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Impact of Optimization Strategy and Adoption Rate on V2X Technology on Environmental Impact
  • Published Date:
    2018-12-31
  • Language:
    English
Filetype[PDF-2.25 MB]


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  • Edition:
    Final Report August 21, 2017 -December 31, 2017
  • Abstract:
    This research evaluated the effects of automated vehicle control strategies on system level emissions, travel time and wait time through a series of traffic lights. The study was conducted using traffic simulation and a realistic vehicle mix. Two control strategies were evaluated including a single vehicle control strategy and a multi-vehicle coordination heuristic. The performance of each control strategy was recorded under various levels of connected and autonomous vehicle technology (V2X technology) and 3 levels of traffic flow. In the single vehicle control strategy each connected and autonomous vehicle calculated optimal speeds for itself to traverse a series of traffic lights. In the coordination heuristic, each autonomous and connected vehicle calculated optimal speeds for itself to traverse a series of traffic lights, but could also issue coordination requests that would allow preceding vehicles to increase their speed slightly, such that the requesting vehicle could also make it through the traffic signal without stopping. Results indicate that the coordination heuristic consistently outperformed the single vehicle optimization strategy and offered significant emissions reductions at high V2X penetration rates. At 1200 vehicles per hour and 100% V2X penetration rate the coordination heuristic reduced emissions by 15%. Results also indicated that both control strategies can have adverse effects at low penetration rates of connected and automated vehicle technology, and should only be employed once connected and automated vehicle technology reaches certain threshold levels that vary by traffic flow. The control strategies employed did increase average travel time, but at the same time decreased average wait time at traffic lights.
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