Role of Lateral Acceleration in Curve Driving: Driver Model and Experiments on a Real Vehicle and a Driving Simulator

Reymond, Gilles; Kemeny, Andras; Droulez, Jacques; Berthoz, Alain

doi:10.1518/001872001775898188

Cited by 201 publications

(143 citation statements)

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“…Finally, as Gibson has already pointed out, kinaesthetic cues also strongly influence the perception of speed [1,14,19]. To simulate vestibular stimuli, accelerations to be perceived by the driver can be rendered by real time generation of simulator cockpit motion, following appropriate vehicle dynamics.…”

Section: Trends In Cognitive Sciencesmentioning

confidence: 99%

“…However, earlier studies have shown that the absence of physical motion in a driving simulator modifies the driver's reactions [19]. Moreover, computational models of self-motion perception [57] and studies performed on a moving-base driving simulator indicate that driver's control strategies on curved roads make use not only of visual, but also of extra-visual information, such as vestibular (see Box 3) and proprioceptive cues [14,58]. So, on the basis of models proposed in earlier studies [58,59], it has been suggested that these cues are used by the driver to control steering and regulate speed.…”

Section: Influence Of Extra-visual Cues In Steeringmentioning

confidence: 99%

“…However, Gibson's original theory also included a definition of the perceptual field of the car itself, bringing to the driver kinaesthetic and tactile cues. These ideas were applied to driving simulation from the early 1980s [13][14][15], and since then many simulator experiments have been carried out for vehicle design [16 -18] and driver perception studies [19,20].…”

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Evaluating perception in driving simulation experiments

Kemeny

Panerai

2003

Trends in Cognitive Sciences

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275

147

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The use of driving simulation for vehicle design and driver perception studies is expanding rapidly. This is largely because simulation saves engineering time and costs, and can be used for studies of road and traffic safety. How applicable driving simulation is to the real world is unclear however, because analyses of perceptual criteria carried out in driving simulation experiments are controversial. On the one hand, recent data suggest that, in driving simulators with a large field of view, longitudinal speed can be estimated correctly from visual information. On the other hand, 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.Vehicle driving implies perception and control of selfmotion at a greater range of velocities than locomotion by walking. It is often considered to be a task dominated by visual information. However, it is well-established that other sensory information, such as that provided by the vestibular and PROPRIOCEPTIVE (see Glossary) channels, also contributes to the perception and control of selfmotion. Motivated by a recent renewed interest in the role and function of these non-visual sensory modalities, we aim in this review to re-evaluate the role of visuovestibular interactions in driving simulation experiments, and to assess how applicable driving simulation is to the real world for studies of vehicle dynamics or driver behaviour.In 1938 Gibson [1] proposed a psychophysical theory of perception for automobile-driving, defining a 'terrain of field of space' for the driver, with the car considered as a tool of locomotion and the driver aiming to drive in the middle of a 'field of safe travel'. In 1950 he described the visual perception of space [2] based on visual depth, distance or orientation stimulus variables. OPTIC FLOW, one of the most important visual cues he proposed, is defined as the visual motion experienced as a result of walking or driving, and it is thought to play a dominant role in the control of heading [3] and collision detection [4 -7]. However, regarding the control of the direction of movement in natural environments (i.e. walking), there is still disagreement over whether the structure of the flow [8,9] or the visual EGOCENTRIC DIRECTION per se [10,11] is the dominant source of information. It is not clear either whether the same strategies used for natural locomotion apply to driving situations where displacements occur at higher velocities. Interestingly, a new point of view on these controversial issues was recently provided by experiments performed in driving simulators [12]. However, Gibson's original theory also included a definition of the perceptual field of the car itself, bringing to the driver kinaesthetic and tactile cues. These ideas were applied to driving simulation from the early 1980s [13][14][15], and since then many simulator experiments have been carried out for...

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Section: Trends In Cognitive Sciencesmentioning

confidence: 99%

Section: Influence Of Extra-visual Cues In Steeringmentioning

confidence: 99%

mentioning

confidence: 99%

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Evaluating perception in driving simulation experiments

Kemeny

Panerai

2003

Trends in Cognitive Sciences

Self Cite

275

147

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“…Vestibular inputs have considerable effects on speed adjustments, especially when driving on curves (Reymond et al, 2001). These effects are not considered in the current model.…”

Section: Main Concepts Of the Steering Modelmentioning

confidence: 99%

Modeling steering using the Queueing Network - Model Human Processor (QN-MHP)

Tsimhoni¹,

Liu²

2003

PsycEXTRA Dataset

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The Queueing Network -Model Human Processor (QN-MHP) is a computational architecture that combines the mathematical theories and simulation methods of queueing networks (QN) with the symbolic and procedure methods of a GOMS-style task description and the Model Human Processor (MHP). Using QN-MHP, a steering model was created to represent the concurrent perceptual, cognitive, and motor activities involved in vehicle steering as truly concurrent processes. The model was compared with driving performance of human subjects and demonstrated realistic steering behavior. It steered a simulated vehicle at a fixed speed within the lane boundaries of straight sections and curves of different radii. In a quantitative validation of several basic measures of driving performance, the steering model yielded steering angle and lateral position similar to the human subject data. This work showed the strength of QN-MHP as a model of driving behavior. Ongoing work further develops the model by expanding the scope of the driving task and by adding a concurrent secondary in-vehicle task.

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“…In [4] a study was carried out to predict motor vehicle collisions in young adults, by making use of a PC-based driving simulator. In [5] the patterns followed by drivers in adjusting the speed in curves is studied by carrying various tests in a motion-based driving simulator. In [6], how the simulator test conditions affect the severity of the 2 of 13 simulator sickness symptoms was studied.…”

Section: Introductionmentioning

confidence: 99%

On a First Evaluation of ROMOT—A RObotic 3D MOvie Theatre—For Driving Safety Awareness

Casas

Portalés

García-Pereira

et al. 2017

MTI

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Abstract:In this paper, we introduce ROMOT, a RObotic 3D-MOvie Theatre, and present a case study related to driving safety. ROMOT is built with a robotic motion platform, includes multimodal devices, and supports audience-film interaction. We show the versatility of the system by means of different types of system setups and generated content that includes a first-person movie and others involving the technologies of virtual, augmented, and mixed realities. Finally, we present the results of some preliminary user tests made at the laboratory level, including the system usability scale. They give satisfactory scores for the usability of the system and the individual's satisfaction.

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Role of Lateral Acceleration in Curve Driving: Driver Model and Experiments on a Real Vehicle and a Driving Simulator

Cited by 201 publications

References 21 publications

Evaluating perception in driving simulation experiments

Evaluating perception in driving simulation experiments

Modeling steering using the Queueing Network - Model Human Processor (QN-MHP)

On a First Evaluation of ROMOT—A RObotic 3D MOvie Theatre—For Driving Safety Awareness

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