Research on influence of sun glare in urban tunnels based on cellular automaton model in the framework of Kerner’s three-phase traffic theory

Hu, Xiaojian; Zhang, Fang; Lü, Jian; Li, Mingyang; Ma, Yongfeng; Qian, Weiping

doi:10.1016/j.physa.2019.121176

Cited by 17 publications

(3 citation statements)

References 62 publications

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“…The indexes of the drivers' eye movements can be also used to evaluate the driving safety. In [27], the influence of sun glare on individual drivers in urban tunnels is quantitatively illustrated by the change rate of driver's pupillary area. The random choice model of deceleration behavior in response to sun glare (DBSG) is established to study the influence of DBSG on traffic safety.…”

Section: Literature Reviewmentioning

confidence: 99%

An Evaluation Method for Visual Search Stability in Urban Tunnel Entrance and Exit Sections Based on Markov Chain

Zhou

Lü

et al. 2020

IEEE Access

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Tunnel section is the throat of transportation and attracts lots of attentions. This paper proposed a method to evaluate the driver's visual search stability based on the Markov Chain properties of eye movements. Firstly, visual and physiological data about 16 participants driving through 13 urban tunnels were collected. Then, the view area was divided into six AOIs (Area of Interest) by fast clustering of the drivers' fixation points. The one-step fixation transition probability and the stable distribution of different lane changing behavior were obtained based on the division of the view area. The probability of transition from the forward windscreen to the left rearview mirror and other 6 visual parameters were selected as indexes by correlation tests. And the first four principal components which covered 96.1% of all information were extracted. Then an evaluation method for visual search stability was implemented by principal component analysis. In order to validate the method, average lane change times, average speed and SDNN (Standard Deviation of NN Intervals) of the drivers' heart rate were clustered into two categories. According to the consistency between the evaluation results and the clustering results, the evaluation method proposed in this paper has been proven to be reliable. Finally, the score threshold for judging the driver's stability was obtained as E = 0.313. The method could be applied to adjustment of tunnel facilities, assistance in driving training and development of auto driving system by assessing whether a driver can take over the control of the vehicle or not.

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Section: Literature Reviewmentioning

confidence: 99%

An Evaluation Method for Visual Search Stability in Urban Tunnel Entrance and Exit Sections Based on Markov Chain

Zhou

Lü

et al. 2020

IEEE Access

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“…Kircher and Ahlstrom conducted a tunnel-driving simulation experiment, and the results showed that tunnel design and illumination had some influence on the drivers' behavior, but visual attention given to the driving task was the most crucial factor, giving rise to significant changes in both driving behavior and visual behavior [16,17]. Hu et al used the change rate of driver pupil area to describe the influence of sunlight under the ventilation shaft of an urban tunnel on drivers and established a random selection model of deceleration behavior under strong solar light [18]. The variations in the drivers' eye movements and speed were much more significant in the entrance zone of a tunnel without spatial intervisibility than in a tunnel with spatial intervisibility [19,20].…”

Section: Literature Reviewmentioning

confidence: 99%

Experimental Analysis of Driver Visual Characteristics in Urban Tunnels

Fang

2021

Applied Sciences

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Through an urban tunnel-driving experiment, this paper studies the changing trend of drivers’ visual characteristics in tunnels. A Tobii Pro Glasses 2 wearable eye tracker was used to measure pupil diameter, scanning time, and fixation point distribution of the driver during driving. A two-step clustering algorithm and the data-fitting method were used to analyze the experimental data. The results show that the univariate clustering analysis of the pupil diameter change rate of drivers has poor discrimination because the pupil diameter change rate of drivers in the process of “dark adaptation” is larger, while the pupil diameter change rate of drivers in the process of “bright adaptation” is relatively smooth. The univariate and bivariate clustering results of drivers’ pupil diameters were all placed into three categories, with reasonable distribution and suitable differentiation. The clustering results accurately corresponded to different locations of the tunnel. The clustering method proposed in this paper can identify similar behaviors of drivers at different locations in the transition section at the tunnel entrance, the inner section, and the outer area of the tunnel. Through data-fitting of drivers’ visual characteristic parameters in different tunnels, it was found that a short tunnel, with a length of less than 1 km, has little influence on visual characteristics when the maximum pupil diameter is small, and the percentage of saccades is relatively low. An urban tunnel with a length between 1 and 2 km has a significant influence on visual characteristics. In this range, with the increase in tunnel length, the maximum pupil diameter increases significantly, and the percentage of saccades increases rapidly. When the tunnel length exceeds 2 km, the maximum pupil diameter does not continue to increase. The longer the urban tunnel, the more discrete the distribution of drivers’ gaze points. The research results should provide a scientific basis for the design of urban tunnel traffic safety facilities and traffic organization.

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“…is statement is related to the phenomenon observed in Section 1. However, unfortunately, in Kerner's abovementioned and following works [4][5][6], clear de nition of HNAC and explicit formulas were not provided, either in other followers' works [7,8].…”

Section: Literature Reviewmentioning

confidence: 99%

Defining Highway Node Acceptance Capacity (HNAC): Theoretical Analysis and Data Simulation

Liu

Dong

et al. 2020

Journal of Advanced Transportation

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A new concept of Highway Node Acceptance Capacity (HNAC) is proposed in this paper inspired by a field data observation. To understand HNAC in microscopic view, boundary condition of successful merging is found using car-following behaviours and lane-changing rules, which could also explain traffic oscillations. In macroscopic view, linear positive relationship between HNAC and background traffic volume is obtained based on moving bottleneck. To determine the explicit form of the relationship, data simulation considering car-following behaviours and traffic flow theory is used. In the results, the synchronization phenomenon of oscillation in on-ramp (with respect to main road) and intersected road is found. The explicit equation of HNAC is determined based on standard deviation and correlation coefficient analysis, and also proved to be accurate with model validation, which is helpful in studies related to propagation mechanism of traffic emergencies on highway network.

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Research on influence of sun glare in urban tunnels based on cellular automaton model in the framework of Kerner’s three-phase traffic theory

Cited by 17 publications

References 62 publications

An Evaluation Method for Visual Search Stability in Urban Tunnel Entrance and Exit Sections Based on Markov Chain

An Evaluation Method for Visual Search Stability in Urban Tunnel Entrance and Exit Sections Based on Markov Chain

Experimental Analysis of Driver Visual Characteristics in Urban Tunnels

Defining Highway Node Acceptance Capacity (HNAC): Theoretical Analysis and Data Simulation

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