Distributed Maneuver Planning With Connected and Automated Vehicles for Boosting Traffic Efficiency

Goulet, Nathan; Ayalew, Beshah

doi:10.1109/tits.2021.3096878

Title: Distributed Maneuver Planning With Connected and Automated Vehicles for Boosting Traffic Efficiency

Journal Article · 26 July 2021 · IEEE Transactions on Intelligent Transportation Systems

DOI: https://doi.org/10.1109/tits.2021.3096878 · OSTI ID:1863342

Goulet, Nathan ^[1]; Ayalew, Beshah ^[2]

Clemson Univ.-International Center for Automotive Research (CU-ICAR), Greenville, SC (United States); Clemson University
Clemson Univ.-International Center for Automotive Research (CU-ICAR), Greenville, SC (United States)

Connected and automated vehicles (CAVs) have the potential to improve traffic throughput and achieve a more efficient utilization of the available roadway infrastructure. They also have the potential to reduce energy consumption through traffic motion harmonization, even when operating in mixed traffic with other human-driven vehicles. The key to realizing these potentials are coordinated control schemes that can be implemented in a distributed manner with the CAVs. In this paper, we propose a distributed predictive control framework that features a two-dimensional maneuver planner incorporating explicit coordination constraints between connected vehicles operating in mixed traffic at various penetration levels. Here, the framework includes a distributed implementation of a reference speed assigner that estimates local traffic speed from on-board measurements and communicated information. We present an extensive evaluation of the proposed framework in traffic micro-simulations at various CAV penetrations from traffic flow, energy use, and lane utilization points of view. Results are compared to a baseline scenario with no CAVs, as well as, a benchmark one-dimensional planner.

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Research Organization:: Clemson Univ., SC (United States)

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

Grant/Contract Number:: EE0008232

OSTI ID:: 1863342

Journal Information:: IEEE Transactions on Intelligent Transportation Systems, Journal Name: IEEE Transactions on Intelligent Transportation Systems Journal Issue: 8 Vol. 23; ISSN 1524-9050

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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33 ADVANCED PROPULSION SYSTEMS
CAVs
connected and automated vehicles
distributed predictive control
maneuver planning
traffic energy efficiency

Title: Distributed Maneuver Planning With Connected and Automated Vehicles for Boosting Traffic Efficiency

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