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Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers

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arxiv 2104.11267 v1 pith:2UKSZ2SO submitted 2021-04-22 eess.SY cs.SY

classification eess.SYcs.SY
keywords energyframeworkvehicledynamicsflowmodelssmoothingsparse
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This work presents an integrated framework of: vehicle dynamics models, with a particular attention to instabilities and traffic waves; vehicle energy models, with particular attention to accurate energy values for strongly unsteady driving profiles; and sparse Lagrangian controls via automated vehicles, with a focus on controls that can be executed via existing technology such as adaptive cruise control systems. This framework serves as a key building block in developing control strategies for human-in-the-loop traffic flow smoothing on real highways. In this contribution, we outline the fundamental merits of integrating vehicle dynamics and energy modeling into a single framework, and we demonstrate the energy impact of sparse flow smoothing controllers via simulation results.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Optimal Control of ODE Car-Following Models: Applications to Mixed-Autonomy Platoon Control via Coupled Autonomous Vehicles

    math.OC 2025-08 conditional novelty 5.0 of 10

    A rigorous optimal control formulation for a mixed-autonomy platoon with the Bando-FtL model is shown to have a minimizer and is solved by adjoint gradient descent, with simulations showing large reductions in acceler...

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