Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 1258197

Design and Comparative Analysis of Several Model Predictive Control Strategies for Autonomous Vehicle Approaching a Traffic Light Crossing


Cvok, Ivan; Pavelko, Lea; Škugor, Branimir; Deur, Joško; Tseng, H. Eric; Ivanovic, Vladimir
Design and Comparative Analysis of Several Model Predictive Control Strategies for Autonomous Vehicle Approaching a Traffic Light Crossing // Energies, 16 (2023), 5; 2006, 20 doi:10.3390/en16042006 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1258197 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Design and Comparative Analysis of Several Model Predictive Control Strategies for Autonomous Vehicle Approaching a Traffic Light Crossing

Autori
Cvok, Ivan ; Pavelko, Lea ; Škugor, Branimir ; Deur, Joško ; Tseng, H. Eric ; Ivanovic, Vladimir

Izvornik
Energies (1996-1073) 16 (2023), 5; 2006, 20

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
automated driving ; autonomous vehicle ; traffic light crossing ; model predictive control ; nonlinear control ; assessment

Sažetak
Recent advancements in automated driving technology and vehicle connectivity are associated with the development of advanced predictive control systems for improved performance, energy efficiency, safety, and comfort. This paper designs and compares different linear and nonlinear model predictive control strategies for a typical scenario of urban driving, in which the vehicle is approaching a traffic light crossing. In the linear model predictive control (MPC) case, the vehicle acceleration is optimized at every time instant on a prediction horizon to minimize the root-mean-square error of velocity tracking and RMS acceleration as a comfort metric, thus resulting in a quadratic program (QP). To tackle the vehicle-distance-related traffic light constraint, a linear time-varying MPC approach is used. The nonlinear MPC formulation is based on the first-order lag description of the vehicle velocity profile on the prediction horizon, where only two parameters are optimized: the time constant and the target velocity. To improve the computational efficiency of the nonlinear MPC formulation, multiple linear MPCs, i.e., a parallel MPC, are designed for different fixed-lag time constants, which can efficiently be solved by fast QP solvers. The performance of the three MPC approaches is compared in terms of vehicle velocity tracking error, root-mean-square acceleration, traveled distance, and computational time. The proposed control systems can readily be implemented in future automated driving systems, as well as within advanced driver assist systems such as adaptive cruise control or automated emergency braking systems.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo



POVEZANOST RADA


Profili:

Avatar Url Lea Pavelko (autor)

Avatar Url Branimir Škugor (autor)

Avatar Url Ivan Cvok (autor)

Avatar Url Vladimir Ivanović (autor)

Avatar Url Joško Deur (autor)

Poveznice na cjeloviti tekst rada:

doi doi.org www.mdpi.com

Citiraj ovu publikaciju:

Cvok, Ivan; Pavelko, Lea; Škugor, Branimir; Deur, Joško; Tseng, H. Eric; Ivanovic, Vladimir
Design and Comparative Analysis of Several Model Predictive Control Strategies for Autonomous Vehicle Approaching a Traffic Light Crossing // Energies, 16 (2023), 5; 2006, 20 doi:10.3390/en16042006 (međunarodna recenzija, članak, znanstveni)
Cvok, I., Pavelko, L., Škugor, B., Deur, J., Tseng, H. & Ivanovic, V. (2023) Design and Comparative Analysis of Several Model Predictive Control Strategies for Autonomous Vehicle Approaching a Traffic Light Crossing. Energies, 16 (5), 2006, 20 doi:10.3390/en16042006.
@article{article, author = {Cvok, Ivan and Pavelko, Lea and \v{S}kugor, Branimir and Deur, Jo\v{s}ko and Tseng, H. Eric and Ivanovic, Vladimir}, year = {2023}, pages = {20}, DOI = {10.3390/en16042006}, chapter = {2006}, keywords = {automated driving, autonomous vehicle, traffic light crossing, model predictive control, nonlinear control, assessment}, journal = {Energies}, doi = {10.3390/en16042006}, volume = {16}, number = {5}, issn = {1996-1073}, title = {Design and Comparative Analysis of Several Model Predictive Control Strategies for Autonomous Vehicle Approaching a Traffic Light Crossing}, keyword = {automated driving, autonomous vehicle, traffic light crossing, model predictive control, nonlinear control, assessment}, chapternumber = {2006} }
@article{article, author = {Cvok, Ivan and Pavelko, Lea and \v{S}kugor, Branimir and Deur, Jo\v{s}ko and Tseng, H. Eric and Ivanovic, Vladimir}, year = {2023}, pages = {20}, DOI = {10.3390/en16042006}, chapter = {2006}, keywords = {automated driving, autonomous vehicle, traffic light crossing, model predictive control, nonlinear control, assessment}, journal = {Energies}, doi = {10.3390/en16042006}, volume = {16}, number = {5}, issn = {1996-1073}, title = {Design and Comparative Analysis of Several Model Predictive Control Strategies for Autonomous Vehicle Approaching a Traffic Light Crossing}, keyword = {automated driving, autonomous vehicle, traffic light crossing, model predictive control, nonlinear control, assessment}, chapternumber = {2006} }

Citati:





    Contrast
    Increase Font
    Decrease Font
    Dyslexic Font