The Effect of a Haptic Guidance Steering System on Fatigue-Related Driver Behavior

Wang, Zheng; Zheng, Rencheng; Kaizuka, Tsutomu; Shimono, Keisuke; Nakano, Kimihiko

doi:10.1109/thms.2017.2693230

Cited by 63 publications

(33 citation statements)

References 38 publications

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“…Many benefits of these systems have been reported: an improvement in tracking performance (e.g., lateral error) [75], [88]- [90]; a lower visual demand, enabling the possibility of performing secondary tasks while driving [75], [88], [89]; reduced driver effort (reductions in the steering reversal rate [79] and driver torque [62], [66], [96]); improved driving under low-visibility conditions [53]; an increase in the TLC [99]; a smooth control transition and greater stability when transferring authority [7], [102], [103]; and a decrease in the number of collisions during obstacle avoidance [81], [90]. One work showed the benefit of the haptic guidance in reducing passive driver fatigue [99], and the consideration of the four design aspects listed above has been shown to result in a significant reduction in driver-automation conflicts [78].…”

Section: A Model-free Coupled Shared Controllersmentioning

confidence: 99%

A Review of Shared Control for Automated Vehicles: Theory and Applications

Marcano

Díaz

Pérez

et al. 2020

IEEE Trans. Human-Mach. Syst.

156

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The last decade has shown an increasing interest on advanced driver assistance systems (ADAS) based on shared control, where automation is continuously supporting the driver at the control level with an adaptive authority. A first look at the literature offers two main research directions: 1) an ongoing effort to advance the theoretical comprehension of shared control, and 2) a diversity of automotive system applications with an increasing number of works in recent years. Yet, a global synthesis on these efforts is not available. To this end, this article covers the complete field of shared control in automated vehicles with an emphasis on these aspects: 1) concept, 2) categories, 3) algorithms, and 4) status of technology. Articles from the literature are classified in theory-and application-oriented contributions. From these, a clear distinction is found between coupled and uncoupled shared control. Also, model-based and model-free algorithms from these two categories are evaluated separately with a focus on systems using the steering wheel as the control interface. Model-based controllers tested by at least one real driver are tabulated to evaluate the performance of such systems. Results show that the inclusion of a driver model helps to reduce the conflicts at the steering. Also, variables such as driver state, driver effort, and safety indicators have a high impact on the calculation of the authority. Concerning the evaluation, driverin-the-loop simulators are the most common platforms, with few works performed in real vehicles. Implementation in experimental vehicles is expected in the upcoming years.

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Section: A Model-free Coupled Shared Controllersmentioning

confidence: 99%

A Review of Shared Control for Automated Vehicles: Theory and Applications

Marcano

Díaz

Pérez

et al. 2020

IEEE Trans. Human-Mach. Syst.

156

View full text Add to dashboard Cite

show abstract

“…A very well-known system is the lane keeping assistant. As described in [115], the lane keeping system helps the driver to keep the vehicle on a lane by applying torque (also called haptic feedback) to the steering wheel. In this work, the impact this system has on driver's fatigue during monotonous driving is investigated by monitoring the standard deviation of lateral position.…”

Section: B Autonomous Systems Developmentmentioning

confidence: 99%

A Review of Driving Simulation Technology and Applications

Bruck

Haycock

Emadi

2021

IEEE Open J. Veh. Technol.

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Driving simulation has become a very useful tool for vehicle design and research in industry and educational institutes. This paper provides a review of driving simulator components, including the vehicle dynamics model, the motion system, and the virtual environment, and how they interact with the human perceptual system in order to create the illusion of the driving. In addition, a sample of current state-of-the-art vehicle simulators and algorithms are described. Finally, current applications are discussed, such as driver-centered studies, chassis and powertrain design, and autonomous systems development.

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“…However, these methods are invasive and require contact with the driver's body. The second method is used to measure the behaviors of vehicles, [7][8][9][10][11] such as speed, steering wheel rotation angle, and lane departure detection; however, this method is affected by driving conditions, driving experience, and vehicle type. The third method analyzes the driver's face, such as the PERCLOS value, blink frequency, head posture, and yawn detection.…”

Section: Introductionmentioning

confidence: 99%

Eye and mouth state detection algorithm based on contour feature extraction

Wang

Yang

et al. 2018

J. Electron. Imag.

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, "Eye and mouth state detection algorithm based on contour feature extraction," J. Electron. Imaging 27(5), 051205 (2018), doi: 10.1117/1.JEI.27.5.051205. Abstract. Eye and mouth state analysis is an important step in fatigue detection. An algorithm that analyzes the state of the eye and mouth by extracting contour features is proposed. First, the face area is detected in the acquired image database. Then, the eyes are located by an EyeMap algorithm through a clustering method to extract the sclera-fitting eye contour and calculate the contour aspect ratio. In addition, an effective algorithm is proposed to solve the problem of contour fitting when the human eye is affected by strabismus. Meanwhile, the value of chromatism s is defined in the RGB space, and the mouth is accurately located through lip segmentation. Based on the color difference of the lip, skin, and internal mouth, the internal mouth contour can be fitted to analyze the opening state of mouth; at the same time, another unique and effective yawning judgment mechanism is considered to determine whether the driver is tired. This paper is based on the three different databases to evaluate the performance of the proposed algorithm, and it does not need training with high calculation efficiency. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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The Effect of a Haptic Guidance Steering System on Fatigue-Related Driver Behavior

Cited by 63 publications

References 38 publications

A Review of Shared Control for Automated Vehicles: Theory and Applications

A Review of Shared Control for Automated Vehicles: Theory and Applications

A Review of Driving Simulation Technology and Applications

Eye and mouth state detection algorithm based on contour feature extraction

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