Methods of Collecting and Analyzing Rearward Visibility Data for Agricultural Machinery: Hazard and/or Object Detectability

J Agric Saf Health. 2017 Jan 26;23(1):39-53. doi: 10.13031/jash.11738.

Abstract

Recent interest in rearward visibility for private, construction, and commercial vehicles and documentation of rearward runovers involving bystanders outside the field of vision of the vehicle operator led to an investigation into the need for enhanced methods of rearward visibility for large, off-highway, agricultural equipment. A review of the literature found limited relevant research and minimal data on incidents involving rearward runovers of bystanders and co-workers. This article reviews the findings regarding the methods identified and tested to collect and analyze rearward visibility data, from the operator's perspective, for large self-propelled agricultural equipment, including the four-wheel drive tractors, combines, agricultural sprayers, and skid-steer loaders that are increasingly found on agricultural production sites. The methods identified, largely drawn from research conducted on private and commercial vehicles, were tested to determine their application in identifying rearward blind spots. These methods are described, and the findings from field-testing of specific machines are provided. Recommendations include establishing an appropriate engineering standard regarding rearward visibility of agricultural equipment with limited rearward vision and the use of rearward alarm systems for warning bystanders of rearward movement.

Keywords: Blind spot; Bystander; Camera; Detection; Hazard; Limited vision; Machine vision; Measurement; Mirrors; Rearward; Self-propelled machinery; Testing; Vision.

MeSH terms

  • Accidents, Occupational / prevention & control*
  • Agriculture*
  • Engineering
  • Equipment Design
  • Equipment Safety
  • Ergonomics*
  • Humans
  • Mobile Applications*
  • Vision, Ocular*