Direct and Indirect Haptic Aiding for Curve Negotiation

Profumo, Luca; Pollini, Lorenzo; Abbink, David A.

doi:10.1109/smc.2013.318

Cited by 21 publications

(21 citation statements)

References 11 publications

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“…In most studies the force exerted by the system was either a function of an external variable that represented the current position of the vehicle with respect to the road (e.g., deviation from lane centre) [6], [27], [32], [38], [39], [45], [46], [58], [65]- [68] or used a look-ahead principle, which determined the future position of the vehicle with respect to the road (e.g., time to line crossing) [12], [30], [41], [47]- [49], [54]- [56], [67], [69]. Guidance systems designed to support car-following often used a function that combined TTC and THW to determine a counterforce on the gas pedal [6], [22], [39], [45].…”

Section: D) Signalmentioning

confidence: 99%

“…Other dependent measures that were used for warning systems were the number of collisions, the number of lane excursions, and the number of warnings received. Guidance systems were often evaluated by means of a performance measure describing how well a task is executed by the participant [6], [12], [34]- [36], [39], [42], [45]- [47], [49], [50], [55], [56], [65], [66], [69], [70]. The dependent measures used to evaluate performance differ across studies, but are usually related to accuracy or precision (e.g., root mean squared error of lane centre error).…”

Section: D) Signalmentioning

confidence: 99%

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The Effect of Haptic Support Systems on Driver Performance: A Literature Survey

Petermeijer

Abbink

Mulder

et al. 2015

IEEE Trans. Haptics

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111

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A large number of haptic driver support systems have been described in the scientific literature. However, there is little consensus regarding the design, evaluation methods, and effectiveness of these systems. This literature survey aimed to investigate: (1) what haptic systems (in terms of function, haptic signal, channel, and supported task) have been experimentally tested, (2) how these haptic systems have been evaluated, and (3) their reported effects on driver performance and behaviour. We reviewed empirical research in which participants had to drive a vehicle in a real or simulated environment, were able to control the heading and/or speed of the vehicle, and a haptic signal was provided to them. The results indicated that a clear distinction can be made between warning systems (using vibrations) and guidance systems (using continuous forces). Studies typically used reaction time measures for evaluating warning systems and vehicle-centred performance measures for evaluating guidance systems. In general, haptic warning systems reduced the reaction time of a driver compared to no warnings, although these systems may cause annoyance. Guidance systems generally improved the performance of drivers compared to non-aided driving, but these systems may suffer from after-effects. Longitudinal research is needed to investigate the transfer and retention of effects caused by haptic support systems.

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Section: D) Signalmentioning

confidence: 99%

Section: D) Signalmentioning

confidence: 99%

The Effect of Haptic Support Systems on Driver Performance: A Literature Survey

Petermeijer

Abbink

Mulder

et al. 2015

IEEE Trans. Haptics

Self Cite

111

View full text Add to dashboard Cite

show abstract

“…Manipulating the wheel correctly could also be tricky in normal driving, for instance, when there is low visibility. Profumo et al (2013) showed that a force-feedback steering wheel could help the driver to handle curves. During a simulated driving task with low visibility, the application of a rotary force on the wheel in the direction of the curves on road helped the driver to maintain his trajectory.…”

Section: Maneuver Supportmentioning

confidence: 99%

The Use of Haptic and Tactile Information in the Car to Improve Driving Safety: A Review of Current Technologies

Gaffary

Lécuyer

2018

Front. ICT

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This paper surveys the haptic technologies deployed in cars and their uses to enhance drivers' safety during manual driving. These technologies enable to deliver haptic (tactile or kinesthetic) feedback at various areas of the car, such as the steering wheel, the seat, or the pedal. The paper explores two main uses of the haptic modality to fulfill the safety objective: to provide driving assistance and warning. Driving assistance concerns the transmission of information usually conveyed with other modalities for controlling the car's functions, maneuvering support, and guidance. Warning concerns the prevention of accidents using emergency warnings, increasing the awareness of surroundings, and preventing collisions, lane departures, and speeding. This paper discusses how haptic feedback has been introduced so far for these purposes and provides perspectives regarding the present and future of haptic cars meant to increase driver's safety.

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“…Bukusoglu et al (2008) proposed shared control as a mechanism to assist a human operator in the manipulation of microspheres with optical tweezers. Shared control was also used by Mulder et al (2012) and Profumo et al (2013) as a driver support system for car pilots and by Glassmire et al (2004) for cooperative manipulation of objects between human workers and a remotely operated humanoid robot.…”

Section: Related Work and Contributionsmentioning

confidence: 99%

Shared planning and control for mobile robots with integral haptic feedback

Masone

Mohammadi

Giordano

et al. 2018

The International Journal of Robotics Research

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This paper presents a novel bilateral shared framework for online trajectory generation for mobile robots. The robot navigates along a dynamic path, represented as a B-spline, whose parameters are jointly controlled by a human supervisor and by an autonomous algorithm. The human steers the reference (ideal) path by acting on the path parameters which are also affected, at the same time, by the autonomous algorithm in order to ensure: i) collision avoidance, ii) path regularity and iii) proximity to some points of interest. These goals are achieved by combining a gradient descent-like control action with an automatic algorithm that re-initializes the traveled path (replanning) in cluttered environments in order to mitigate the effects of local minima. The control actions of both the human and the autonomous algorithm are fused via a filter that preserves a set of local geometrical properties of the path in order to ease the tracking task of the mobile robot. The bilateral component of the interaction is implemented via a force feedback that accounts for both human and autonomous control actions along the whole path, thus providing information about the mismatch between the reference and traveled path in an integral sense. The proposed framework is validated by means of realistic simulations and actual experiments deploying a quadrotor UAV supervised by a human operator acting via a force-feedback haptic interface. Finally, a user study is presented in order to validate the effectiveness of the proposed framework and the usefulness of the provided force cues.

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Direct and Indirect Haptic Aiding for Curve Negotiation

Cited by 21 publications

References 11 publications

The Effect of Haptic Support Systems on Driver Performance: A Literature Survey

The Effect of Haptic Support Systems on Driver Performance: A Literature Survey

The Use of Haptic and Tactile Information in the Car to Improve Driving Safety: A Review of Current Technologies

Shared planning and control for mobile robots with integral haptic feedback

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