Autonomous vehicle velocity and steering control through nonlinear model predictive control scheme

Du, Xinxin; Tan, Kok Hian

doi:10.1109/itec-ap.2016.7513089

Cited by 11 publications

(7 citation statements)

References 8 publications

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“…Note that some of these parameters are directly related to the comfort 1,15,16,19,21 and the rest are common performance measures of autonomous driving. 23,47…”

Section: Resultsmentioning

confidence: 99%

“…Note that some of these parameters are directly related to the comfort 1,15,16,19,21 and the rest are common performance measures of autonomous driving. 23,47 The MSDV is explained previously and defined by equation (14). The jerk and acceleration, which are used in the MSDV, are double and single derivatives of the velocity at the center of gravity of the vehicle, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…The performance criterion and constraint structure for the comfort that have been demonstrated are in parallel with the previous studies. 15,16,19,21 Du and Tan 23 performed simultaneous speed and steering control using genetic algorithm based constrained nonlinear model predictive control. In order to improve passenger comfort, lower and upper limits of acceleration amplitudes were determined.…”

Section: Introductionmentioning

confidence: 99%

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Carsickness-based design and development of a controller for autonomous vehicles to improve the comfort of occupants

Sever

Zengin

Kirli

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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It is anticipated that passengers in autonomous vehicles will be more occupied with in-vehicle activities. Loss of the authority on driving and engaging in non-driving tasks could cause lower predictability of car motions. This decrease in predictability is expected to increase the sensitivity to carsickness. It appears that it is crucial to develop controllers for autonomous driving with the capability of improving passenger comfort by reducing carsickness. In this regard, it can be asked how the motion variables can be used for the minimization of a carsickness-related measure, while the vehicle is required to follow a given path. In this study, an optimal control approach is being proposed to minimize a quantitative measure of carsickness. In order to address carsickness during autonomous maneuvers, the well-known motion sickness dose value formulation in ISO 2631-1 is augmented with horizontal direction motion components to define a performance measure. The performance measure includes the motion sensed in vestibular system rather than the motion occurring in the vehicle itself. Therefore, mathematical model of the vestibular system is included in the design of controller. Effects of acceleration and jerk are included in performance measure simultaneously. Control oriented linear parameter varying vehicle model is developed to design the path following controller. By means of simulation studies in which path following control is implemented, motion sickness dose values of the controlled vehicle are examined. It is shown by a regular lane change test at various speeds that the proposed controller, which seeks the minimization of the motion sickness dose value, achieves a reduction of the acceleration and jerk felt by a passenger, while the vehicle follows the given path.

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“…Note that some of these parameters are directly related to the comfort 1,15,16,19,21 and the rest are common performance measures of autonomous driving. 23,47…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Carsickness-based design and development of a controller for autonomous vehicles to improve the comfort of occupants

Sever

Zengin

Kirli

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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show abstract

“…While no further evaluation of passenger comfort is made, it is worth mentioning, that Mohseni 2017 apply their cost function to several vehicles so as to plan cooperative maneuvers, such as synchronized lane changes or the zipper-like opening of a passage for an emergency vehicle (illustrated in figure 3). In Du 2016 a nonlinear model predictive control (NMPC) scheme is used to control the velocity and steering of a vehicle [8]. Genetic algorithms are utilized to optimize a cost function, that is designed specifically to take the safety and comfort of human passengers into account.…”

Section: State Of the Artmentioning

confidence: 99%

Optimizing Passenger Comfort in Cost Functions for Trajectory Planning

Elsner

2018

Preprint

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Current advances in the development of autonomous cars suggest that driverless cars may see wide-scale deployment in the near future. Research by both industry and academia is driven by potential benefits of this new technology, including reductions in fatalities and improvements in traffic and fuel efficiency as well as greater mobility for people who will or cannot drive cars themselves. A deciding factor for the adoption of selfdriving cars besides safety will be the comfort of the passengers. This report looks at cost functions currently used in motion planning methods for autonomous on-road driving. Specifically, how the human perception of how comfortable a trajectory is, can be formulated within cost functions.

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“…Aunque existen técnicas de control robusto basadas en controladores MPC que debido a su robustez ante imprevistos y su capacidad de rechazar perturbaciones tienen muy buenos resultados [6],éstas son técnicas complejas y por lo tanto computacionalmente exigentes. Por lo que numerosos trabajos están enfocados en la optimización de modelos para MPC, principalmente empleando modelos complejos y no lineales XXXVIII Jornadas de Automática 122 https://doi.org/10.17979/spudc.9788497497749.0122 [2], [5], [16].…”

Section: Introductionunclassified

Control MPC basado en un modelo LTV para seguimiento de trayectoria con estabilidad garantizada

Mata¹,

Zubizarreta²,

Nieva³

et al. 2020

XXXVIII Jornadas De Automática: Gijón, 6, 7, Y 8 De Septiembre De 2017

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Este artículo presenta una aplicación de seguimiento de trayectoria para vehículos mediante Control Predictivo basado en Modelo (MPC) con un modelo Linealmente Variable en el Tiempo (LTV) con estabilidad garantizada. El sistema de control considera tanto el error lateral como el error de orientación respecto de la trayectoria de referencia para garantizar un correcto seguimiento de la trayectoria bajo ciertos criterios de confort. Además, también se consideran restricciones estrictas en la señal de control, en la variación de la señal de control y en el error lateral de seguimiento de la trayectoria, así como se tienen en cuenta consideraciones de estabilidad. Se exponen los resultados para diferentes tipos de trazados, concluyendo con un circuito y para un rango muy amplio de velocidades.

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Autonomous vehicle velocity and steering control through nonlinear model predictive control scheme

Cited by 11 publications

References 8 publications

Carsickness-based design and development of a controller for autonomous vehicles to improve the comfort of occupants

Carsickness-based design and development of a controller for autonomous vehicles to improve the comfort of occupants

Optimizing Passenger Comfort in Cost Functions for Trajectory Planning

Control MPC basado en un modelo LTV para seguimiento de trayectoria con estabilidad garantizada

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