Steering Force Feedback for Human–Machine-Interface Automotive Experiments
TL;DR: In this paper, a velocity-controlled three-phase brushless servomotor is used for haptic control of a steering wheel for human-machine-interface automotive experiments, which can reproduce a large range of steering wheel dynamics and forces.
Abstract: Driving-simulator fidelity is usually defined by the quality of its visual and motion cueing system. However, the quality of its haptic cues is also very important and is determined by both hardware and control properties. Most experiments with haptic steering systems employ commercially available systems and do not address the system's fidelity. The goal of this paper is to offer guidelines for the development of hardware, performance evaluation, and system control in order to engineer realistic haptic cues on the steering wheel. A relatively low-cost solution for hardware is deployed, consisting of a velocity-controlled three-phase brushless servomotor, of which its high-bandwidth control allows for a realistic representation of forces. A method is presented to overcome electromagnetic interference produced by the industrial servomotor and the controller through careful amplification and filtering. To test the system, different inertia-spring-damper systems were simulated and evaluated in time and frequency domain. In conclusion, the designed system allowed reproduction of a large range of steering-wheel dynamics and forces. As a result, the developed system constitutes an efficient haptic device for human-machine-interface automotive experiments.
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TL;DR: Test results show that an automated vehicle with optimized plant and controller can perform its tasks well under aggressive, moderate, and conservative driving styles, further improving the overall performance.
Abstract: This paper studies the codesign optimization approach to determine how to optimally adapt automatic control of an intelligent electric vehicle to driving styles. A cyber-physical system (CPS)-based framework is proposed for codesign optimization of the plant and controller parameters for an automated electric vehicle, in view of vehicle's dynamic performance, drivability, and energy along with different driving styles. System description, requirements, constraints, optimization objectives, and methodology are investigated. Driving style recognition algorithm is developed using unsupervised machine learning and validated via vehicle experiments. Adaptive control algorithms are designed for three driving styles with different protocol selections. Performance exploration method is presented. Parameter optimizations are implemented based on the defined objective functions. Test results show that an automated vehicle with optimized plant and controller can perform its tasks well under aggressive, moderate, and conservative driving styles, further improving the overall performance. The results validate the feasibility and effectiveness of the proposed CPS-based codesign optimization approach.
213 citations
Cites background from "Steering Force Feedback for Human–M..."
...To address these challenges, researchers have explored advanced driver assistance systems (ADAS), and human– machine interface (HMI) from a variety of points of view [10], [11]....
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01 May 2014
TL;DR: A driving simulator experiment, which evaluates a road-departure prevention (RDP) system in an emergency situation, concludes that a low level of automation, in the form of HF, does not prevent road departures in anEmergency situation.
Abstract: This paper presents a driving simulator experiment, which evaluates a road-departure prevention (RDP) system in an emergency situation. Two levels of automation are evaluated: 1) haptic feedback (HF) where the RDP provides advisory steering torque such that the human and the machine carry out the maneuver cooperatively, and 2) drive by wire (DBW) where the RDP automatically corrects the front-wheels angle, overriding the steering-wheel input provided by the human. Thirty participants are instructed to avoid a pylon-confined area while keeping the vehicle on the road. The results show that HF has a significant impact on the measured steering wheel torque, but no significant effect on steering-wheel angle or vehicle path. DBW prevents road departure and tends to reduce self-reported workload, but leads to inadvertent human-initiated steering resulting in pylon collisions. It is concluded that a low level of automation, in the form of HF, does not prevent road departures in an emergency situation. A high level of automation, on the other hand, is effective in preventing road departures. However, more research may have to be done on the human response while driving with systems that alter the relationship between steering-wheel angle and front-wheels angle.
58 citations
Cites background or methods from "Steering Force Feedback for Human–M..."
...Driver-in-the-loop testing of the RDP controller was performed in fixed-base configuration of the X-Car driving simulator [26]....
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...Steering force feedback is delivered through a brushless three-phase motor, evaluated for its high fidelity in conjunction with its controllers [26]....
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Patent•
15 Sep 2014
Abstract: A method of controlling an electric power steering system of a vehicle is provided. The method estimates steering rack force to be caused by a tire of the vehicle and a surface of a ground with which the tire is in contact in response to determining that one or more hand wheel torque sensors of the vehicle are not enabled. The method generates a steering assist torque command based on the estimated steering rack force. The method controls the electric power steering system using the steering assist torque command.
57 citations
01 Oct 2015
TL;DR: The design and implementation of a fuzzy logic system for the steering control of autonomous vehicles inside the roundabout is proposed, and Cascade architecture for lateral control and parametric trajectory generation are used.
Abstract: Graphical abstractDisplay Omitted HighlightsThis paper shows a real experiment with autonomous vehicles in urban roundabouts.A parametric curve generation in used in the path planning, which in divided in three stages: entrance, inside and exit of the roundabout.Lane changes experiments show that the controller proposed (based on fuzzy logic) is stable.The range of speed used in the experiment is between 8km/h and 24km/h. The system was designed for 20km/h max.The real situation experiments show that our proposal is valid for urban scenarios. The expansion of roads and the development of new road infrastructures have increased in recent years, linked to the population growing in large cities. In the last two decades, roundabouts have largely replaced traditional intersections in many countries. They have the advantage of allowing drivers continuous flow when traffic is clear, without the usual delay caused by traffic lights. Although roundabouts with and without traffic-signal control have been widely used and considered in the literature, driverless control on roundabouts has not been studied in depth yet. The behavior of autonomous vehicles in roundabouts can be divided into three stages: entrance, inside, and exit. The first and last may be handled as an extension of intersections. However, autonomous driving on the roundabout requires special attention. In this paper, the design and implementation of a fuzzy logic system for the steering control of autonomous vehicles inside the roundabout is proposed. Cascade architecture for lateral control and parametric trajectory generation are used. Fuzzy control has proved to be easy to define using expert knowledge. Experiments with a real prototype have been carried out, taking into account different speed profiles and lane change maneuvers inside the roundabout, with very satisfactory results.
57 citations
TL;DR: The goal of this paper was to quantify the driver's arms' time-variant admittance in real driving and to provide a range of parametrically fitted values on the estimated frequency response functions.
Abstract: Attempts to measure and model driver steering behavior have been so far mainly performed with driving simulators and time-invariant techniques. The goal of this paper was to quantify the driver's arms' time-variant admittance in real driving and to provide a range of parametrically fitted values on the estimated frequency response functions. The human arms' neuromuscular (NMS) admittance was estimated by applying torque disturbances on the steering wheel during real car test-track driving. To capture the time-variant behavior, the admittance was estimated using a 1.28-s sliding time window. The results showed that drivers adapt their admittance while cornering, exposing a variant behavior during different corners and driving speeds. The frequency response function (FRF) of the admittance while cornering has the properties of a second-order system. During cornering, drivers have increased stiffness values, whilst in straight driving, the FRFs resemble a second-order system ( -40 dB/decade gain drop; double pole at low frequencies) for low frequencies, with a zero for frequencies above 6 Hz (on average). The FRFs during cornering were parametrically fitted to a second-order inertia-spring-damper model. The fitted parameter values can be used for NMS driver models and motivate the stability analysis of the combined closed-loop driver steering system.
35 citations
Cites methods from "Steering Force Feedback for Human–M..."
...An identification process described in [38] and [39] was employed to estimate the NMS admittance (a process which has also been used to estimate the fidelity of driving simulator [40])....
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References
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Book•
31 Oct 2005
TL;DR: In this paper, the authors present a mean value model of SI and Diesel engines, and design and analysis of passive and active automotive suspension components, as well as semi-active and active suspensions.
Abstract: 1. Introduction.- 2.Lateral Vehicle Dynamics.- 3. Steering Control For Automated Lane Keeping.- 4. Longitudinal Vehicle Dynamics.- 5. Introduction to Longitudinal Control.- 6. Adaptive Cruise Control.- 7. Longitudinal Control for Vehicle Platoons.- 8. Electronic Stability Control.- 9. Mean Value Modeling Of SI and Diesel Engines.- 10. Design and Analysis of Passive Automotive Suspensions.- 11. Active Automotive Suspensions.-12. Semi-Active Suspensions.- 13. Lateral and Longitudinal Tires Forces.- 14. Tire-Road Friction Measurement on Highway Vehicles.- 15. Roll Dynamics and Rollover Prevention.- 16. Dynamics and Control of Hybrid Gas Electric Vehicles.
3,669 citations
"Steering Force Feedback for Human–M..." refers background in this paper
...reduction of the self-aligning moment at the steering wheel, when the front tires approach their lateral force peak, is a valuable feedback to the driver [8]....
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Book•
31 Dec 2003TL;DR: Focusing mainly on frequency domain techniques, System Identification: A Frequency Domain Approach, Second Edition also studies in detail the similarities and differences with the classical time domain approach.
Abstract: Preface to the First Edition Preface to the Second Edition Acknowledgments List of Operators and Notational Conventions List of Symbols List of Abbreviations Chapter 1 An Introduction to Identification Chapter 2 Measurement of Frequency Response Functions Standard Solutions Chapter 3 Frequency Response Function Measurements in the Presence of Nonlinear Distortions Chapter 4 Detection, Quantification, and Qualification of Nonlinear Distortions in FRF Measurements Chapter 5 Design of Excitation Signals Chapter 6 Models of Linear Time-Invariant Systems Chapter 7 Measurement of Frequency Response Functions The Local Polynomial Approach Chapter 8 An Intuitive Introduction to Frequency Domain Identification Chapter 9 Estimation with Know Noise Model Chapter 10 Estimation with Unknown Noise Model Standard Solutions Chapter 11 Model Selection and Validation Chapter 12 Estimation with Unknown Noise Model The Local Polynomial Approach Chapter 13 Basic Choices in System Identification Chapter 14 Guidelines for the User Chapter 15 Some Linear Algebra Fundamentals Chapter 16 Some Probability and Stochastic Convergence Fundamentals Chapter 17 Properties of Least Squares Estimators with Deterministic Weighting Chapter 18 Properties of Least Squares Estimators with Stochastic Weighting Chapter 19 Identification of Semilinear Models Chapter 20 Identification of Invariants of (Over) Parameterized Models References Subject Index Author Index About the Authors
2,379 citations
"Steering Force Feedback for Human–M..." refers methods in this paper
...To enable accurate system identification, the torque disturbance signal was designed in the frequency domain as a multisine signal with an optimized crest factor, so as not to introduce bias or variance in the estimated spectral densities [26]....
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...Second, the virtual models were estimated back using closed-loop system identification techniques [26]–[28]....
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TL;DR: Recent psychophysical studies have revealed an unexpectedly important contribution of vestibular cues in distance perception and steering, prompting a re-evaluation of the role of visuo-vestibular interaction in driving simulation studies.
381 citations
TL;DR: Experimental results verify that with precise steering control and accurate state information, the handling modification is exactly equivalent to changing the front tire cornering stiffness.
Abstract: While changing the handling characteristics of a conventional vehicle normally requires physical modification, a vehicle equipped with steer-by-wire can accomplish the same effect through active steering intervention. This paper presents an intuitive method for altering a vehicle's handling characteristics by augmenting the driver's steering command with full vehicle state feedback. The vehicle can be made more or less responsive depending on the driver's preference and particular operating conditions. Achieving a smooth, continuous change in handling quality requires both accurate state estimation and well-controlled steering inputs from the steer-by-wire system. Accurate estimates of vehicle states are available from a combination of global positioning system (GPS) and inertial navigation system (INS) sensor measurements. By canceling the effects of steering system dynamics and tire disturbance forces, the steer-by-wire system is able to track commanded steer angle with minimal error. Experimental results verify that with precise steering control and accurate state information, the handling modification is exactly equivalent to changing the front tire cornering stiffness.
239 citations
01 Oct 2008
TL;DR: This paper proposes haptic guidance based on the concept of shared control, where both the driver and the support system influence the steering wheel torque, to support drivers in actively producing (more) optimal steering actions during curve negotiation.
Abstract: Haptic feedback on the steering wheel is reported in literature as a promising way to support drivers during steering tasks. Haptic support allows drivers to remain in the direct manual control loop, avoiding known human factors issues with automation. This paper proposes haptic guidance based on the concept of shared control, where both the driver and the support system influence the steering wheel torque. The haptic guidance is developed to continuously generate relatively low forces on the steering wheel, requiring the driver's active steering input to safely negotiate curves. An experiment in a fixed-base driving simulator was conducted, in which 12 young, experienced drivers steered a vehicle - with and without haptic guidance - at a fixed speed along a road with varying curvature. The haptic guidance allowed drivers to slightly but significantly improve safety boundaries in their curve negotiation behavior. Their steering activity was reduced and smoother. The results indicated that continuous haptic guidance is a promising way to support drivers in actively producing (more) optimal steering actions during curve negotiation.
152 citations