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Mid-America Transportation Center

Effect of Freeway Level of Service and Driver Education on Truck Driver's Stress - Phase 1

Final Report
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Researchers

  • Principal Investigator: Anuj Sharma (asharma3@unl.edu 402-472-6391)
  • Co-Principal Investigator: Senem Velipasalar (svelipasalar2@unl.edu 402-472-1976)
  • Graduate Students
  • David Engel
  • Sanjay Singh
  • Jayasri Jardanan
  • Project Status
    Complete
    Sponsors & Partners
  • University of Nebraska-Lincoln Civil Engineering Department
  • About this Project
    Brief Project Description & Background
    This project aims to model truck driver's stress on freeways as a function of variables such as: level of service, time of day, weather conditions, and level of driver training. The Highway Capacity Manual uses density to measure the level of service on basic, weaving, and merging sections of freeways. The efficiency of flow can be estimated by calculating the speed of traffic and travel time from density. There is a need for a methodology to estimate safety as a function of density. A truck driver's stress model will be able to fill this gap in knowledge. The driver's stress will be measured using physiological markers such as an electrocardiogram, respiration temperature, posture and blood pressure, etc. The technology used for these measurements will not be obtrusive to the driving tasks. The predicted stress level can be used as a surrogate measure for safety. The study subjects will include trainees from a six-week truck driving certification course offered by Central Community College's Truck Driving Program. The subject will be observed under simulated and real-world driving environments for the data collection. The Community college hosts more than 100 participants per year. This study will use a sample set of 50 subjects. A second phase for this proposal will be submitted next year to evaluate truck driver stress in urban street settings. Partial support for this proposal comes from Layman Award endowed on Dr Anuj Sharma and Dr Senem Velipasalar, by the University of Nebraska Lincoln to produce prominent scholarly work.
    Research Objective
    The research objective is to evaluate the stress introduced by various stimuli in freeway truck driving
    Potential Benefits
    The model of truck driver stress level for this project can be applied as a measure of safety for improving the traffic facility design
    Abstract
    This project aims to model truck driver's stress on freeways as a function of variables such as: level of service, time of day, weather conditions, and level of driver training. The Highway Capacity Manual uses density to measure the level of service on basic, weaving, and merging sections of freeways. The efficiency of flow can be estimated by calculating the speed of traffic and travel time from density. There is a need for a methodology to estimate safety as a function of density. A truck driver's stress model will be able to fill this gap in knowledge. The driver's stress will be measured using physiological markers such as an electrocardiogram, respiration temperature, posture and blood pressure, etc. The technology used for these measurements will not be obtrusive to the driving tasks. The predicted stress level can be used as a surrogate measure for safety. The study subjects will include trainees from a six-week truck driving certification course offered by Central Community College's Truck Driving Program. The subject will be observed under simulated and real-world driving environments for the data collection. The Community college hosts more than 100 participants per year. This study will use a sample set of 50 subjects. A second phase for this proposal will be submitted next year to evaluate truck driver stress in urban street settings. Partial support for this proposal comes from Layman Award endowed on Dr Anuj Sharma and Dr Senem Velipasalar, by the University of Nebraska Lincoln to produce prominent scholarly work.
    Project Amount
    $ 76,291
    Technology Transfer Activities
    This project aims to model truck driver's stress on freeways as a function of variables such as: level of service, time of day, weather conditions, and level of driver training. The Highway Capacity Manual uses density to measure the level of service on basic, weaving, and merging sections of freeways. The efficiency of flow can be estimated by calculating the speed of traffic and travel time from density. There is a need for a methodology to estimate safety as a function of density. A truck driver's stress model will be able to fill this gap in knowledge. The driver's stress will be measured using physiological markers such as an electrocardiogram, respiration temperature, posture and blood pressure, etc. The technology used for these measurements will not be obtrusive to the driving tasks. The predicted stress level can be used as a surrogate measure for safety. The study subjects will include trainees from a six-week truck driving certification course offered by Central Community College's Truck Driving Program. The subject will be observed under simulated and real-world driving environments for the data collection. The Community college hosts more than 100 participants per year. This study will use a sample set of 50 subjects. A second phase for this proposal will be submitted next year to evaluate truck driver stress in urban street settings. Partial support for this proposal comes from Layman Award endowed on Dr Anuj Sharma and Dr Senem Velipasalar, by the University of Nebraska Lincoln to produce prominent scholarly work.