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Eco-Trajectory Planning with Consideration of Queue along Congested Corridor for Hybrid Electric Vehicles

Journal Article · · Transportation Research Record
 [1];  [2];  [3];  [4];  [5]
  1. Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI; DOE/OSTI
  2. University of Michigan Transportation Research Institute, Ann Arbor, MI
  3. Department of Mechanical Engineering, University of Michigan, Ann Arbor, MI
  4. Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA
  5. Department of Naval Architecture and Marine Engineering, University of Michigan, Ann Arbor, MI
+ Show Author Affiliations

At signalized intersections, vehicle speed profile plays a vital role in determining fuel consumption and emissions. With advances of connected and automated vehicle technology, vehicles are able to receive predicted traffic information from the infrastructure in real-time to plan their trajectories in a fuel-efficient way. In this paper, an eco-driving model is developed for hybrid electric vehicles in a congested urban traffic environment. The vehicle queuing process is explicitly modeled by the shockwave profile model with consideration of vehicle deceleration and acceleration to provide a green window for eco-vehicle trajectory planning. A trigonometric speed profile is applied to minimize fuel consumption and maximize driving comfort with a low jerk. A hybrid electric vehicle fuel consumption model is built and calibrated with real vehicle data to evaluate the energy benefit of the eco-vehicles. Simulation results from a real-world corridor of six intersections show that the proposed eco-driving model can significantly reduce energy consumption by 8.7% on average and by 23.5% at maximum, without sacrificing mobility.

Research Organization:
Univ. of Michigan, Ann Arbor, MI (United States)
Sponsoring Organization:
USDOE Advanced Research Projects Agency - Energy (ARPA-E)
DOE Contract Number:
AR0000797
OSTI ID:
1613724
Journal Information:
Transportation Research Record, Journal Name: Transportation Research Record Journal Issue: 9 Vol. 2673; ISSN 0361-1981
Publisher:
National Academy of Sciences, Engineering and Medicine
Country of Publication:
United States
Language:
English

References (10)

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  • De Nunzio, Giovanni; de Wit, Carlos Canudas; Moulin, Philippe
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journal October 2015
A shockwave profile model for traffic flow on congested urban arterials journal December 2011
Predictive intelligent driver model for eco-driving using upcoming traffic signal information journal October 2018

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