Prediction of effort and eye movement measures from driving scene components

Cabrall, Christopher; Happee, Riender; Winter, Joost de

doi:10.1016/j.trf.2019.11.001

Cited by 11 publications

(6 citation statements)

References 12 publications

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“…This suggests that changes in TSIV have a significant effect on the change in drivers’ average saccade amplitude, with both too little and too much TSIV resulting in decreased average saccade amplitudes. This reflects the limited information that can be obtained with each fixation during the driver’s visual search under conditions of TSIV insufficient and overload, resulting in smaller subsequent saccade distances [ 39 ], as well as the greater difficulty for the driver to extract information, which makes the saccade amplitude smaller.…”

Section: Discussionmentioning

confidence: 99%

Analysis of Traffic Signs Information Volume Affecting Driver’s Visual Characteristics and Driving Safety

Han

Wang

et al. 2022

IJERPH

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To study the influence of traffic signs information volume (TSIV) on drivers’ visual characteristics and driving safety, the simulation scenarios of different levels of TSIV were established, and 30 participants were recruited for simulated driving tests. The eye tracker was used to collect eye movement data under three-speed conditions (60 km/h, 80 km/h, and 100 km/h) and different levels of TSIV (0 bits/km, 10 bits/km, 20 bits/km, 30 bits/km, 40 bits/km, and 50 bits/km). Principal component analysis (PCA) was used to select indicators sensitive to the influence of TSIV on the drivers’ visual behavior and to analyze the influence of TSIV on the drivers’ visual characteristics and visual workload intensity under different speed conditions. The results show that the fixation duration, saccade duration, and saccade amplitude are the three eye movement indicators that are most responsive to changes in the TSIV. The driver’s visual characteristics perform best at the S3 TSIV level (30 bits/km), with the lowest visual workload intensity, indicating that drivers have the lowest psychological stress and lower driving workload when driving under this TSIV condition. Therefore, a density of 30 bits/km is suggested for the TSIV, in order to ensure the security and comfort of the drivers. The theoretical underpinnings for placing and optimizing traffic signs will be provided by this work.

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Section: Discussionmentioning

confidence: 99%

Analysis of Traffic Signs Information Volume Affecting Driver’s Visual Characteristics and Driving Safety

Han

Wang

et al. 2022

IJERPH

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show abstract

“…As a consequence of this, having a saccade amplitude that is sufficiently large is advantageous for the driver in their capacity to anticipate and access information concerning the traffic situation that is all around them. This, in turn, eliminates or significantly reduces the driver's experience of strain (69,70). Statistical characteristics and changing trends of drivers' saccade amplitude under different levels of TSIV are respectively shown in Table 8 and Figure 5.…”

Section: Analysis Of Saccade Amplitudementioning

confidence: 97%

Evaluation of Traffic Signs Information Volume at Highway Tunnel Entrance Zone Based on Driver’s Visual Characteristics

Han,

Du,

2023

Transportation Research Record: Journal of the Transportation R

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Reasonable and appropriate traffic sign information volume (TSIV) is crucial to ensure road traffic safety, especially at the entrance zones of highway tunnels. This research compares how various levels of TSIV affect both visual characteristics and visual workload of drivers through real road driving tests. Forty participants were recruited to conduct a field driving experiment at six highway tunnels. The eye movement data of drivers were collected by an eye tracker and the effects of TSIV on drivers’ eye movement characteristics, visual stability, visual SampEn (sample entropy), and visual workload intensity were analyzed and evaluated. At the T3 level (48.31 bits) of TSIV, the drivers’ average fixation duration and average saccade duration were both at the lowest value, while the drivers’ average saccade amplitude reached the maximum, and the dispersion of the three eye movement indicators was the smallest. In addition, the drivers’ visual SampEn increased continuously when approaching the tunnel portal, and was the lowest at T3 level. With the increase of TSIV, drivers’ visual workload intensity decreased first and then increased, the minimum being at T3 level. The drivers’ visual behavior is more stable, visual coordination ability is better, and visual workload and psychological pressure are least under the T3 level, which is beneficial to ensure driving safety at the entrance zone of a highway tunnel. Inappropriate levels of TSIV at highway tunnel entrance zones will cause inevitable risks to driving safety.

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“…Sometimes for convenience, the size of AOIs can be simplified into a rectangle [113]. Second, the whole stimuli can be separated into several AOIs [20]. In addition, there are dynamic AOIs defined by stimuli that changes as time goes [20], [63].…”

Section: B Stimulus-generated Aoismentioning

confidence: 99%

“…Those focused on safety measure hazard detection [13], steering [14], automated driving [15], luminance [16] by drivers; and landing [17], conflict detection [18], air traffic control [19] by pilots. Mental tests address mental workload [20], [21], and fatigue [22], [23].…”

mentioning

confidence: 99%

A Survey of Eye Tracking in Automobile and Aviation Studies: Implications for Eye-Tracking Studies in Marine Operations

Mao

Hildre

et al. 2021

IEEE Trans. Human-Mach. Syst.

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In the last decade researchers have increasingly considered eye tracking of the operators of cars and airplanes as a means to address human error and evaluate operational effectiveness. This article presents a systematic survey of recently published papers about this approach in service to the question as to whether eye tracking can be used to address operational safety in marine operations. The surveyed papers are selected systematically and were categorized according to several defined characteristics. Eye tracking depends on defining operators' areas of interest (AOIs) and measuring operators focus on them over time. We identified the method of defining AOIs as a key distinction between studies; the papers fell into four categories, depending on whether researchers relied on an expert, based it on the stimulus itself, or used an attention map or a clustering algorithm to define the AOIs they used. The article also summarizes and analyzes the design and procedure of the eye-tracking experiments in the papers. Based on the features of marine operation, instruction on AOI definition in different scenarios is extracted; guidelines on experimental design and procedure selection are provided. In the article's conclusion we apply the results to a case study of a heavy-lifting operation to demonstrate the effectiveness of eye-tracking in marine operations. Index Terms-Area of interest (AOI) definition method, automobile and aviation, eye tracking, knowledge transfer, marine operation. I. INTRODUCTION E YE tracking is a sensor technology that captures human eye behavior. It has been widely used to gain insight about automobile operation [1], [2], aviation [3], [4], web searching [5], reading [6], drawing [7], medical surgery [8], energy [9], mining [10], offshore [11], and the effect of depictions of healthy and unhealthy foods on children [12]. Among these, automobile and aviation are the two frequently studied fields with a wide range of research applications. Studies in these areas have focused either directly on safety or mental testing of drivers/pilots.

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Prediction of effort and eye movement measures from driving scene components

Cited by 11 publications

References 12 publications

Analysis of Traffic Signs Information Volume Affecting Driver’s Visual Characteristics and Driving Safety

Analysis of Traffic Signs Information Volume Affecting Driver’s Visual Characteristics and Driving Safety

Evaluation of Traffic Signs Information Volume at Highway Tunnel Entrance Zone Based on Driver’s Visual Characteristics

A Survey of Eye Tracking in Automobile and Aviation Studies: Implications for Eye-Tracking Studies in Marine Operations

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