATV design, ensuring safer and more inclusive use of these vehicles.

The ATV Fitment & Safety Checklist is being developed to assist parents, employers, and guardians in evaluating whether an operator meets the physical requirements for safe ATV operation.

Check List Focus Area

• Appropriate ATV size recommendations 

• Minimum required strength levels

Key Research Findings

Extensive field testing, simulations, and ergonomic assessments revealed several safety concerns:

• Children and smaller operators struggle to properly reach and engage ATV controls, increasing incident risks.
• Break and steering force requirements often exceed their physical capabilities, making sudden stops and turns difficult.
• Field of view limitations impact hazard awareness and reaction time.
• There is a need for ATV design modifications for smaller riders.

Technology and Tools Used 

• Vive Tracking System – To captures the ATV dimensions with 1 mm accuracy for simulating ATV

Ergonomic Force Measurement

• Determine the minimum strength need to operate ATV controls
   

ATV Fitment App Development

• Provide step-by-step instructions for assessing the physical capabilities and readiness of youth operating a specific ATV

Funding and Collaboration

The youth research is funded by CDC/NIOSH as part of the National Children's Center for Rural and Agricultural Health and Safety (NCCRAHS) five-year renewal project. This project integrates findings from youth ATV safety studies and female operator ergonomic evaluations funded by a  Central States Center for Agricultural Safety and Health (CS-CASH) seed grant, ensuring that ATV design considerations accommodate a female operator. 

Why This Research Matters

• Improves ATV safety for youth and female agricultural workers by identifying physical mismatches.
• Reduces injury risks associated with poor reachability and control accessibility (reachability, strength and field of vision).
• Provides data-driven (personalized) recommendations for safer ATV operation 

AgroGuardian is an advanced safety system designed to predict, detect, and alert emergency responders or supervisors in the event of an ATV rollover incident. This innovative system enhances real-time monitoring and accident response, reducing the risk of serious injuries in agricultural settings.

Key Features:

• Rollover Prediction – Uses AI and sensor-based technology to assess ATV stability and issue warnings before a rollover occurs.
• Instant Detection – Monitors vehicle orientation, acceleration, and tilt angles to detect rollover events in real time.
• Emergency Notification – Sends immediate alerts to emergency contacts, family members (emergency contact), farm supervisors, or response teams in case of an accident.
• Data Logging & Analysis – Collects and stores ATV movement data for post-incident analysis and safety improvements.

How It Works:

• Sensors Continuously track ATV motion, analyzing stability in time

• When a high-risk maneuver or rollover is detected, the system triggers an alert.

• An emergency message is sent via wireless communication to pre-designated contacts.

• An emergency message is sent via wireless communication to pre-designated contacts.

Agricultural workers are at high risk for heat-related illnesses (HRI) due to prolonged exposure to high temperatures, direct sunlight, and strenuous physical activity. Heat stress can lead to heat exhaustion, heatstroke, and long-term health complications, impacting both worker safety and productivity.

Our research focuses on developing strategies to predict, monitor, and mitigate heat-related risks for farmworkers. This includes environmental monitoring, predictive modeling, and intervention strategies based on real-world data.

Key Research Area

• Environmental Monitoring – Installing and maintaining weather stations to measure temperature, humidity, solar radiation, and wind speed in agricultural fields.

Technology and Data Collection

• Four Weather Stations across California collect continuous environmental data.
   

The use of autonomous vehicles, robotics, and AI-driven technologies in agriculture has the potential to enhance productivity, reduce labor costs, and improve precision farming. However, these technologies also introduce new risks to worker safety and health, requiring proactive measures to ensure safe implementation and operation.

To address these concerns, our research team is conducting:

• Literature Reviews – Examining existing studies, standards, and regulations on automation risks and best practices in agriculture.
• Safety Assessments – Evaluating potential collision risks, sensor limitations, and operator-machine interactions.
• Pilot Projects – Investigating strategies to integrate autonomous technologies safely in farm environments.