Evaluation of Warning Methods for Remotely Supervised Autonomous Agricultural Machines

Abstract

HighlightsHumans who supervise autonomous agricultural machines require some type of warning to perceive abnormal conditions in the machine or its environment.Visual and tactile warnings were the most suitable warning methods for in-field and close-to-field remote supervision.This study will help improve the performance of remote supervisors and minimize unexpected incidents or liabilities during operation of autonomous machines.Abstract. As agricultural machinery moves toward full autonomy, human supervisors will need to monitor the autonomous machines during operation and minimize system failures or malfunctions. However, to intervene in an emergency, the supervisor must first recognize the emergency in a timely manner. Existing warning devices rely on the human visual, auditory, and tactile senses. However, these warning methods vary in their ability to attract attention. Hence, it is important to determine which warning method is best suited to draw the attention of a remote supervisor of an autonomous machine in an emergency. To achieve this objective, participants were recruited and asked to interact with a simulation of an autonomous sprayer. Seven warning methods (presented alone or in combinations of visual, auditory, and tactile sensory cues) and four remote supervision scenarios (in-field, close-to-field, farm office, outside the farmland) were considered in this study. The findings revealed that a combination of tactile and visual methods was most suitable for in-field and close-to-field remote supervision, in comparison to the other warning methods. However, there was insufficient evidence to recommend the best warning methods for supervisors at the farm office or outside the farmland. This study will help improve the performance of remote supervisors and minimize unexpected incidents during field operations with autonomous agricultural machines. Keywords: Agricultural machines, Remote supervision, User-centered design, Warning system.

Toward AI-enabled augmented reality to enhance the safety of highway work zones: Feasibility, requirements, and challenges

“…Like this work, studies in other fields have also attempted to answer this question within their respective contexts. For example, Edet et al [82] conducted a study in the context of autonomous vehicles in agriculture. In pursuit of their objective, their study employed a virtual simulation of an autonomous sprayer to measure the operator's reaction time to seven warning methods, which were presented either individually or in combinations of visual, auditory, and tactile sensory cues.…”

The Effect of Directional Tactile Memory of the Back of the User on Reaction Time and Accuracy

“…There are many applications where the elements of the environment need to be taken into consideration when performing a task, such as in semi-autonomous vehicles [34], flight control systems [35] and healthcare devices for surgery [36,37]; this is particularly important for for autonomous agriculture machine operators [38]; visually impaired individuals [39][40][41]; and construction workers [42]. In all these cases, tactile memory could potentially make performing the task more efficient and safe.…”

REDA: A New Methodology to Validate Sensor Systems for Person Detection under Variable Environmental Conditions

“…One variant for safeguarding autonomous machines is the use of supervisors who can observe the autonomous operation, intervene if necessary, and prevent dangerous situations. Various warning systems were tested in a study [ 2 ]. If these systems are to manage without a supervisor, the selection of sensor systems and the corresponding evaluation method is of decisive importance.…”