
==== Front
Heliyon
Heliyon
Heliyon
2405-8440
Elsevier

S2405-8440(24)12564-9
10.1016/j.heliyon.2024.e36533
e36533
Research Article
Research on the nighttime visibility of white pavement markings
Guan Yanyan a
Hu Jiangbi hujiangbi@bjut.edu.cn
a⁎
Wang Ronghua a
Cao Qingyun a
Xie Fangchen b
a Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing, 100124, China
b Guizhou Naqing Expressway Co. Ltd, Guizhou, 553400, China
⁎ Corresponding author. hujiangbi@bjut.edu.cn
19 8 2024
30 8 2024
19 8 2024
10 16 e3653310 5 2024
16 8 2024
18 8 2024
© 2024 Published by Elsevier Ltd.
2024

https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
At night, clear pavement markings are essential for driver safety. Currently, markings visibility evaluation relies on the retroreflectivity, but the impact of line width is unclear. To quantify the impact of line width on visibility and to refine visibility evaluation methods, a driver visual detection experiment was designed using both qualitative and quantitative approaches. Twenty-four drivers of small vehicles were randomly recruited to participate in visual detection tests of a total of 54 white pavement markings (comprising 6 widths and 9 retroreflectivity levels) under the illumination of high beams, following the principle of using the “emergence point” as the critical state for assessing pavement marking visibility. This study indicated that widening pavement markings significantly enhances their visibility, particularly for markings with low retroreflectivity. A visibility evaluation model was established to quantify the impact of width and retroreflectivity on the visual distance of markings. The model confirms that widening markings can improve visibility, thereby reducing the required level of retroreflectivity. The research methodology and findings provide technical support for managers to more accurately assess nighttime safety visibility during pavement marking operation and maintenance.

Keywords

Maintenance and operations management
Retroreflectivity
Line width
Visibility evaluation model
==== Body
pmc1 Introduction

Nighttime road visibility is diminished without artificial lighting, posing challenges for drivers to discern information like lane contours and line directions due to inadequate visibility of pavement markings, thereby impacting road safety service levels and traffic efficiency. Good visibility of pavement markings significantly enhances safety, leading to fewer crashes [1]. In contrast, poor visibility of markings correlates with higher crash rates [2]. Over time, the visibility of markings diminishes [3], increasing safety hazards when drivers cannot see them clearly. Thus, timely and effective assessment and maintenance of pavement markings are crucial for ensuring road safety.

Currently, at the standard level, both domestic and international standards utilize the coefficient of retroreflected luminance (RL, measured in mcd/m2/lx) of pavement markings as a crucial indicator for assessing nighttime visibility [4]. Although the thresholds for this coefficient vary across different road traffic environments, distinctions regarding the different widths of pavement markings have not been quantified. The European Standard EN 1436 [5] established by the European Committee for Standardization, specifies threshold values for the RL of white and yellow pavement markings based on different levels. The U.S. standard MUTCD [6], encourages the use of wider markings on high-speed roads and sets two levels of RL thresholds based on the road speed limits. In China, the standards prescribe the RL thresholds based solely on the color of the pavement markings [7].

Research on the safety threshold of the RL for pavement markings is primarily derived from the analysis of nighttime road traffic accident data, subjective evaluations by drivers (such as scoring and rating), and driving simulator studies. Smadi et al., by assessing the relationship between measured RL values of longitudinal pavement markings and accidents, found statistical significance in the impact of the RL below 200 mcd/m2/lx on nighttime accidents and single-vehicle nighttime accidents [8]. Abboud and colleagues established a relationship model between the RL and accidents in Alabama, determining a minimum RL threshold of 150 mcd/m2/lx based on critical crash rates for white pavement markings [9]. Through the analysis of nighttime road traffic crashes data, models were established to explore the relationship between the RL for pavement markings and nighttime traffic crashes [[10], [11], [12], [8], [9]]. The obtained RL threshold levels mostly ranged between 50 and 200 mcd/m2/lx. David et al. estimated the visible distance of pavement markings by counting the number of visible dashed lines under static conditions, establishing a model for the relationship between the RL and the visible distance of pavement markings to assess their visibility [13]. This study found that at least 6 visible dashed lines under dry road conditions were considered acceptable for pavement marking visibility, corresponding to a minimum retroreflectivity coefficient of 120 mcd/m2/lx. Carlson et al. conducted subjective evaluations to rate pavement markings at different retroreflectivity levels, aiming to investigate the minimum retroreflectivity level for pavement markings [14]. Most of these subjective studies indicate that pavement markings with the RL of 100 ± 30 mcd/m2/lx are the preferred minimum level for nighttime driving [15]. Chou et al. utilized VR technology to create an immersive driving environment, discovering that the driver's demand for the RL increases with the speed of the vehicle. At a speed of 50 km/h, a coefficient of retroreflected luminance of 80 mcd/m2/lx is required, whereas at 65 km/h, 130 mcd/m2/lx is needed to meet the requirements of 85 % of drivers in Taiwan [16]. Research quantifying the relationship between pavement marking characteristics and their visibility from the perspective of the human eye during real vehicle driving is still insufficient.

In recent years, the impact of pavement marking width on road safety has garnered significant attention from scholars. The variation in road marking width affects a driver's ability to stay within the lane, with wider markings making it less likely for drivers to deviate from their designated lanes [17,18]. Numerous studies, through the analysis of road traffic accident data, have found that broader markings contribute to a reduction in the number of traffic accidents [[19], [20], [21]]. Lundkvist et al. analyzed driver behavior on straight road segments marked with 10 cm and 20 cm wide white edge lines. The study revealed that the 20 cm wide white edge lines altered the lateral position of vehicles, bringing the driving trajectory closer to the road edge and reducing the risk of head-on collisions with increasing distance between passing vehicles [22]. Xu pointed out that markings of different widths exhibit varying levels of conspicuity, suggesting that increasing marking width based on actual conditions enhances visibility. This low-cost method significantly improves safety outcomes [23]. Existing literature primarily focuses on demonstrating the advantages of relatively wider markings for driving safety. However, there is still a gap in research quantifying the visibility differences for markings of different widths.

This study aims to quantitatively evaluate the impact of various pavement marking widths and retroreflectivity on the visual detection distance of white markings through real-vehicle tests and to refine the evaluation model for nighttime visibility of pavement markings. The findings will provide technical support for management personnel to conduct more precise evaluations of pavement marking visibility during nighttime operational periods.

2 The critical visual state of pavement markings

During nighttime driving, retroreflective pavement markings ensure visibility by reflecting the vehicle's headlights back to the driver's eyes. As the distance between the headlights and the markings increases, the loss of luminous flux amplifies. This is due to light propagation through the air, and the illuminated area expands. Consequently, the light received by distant markings diminishes, reducing the retroreflected light reaching the driver. When the retroreflected light falls below the photoreceptor cells' sensitivity threshold in the driver's retina, the markings become invisible. This results in a rectangle in the driver's field of vision that gradually dims until it disappears, resembling a surface of short horizontal lines decreasing in brightness.

The point where pavement markings become invisible is termed the “vanishing point”. As the vehicle advances, increased illumination causes the “vanishing point” to transition into an “emergence point”, followed by a new “vanishing point”. This shifting allows the driver to maintain visibility of a certain distance of pavement markings under dynamic driving conditions, as shown in Fig. 1. The transition of markings from “vanishing” to “emergence” categorizes their states into three levels based on distance changes: beyond the visible range (markings are invisible), within the visible range (markings form a rectangular surface with decreasing luminance), and at the farthest end of the visible range (“vanishing point” or “emergence point”, appearing as a fuzzy horizontal line). The distance from the driver's eye to the farthest end of the visible range is the visual distance of pavement markings. A fuzzy horizontal line just appearing in the field of view is regarded as the critical visual state of pavement markings, as shown in Table 1.Fig. 1 The state of pavement markings being visible.

Fig. 1

Table 1 Subjective evaluation scale of the state of pavement markings being visible.

Table 1Levels	The state of pavement markings being visible within the drivers' field of vision	
1	Invisible	
2	Blurred horizontal lines just inside the field of view	
3	Bars of diminishing brightness inside the field of view	

3 Methods

Data collection in this experiment focused on the visual distance of pavement markings with different widths and various coefficients of retroreflected luminance obtained by participants under nighttime road conditions. The purpose was to evaluate the nighttime visibility of pavement markings. To accomplish the research objectives, an integrated quantitative and qualitative approach was employed for experimental data collection. Tailored designs and selections were implemented for the experimental samples, scenarios, vehicle, participants, and experimental procedure.

3.1 Samples and scenarios

The thermoplastic pavement marking is currently the most widely used type of marking in road traffic marking in China. Based on the considerations of the current standards for pavement marking width design and retroreflective properties, 54 pieces of white thermoplastic reflective marking samples were made using the hand-push thermoplastic line-marking machine ATM-95 for this experiment. These samples included six widths and nine retroreflectivity levels, as presented in Table 2 below. All 54 completed samples met all relevant requirements of the current specifications “Specification and test method for road traffic markings” (GB/T 16311–2009) [7].Table 2 Different combinations of marking samples.

Table 2Sample Number	Size, cm	Retroreflectivity, mcd/m2/lx	Sample Number	Size, cm	Retroreflectivity, mcd/m2/lx	Sample Number	Size, cm	Retroreflectivity, mcd/m2/lx	
1	5 × 600	33	19	15 × 600	33	37	25 × 600	33	
2	5 × 600	60 ± 1	20	15 × 600	60 ± 1	38	25 × 600	60 ± 1	
3	5 × 600	100 ± 1	21	15 × 600	100 ± 1	39	25 × 600	100 ± 1	
4	5 × 600	150 ± 1	22	15 × 600	150 ± 1	40	25 × 600	150 ± 1	
5	5 × 600	220 ± 2	23	15 × 600	220 ± 2	41	25 × 600	220 ± 2	
6	5 × 600	250 ± 2	24	15 × 600	250 ± 2	42	25 × 600	250 ± 2	
7	5 × 600	300 ± 3	25	15 × 600	300 ± 3	43	25 × 600	300 ± 3	
8	5 × 600	350 ± 3	26	15 × 600	350 ± 3	44	25 × 600	350 ± 3	
9	5 × 600	420 ± 4	27	15 × 600	420 ± 4	45	25 × 600	420 ± 4	
10	10 × 600	33	28	20 × 600	33	46	30 × 600	33	
11	10 × 600	60 ± 1	29	20 × 600	60 ± 1	47	30 × 600	60 ± 1	
12	10 × 600	100 ± 1	30	20 × 600	100 ± 1	48	30 × 600	100 ± 1	
13	10 × 600	150 ± 1	31	20 × 600	150 ± 1	49	30 × 600	150 ± 1	
14	10 × 600	220 ± 2	32	20 × 600	220 ± 2	50	30 × 600	220 ± 2	
15	10 × 600	250 ± 2	33	20 × 600	250 ± 2	51	30 × 600	250 ± 2	
16	10 × 600	300 ± 3	34	20 × 600	300 ± 3	52	30 × 600	300 ± 3	
17	10 × 600	350 ± 3	35	20 × 600	350 ± 3	53	30 × 600	350 ± 3	
18	10 × 600	420 ± 4	36	20 × 600	420 ± 4	54	30 × 600	420 ± 4	

The experiment was conducted on a 400-m-long, 3.75-m-wide dual-lane road segment. The road segment was straight with a smooth and dry surface and lacks road lighting. The pavement marking samples were positioned on the right side of the test vehicle, with approximately 1.9 m of lateral distance between them. The pavement marking samples were arranged parallel to the road and placed adjacent to the existing right edge line of the test road, as shown in Fig. 2. The experiment was conducted at night.Fig. 2 Experimental scenarios.

Fig. 2

3.2 Vehicle and participants

A small vehicle was chosen as the test vehicle. Considering the sales volume of small vehicles and the development trend of vehicle headlights, the test vehicle was equipped with LED headlights. To validate the effectiveness of the high beam light source of this vehicle during the experiment, illuminance values were measured using the CL-500A spectroradiometer at HV, 1125L, 2250L, 1125R, and 2250R positions along the light source illumination distance of 25 m. The test results complied with the specification [24], as shown in Table 3.Table 3 Test results of high beam illuminance of test vehicle.

Table 3Test point	Illuminance Threshold, lx	Measured Illuminance, lx	
Emax	≥48and≤240	151.9	
HV	≥0.80Emax	129	
HV to 1125L and R	≥24	≥75.1	
HV to 2250L and R	≥6	≥52.2	

According to the 2021 driver statistics released by the Ministry of Public Security, vehicle drivers in China were predominantly aged between 26 and 50, accounting for 70.71 % of the total population. The gender ratio within this age range was approximately 7:3 between males and females. In order to address the visual detection needs of the majority of drivers regarding pavement markings, a random selection of 24 drivers, aged between 26 and 50 years, was chosen as participants in the experiment (mean age = 35.5 years; standard deviation = 6.3 years). Among them, there were 17 male drivers and 7 female drivers, all with a visual acuity of 4.9 or higher in both eyes, and without any color vision deficiencies or ocular impairments. Additionally, the participants were required to ensure adequate rest, exhibit normal responsiveness, and refrain from alcohol consumption or medication use. After the experiment, each participant received an honorarium of 400 CNY.

3.3 Experimental procedure

Participants' schedules were adjusted to ensure mental alertness. Before testing, participants were trained on the evaluation scale and driving tasks, practicing twice. Each pavement marking sample was sequentially numbered 1–54, and the corresponding marking width and RL were recorded in the data log.

The schematic diagram of the experimental design is shown in Fig. 3. The starting position of the vehicle and the positions of the marking samples were marked on the test road. The samples were randomly placed by the experimenter. With the high beams of the test vehicle turned on, a participant drove the vehicle slowly from the starting position at a speed of 0–5 km/h. The vehicle was stopped when the marking sample reached Level 2 on the subjective evaluation scale within the driver's field of vision (Table 1). At this point, The tester measured the longitudinal distance from the detection point to the proximal end of the marking sample (relative to the participant) with a roller rangefinder. This process was repeated with different drivers and marking samples until all test combinations were completed.Fig. 3 Schematic diagram of the experimental design.

Fig. 3

4 Results

To enhance data accuracy and effectiveness, aberrant data influenced by external factors were carefully excluded and the test was repeated. Ultimately, 1296 sets of visual detection distance data for pavement markings with varying widths and retroreflectivity levels were obtained.

4.1 Effect of pavement marking width on visual detection distance

When analyzing the visibility data of pavement markings with identical retroreflectivity levels, it was noted that the visual detection distances obtained by the 24 participants did not conform to a normal distribution. To account for potential influences of participant gender and age on the experimental data, an error analysis was conducted on their visual detection distances. The different box plots in Fig. 4 indicate that drivers detected pavement markings with varying widths and retroreflectivity. Each box plot represents the actual deviations in visual detection distance data for 36 participants. The findings revealed consistent distribution characteristics of visual detection distances among the 24 participants, with an interquartile range (IQR) of less than 5 m, as depicted in Fig. 4 In light of an unknown overall distribution, non-parametric test methods (specifically, the Kruskal-Wallis test for more than two independent groups) were employed to assess the impact of pavement marking width on the visual detection distances obtained by drivers. The results indicated that different widths of pavement markings exhibited significant differences in visual detection distances (p < 0.01), as presented in Table 4 below.Fig. 4 Distribution of detection distance for different pavement markings: (a) All markings with RL values of 33, 150, and 300 mcd/m2/lx; (b) All markings with RL values of 60, 220, and 350 mcd/m2/lx; (a) All markings with RL values of 100, 250, and 420 mcd/m2/lx.

Fig. 4

Table 4 Kruskal-Wallis test.

Table 4All	33 mcd/m2/lx	60 mcd/m2/lx	100 mcd/m2/lx	1050 mcd/m2/lx	220 mcd/m2/lx	250 mcd/m2/lx	300 mcd/m2/lx	350 mcd/m2/lx	420 mcd/m2/lx	
H	134.51	136.40	137.57	137.63	136.88	135.35	133.97	126.76	125.84	
p	0.00*	0.00*	0.00*	0.00*	0.00*	0.00*	0.00*	0.00*	0.00*	

Using the average value of the driver's visual detection distance as a reference, the effective visual detection distance provided by pavement markings with different RL varies with the width of the markings, as depicted in Fig. 5(a). There is a positive correlation between marking width and visual detection distance, as the visual detection distance obtained by drivers gradually increases with the marking width. However, the rate of visual detection distance growth decreases progressively with increasing marking width, particularly for markings with higher retroreflective levels, as illustrated in Fig. 5(b). Consequently, the influence of width on visual perception diminishes, and the increase in visual detection distance by widening markings with high visibility becomes less pronounced.Fig. 5 Distribution of detection distances for pavement markings and their growth rates: (a) Detection distances for varying markings; (b) Growth rates of detection distances with marking widths.

Fig. 5

4.2 Effect of pavement marking coefficient of retroreflected luminance on visual detection distance

Similar to the analysis of the effect of pavement marking width on visual detection distance, a non-parametric test suitable for an unknown overall distribution was employed to examine the effect of the RL of the markings on the visual detection distance when the pavement marking widths were identical (the Kruskal-Wallis test was utilized for testing two or more independent groups). The results indicate a significant difference in the 95 % confidence interval for the effect of the RL of pavement markings on the visual detection distance (p < 0.01), as presented in Table 5 below.Table 5 Kruskal-Wallis test.

Table 5All	5 cm	10 cm	15 cm	20 cm	25 cm	30 cm	
H	208.25	208.74	209.20	209.10	206.36	203.25	
p	0.00*	0.00*	0.00*	0.00*	0.00*	0.00*	

Using the average value of the driver's visual detection distance as a reference, the effective visual detection distance provided by pavement markings with different width varies with the RL of the markings, as depicted in Fig. 6(a). The visual detection distance obtained by the driver gradually increases with an increase in the RL of the markings, suggesting a positive correlation between the RL of the markings and the visual detection distance. Nonetheless, as the RL of the pavement markings increases, the growth rate of visual detection distance gradually diminishes, as illustrated in Fig. 6(b). This implies that the increase in the RL of pavement markings has a diminishing effect on their visibility gain. Additionally, we observed that a slight increase in the RL yields a relatively significant increase in detection distance at lower reflection levels. However, when the RL of pavement markings exceeds 250 mcd/m2/lx, further increases in the coefficient result in only marginal increases in detection distance. The intensity of light from vehicle headlamps illuminating the pavement markings follows the inverse square law, whereby the illuminance decreases proportionally to the square of the distance. Consequently, the visual detection distance provided by the markings is constrained by the distance of illumination from the vehicle headlamps. So the visibility of the markings does not exhibit a linear increase with an increase in the width or retroreflectivity of the markings.Fig. 6 Distribution of detection distances for pavement markings and their growth rates: (a) Detection distances for varying markings; (b) Growth rates of detection distances with marking retroreflectivity.

Fig. 6

4.3 The visibility model for pavement markings

The effects of pavement marking width and retroreflectivity on visual detection distance were investigated through partial correlation analysis, with the width of markings and the RL serving as independent variables and the mean visual detection distance as the dependent variable. A strong correlation was observed between the visual detection distance and the RL of the pavement markings, with a correlation coefficient of 0.937, while the correlation between the visual detection distance and the width of the pavement markings was slightly lower, with a correlation coefficient of 0.799. Utilizing the pavement markings width and RL as independent variables and visual detection distance as the dependent variable, a power function was employed to model the relationship among them, expressed in equation (1). The variation trend of visual detection distance with pavement marking widths ranging from 5 cm to 30 cm and the RL from 33 to 420 mcd/m2/lx is depicted in Fig. 7. The visual detection distance consistently increases with the enlargement of pavement markings width and the RL. Notably, the RL of the pavement markings exerted a more pronounced effect on visual detection distance compared to the width of the markings.(1) D=2.80+0.63×RL+2.53×W−7×10−4×RL2−0.03×W2

where RL is the RL of the pavement markings; W is the width of markings; D is the visual detection distance of markings.Fig. 7 Trends in visual detection distance of pavement markings.

Fig. 7

The regression model based on this function underwent an F-test (p < 0.01), demonstrating significance. Moreover, the coefficient of determination indicated a high degree of fit with the sample data, exceeding 0.99, signifying excellent fitting effectiveness.

The anticipation of road channelization information ahead by drivers depends on the length of the visual detection distance of pavement markings, directly impacting subsequent driving behavior choices. In instances where pavement marking visibility is inadequate, compensatory measures such as speed reduction are often employed by drivers to mitigate poor road visibility conditions [24]. Conversely, when drivers are compelled to maintain a minimum speed on the road, pavement markings are required to furnish a safe visibility distance, affording drivers ample time to process the visual information conveyed by the markings; failure to do so poses a driving risk. This period is denoted as the preview time, representing the duration taken by drivers to traverse from their current position to the farthest end of the visual detection distance of the pavement markings [25]. Schnell et al. recommend a minimum pavement marking preview time of 3.65s [26]. This preview time was derived from the 3-s preview time established as the lower bound by the Comité Internationale de L'Éclairage (CIE) plus one 85th percentile driver eye fixation duration of 0.65s for nighttime freeway driving [27]. A preview time of 3.65 s is deemed as the shortest duration meeting both safety and comfort standards for drivers within existing studies [28]. Therefore, when evaluating the nighttime visibility of pavement markings, the visibility distance calculated using the width and retroreflectivity of the markings based on the visibility model should be at least 3.65v.

5 Discussion

In determining the detection distance of pavement markings, previous studies mostly relied on the distance to the end of the markings perceived by the subjects [28]. Experimenters created an illusion by interrupting the continuous longitudinal markings, giving the impression of reaching an end point, and participants were instructed to indicate the starting position of the detection distance when they saw the end of the markings. Although drivers perceive the true distance of the markings as the “vanishing point” from the driving position to the markings, this “vanishing point” is difficult to precisely determine. Theoretically, the “vanishing point” of continuous markings always exists and moves forward as the driver progresses. However, the required “vanishing point” for experimental research appears at the location where the markings are interrupted, making it easy for participants to misjudge the “vanishing point” position, resulting in less-than-ideal detection distance data. Based on this phenomenon, the authors decided to use the “emergence point” of the markings as the critical state of visibility, which differs from previous studies. As the intensity of the light from the vehicle headlights with the increase in distance from the light source and decreasing, pavement markings with the distance of the luminance gradually weakened. The luminance of the pavement markings weakened to the driver's human eye visual discrimination ability threshold, the more distant markings will disappear, if the more distant markings are truncated, the location of the truncation can be called the marking of the “vanishing point”. For the same reason, if the nearer pavement markings are truncated, the location of the truncation can be referred to as the “emergence point” of the markings. Therefore, using the “emergence point” to indicate the critical visibility state of the markings is reasonable. On the other hand, there is only one “emergence point” for the markings, which is relatively easy for drivers to perceive, reducing the probability of misjudgment and enhancing the reliability of the research conclusions.

So far, the difference in retroreflection levels due to varying widths has not been specified by relevant standards in developed countries such as Europe [5] and the United States [6]. In recent years, researchers have found through comparing the crash rates using pavement markings of different widths (10 cm, 15 cm, 20 cm) that wider longitudinal markings can reduce crashes [21]. In our study, we investigated pavement markings with widths ranging from 5 to 30 cm, encompassing the widths commonly used in practice. It was confirmed that widening pavement markings enhances visibility and reduces the required pavement marking retroreflectivity. This finding can serve as a technical guideline for future transportation agencies, road construction, and operation managers regarding the design and maintenance of pavement markings. Additionally, the parameter Qd was not explicitly considered in the study, which could have influenced the results. The impact of Qd will be explored in the future research, particularly in scenarios characterized by low Qd and high RL. Such conditions may reveal critical dynamics that were not captured in the present study.

In addition to intrinsic characteristics such as width and reflectivity, the visibility of pavement markings is also influenced by headlamp illumination. Variations in the visibility of markings under different types of vehicle headlamps (xenon, halogen, and LED lights) have been observed in studies [29]. Even when using the same type of headlamp, the degree of attenuation in light intensity varies with different periods of use. When the headlights illumination is weak, the luminance of pavement markings perceived by the driver's eye decreases, thus shortening the visual distance. And testing more detailed data will be necessary in the future. Moreover, at intermediate levels of visual adaptation (0.005 cd/m2 ∼ 5 cd/m2), the sensitivity of the human eye to the spectrum changes with varying levels of luminance. In previous research, the impact of the relative color temperature of the illuminating light source on the visual effectiveness of the human eye was also noted [30]. The pavement marking visibility evaluation model presented in this paper is based on experimental data obtained under illumination from vehicle LED headlamps, which may imply limitations in practical applications. Therefore, future research may necessitate more experimental studies on the relationship between the relative color temperature, illuminance, and other characteristics of different vehicle headlamps and the visibility of pavement markings, further refining the visibility evaluation model of pavement markings. Also, glare can affect the visual function of a driver's eyes, and in severe cases (such as when the angle between the driver's line of sight and the glare source is small), it can even cause disability. However, the specific impact of glare on the visibility of pavement markings requires further research.

In the study of visual evaluation models for pavement markings, Spieringhs et al. developed a contrast threshold model for markings against the road background by observing rendered images of highway scenes on a display [31]. Brémond et al. reviewed and discussed the development of visual performance models in road lighting over the past 100 years [32]. The visibility models discussed in these studies likely emphasize the overall impact of lighting conditions on the visibility of road targets, providing important references for road lighting design to ensure nighttime driving safety. While also aimed at ensuring night-time driving safety, the nighttime visibility model in this research focuses more on the specific characteristics of pavement markings in actual road conditions. It aims to help pavement marking managers evaluate the visibility of markings more accurately for timely maintenance and to ensure nighttime driving safety. However, incorporating lighting parameters into the experiments to further refine the visibility model is necessary for future research.

6 Conclusions

Through theoretical analysis, this study proposed the critical visual state of pavement markings, and an outdoor real-vehicle experiment was designed to acquire visual detection distance data for pavement markings with varying widths and retroreflectivity levels. The following main conclusions were drawn from the data analysis:(1) The visibility of pavement markings is significantly influenced by their width, resulting in drivers detecting pavement markings at greater distances as their width increases. Nevertheless, the rate of increase in visual detection distance diminishes as the width of the markings increases, especially for markings with higher retroreflective levels.

(2) A positive correlation exists between the RL of pavement markings and their visibility, indicating that higher RL contribute to better visibility. However, the visibility enhancement diminishes as the coefficient increases, especially once it surpasses 250 mcd/m2/lx.

(3) A correlation model was established with the width and the RL of pavement markings as independent variables and visual distance as the dependent variable. This model quantifies the increases in pavement markings' visibility attributable to the width and the RL, providing technical guidance for enhancing pavement markings' visibility at night.

Data availability statement

Pavement markings visibility data have been deposited at Zenodo (https://zenodo.org/) with the DOI 10.5281/zenodo.13325180.

CRediT authorship contribution statement

Yanyan Guan: Writing – original draft, Supervision, Software, Resources, Investigation, Formal analysis, Data curation. Jiangbi Hu: Visualization, Validation, Methodology, Conceptualization. Ronghua Wang: Validation, Supervision, Data curation. Qingyun Cao: Writing – review & editing, Data curation. Fangchen Xie: Validation, Supervision.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This study was supported by the Science and Technology Project Funds of Guizhou Naqing Expressway Co. Ltd, under project number 2022-122-017. The authors would like to express heartfelt gratitude to Zhejiang Brother Guidepost Paint Co., Ltd. for providing the pavement marking samples for this study.
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References

1 Bektas B.A. Gkritza K. Smadi O. Pavement marking retroreflectivity and crash frequency: segmentation, line type, and imputation effects J. Transport. Eng. 142 8 2016 04016030 10.1061/(ASCE)TE.1943-5436.0000863
2 Avelar R.E. Carlson P.J. Link between pavement marking retroreflectivity and night crashes on Michigan two-lane highways Transport. Res. Rec. 2404 1 2014 59 67 10.3141/2404-07
3 Mazzoni L.N. Ho L.L. Vasconcelos K.L. Bernucci L.L.B. Probabilistic service life model of pavement marking by degradation data Transport. Res. Rec. 2676 10 2022 328 340 10.1177/03611981221089304
4 Spielhofer R. Osichenko D. Leal D. Benbow E. Wright A. Identifying the key characteristics for road marking and stud condition measurements Proceedings of the Conference of European Directors of Roads 2016 Westminster, UK
5 BS EN1436 Road Marking Materials-Road Marking Performance for Road Users and Test Methods 2018
6 MUTCD Manual on Uniform Traffic Control Devices for Streets and Highways 2023
7 Specification and test method for road traffic markings. GB/T 16311 https://std.samr.gov.cn/gb
8 Smadi Omar Gkritza Pavement marking retroreflectivity and crash frequency: segmentation, line type, and imputation effects J. Transport. Eng. 2016 10.1061/(ASCE)TE.1943-5436.0000863
9 Abboud N. Bowman B. Cost- and longevity-based scheduling of paint and thermoplastic striping Transport. Res. Rec. 1794 2002 55 62 10.3141/1794-07
10 Park E.S. Carlson P.J. Pike A. Safety effects of wet-weather pavement markings Accid. Anal. Prev. 133 2019 105271 10.1016/j.aap.2019.105271
11 Smadi O. Souleyrette R.R. Ormand D.J. Hawkins N. Pavement marking retroreflectivity: analysis of safety effectiveness Transport. Res. Rec. 2056 2008 17 24 10.3141/2056–03 2056
12 Carlson P. Park E.S. Kang D.H. Investigation of longitudinal pavement marking retroreflectivity and safety Transport. Res. Rec. 2337 2013 59 66 10.3141/2337-08 2013
13 David M. Burns Pavement marking photometric performance and visibility under dry, wet, and rainy conditions: pilot field study Transport. Res. Rec. 1973 1 2018 113 119 10.1177/0361198106197300114
14 Carlson P.J. Park E.S. Andersen C.K. The benefits of pavement markings: a renewed perspective based on recent and ongoing research Transport. Res. Rec. 2107 2107 2009 59 68 10.3141/2107-06
15 Babić D. Fiolić M. Babić D. Gates T. Road markings and their impact on driver behaviour and road safety: a systematic review of current findings J. Adv. Transport. 2020 1 2020 1 19 10.1155/2020/7843743
16 Chou C.P. Huang P.H. Chen A.C. Virtual reality application on road markings' visibility analysis Transport. Res. Rec. 5 2021 10.1177/03611981211017912
17 Mcknight A.S. Mcknight A.J. Tippetts A.S. The effect of lane line width and contrast upon lane keeping Accid. Anal. Prev. 1998 617 624 10.1016/S0001-4575(98)00015-3 9678215
18 Chang K. Ramirez M.V. Dyre B. Effects of longitudinal pavement edgeline condition on driver lane deviation Accid. Anal. Prev. 128 JUL 2019 87 93 10.1016/j.aap.2019.03.011 30991291
19 Park E.S. Carlson P.J. Porter R.J. Safety effects of wider edge lines on rural, two-lane highways Accid. Anal. Prev. 48 2012 317 325 10.1016/j.aap.2012.01.028 22664696
20 Park E.S. Carlson P. Proter R.J. Andersen C.K. Safety of wider edge lines on rural, two-lane highways Accid. Anal. Prev. 48 9 2012 317 325 10.1016/j.aap.2012.01.028 22664696
21 Hussein M. Sayed T. El-Basyouny K. Leur P.D. Investigating safety effects of wider longitudinal pavement markings Accid. Anal. Prev. 142 2020 105527 10.1016/j.aap.2020.105527
22 Lundkvist S.O. Ytterbom U. Runersjoe L. Continuous Edgeline on Nine-meter-wide Two-Lane Roads 1990 Swedish Road and Traffic Research Institute Stockholm, Sweden
23 Xu Y.C. Analyze the functions of marking and the details to be paid attention to when setting with an example Auto & Safety 2 2020 96 102
24 Automotive headlamps with LED light sources and/or LED modules, GB 25991 https://std.samr.gov.cn/gb
25 Cost 331, Requirements for Horizontal Road Markings 1999 European Commission Directorate General Transport Brussels, Belgium
26 Schnell T. Zwahlen H.T. Driver preview distances at night based on driver eye scanning recordings as a function of pavement marking retroreflectivities Transport. Res. Rec. 1692 1999 129 141 10.3141/1692-14
27 Zwahlen H.T. Conspicuity of suprathreshold reflective targets in a driver's peripheral visual field at night Transport. Res. Rec. 1213 1989 35 46
28 Gibbons R. Williams B. Cottrell B. Assessment of durability of wet night visible pavement markings: visibility experiment Transport. Res. Rec.: J. Transport. Res. Board 2013 10.3141/2337-09
29 Uchida M. Kita Y. Minoda T. Ueki R. Kawanobe S. Visibility of pavement markings with LED headlamps SAE 2014 World Congress & Exhibition 2014 10.4271/2014-01-0438
30 Hu J.B. Guan Y.Y. Wang R.H. Cao Q.Y. Guo Y.P. Hu Q.X. Investigating the daytime visibility requirements of pavement marking considering the influence of CCT and illuminance of natural light Int. J. Environ. Res. Publ. Health 19 5 2022 3051 10.3390/ijerph19053051
31 Spieringhs R.M. Smet K. Heynderickx I. Hanselaer P. Road marking contrast threshold revisited Leukos 18 4 2021 493 512 10.1080/15502724.2021.1993893
32 Brémond R. Visual performance models in road lighting: a historical perspective Leukos 17 1 2020 1 30 10.1080/15502724.2019.1708204
