Type of Document Master's Thesis Author Grove, Kevin Author's Email Address email@example.com URN etd-05302008-121937 Title EVALUATION OF PACKAGE DELIVERY TRUCK DRIVERS: TASK ANALYSIS AND DEVELOPMENT/VALIDATION OF AN OBJECTIVE VISUAL BEHAVIOR MEASURE TO ASSESS PERFORMANCE Degree Master of Engineering Department Industrial and Systems Engineering Advisory Committee
Advisor Name Title Dr. Jeff Lancaster Committee Co-Chair Dr. John G. Casali Committee Co-Chair Dr. Tonya Smith-Jackson Committee Member Keywords
- Head Down Time
- Package Delivery Driver
- Visual Attention
- Task Analysis
Date of Defense 2008-04-24 Availability unrestricted AbstractThe job of a package delivery driver (PDD) is complex and demanding. These drivers must possess many skills in order to succeed in their work, including physical stamina, appropriate decision-making, positive customer interaction, and most importantly, operational safety. Companies must use significant resources, not only to provide insurance for existing drivers, but also to train new drivers to use their visual attention effectively while driving, and companies have a vested interest in ensuring that the most capable trainees are selected for jobs. Currently, subjective assessments of supervisors or managers are typically used to make these determinations. While these are valuable methods for assessing drivers, an objective measure of how well the driver is using his/her visual attention would both assist evaluators in making judgments, as well as make those judgments more accurate. The purpose of the study described herein was to 1) conduct a task analysis of the driving component of the PDD job responsibilities, and 2) create and test an objective measure that a package delivery company could use to evaluate the performance of its drivers.
A detailed task analysis based on numerous observations of drivers in their normal work routines was conducted for this research in order to understand these complex tasks. A framework was created for understanding this system of tasks, which was then used to organize all tasks that drivers were observed to perform into more general, goal-oriented activities. Using this task analysis, incidents were identified that were observed while drivers were behind the wheel. This information demonstrated that breakdowns were occurring within the tasks drivers were performing and that improved methods of training and evaluations may be needed as a result.
A construct of visual behavior called Head Down Time (HTD) was then created and tested. An individual HDT is defined as the sum of time of all eye gazes away from the primary display (i.e. windshield) between two distinct eye gazes at the primary display while the vehicle is in motion. HDT was evaluated for its ability to differentiate levels of experience between drivers, its relationship to types of route on which drivers delivered, and its relationship to the driving-related incidents that were observed. HDTs were shown to be differed significantly between drivers of low and high experience, with experienced drivers displaying shorter durations of HDT when compared to inexperienced drivers. HDTs also differed in duration when analyzed by the type of route upon which drivers operated. Commercial and urban routes, while not significantly different with respect to HDT, were shown to have increased HDT durations when compared to rural routes and, in turn, residential routes were found to have significantly longer HDTs than did rural routes and may have significantly shorter durations compared to commercial and urban. Finally, HDTs that were associated with observed driving incidents in terms of chronological proximity were shown to be of significantly longer duration than were HDTs that were not associated with incidents. All tests were conducted using appropriate statistical measures, including t-tests at a level of α = 0.05 for each dataset.
Applications of this research include: 1) improvement of PDD training and evaluation methods through use of a detailed task analysis, 2) improvement in how package delivery companies define incidents and train PDD toward the prevention of incidents based on task analysis and observations as to incident frequency, and 3) the further development of HDT as a possible objective measure to supplement the training and evaluation of PDD.
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