Predicting Stress among Pedestrian Traffic Workers Using Physiological and Situational Measures

Abstract

Traffic workers are vulnerable to accidents and must make critical decisions to avoid conflicts between road users. This can lead to high stress levels, which may hinder their capacity to mitigate the occurrence of hazards. Measuring stress on the field could represent an efficient solution to help pinpoint risky situations and identify factors that increase risk. The goal of this study was to verify whether stress among traffic workers could be predicted using physiological measures and characteristics of the work situation. Nineteen police officers in Quebec City and Montreal, Canada, performed traffic duties while their physiological activity was assessed by a wearable physiological harness. Every 15 minutes, change in subjective stress was also measured. Results showed that decision-tree models outperformed multifactorial logistic regressions for predicting subjective stress based on both situational factors and physiological measures. This demonstrated the potential of using such measures to monitor stress among traffic workers.