A Unified Approach to Threat Assessment and Control for Automotive Active Safety

Gray, Andrew; Ali, Mohammad; Gao, Yiqi; Hedrick, J. Karl; Borrelli, Francesco

doi:10.1109/tits.2013.2262097

Cited by 71 publications

(28 citation statements)

References 17 publications

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“…This signal is only used if the car is at risk of departing the lane and the torque on the steering column from the driver is sufficiently small (a threshold test that the authors use as a proxy for diminished capability due to inattention, tiredness, illness). In [15] a model predictive control system synthesizes both steering and braking signals for a nonlinear model of vehicle motion (which includes a simple but data driven model of driver behaviour). These signals are only nonzero if the driver model is unable to maintain the lane constraints, so they are added continuously to the driver's input but only affect that input when necessary.…”

Section: A Shared Controlmentioning

confidence: 99%

Shared control policies for safe wheelchair navigation of elderly adults with cognitive and mobility impairments: Designing a wizard of oz study

Mitchell¹,

Viswanathan²,

Adhikari³

et al. 2014

2014 American Control Conference

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Older adults often lack the ability or strength to walk or to self-propel in manual wheelchairs. However, the need for a significant level of cognitive capacity to safely operate current powered wheelchair technology tends to exclude users with cognitive impairments. The resulting lack of mobility for a significant proportion of elderly residents in long term care leads to negative social, mental and physical outcomes. In this paper, we review shared (or collaborative) control policies implemented by smart wheelchair prototypes that have been tested by participants from their target populations, and highlight key usability findings and clinical insights. We discuss desirable features for control policies in new intelligent wheelchairs for cognitively impaired older adults. We then propose a method to evaluate these policies in a Wizard of Oz study conducted with cognitively impaired participants living in long term care facilities.

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Section: A Shared Controlmentioning

confidence: 99%

Shared control policies for safe wheelchair navigation of elderly adults with cognitive and mobility impairments: Designing a wizard of oz study

Mitchell¹,

Viswanathan²,

Adhikari³

et al. 2014

2014 American Control Conference

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“…On the other hand, driver assistance control problems for collision avoidance have been studied in several literatures. MPC based approaches for driver assistance control have been reported (Ercan et al 2016;Anderson et al 2010;Gray et al 2013;Erlien et al 2016). In these methods, the cost functions of the MPC algorithms are chosen so that the front wheel turn angle or the steering torque commanded by a human driver is corrected so as to prevent collisions only when the control action of the human driver is insufficient for collision avoidance.…”

Section: Introductionmentioning

confidence: 99%

Driver steering assistance for collision avoidance and turning performance optimization by constrained MPC

Wada

Matsumoto

2021

Mechanical Engineering Journal

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A driver steering assistance control algorithm for a vehicle with an active front steering system is proposed in this paper. The control algorithm is designed so as to optimize turning performance and realize collision avoidance simultaneously under magnitude constraints on the front wheel turn angle and the lateral tire force. The control algorithm is developed based on a model predictive control law for tracking a time-varying reference signal. The proposed control algorithm is reduced to a convex quadratic programming problem. The effectiveness of the proposed method is shown by human-in-the-loop simulations.

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“…Model predictive control (MPC) has for a long time been a well‐known and proven tool for motion planning and COLAV for, for example, ground and automotive robots (Gray, Ali, Gao, Hedrick, & Borrelli, ; Keller, Haß, Seewald, & Bertram, ; Ögren & Leonard, ), aerospace applications (Kuwata & How, ), and underwater vehicles (Caldwell, Dunlap, & Collins, ). In the later years, MPC has also been applied for COLAV in the maritime domain, both using sample‐based approaches where one considers a finite space of control inputs (Hagen, Kufoalor, Brekke, & Johansen, ; Johansen, Perez, & Cristofaro, ; Švec et al, ) and conventional gradient‐based search algorithms (Abdelaal & Hahn, ; Eriksen & Breivik, ).…”

Section: Introductionmentioning

confidence: 99%

The branching‐course model predictive control algorithm for maritime collision avoidance

Eriksen

Breivik

Wilthil

et al. 2019

Journal of Field Robotics

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This article presents a new algorithm for short-term maritime collision avoidance (COLAV) named the branching-course model predictive control (BC-MPC) algorithm. The algorithm is designed to be robust with respect to noise on obstacle estimates, which is a significant source of disturbance when using exteroceptive sensors such as, for example, radars for obstacle detection and tracking. Exteroceptive sensors do not require vesselto-vessel communication, which enables COLAV toward vessels not equipped with, for example, automatic identification system transponders, in addition to increasing the robustness with respect to faulty information which may be provided by other vessels. The BC-MPC algorithm is compliant with Rules 8, 13, and 17 of the International Regulations for Preventing Collisions at Sea (COLREGs), and favors maneuvers following Rules 14 and 15. Specifically, the algorithm can ignore the specific maneuvering regulations of Rules 14 and 15, which may be required in situations where Rule 17 revokes a stand-on obligation. The algorithm is experimentally validated in several fullscale experiments in the Trondheimsfjord in 2017 using a radar-based system for obstacle detection and tracking. To complement the experimental results, we present simulations where the BC-MPC algorithm is tested in more complex scenarios involving multiple obstacles and several simultaneously active COLREGs rules. The COLAV experiments and simulations show good performance. K E Y W O R D S control, marine robotics, planning

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A Unified Approach to Threat Assessment and Control for Automotive Active Safety

Cited by 71 publications

References 17 publications

Shared control policies for safe wheelchair navigation of elderly adults with cognitive and mobility impairments: Designing a wizard of oz study

Shared control policies for safe wheelchair navigation of elderly adults with cognitive and mobility impairments: Designing a wizard of oz study

Driver steering assistance for collision avoidance and turning performance optimization by constrained MPC

The branching‐course model predictive control algorithm for maritime collision avoidance

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