A usability assessment of riding lawn-mowing equipment with varying levels of design standards compliance.

The use of riding lawn equipment (RLE) is related to a significant number of accidents every year. To provide basis for product design and enhance user performance and safety, a usability and performance assessment of modern riding lawn-mowing tractor designs and features was conducted in a real-world test environment. Five current commercially available RLEs were tested with response measures including task performance time and accuracy, physiological workload, system usability scores (SUS), and subjective rankings of RLE models. This data was used to identify sensitivity of responses to variations in RLE design features and functionality. The data was also used to assess the validity of new tractor design standard conformance tool, the RLEval methodology. This tool made comprehensive evaluation of RLE models compliance with over 70 specific design standards and was applied by human factors experts. Experiment results revealed sensitivity of all response measures to design differences among the five RLE models, except the objective workload measures. Response measures including task performance, SUSs and subjective rankings showed partial agreement with the RLEval scores. In general, the study results demonstrated a comprehensive experimental methodology for usability and performance evaluations of RLEs as well as merit of using the RLEval as preliminary method to compare design features. Some aspects of the usability experimentation and the RLEval method appear to be complementary.

An empirical assessment of driver motivation and emotional states in perceived safety margins under varied driving conditions.

Motivation models in driving behaviour postulate that driver motives and emotional states dictate risk tolerance under various traffic conditions. The present study used time and driver performance-based payment systems to manipulate motivation and risk-taking behaviour. Ten participants drove to a predefined location in a simulated driving environment. Traffic patterns (density and velocity) were manipulated to cause driver behaviour adjustments due to the need to conform with the social norms of the roadway. The driving environment complexity was investigated as a mediating factor in risk tolerance. Results revealed the performance-based payment system to closely relate to risk-taking behaviour as compared with the time-based payment system. Drivers conformed with social norms associated with specific traffic patterns. Higher roadway complexity led to a more conservative safety margins and speeds. This research contributes to the further development of motivational models of driver behaviour. PRACTITIONER SUMMARY: This study provides empirical justification for two motivation factors in driver risk-taking decisions, including compliance with social norm and emotions triggered by incentives. Environment complexity was identified as a mediating factor in motivational behaviour model. This study also recommended safety margin measures sensitive to changes in driver risk tolerance.