Real-time characterisation of driver steering behaviour

Best, Matt C.

doi:10.1080/00423114.2018.1447678

Cited by 14 publications

(9 citation statements)

References 24 publications

(32 reference statements)

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“…The proposed Expert Pilot Model (EPM) is based on a simple driver model initially developed for ground vehicles. 14 By continuously adapting the steering, the aircraft is kept on a path towards a single reference point on the road ahead. The amount of look-ahead varies with speed, so a finite preview time T p is considered.…”

Section: Control Methodologymentioning

confidence: 99%

Optimal predictive steering control for autonomous runway exits

Huang

Best

Knowles

2020

Advances in Mechanical Engineering

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In this paper, we present a real-time optimal controller, Predictive Steering Control (PSC), to perform high-speed runway exit manoeuvres. PSC is developed based on a time-varying LQR with look-ahead. The aircraft’s ground dynamics are described by a high-fidelity nonlinear model. The proposed controller is compared with an Expert Pilot Model (EPM), which represents a pilot, in several different speed runway exit manoeuvres. With an improved road preview mechanism and optimal feedback gain, the predictive steering controller outperforms the expert pilot’s manual operations by executing the runway exit manoeuvre with a lower track error. To investigate the optimality of PSC, its solution is further optimised using a numerical optimal controller Generalized Optimal Control (GOC). PSC is shown to be close to the final optimal solution. To study robustness, PSC is tested with various aircraft configurations, road conditions and disturbances. The simulation results show that PSC is robust to disturbances within a normal range of operational parameters.

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Section: Control Methodologymentioning

confidence: 99%

Optimal predictive steering control for autonomous runway exits

Huang

Best

Knowles

2020

Advances in Mechanical Engineering

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“…Sophisticated semi-automated systems have been developed, however still only for the highest level of professional football. [18] • GPS-based technologies for tracking analysis [27]. While they show good results for tracking large movements in vast areas [28] and they are widely used for those instances, these technologies are limited in their precision for differentiating fine movements, and as such of little use for fine movement analysis.…”

Section: State Of the Artmentioning

confidence: 99%

Conceptualisation of Virtual Reality Experiments for Optimised Sinus Surgery Planning and Execution

Kunica¹,

Poje²,

Mlivić³

et al. 2023

Int J Ind Eng Manag

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Contemporary research in the field of technology and production is focused on the intensive development of highly automated --so called intelligent and autonomous devices and systems, for smaller (discretized) production volumes (of products and business --production activities of their realization). This development implies a need to create a new knowledge and change --re-evaluate and upgrade of existing knowledge: project approaches and content related to product, process, and system design, as well as a need to include traditional non-engineering areas such as biology and medicine (neuroscience, anatomy, psychiatry). Regarding products, especially, it is interesting to consider the performance of processes in which deformable objects and sculpture surfaces appear in different industries. Consideration of advanced sensorics and virtual reality (VR) involves the analysis of manual processes [1], as yet the most widespread, and as a basis for better understanding and optimization (stabilization) as well as standardization ("normization") of manual processes [2], thus enabling development of mechatronic devices for automatic process execution.Technology development allows the design and standardization of manual work in human activities which are yet to be observed, especially those of low-volume discrete production, such as in ear, nose and throat (ENT) surgery, particularly endoscopic sinus surgery (ESS). The paper considers the possibilities of developing an approach that would be useful for specific ESS manual work analysis and design and its automation in a future. The consideration includes, beside other aspects, initial steps, such as the traditional work motion capture by camera and experiments by Leap Motion Controller, Perception Neuron 2.0 and Emotiv Epoc+.

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“…Kalman filters are widely used for real-time state estimation of non-linear systems and they can also be applied to identify the parameters of a nonlinear model, for example in Refs. [20][21][22] The adaptation of model parameters can be achieved either alongside or independently from the estimated states, through the use of either an Extended Kalman Filter (EKF) or an Unscented Kalman Filter (UKF). Actually, Ma et al 17 concludes that either filter can identify parameters equally effectively; the UKF is preferred over EKF here as it eliminates the need for computing system Jacobians.…”

Section: Unscented Kalman Filtermentioning

confidence: 99%

“…The observation in Best 20 is that most drivers target a consistent lateral acceleration, usually in the range of 2–4 m/s 2 . This makes for a good means of parametrising driving style.…”

Section: Introductionmentioning

confidence: 99%

Characterisation of driver longitudinal behaviour using an Unscented Kalman Filter

Mladenov

Best

2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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This paper presents a real-time driver characterisation algorithm that models the driver based on 10 parameters governing their control of vehicle longitudinal speed and acceleration. It utilises an open-loop longitudinal model in conjunction with an Unscented Kalman Filter (UKF). The algorithm can operate in real-time using velocity and acceleration measurements, in addition to a-priori knowledge of the path curvature and road features such as speed limit locations. The UKF also enables a system identification process to estimate average response of each driver. These identified parameters are subsequently fitted to independent measures of fuel economy and safety to demonstrate possible uses for the characterisations. In addition to the comprehensive characterisation of the drivers’ behaviour the work is also novel in its unique approach to identifying time-based parameters within a time-varying dynamic system (UKF). Possible applications include insurance black box assessments of driver aggressiveness and safety, and in autonomous driving algorithms by providing a model to closely replicate the specific driving styles of various users.

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Real-time characterisation of driver steering behaviour

Cited by 14 publications

References 24 publications

Optimal predictive steering control for autonomous runway exits

Optimal predictive steering control for autonomous runway exits

Conceptualisation of Virtual Reality Experiments for Optimised Sinus Surgery Planning and Execution

Characterisation of driver longitudinal behaviour using an Unscented Kalman Filter

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