Research Framework For Studying Public Transit Bus Driver Distraction
Free (open access)
137 - 148
K. A. D’Souza & S. K. Maheshwari
Over 3,000 people are killed and 400,000 injured annually in the US due to motor vehicle crashes involving a distracted driver. In the case of passenger vehicles, most of the distraction is within the control of the driver. However, for public transit vehicles, some distractions are caused by factors beyond the driver’s control such as operating the fare box or attending to passengers. Research on the distraction of transit bus drivers is very limited, although injuries from transit vehicle accidents are generally higher because buses usually carry many passengers. This paper proposes a modular research framework for conducting a driver distraction study for transit buses. The research framework provides standardized methodologies structured into four modules – Data Collection, Analysis, Validation and Result Interpretation. The Data Collection module consists of approaches for collecting data from accident databases, surveys, and route observation. The Analysis module provide methods for classification of distracting activities, and development of statistical models that construct relationships between high risk distracting activities and driver attributes and external factors. The Validation module presents simple observation and discussion methods to sophisticated simulation techniques to check the model results. The final module contains guidelines for Results Interpretation and Usage. The framework’s standardized techniques are expected to reduce the overall time and cost of conducting a transit bus driver distraction study. Keywords: transit bus driver distraction, distraction risk index, research framework for bus driver distraction, modelling and predicting driver distraction, model validation, Monte Carlo simulation, route observations.
Keywords: transit bus driver distraction, distraction risk index, researchframework for bus driver distraction, modelling and predicting driverdistraction, model validation, Monte Carlo simulation, route observations.