Energy-Efficient Driving in Connected Corridors via Minimum Principle Control: Vehicle-in-the-Loop Experimental Verification in Mixed Fleets

Ard, Tyler; Guo, Longxiang; Han, Jihun; Jia, Yunyi; Vahidi, Ardalan; Karbowski, Dominik

doi:10.1109/tiv.2023.3234261

Title: Energy-Efficient Driving in Connected Corridors via Minimum Principle Control: Vehicle-in-the-Loop Experimental Verification in Mixed Fleets

Journal Article · Wed Jan 04 00:00:00 UTC 2023 · IEEE Transactions on Intelligent Vehicles

DOI: https://doi.org/10.1109/tiv.2023.3234261 · OSTI ID:2426321

^[1]; Guo, Longxiang ^[2];

^[3];

^[2];

^[1]; Karbowski, Dominik ^[3]

Clemson Univ., SC (United States)
Clemson Univ., Greenville, SC (United States)
Argonne National Laboratory (ANL), Argonne, IL (United States)

Connected and automated vehicles (CAVs) can plan and actuate control that explicitly considers performance, system safety, and actuation constraints in a manner more efficient than their human-driven counterparts. In particular, eco-driving is enabled through connected exchange of information from signalized corridors that share their upcoming signal phase and timing (SPaT). This is accomplished in the proposed control approach, which follows first principles to plan a free-flow acceleration-optimal trajectory through green traffic light intervals by Pontryagin's Minimum Principle in a feedback manner. Urban conditions are then imposed from exogeneous traffic comprised of a mixture of human-driven vehicles (HVs) - as well as other CAVs. As such, safe disturbance compensation is achieved by implementing a model predictive controller (MPC) to anticipate and avoid collisions by issuing braking commands as necessary. The control strategy is experimentally vetted through vehicle-in-the-loop (VIL) of a prototype CAV that is embedded into a virtual traffic corridor realized through microsimulation. Up to 36% fuel savings are measured with the proposed control approach over a human-modelled driver, and it was found connectivity in the automation approach improved fuel economy by up to 26% over automation without. Additionally, the passive energy benefits realizable for human drivers when driving behind downstream CAVs are measured, showing up to 22% fuel savings in a HV when driving behind a small penetration of connectivity-enabled automated vehicles.

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Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Office of Sustainable Transportation. Vehicle Technologies Office (VTO)

Grant/Contract Number:: AC02-06CH11357

OSTI ID:: 2426321

Journal Information:: IEEE Transactions on Intelligent Vehicles, Journal Name: IEEE Transactions on Intelligent Vehicles Journal Issue: 2 Vol. 8; ISSN 2379-8858

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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Title: Energy-Efficient Driving in Connected Corridors via Minimum Principle Control: Vehicle-in-the-Loop Experimental Verification in Mixed Fleets

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