Designing an Experimental Platform to Assess Ergonomic Factors and Distraction Index in Law Enforcement Vehicles during Mission-Based Routes.

Mission-based routes for various occupations play a crucial role in occupational driver safety, with accident causes varying according to specific mission requirements. This study focuses on the development of a system to address driver distraction among law enforcement officers by optimizing the Driver-Vehicle Interface (DVI). Poorly designed DVIs in law enforcement vehicles, often fitted with aftermarket police equipment, can lead to perceptual-motor problems such as obstructed vision, difficulty reaching controls, and operational errors, resulting in driver distraction. To mitigate these issues, we developed a driving simulation platform specifically for law enforcement vehicles. The development process involved the selection and placement of sensors to monitor driver behavior and interaction with equipment. Key criteria for sensor selection included accuracy, reliability, and the ability to integrate seamlessly with existing vehicle systems. Sensor positions were strategically located based on previous ergonomic studies and digital human modeling to ensure comprehensive monitoring without obstructing the driver's field of view or access to controls. Our system incorporates sensors positioned on the dashboard, steering wheel, and critical control interfaces, providing real-time data on driver interactions with the vehicle equipment. A supervised machine learning-based prediction model was devised to evaluate the driver's level of distraction. The configured placement and integration of sensors should be further studied to ensure the updated DVI reduces driver distraction and supports safer mission-based driving operations.

Evaluation of advanced curve speed warning system to prevent fire truck rollover crashes.

INTRODUCTION: A disproportionately high number of deadly crash-incidents involve fire-tanker rollovers during emergency response driving. Most of these rollover incidents occur at dangerous horizontal curves ("curves") due to unsafe speed. This study examined the effects of a curve speed warning system (CSWS) on fire tanker drivers' emergency response behavior to develop system improvement suggestions. METHOD: Twenty-four firefighters participated in driving tests using a simulator. A fire tanker model, carrying a full tank of water, was used in emergency driving tests performed with and without CSWS. The CSWS was designed using the algorithm for passenger vehicles with a few initial modifications considering the unique requirements of heavy fire tanker and emergency driving. RESULTS: The results indicated that the CSWS was effective in issuing preemptive warnings when the drivers were approaching curves with unsafe speed during emergency response. Warnings occurred more frequently at curves with smaller radius. Although the CSWS improved driving performance, it did not significantly reduce the number of rollover events. A detailed analysis of the rollover events provided suggestions for improvement of CSWS algorithms. CONCLUSIONS: To further improve the CSWS algorithm, the following may be considered: including increased safety speed margin below the rollover critical speed, moving the speed warning trigger from the curve apex to the curve entry point, extending the safe speed-control zone to cover the entire curve, and employing artificial intelligence to accommodate individual driving styles. PRACTICAL APPLICATIONS: Fire tankers continue to be at increased risk of rollover during emergency response due to unsafe negotiation of dangerous curves. Development and use of advanced driver assist systems such as CSWS evaluated in this study may be an effective strategy to prevent deadly rollover crash-incidents. The knowledge generated by this study will be useful for system designers to improve the CSWS specifically designed for heavy emergency vehicles.

Evaluation of advanced curve speed warning system for fire trucks.

A curve speed warning system (CSWS) for firetrucks was developed and tested in this study. The CSWS algorithm was developed based on guidelines in the public domain for general vehicles and modified for firetrucks for their configuration and emergency driving. Twenty-four firefighters participated in the test in a driving simulator. The results show that the CSWS was effective in issuing preemptive warnings when the drivers were approaching curves with unsafe speed during emergency responses. Drivers reduced their driving speed at curve approaching and entering phases for most challenging curves, without affecting the overall time in completing the test route. Drivers had reduced number of severe braking and decreased average in-curve distance traveled over the safety speed limits, when the CSWS was in use. Drivers also rated the CSWS as assisting, effective and useful. In summary, the CSWS can enhance firetruck safety during emergency driving without sacrificing drivers' precious response time.

Occupational injuries in Ohio wood product manufacturing: a descriptive analysis with emphasis on saw-related injuries and associated causes.

BACKGROUND: Stationary sawing machinery is often a basic tool in the wood product manufacturing industry and was the source for over 2,500 injury/illness events that resulted in days away from work in 2010. METHODS: We examined 9 years of workers' compensation claims for the state of Ohio in wood product manufacturing with specific attention to saw-related claims. For the study period, 8,547 claims were evaluated; from this group, 716 saw-related cases were examined. RESULTS: The sawmills and wood preservation sub-sector experienced a 71% reduction in average incidence rate and an 87% reduction in average lost-time incidence rate from 2001 to 2009. The top three injury category descriptions for lost-time incidents within saw-related claims were fracture (35.8%), open wounds (29.6%), and amputation (14.8%). CONCLUSIONS: For saw-related injuries, preventing blade contact remains important but securing the work piece to prevent kickback is also important.