Identifying Equipment Factors Associated with Snowplow Operator Fatigue

Abstract

A recent body of research in fatigue management indicates that other factors, including in-cab and external equipment, contribute to operator fatigue. The goal of this project was to identify winter road maintenance equipment (in-cab and external) that may increase or mitigate snowplow operator fatigue. To accomplish this goal, questionnaires from 2011 snowplow operators were collected from 23 states in the U.S. Results confirmed previous research that fatigue is prevalent in winter road maintenance operations. Winter road maintenance equipment that produced excessive vibrations, noise, reduced visibility, and complex task demands were found to increase snowplow operators' self-reported fatigue. Similarly, equipment that reduced vibrations and external noise, improved visibility, and limited secondary tasks were found to reduce snowplow operator's self-reported fatigue. Based on the questionnaire responses and the feasibility of implementation, the following equipment may help to mitigate or prevent snowplow operator fatigue: dimmable interior lighting, LED bulbs for exterior lighting, dimmable warning lights, a CD player or satellite radio in each vehicle, heated windshield, snow deflectors, narrow-beam auxiliary lighting, and more ergonomically designed seats with vibration dampening/air-ride technology.

Driver Drowsiness Multi-Method Detection for Vehicles with Autonomous Driving Functions

“…This was especially evident on days 3 and 4, and more so on day 4, as the route was well known and the driver did not pay as much attention to driving. According to [ 28 ], due to the rainy weather during the last two days of data collection, the driver’s state of fatigue may also have been accentuated by the use of windscreen wipers.…”

Challenges in Conducting Empirical Epidemiological Research with Truck and Bus Drivers in Diverse Settings in North America

“…Age has also shown correlation with employment patterns and safety-critical event risk [16]. Using previously collected data, Camden et al, classified drivers using employment data within one of the following employment statuses: (1) continuous employment, (2) multiple employment periods, (3) ceased employment following a crash, or (4) ceased employment not following a crash [14,16].…”

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