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Mid-America Transportation Center

IntelliDrive Technology based Yellow Onset Decision Assistance System for Trucks

Final Report
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Researchers

  • Principal Investigator: Anuj Sharma (asharma3@unl.edu 402-472-6391)
  • Graduate Students
  • Venkata Anath-Choalla
  • Project Status
    Complete
    About this Project
    Brief Project Description & Background
    This project aims to develop a prototype Yellow Onset Decision Assistance (YODA) system for trucks based on Intellidrive (Vehicle to Infrastructure Communication) technology. Drivers need to make a decision to stop or go on the onset of yellow. An erroneous decision to stop when it would have been safer to proceed can lead to severe rear end collisions. Similarly an erroneous decision to go when it would be advisable to stop can lead to red light running incidences and T-bone collisions. Trucks are relatively less maneuverable and have lower available acceleration and comfortable deceleration rates. The line of sight of truck or bus drivers is much higher than passenger vehicle and they may have difficulty in responding to the brake lights of the leading car. So, trucks are at a higher risk of crashes in above situations. Dilemma zone protection systems are used at high speed intersection to enhance the safety of operation. These systems are generally designed based on dilemma zone boundaries for cars and are static system with no intelligence to adapt to existing traffic, weather or visibility conditions. This research proposes to develop a prototype YODA system that would constitute of a pole mounted unit and an in-vehicle unit. The in-vehicle unit would request decision assistance from the pole mounted unit as the truck approaches an intersection. Based on the existing traffic, weather and visibility conditions the pole mounted unit would respond to the in-vehicle unit with a recommended course of action.
    Research Objective
    This research proposes to develop a system that is smart and dynamic and is able to cater individual vehicle assistance needs. Yellow Onset Driver Assistance (YODA) system would consist of a pole mounted unit and an in-vehicle unit. The in-vehicle unit would request decision assistance from the pole mounted unit as a truck approaches an intersection. Based on the existing traffic, weather and visibility conditions the pole mounted unit would respond to the in-vehicle unit with a recommended course of action.
    Potential Benefits
    The developed YODA system will reduce Red Light Running, traffic crashes and increase mobility at high speed intersections
    Abstract
    This project aims to develop a prototype Yellow Onset Decision Assistance (YODA) system for trucks based on Intellidrive (Vehicle to Infrastructure Communication) technology. Drivers need to make a decision to stop or go on the onset of yellow. An erroneous decision to stop when it would have been safer to proceed can lead to severe rear end collisions. Similarly an erroneous decision to go when it would be advisable to stop can lead to red light running incidences and T-bone collisions. Trucks are relatively less maneuverable and have lower available acceleration and comfortable deceleration rates. The line of sight of truck or bus drivers is much higher than passenger vehicle and they may have difficulty in responding to the brake lights of the leading car. So, trucks are at a higher risk of crashes in above situations. Dilemma zone protection systems are used at high speed intersection to enhance the safety of operation. These systems are generally designed based on dilemma zone boundaries for cars and are static system with no intelligence to adapt to existing traffic, weather or visibility conditions. This research proposes to develop a prototype YODA system that would constitute of a pole mounted unit and an in-vehicle unit. The in-vehicle unit would request decision assistance from the pole mounted unit as the truck approaches an intersection. Based on the existing traffic, weather and visibility conditions the pole mounted unit would respond to the in-vehicle unit with a recommended course of action.
    Project Amount
    $ 59,082