Using the visual intervention influence of pavement markings for rutting mitigation–part I: preliminary experiments and field tests

Wu, Gang; Chen, Feng; Pan, Xiaodong; Xu, Mi; Zhu, Xingyi

doi:10.1080/10298436.2017.1334460

Cited by 39 publications

(32 citation statements)

References 26 publications

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“…However, it may be interesting to study how the visual intervention of road markings affects driving performance behaviour in older drivers. Indeed, some studies state that a comb-shaped marking could solve some traffic problems associated with driving safety [26,27]. Similarly, general driving performance was also more deteriorated in the cataract group, as shown by the results corresponding to the overall driving performance score.…”

Section: Discussionmentioning

confidence: 93%

Intraocular scattering as a predictor of driving performance in older adults with cataracts

et al. 2020

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Cataracts can limit a person's ability to perform vision-dependent tasks safely, affecting the quality of life of older people. This study examines the relationship between visual function and driving, by studying which visual parameters might be important for predicting driving performance in older drivers with and without cataracts, ascertaining whether the objective measurement of intraocular scattering should be considered in assessment procedures for older drivers. This cross-sectional study involved a total of 20 older drivers (10 patients with bilateral cataracts and 10 control subjects). All participants were examined for visual acuity, contrast sensitivity, visual discrimination capacity, and intraocular scattering. Driving performance was also tested using a driving simulator. To study the relationship between visual parameters and driving performance, a correlation analysis and regression model were used. Drivers with cataracts showed a significantly impaired (p<0.05) visual function, with an Objective Scattering Index (OSI) 3.5 times greater than the control group. Driving performance was also significantly worse (p<0.05) in drivers with cataracts, reflected by a notable deterioration in lane keeping. The correlation analysis showed significant associations between driving performance and all the visual parameters studied. Finally, the regression model revealed that the OSI was the best predictor of driving performance, accounting for 51.3% of its variance. Visual function and driving performance are markedly deteriorated when cataracts are present. Our results demonstrate that the objective scattering index (OSI) has a high predictive power when it comes to simulated driving performance in older drivers, both with and without cataracts, suggesting that scatter measurements could be important in helping better understand visual limitations in older drivers.

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Section: Discussionmentioning

confidence: 93%

Intraocular scattering as a predictor of driving performance in older adults with cataracts

et al. 2020

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“…For example, the team of Harbin Institute of Technology studied the relationship between the drivers physiological characteristics and driving behavior [33]. e team of Jilin University [34,35], Sun Yat-sen University [36] and Tongji University [37] analyzed the relationship between fatigue and driving risk based on the drivers' physiological features.…”

Section: Related Workmentioning

confidence: 99%

Physiological Characteristics and Nonparametric Test for Master-Slave Driving Task’s Mental Workload Evaluation in Mountain Area Highway at Night

Wang

Liu

Feng

2019

Journal of Advanced Transportation

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With the rapid development of advanced mobile intelligent terminals, driving tasks are diverse, and new tra c safety problems occur. We propose a new research on physiological characteristics and nonparametric tests for the master-slave driving task, especially for evaluation of drivers' mental workload in mountain area highway in nighttime scenario. First, we establish the experimental platform based driving simulator and design the master-slave driving task. Second, based on the physiological data and subjective evaluation for mental workload, we use statistical methods to composite the physical changes evolution analysis in a driving simulator. Finally, we nished nonparametric test of the drivers' psychological load and road test. e results show that in compassion with the daytime scenario, drivers should pay much e ort to driving skills and risk identi cation in the nighttime scenario. us, in the same driving condition, drivers should bear the higher level of mental workload, and it has been subjected to even greater pressures and intensity of emotions.

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“…Driving performance in tunnels is different from freeway driving, and darker lighting conditions and enclosed space will make drivers nervous and increase the effort required to maintain lateral control of the vehicle, which will affect drivers' psychological state and driving behavior [3,4]. Related research shows that visual intervention is an effective method in vehicle trajectories' intervention [5,6], and the tunnel safety can be improved by using visual intervention method to affect the driver's driving behavior in tunnel section. erefore, it is of practical significance to study the driver's physiological and psychological state in tunnel environment, which reduces the accident rate in tunnel environment.…”

Section: Introductionmentioning

confidence: 99%

Model of Driver’s Eye Movement and ECG Index under Tunnel Environment Based on Spatiotemporal Data

Shen

Wang

2020

Journal of Advanced Transportation

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In order to improve the driver's physiological and psychological state, the driver's mental load which is caused by sight distance, lighting, and other factors in the tunnel environment should be quantified via modeling the spatiotemporal data. e experimental schemes have been scientifically designed based on methods of traffic engineering and human factor engineering, which aims to test the driver's spatiotemporal data of eye movement and ECG (electrocardiogram) index in the tunnel environment. Firstly, the changes in the driver's spatiotemporal data are analyzed to judge the changing trend of the driver's workload in the tunnel environment. e results show that the cubic spline interpolation function model can fit the dynamic changes of average pupil diameter and heart rate (HR) growth rate well, and the goodness of fit for the model group is above 0.95. So, tunnel environment makes the driver's typical physiological indicators fluctuate in the coordinates of time and space, which can be modeled and quantified. Secondly, in order to analyze the classification of tunnel risk level, a fusion model has been built based on the functions of average pupil diameter and HR growth rate. e tunnel environmental risk level has been divided into four levels via the fusion model, which can provide a guidance for the classification of tunnel risk level. Furthermore, the fusion model allows tunnel design and construction personnel to adopt different safety design measures for different risk levels, and this method can effectively improve the economy of tunnel operating safety design.

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Using the visual intervention influence of pavement markings for rutting mitigation–part I: preliminary experiments and field tests

Cited by 39 publications

References 26 publications

Intraocular scattering as a predictor of driving performance in older adults with cataracts

Intraocular scattering as a predictor of driving performance in older adults with cataracts

Physiological Characteristics and Nonparametric Test for Master-Slave Driving Task’s Mental Workload Evaluation in Mountain Area Highway at Night

Model of Driver’s Eye Movement and ECG Index under Tunnel Environment Based on Spatiotemporal Data

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