A V Desai1, M A Haque. 1. Department of Mechanical and Nuclear Engineering, the Pennsylvania State University, University Park, 16802, USA.
Abstract
INTRODUCTION: Alertness of individuals operating vehicles, aircrafts, and machinery is a pre-requisite for safety of the individual and for avoiding economic losses. In this paper, we present a new technique for determining the alertness level of the operator and elaborate the methodology for the specific case of highway driving METHOD: Our hypothesis is that the time derivative of force exerted by the driver at the vehicle-human interfaces can be used to construct a signature of individual driving styles and to discern different levels of alertness RESULTS: In this study, we present experimental results corroborating this hypothesis and introduce a parameter, 'spikiness index,' for the time series data of the force derivative to quantify driver alertness IMPACT ON INDUSTRY: The low cost, ruggedness, and low-volume data processing requirements of the proposed technique give it a competitive edge over existing predominantly image processing based vigilance monitoring systems.
INTRODUCTION: Alertness of individuals operating vehicles, aircrafts, and machinery is a pre-requisite for safety of the individual and for avoiding economic losses. In this paper, we present a new technique for determining the alertness level of the operator and elaborate the methodology for the specific case of highway driving METHOD: Our hypothesis is that the time derivative of force exerted by the driver at the vehicle-human interfaces can be used to construct a signature of individual driving styles and to discern different levels of alertness RESULTS: In this study, we present experimental results corroborating this hypothesis and introduce a parameter, 'spikiness index,' for the time series data of the force derivative to quantify driver alertness IMPACT ON INDUSTRY: The low cost, ruggedness, and low-volume data processing requirements of the proposed technique give it a competitive edge over existing predominantly image processing based vigilance monitoring systems.