Driver Modeling for Teleoperation with Time Delay

Vozar, Steve; Tilbury, Dawn M.

doi:10.3182/20140824-6-za-1003.02275

Cited by 17 publications

(11 citation statements)

References 10 publications

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“…Tests of a real vehicle on a closed track with constant 500 ms delay showed a lateral offset standard deviation of 0.4 meters, demonstrating that the operator was able to safely follow a lane at 30 km/h (Gnatzig et al, 2013). Other studies have shown worse driver performance when delays are greater than 300ms (Neumeier et al, 2019b) and 700 ms (Davis et al, 2010;Vozar and Tilbury, 2014). These studies have generally been conducted in simulation or in controlled, low-risk environments; it is not clear whether results will transfer to dynamic driving environments.…”

Section: Technical Feasibilitymentioning

confidence: 86%

Non-technological challenges for the remote operation of automated vehicles

Goodall

2020

Transportation Research Part A: Policy and Practice

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No existing automated vehicle can operate in all conditions and environments. In order to allow unmanned operation of automated vehicles in all conditions, many developers have the capability for human drivers to operate the vehicle from a remote location using wireless communication. This practice, referred to as remote operation or teleoperation, is prevalent among industry, yet has received little attention in the legal and transportation literature. This paper describes the legal environment for remote operation of vehicles, both in terms of existing motor vehicle codes and model legislation. The operational performance of remote operation is explored, and a model is developed to estimate the number of remote operators needed to manage large automated vehicle fleets using reasonable assumptions.

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Section: Technical Feasibilitymentioning

confidence: 86%

Non-technological challenges for the remote operation of automated vehicles

Goodall

2020

Transportation Research Part A: Policy and Practice

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“…A common recommendation for interaction is that the latency of operations—the time between motor command and updated display—should be less than about 300 ms if performance is to be unaffected, and experienced as seamless ( Ballard, Hayhoe, Pook & Rao, 1997 ; Gray & Fu, 2004 ; Vozar & Tilbury, 2014 ). As a step toward understanding this phenomenon, Liu and Heer (2014) examined the effect of latency on exploratory visual analysis, using a simplified version of a real-world dataset.…”

Section: Interaction In Visualizationmentioning

confidence: 99%

Visualization as a stimulus domain for vision science

Rensink

2021

Journal of Vision

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Traditionally, vision science and information/data visualization have interacted by using knowledge of human vision to help design effective displays. It is argued here, however, that this interaction can also go in the opposite direction: the investigation of successful visualizations can lead to the discovery of interesting new issues and phenomena in visual perception. Various studies are reviewed showing how this has been done for two areas of visualization, namely, graphical representations and interaction, which lend themselves to work on visual processing and the control of visual operations, respectively. The results of these studies have provided new insights into aspects of vision such as grouping, attentional selection and the sequencing of visual operations. More generally yet, such results support the view that the perception of visualizations can be a useful domain for exploring the nature of visual cognition, inspiring new kinds of questions as well as casting new light on the limits to which information can be conveyed visually.

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“…These models can be used to simulate human drivers when testing new vehicle designs and technologies, 6,33 and despite the complexity of human behavior, low order models are often sufficient for many control tasks. 34 In our prior work, we introduced 8 and performed a stability analysis 35 on a low-order model inspired by MacAdam 31 that can be used to simulate human steering behavior in a teleoperated navigation task in the presence of latency. In this paper, we discuss the development of this model in further detail.…”

Section: Control Theoretic Modelsmentioning

confidence: 99%

“…We performed a stability analysis on this steering model for constant latencies. 35 The analysis was carried out considering the robot traveling along a straight-line path and indicated that the maximum allowable delay, while maintaining stability, depends on robot speed, turn gain, lookahead distance, and control gains. More specifically, the criteria found agree that the ratio of K p /K d must decrease as latency increases.…”

Section: Model Parameter Tuningmentioning

confidence: 99%

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Development and analysis of an operator steering model for teleoperated mobile robots under constant and variable latencies

Vozar¹,

Storms²,

Tilbury³

2016

Robotica

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SUMMARYLatency hinders a mobile robot teleoperator's ability to perform remote tasks. However, this effect is not well modeled. This paper develops a model for teleoperator steering behavior as a PD controller based on projected lateral displacement, which was tuned to reflect user performance determined by a 31-subject user study under constant and variable latency (having mean latencies between 0 and 750 ms). Additionally, we determined that operator performance under variable latency could be mapped to the expected performance of an equivalent constant latency. We then tested additional latency distributions in simulation and demonstrated equivalent steering performance among several different latency distributions.

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Driver Modeling for Teleoperation with Time Delay

Cited by 17 publications

References 10 publications

Non-technological challenges for the remote operation of automated vehicles

Non-technological challenges for the remote operation of automated vehicles

Visualization as a stimulus domain for vision science

Development and analysis of an operator steering model for teleoperated mobile robots under constant and variable latencies

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