4.7 Article

Cooperative Time and Energy-Optimal Lane Change Maneuvers for Connected Automated Vehicles

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2020.3036420

Keywords

Autonomous vehicles; intelligent vehicles; cooperative systems; optimal control

Funding

  1. Honda Research and Development Americas, Inc.
  2. NSF [ECCS-1931600, DMS166464, CNS-1645681]
  3. Air Force Office of Scientific Research (AFOSR) [FA9550-19-1-0158]
  4. Advanced Research Project Agency-Energy's (ARPA-E's) NEXTCAR Program [DE-AR0000796]
  5. MathWorks

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In this article, optimal control policies for a Connected Automated Vehicle (CAV) cooperating with neighboring CAVs are derived to implement a lane change maneuver. The authors optimize the maneuver time and minimize the energy consumption for all cooperating vehicles. Different solution methods are provided, including a real-time approach based on Control Barrier Functions. The simulation results show the effectiveness of these controllers in improving performance compared to human-driven vehicles.
We derive optimal control policies for a Connected Automated Vehicle (CAV) cooperating with neighboring CAVs in order to implement a lane change maneuver consisting of a longitudinal phase where the CAV properly positions itself relative to the cooperating neighbors and a lateral phase where it safely changes lanes. For the first phase, we optimize the maneuver time subject to safety constraints and subsequently minimize the associated surrogate energy consumption of all cooperating vehicles in this maneuver. For the second phase, we jointly optimize time and energy approximation and provide three different solution methods including a real-time approach based on Control Barrier Functions (CBFs). We prove structural properties of the optimal policies which simplify the solution derivations and, in the case of the longitudinal maneuver, lead to analytical optimal control expressions. The solutions, when they exist, are guaranteed to satisfy safety constraints for all vehicles involved in the maneuver. Simulation results where the controllers are implemented show their effectiveness in terms of significant performance improvements compared to maneuvers performed by human-driven vehicles.

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