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Article

Systematic Testing of Road Markings’ Retroreflectivity to Increase Their Sustainability through Improvement of Properties: Croatia Case Study

by
Darko Babić
1,
Mario Fiolić
1,
Dario Babić
1 and
Tomasz E. Burghardt
2,*
1
Faculty of Transport and Traffic Sciences, University of Zagreb, Vukelićeva 4, 10000 Zagreb, Croatia
2
M. Swarovski GmbH, Wipark, 14 Straße 11, 3363 Neufurth, Austria
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(15), 6653; https://doi.org/10.3390/su16156653
Submission received: 28 June 2024 / Revised: 29 July 2024 / Accepted: 29 July 2024 / Published: 3 August 2024
(This article belongs to the Special Issue Sustainable Transportation: Driving Behaviours and Road Safety)
Browse Figures
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Abstract

:
Road markings are important elements of road infrastructure, influencing traffic safety. Since they are deteriorating systems, their upkeep through renewals is important. To assure the quality of the renewal jobs, the systematic testing of retroreflectivity, which is the key performance parameter of road markings, was imposed in Croatia. Results from two decades of annual measurements of renewal jobs are provided. For the first decade, the measurements were taken statically, at spot locations, and later dynamically, across the entire road segments. When the evaluation started, only 1 out of 18 tested job sites was exceeding the minimum requirements; only after 8 years of measurements, 100% of the jobs exceeded the minimum demands. A subsequent switch to dynamic testing revealed that, on average, only 71% of the renewed road markings were in satisfactory condition and approximately 1.22% of the analysed line lengths had grossly substandard retroreflectivity. These results demonstrated that the field verification of jobs quality is necessary and simultaneously showed that static localised testing was not adequate. The outcome underlines the need for the strict supervision of road maintenance contracts to maximise the benefits for the society: through the better visibility of road markings, road safety should also improve, and the entire system will become more sustainable.

1. Introduction

Road markings (RMs)—longitudinal or transverse lines or symbols on installed on pavements—are one of the most important safety features on almost all modern roads. They are fundamental elements of road infrastructure that are perceived by drivers; their impact on road safety and drivers’ behaviour was recently reviewed [1]. In addition, RMs were reported as necessary for the proper functioning of advanced driver assistance systems [2]. Known and proven material and installation technologies, the existing presence on the majority of roads worldwide, high usefulness for the drivers and also for lane-keeping assistance systems, and effectiveness without any external energy source belong to the advantages of RMs that make them currently irreplaceable. Furthermore, there is no known substitution to the use of RMs because of an excellent cost-to-benefit ratio that they provide [3]. All of this makes RMs a highly sustainable solution for use on almost all paved roads to increase traffic safety.
For appropriate function, RMs must be visible, which is achieved through colour contrasting with the roadway surface; at night, the visibility is enhanced through retroreflectivity [4]. As materials, RMs are speciality heavy-duty industrial maintenance coatings; they are unique because of being dual-layer systems comprising the bottom paint layer and strewn on it a layer of drop-on glass beads (GBs). Of particular importance are the GBs, which simultaneously provide retroreflectivity and protect the paint layer from abrasion [5]. RMs are deteriorating systems, and upon the loss of functional properties, their renewal with another layers of the paint and the GBs is necessary; hence, layer stacking occurs [5]. The environmental sustainability of RMs is directly connected with their functional service life [6], which was reported by us, based on extensive field research supported by laboratory assessment, to be affected by both the initial properties and the choice of materials [7].
Retroreflectivity—the phenomenon of reflecting the light from a vehicle’s headlights back towards the driver—is the property of RMs used to determine their performance and to indicate the need for renewal. Retroreflectivity is measured as a coefficient of retroreflected luminance (RL) and expressed in millicandelas per square metre per lux, mcd/m2/lx. It is achieved because of the drop-on GBs partially embedded in the paint layer [8,9]. Because the tyres of all vehicles that encroach on the RMs are rolling on the GBs, they can become damaged or extracted from the film, which causes a decrease in RL [10]. Note: as long as the drop-on GBs are present, tyres have no contact whatsoever with the paint layer—it is physically impossible because the tyre tread is approximately 10× larger than spaces between the GBs. Daytime visibility, assessed as luminance coefficient in diffuse illumination (Qd) and also expressed in mcd/m2/lx, is an equally important performance parameter as it meaningfully affects the contrast and thus the visibility of RMs. Nonetheless, Qd is seldom considered as critical, because in the vast majority of cases, RL decreases first.
It has been consistently demonstrated that road users appreciate RMs with high RL, which make the task of driving in darkness easier [11,12,13]. Studies have shown that an increase in RL was associated with a lower crash rate at night on unlit roads in the absence of other interfering factors [14,15], even if some researchers pointed out the weaknesses of such analyses [16]. The minimum RL that is recommended by the European Union Road Federation to be maintained at all roads at all times is 150 mcd/m2/lx [17]. This value coincides with the outcome of studies based on a visual assessment of drivers’ needs [18,19]. In most European countries, RL > 200–300 mcd/m2/lx is demanded from newly applied RMs, but a decrease in RL to circa 100 mcd/m2/lx after winter is typically considered as acceptable. The imposition of the minimum initial RL seems reasonable because of the deteriorating nature of RMs.
Given the above, it is surprising that some road administrators (personal communications) do not routinely verify the RL of newly applied RMs despite the availability of tools and standardised procedures. To assess the key properties—RL and Qd—of freshly renewed RMs, before payments to the applicators were made, testing was imposed in Croatia. Herein, the results from systematic evaluation performed at selected roads over two decades are provided. Surprisingly, despite the relative abundance of literature related to RMs, particularly in North America [20], no similar analyses have been reported so far. The different line arrangement and large dataset spanning testing over two decades and multiple renewals makes this a novel contribution. The results presented in this first article on this topic can be used as a reference for road administrators, but they also should be of interest to policymakers, road safety advocates, and—due to the association between poorly maintained RMs and emissions of microplastics—to environmental scientists. The proper utilisation of the provided results would lead to an increased sustainability of RMs: improving their initial quality should translate to prolonged functional service life, which would lead to better visibility for road users. Hence, overall system sustainability—not only from an environmental but also from a social perspective—could be realised.

2. Methodology

2.1. Data Collection and Measurement Procedures

Data for this study were collected by a laboratory certified according to the standard ISO/IEC 17025 [21]; measurements were taken on request from the road administrator. Standard retroreflectometers, properly calibrated per requirements of the testing laboratory certification, were utilised for measurements. The requirements for the measurement procedures of RL and Qd are defined in standard EN 1436 [22]. The standard defines a 30 m geometry, which corresponds to a visibility of RMs at a distance of 30 m by a driver with eyes at the height of 1.20 m when the RMs are illuminated with vehicle headlights located 0.65 m above ground. Consequently, the observation angle is 2.29° and the illumination angle is 1.24° to give a 1.05° difference in the angular planes.
The testing laboratory lacked the knowledge about the contractors and the specifics related to the utilised materials, so any conflicts of interest between the testing team and the application crew were avoided. Nonetheless, it was known that in all of the cases, solventborne paints reflectorised with GBs with a refractive index of 1.5 were utilised. Since the measurements were taken relatively shortly after the application of the RMs, it was assumed that the role of paint selection should not affect the outcome [7]. However, the quality of the used drop-on GBs, which was not estimated, might have played a role [23,24]. The results were provided to the road administrator, at whose discretion was acceptance or rejection of the job and/or any financial penalties or rewards to the contractors. Moreover, the laboratory was not informed about the outcome in any of the cases and was not requested to verify the results from the possible re-painting of rejected jobs. The dataset provided herein comprises data collected between 2003 and 2022; RL and Qd were measured with a static method (spot testing) until 2013, and then RL was assessed dynamically (entire road segment testing).
Historically, measurements of RL and Qd were taken statically at predetermined spot locations. Two location selection methods for the static evaluation of RL and Qd were used: firstly, between 2003 and 2010, the so-called Kentucky method was utilised [25], and then, between 2011 and 2013, locations were selected per ZTV M 02 protocol [26]. According to the Kentucky method, measurements are to be performed in the first third of the length of the road section on which RMs were applied by one application team in one day. In the first third of the section, a single zone of 500 m is to be evaluated with 10 measurements (each in triplicate) 50 m apart. The main disadvantage of this protocol is that the test is performed only on a small section of the application job, leading to potential misrepresentation. This weakness was alleviated through using the procedure described in ZTV M 02: the number of measuring sections depends on the length of longitudinal markings and the area of other markings, as shown in Table 1 and schematically visualised in Figure 1. The measurement segments, all of them 100 m long, are selected randomly throughout the marked section, and data are collected from five locations 25 m apart. For dashed markings, a length of 10 lines is to represent a section, and the measurements are allocated in the middle point of every second line in that section. In relation to the Kentucky method, the randomness of measurement sections helps to create a more representative picture of RL for the entire length of the marked road [27].
Nowadays, dynamic testing, with a retroreflectometer installed on a moving vehicle, is more frequently used; much more accurate overall assessment can be obtained [27]. During the dynamic testing, RL is measured almost continuously (raw data point collected every two milliseconds) and then averaged per 50 m sections (other section lengths are also possible) during normal driving with speeds up to 130 km/h. While the main advantages are continuity of data collection and the absence of any obstruction to vehicular traffic, measurements of Qd are not possible because uniform illumination cannot be obtained. A vehicle with the retroreflectometer side-mounted to measure the centre line is shown in Figure 2.

2.2. RL and Qd Requirements

The requirements for RL and Qd in Croatia are listed in Table 2 [28]; there is no differentiation between various locations. The measurements of new or renewed RMs are to be taken between 30 and 60 days after their application, when it is expected that the maximum RL is achieved [29]. There is no defined time when RMs are to be classified as used; however, mutual understanding is that the term applies after winter exposure. For all of the cases presented herein, Type I materials (paints, applied at layers < 1 mm wet film) were utilised. Note that the Type I and Type II classifications per Croatian requirements [28] do not match the definitions set in standard EN 1436 [22], where the types are differentiated not based on layer thickness or kind of material but on visibility under the conditions of wetness: RMs of Type I are those ‘that do not necessarily have special properties intended to enhance the retroreflection in wet or rainy conditions’ and Type II are those ‘with special properties intended to enhance the retroreflection in wet or rainy conditions’.

2.3. Measurement Locations

The data presented herein are limited to six bidirectional single carriageway roads in Croatia; the traffic load (per official counts) at the assessed segments and the lengths of analysed longitudinal markings are listed in Table 3. Measurements were taken at road sections that were renewed regardless of their location in towns, villages, or in rural areas. Data for only longitudinal markings (edge and centre lines) are provided because of the different materials and renewal schedules for some of the transverse markings and pedestrian crossing ‘zebra’ stripes. For subsequent data presentation, it is assumed that the right edge line was on the right in the direction of the increasing kilometre marks. Static measurements were taken in 4 sections, between 30 and 60 days after application, in the same locations for both the Kentucky and the ZTV M 02 methods. Since 2014, RL was assessed using the dynamic procedure (Qd was not measured) and comprised the entire line markings’ lengths. For clarity of presentation, results from all lines measured dynamically were combined because the analysis of raw data indicated no meaningful differences. Importantly, the dynamic testing was conducted between 30 and 150 days after the renewal of the RMs per modified request from the road administrator that departed from the standard requirements. Such an occasionally prolonged period between the renewal job and measurements could have in some cases affected the outcome. In total, the static measurements were taken at 840 points (10–20 locations per line per road per annum). The total examined line length using a dynamic retroreflectometer was 2867 km (circa 930 km of roads—3 lines per road, with some sections marked with a centre double line).

3. Results

3.1. Static Measurements of RL and Qd

The average RL values for RMs applied at different roads, from the year-by-year testing at the same spots between 2003 and 2013, are shown in Table 4, Qd values are in Table 5, and their averages are visualised in Figure 3. For data presentation clarity, standard deviations are omitted. Consistently, in all of the cases, increases were measured not only in the number of accepted jobs but also in the measured values, from an average RL of 200 to 293 mcd/m2/lx (an increase of 46%) and from an average Qd of 145 to 177 mcd/m2/lx (an increase of 22%). The levelling off of the values can be explained by approaching the maximum achievable with the utilised materials. Higher RL values can be obtained only with GBs having an increased refractive index; the use of such GBs and the advantages that they bring, particularly in combination with the highest quality paints, were discussed by us elsewhere [7]. In the case of the centre line, which exhibited the highest average increase in RL, one might also consider the effects of directionality [31]; however, for the cases studied herein, the RL of the centre line was always measured in the direction of application of the markings.
To check whether the measured differences were statistically significant, analyses of variance (ANOVA) using Bonferroni correction with the confidence level set at 0.05 were performed for both RL and Qd, despite the drawback of relatively small sample size. For both variables, ANOVA’s sphericity assumption was violated (Mauchly’s p < 0.005), so Greenhouse–Geisser correction was used. Overall, a within-subject test demonstrated statistically significant differences over the years in both RL [F (3.401, 57.817) = 51.011, p < 0.005, ƞ2 = 0.750)] and Qd [F (3.187, 54.177) = 21.985, p < 0.005, ƞ2 = 0.564)].

3.2. Dynamic Testing of RL

With the development of dependable equipment for the dynamic testing of RL, static measurements were abandoned as less reliable, more labour-intensive, and associated with hazard to the measurement team. The results from the dynamic testing conducted at the same roads between 2015 and 2022 are shown in Table 6. Even though the verification range was abandoned in 2019, the collected data were split into bins that included it. Measurements were not necessarily taken 30–60 days after renewal but rather in autumn; hence, the RMs were renewed, but the period they were in service could reach even 5 months. Since dynamic testing permits for continuous measurements, data are shown for the number of kilometres of each RL range. The average full acceptance rate (i.e., RL > 220 mcd/m2/lx) and the acceptance ranges for individual roads are charted in Figure 4, which should be compared with the 100% acceptance that was measured statically at spot locations (Cf. Figure 3). Amongst interesting observations, one should note a meaningful decline in RL that occurred in 2017–2018 and again in 2022 with only 62–66% average distances for all roads exceeding the acceptance level. The average RL decreased from >290 mcd/m2/lx measured in 2012, 2013, and 2016 to only 240 mcd/m2/lx in 2022. The measured RL values were not changing systematically and varied between the roads—we cannot provide a tenable explanation at present. These results may indicate, amongst other possibilities, (1) the lack of systematic correlation between RL measured at spot locations and at the entire marked lines, (2) poor workmanship, (3) lower quality of materials, (4) adverse effects during the measurements, and/or (5) different periods between the application and evaluation—exact reasons for RL values lower than were measured previously remain unknown.
One of the implications of this study is the connection between the RL values of the RMs and the potential emissions of microplastics from them. RMs were initially reported as a meaningful source of microplastic pollution; nonetheless, while theoretical ponderings indicated high levels of emissions, field research indicated that erosion (i.e., the complete abrasion) of RMs occurred quite seldom and was associated with extraordinary usage conditions or with grossly negligent maintenance, and the protective role of drop-on GBs, which simultaneously deliver RL, was emphasised [5]; hence, it was reasoned that unless the RL values decreased below a threshold level, no meaningful abrasion and thus emission of microplastics would be taking place. So far, no reliable report related to abrasion of RMs at longitudinal lines was published.
For this study, we assumed, based on professional experiences and limited field studies [5], that drop-on GBs must be present and protect the underlaying paint layer if RL values of >100 mcd/m2/lx were recorded. Nonetheless, cautions related to the possibility of damage to the GBs instead of their extraction from the film must be heeded [10]. Such low RL values, below the minimum requirement for used markings (Cf. Table 2), were found to be present also in this study of renewed RMs; data for the distances of such sections are provided in Table 7 (note that these distances were included in Table 6 as belonging to RL < 180 mcd/m2/lx). The distances were very short indeed: out of the total tested 2867 km of lines, RL < 100 mcd/m2/lx was measured at only 35.0 km (i.e., 1.22%). However, one should note that the majority of the grossly substandard RL was measured at D36, which is a curvy road through a hilly region (the low RL was measured mostly at the inner line markings at curves) and at route D30, which is undergoing a road construction (hence, excessive damage due to heavy vehicles and dirt accumulation was occurring in some sections). If the curvy route D36 and route D30 were to be excluded, a substandard RL would apply to only 9.8 km out of the measured 2024 km (i.e., 0.48% of the total distance). However, that is a notable length of RMs not meeting even the minimum RL requirements especially because the period before renewal and measurements was not grossly excessive. It is very likely that the RMs at the curves were exposed to so many vehicle passes that not only the point of the highest RL was missed but also major deterioration took place. This important issue may be associated with the modelling of the deterioration of RMs; various models were presented [20,32,33], including one based on the Croatian dataset [34].
Nonetheless, regarding microplastic pollution, one cannot consider that RMs with RL values of <100 mcd/m2/lx would contribute, but only could—this threshold value should be treated as an indicator of the oncoming abrasion. Importantly, visual assessment of the associated representative images (taken by the dynamic retroreflectometer equipment) indicated no meaningful regions with erosion (i.e., complete abrasion). Analysis of the other available dynamic RL testing data and associated images, particularly from measurements taken before renewals, is required to clarify the issue of RMs erosion and abrasion at longitudinal lines.

4. Discussion

The initially measured poor performance of the tested RMs was subjectively, but based on the practices observed in the field and unrelated non-systematic testing, attributed to the lack of supervision: the road administrator probably accepted in good faith that all of the work was completed lege artis. Only occasional visual checks were made (personal communication), but without instrumental measurements taken by an independent party, it was not really possible to assure constant quality. Once the policy of checks was implemented, the work quality had to increase because inadequate performance parameters, objectively measured according to established procedures, could become the basis for rejection of the job, thus forcing the contractors to repeat the work at their own expense. In addition, the road administrator could exclude a contractor delivering inadequately completed jobs from future tenders. Whereas there could be other reason for the increase in the jobs’ quality than the claimed supervision, it is the simplest and most tenable explanation for the increase in the initially measured properties.
Whereas there was a steady increase in RL and Qd at the measurement locations after job supervision was enacted, subsequent testing of the entire road stretches using a dynamic retroreflectometer revealed that adequate RL values could be present at only 22% of the tested line length of some roads. We cannot pinpoint the main reason for such results after the switch to dynamic RL measurements—while substandard workmanship could be the easiest explanation, there are other equally plausible explanations. The use of the static measurements could be burdened with a systemic error associated with the selection of locations (for example, disregarding curves) and significantly smaller number of data points; this could be a valid explanation even if it seems to contradict previously reported good data correlation [35]. It is also possible that the period between the renewal of the RMs and the testing could be excessive in some cases, so the RMs became worn [10]. An equally tenable explanation was suggested by a representative of a local applicator company (personal communication): the decrease in the quality of paint. Particularly, limiting the content of titanium dioxide pigment, which has a high refractive index that is necessary for obtaining retroreflection [36], could cause a significant decrease in RL. This could be a valid issue since it was shown that compositional changes to make a paint more environmentally friendly could cause higher long-term emissions due to lower durability. Since all of the tested RMs were renewed, potential effects of lower or higher governmental expenditures could be excluded in these cases.
While the absence of control sections, where RL would be tested but not reported to the road administrator, may be considered as a weakness of this study, one must note that it would be a futile effort and contrary to good practices. Failure to report such stretches to the road administrator could also be a violation of the laws. Therefore, the authors assume that job quality increase or decrease was uniform regardless of the testing. Amongst research needs, to confirm the results presented herein from the dynamic testing, simultaneous spot testing at the same roads in the same or different locations should be performed.
It has been repeatedly shown by us, based on results from field tests, that the use of high-end materials for RMs would lead to lower long-term costs and simultaneously lower environmental impact because such materials are capable of significantly prolonging the functional service life of RMs [7]. Hence, it was consistently shown that sustainability was tantamount with the durability. Consequently, long-term performance-based contracts for the maintenance of RMs were envisaged as the best solution that would benefit the following simultaneously:
  • The road administrators and taxpayers—through lowering the overall expenses;
  • The road users—through increased quality and thus better visibility of RMs;
  • The applicator companies—through stability of work and guaranteed revenues; and
  • The environmental sustainability—through the selection of the most durable materials that were shown to be the least costly in such cases.
From the perspective of environmental protection, the imposition of such contracts could be an example of employing a free market economy in selecting the most efficient and sustainable solutions instead of regulatory actions [37,38]. As a method to further increase the sustainability of RMs, one should additionally propose the use of Type II structured RMs that provide simultaneously much better visibility for drivers, are better recognised by driver assistance systems, and are generally known to be more durable than Type I flat line markings. The utilisation of properly selected GBs could enhance the properties and the sustainability further, particularly through prolonging functional service life [7]. While discussing such possibilities is beyond the scope of this report, one must note that control of the quality of RMs would be necessary. Indeed, the absence of supervision was very likely the chief contributing factor to the reported overall failure of a maintenance contract in North America [39].
Even though there was a reported correlation between RL and road safety [14,15], it is not possible to positively make such a correlation based on the data provided herein due to a plethora of other factors that could have played a role. Nonetheless, as shown in Table 8 [40], there was a decrease in the number of road accidents, fatalities, and injuries in Croatia between 2003 and 2013 but with their severity increasing. Since 2013, the number of accidents slightly increased, but there was a continuous decrease in the number of fatalities and injuries and their severity. The three-year average fatality rate per distances driven in Croatia remained very high, at 20.0 and 10.4 per 109 kilometres travelled, correspondingly for the periods 2010–2012 and 2020–2022, which positions Croatia in the top four out of 25 European Union countries reporting such data, with rates more than twice the average [41]. There is enormous expense associated with vehicular crashes [42]; in Croatia, it was estimated at 0.9–1.5 × 109 euros—approximately 2.3% of the country’s gross domestic product [40]. Hence, the use of such a relatively simple and inexpensive safety solution as the maintenance of RMs in good condition appears a good and sustainable investment [43], particularly since it was reported that a better quality of RMs was associated with a higher obedience of traffic rules [44].
The outcome of this research resulted in the uncovering knowledge voids that should be filled with new research. Amongst the topics other than mentioned above, we can list the following: (1) the validity of spot measurement methods in predicting the RL values of the entire marked areas, (2) the exact reasons for substandard RL at some locations, (3) accurate determination of the maximum achieved RL under specific traffic loads and with different materials, (4) the possibility of evaluation of RL under wet conditions as a requirement for the acceptance of jobs where RMs of Type II are demanded, (5) modelling and field research related to the emissions of microplastics from RMs as a function of the RL decrease, (6) the evaluation of renewal jobs completed by different application crews as a method of pinpointing some of the measured discrepancies, and (7) testing of the used materials in cases of less-than-perfect field performance under laboratory and/or controlled field conditions.

5. Conclusions

In conclusion, to maintain the high initial quality of RMs, supervision is necessary, as was shown based on the presented outcome. Within 10 years of systematic testing at spot locations, significant increases in RL were measured from 200 mcd/m2/lx to >290 mcd/m2/lx; Qd also increased—the renewal jobs reached full acceptance level. Nonetheless, after the switch to dynamic testing of the entire line lengths, meaningfully lower RL values were measured, with an average that decreased to only 240 mcd/m2/lx; in some cases, only 22% of the line lengths exceeded the minimum requirement. This decrease, not systematic but rather randomly occurring at different roads and different times, remains troublesome as it may indicate either the inadequacy of prior testing procedures or emerging issues like a decrease in the materials quality. Amongst other results, one must note that circa 1.22% of the tested total line lengths had RL < 100 mcd/m2/lx.
Since RMs belong to the basic road safety elements, they should remain well maintained to be visible for drivers under all conditions—road administrators are obliged to do so per statutory requirements. Furthermore, the recent requirement in the European Union for the installation of the Lane Keeping Assistant function in all new vehicles underlines the importance of such maintenance, because properly defined RMs are necessary for the correct functioning of this feature. RMs are a sustainable solution with a very low environmental impact and carbon footprint in comparison with the benefits that they provide, so their appropriate maintenance is in the interest of the entire society.

Author Contributions

Conceptualisation: D.B. (Darko Babić), M.F. and D.B. (Dario Babić); methodology: D.B. (Darko Babić), D.B. (Dario Babić) and T.E.B.; software: M.F.; validation: D.B. (Darko Babić), M.F. and T.E.B.; formal analysis: M.F., D.B. (Dario Babić) and T.E.B.; investigation: M.F.; resources: D.B. (Darko Babić) and D.B. (Dario Babić); data curation: D.B. (Darko Babić), M.F. and D.B. (Dario Babić); writing—original draft preparation: D.B. (Darko Babić), M.F., D.B. (Dario Babić); writing—review and editing: M.F., D.B. (Dario Babić) and T.E.B.; visualisation: D.B. (Darko Babić) and T.E.B.; supervision: D.B. (Darko Babić) and D.B. (Dario Babić); project administration: D.B. (Darko Babić); funding acquisition: D.B. (Darko Babić) and D.B. (Dario Babić). All authors have read and agreed to the published version of the manuscript.

Funding

This research received no specific external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Raw data can be made available upon reasonable request.

Conflicts of Interest

Tomasz E. Burghardt is employed by a manufacturer of road marking materials. Neither him nor his employer had any influence on the design of the study, in the collection, analyses, or interpretation of data, or in the decision to publish the results. The other authors declare no conflicts of interest.

References

  1. 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, 7843743. [Google Scholar] [CrossRef]
  2. Hillel, A.B.; Lerner, R.; Levi, D.; Raz, G. Recent progress in road and lane detection: A survey. Mach. Vis. Appl. 2014, 25, 727–745. [Google Scholar] [CrossRef]
  3. Miller, T.R. Benefit–cost analysis of lane marking. Transport. Res. Rec. 1992, 1334, 38–45. [Google Scholar]
  4. Brémond, R. Visual performance models in road lighting: A historical perspective. Leukos 2020, 17, 212–241. [Google Scholar] [CrossRef]
  5. Burghardt, T.E.; Pashkevich, A.; Babić, D.; Mosböck, H.; Babić, D.; Żakowska, L. Microplastics and road markings: The role of glass beads and loss estimation. Transport. Res. Part D Transp. Environ. 2022, 102, 103123. [Google Scholar] [CrossRef]
  6. Cruz, M.; Klein, A.; Steiner, V. Sustainability assessment of road marking systems. Transport. Res. Procedia 2016, 14, 869–875. [Google Scholar] [CrossRef]
  7. Burghardt, T.E.; Babić, D.; Pashkevich, A. Sustainability of thin layer road markings based on their service life. Transport. Res. Part D Transp. Environ. 2022, 109, 103339. [Google Scholar] [CrossRef]
  8. Pocock, B.W.; Rhodes, C.C. Principles of glass-bead reflectorization. Highway Res. Board Bull. 1952, 57, 32–48. [Google Scholar]
  9. Vedam, K.; Stoudt, M.D. Retroreflection from spherical glass beads in highway pavement markings. 2: Diffuse reflection (a first approximation calculation). Appl. Optics 1978, 17, 1859–1869. [Google Scholar] [CrossRef] [PubMed]
  10. Burghardt, T.E.; Pashkevich, A.; Fiolić, M.; Żakowska, L. Horizontal road markings with high retroreflectivity: Durability, environmental, and financial considerations. Adv. Transport. Stud. Int. J. 2019, 47, 49–60. [Google Scholar]
  11. Zwahlen, H.; Schnell, T. Visibility of road markings as a function of age, retroreflectivity under low-beam and high-beam illumination at night. Transport. Res. Record 1999, 1692, 152–163. [Google Scholar] [CrossRef]
  12. Horberry, T.; Anderson, J.; Regan, M.A. The possible safety benefits of enhanced road markings: A driving simulator evaluation. Transport. Res. Part F Traffic Psychol. Behav. 2006, 9, 77–87. [Google Scholar] [CrossRef]
  13. Diamandouros, K.; Gatscha, M. Rainvision: The impact of road markings on driver behaviour-wet night visibility. Transport. Res. Procedia 2016, 14, 4344–4353. [Google Scholar] [CrossRef]
  14. Avelar, R.E.; Carlson, P.J. Link between pavement marking retroreflectivity and night crashes on Michigan two-lane highways. Transport. Res. Record 2014, 2404, 59–67. [Google Scholar] [CrossRef]
  15. Carlson, P.J.; Avelar, R.E.; Park, E.S.; Kang, D.H. Nighttime safety and pavement marking retroreflectivity on two-lane highways: Revisited with North Carolina Data. In Proceedings of the Transportation Research Board 94th Annual Meeting, Washington, DC, USA, 11–15 January 2015. paper 15-5753. [Google Scholar]
  16. Hauer, E. On the relationship between road safety research and the practice of road design and operation. Accid. Anal. Prev. 2019, 128, 114–131. [Google Scholar] [CrossRef]
  17. Marking a Road toward a Safer Future. An ERF Position Paper on How Road Markings Can Make Our Road Safer; European Union Road Federation: Brussels, Belgium, 2015; Available online: https://erf.be/publications/marking-the-way-towards-a-safer-future (accessed on 27 June 2024).
  18. Lee, H.S.; Oh, H.U. Minimum retroreflectivity for pavement markings by driver’s static test response. J. East. Asia Soc. Transport. Stud. 2005, 6, 1089–1099. [Google Scholar] [CrossRef]
  19. Gibbons, R.B.; Williams, B.; Cottrell, B. The refinement of drivers’ visibility needs during wet night conditions. Transport. Res. Rec. 2012, 2272, 113–120. [Google Scholar] [CrossRef]
  20. Karimzadeh, A.; Shoghli, O. Predictive analytics for roadway maintenance: A review of current models, challenges, and opportunities. Civil Eng. J. 2020, 6, 602–625. [Google Scholar] [CrossRef]
  21. Standard ISO/IEC 17025; General Requirements for the Competence of Testing and Calibration Laboratories. International Standards Organization: Geneva, Switzerland, 2017.
  22. European Standard EN 1436; Road Marking Materials—Road Marking Performance for Road Users and Test Methods. European Committee for Standardization: Brussels, Belgium, 2018.
  23. Smadi, O.; Hawkins, N.; Aldemir-Bektas, B.; Carlson, P.; Pike, A.; Davies, C. Recommended laboratory test for predicting the initial retroreflectivity of pavement markings from glass bead quality. Transport. Res. Rec. 2014, 2440, 94–102. [Google Scholar] [CrossRef]
  24. Mazzoni, L.N.; Vasconcelos, K.; Albarracín, O.; Bernucci, L.; Linhares, G. Field data analysis of pavement marking retroreflectivity and its relationship with paint and glass bead characteristics. Appl. Sci. 2024, 14, 4205. [Google Scholar] [CrossRef]
  25. Kentucky Method 64-202-12; Evaluation of Retroreflectivity on Permanent Pavement Markings Using Mobile 30 Meter Geometry Instruments. Kentucky Transportation Cabinet: Frankfort, KY, USA, 2012.
  26. ZTV M 02; Zusätzlichen Technischen Vertragsbedingungen und Richtlinien für Markierungen auf Straßen. Forschungsgesellschaft für Straßen- und Verkehrswesen: Köln, Germany, 2002. (In German)
  27. Babić, D.; Fiolić, M.; Žilioniene, D. Evaluation of static and dynamic method for measuring retroreflection of road markings. Građevinar 2017, 69, 907–914. [Google Scholar] [CrossRef]
  28. Smjernice i Tehnički Zahtjevi za Izvođenje Radova na Obnavljanju Oznaka na Kolniku—Horizontalna Signalizacija; Hrvatske ceste d.o.o.: Zagreb, Croatia, 2010. (In Croatian)
  29. Sarasua, W.; Clarke, D.; Davis, W. Evaluation of Interstate Pavement Marking Retroreflectivity; Report FHWA-SC-03-01; South Carolina Department of Transportation: Columbia, SC, USA, 2003. [Google Scholar]
  30. ONR 22440-1; Bodenmarkierungen. Funktionsdauer—Teil 1: Allgemeines. Österreichisches Normungsinstitut: Wien, Austria, 2010. (In German)
  31. Rasdorf, W.J.; Zhang, G.; Hummer, J.E. The impact of directionality on paint pavement marking retroreflectivity. Public Work. Manag. Policy 2009, 13, 265–277. [Google Scholar] [CrossRef]
  32. Idris, I.I.; Mousa, M.; Hassan, M. Modeling retroreflectivity degradation of pavement markings across the US with advanced machine learning algorithms. J. Infrastr. Preserv. Resil. 2024, 5, 3. [Google Scholar] [CrossRef]
  33. Abu-Lebdeh, G.; Al-Omari, B.H.; Ahmed, K.; Long, D. Modeling the impact of winter maintenance on pavement marking retroreflectivity. Procedia Eng. 2012, 50, 942–956. [Google Scholar] [CrossRef]
  34. Babić, D.; Ščukanec, A.; Babić, D.; Fiolić, M. Model for predicting road markings service life. Balt. J. Road Bridge Eng. 2019, 14, 341–359. [Google Scholar] [CrossRef]
  35. Choubane, B.; Sevearance, J.; Lee, H.; Upshaw, P.; Fletcher, J. Repeatability and reproducibility of mobile retroreflectivity units for measurement of pavement markings. Transport. Res. Rec. 2013, 2337, 74–82. [Google Scholar] [CrossRef]
  36. de Jong, H.; Flapper, J. Titanium dioxide: Ruling opacity out of existence? Eur. Coat. J. 2017, 10, 52–55. [Google Scholar]
  37. de Medeiros, J.F.; Duarte Ribeiro, J.L.D.; Cortimiglia, M.N. Success factors for environmentally sustainable product innovation: A systematic literature review. J. Clean. Prod. 2014, 65, 76–86. [Google Scholar] [CrossRef]
  38. Jaffe, A.B.; Newell, R.G.; Stavins, R.N. Environmental policy and technological change. Environ. Resour. Econ. 2002, 22, 41–70. [Google Scholar] [CrossRef]
  39. Damnjanovic, I.; Pike, A.; Martinez, E. Analysis of performance-based pavement markings and markers contracts: Case study from San Antonio. J. Manag. Eng. 2018, 34, 05017010. [Google Scholar] [CrossRef]
  40. Bilten o Sigurnosti Cestovnog Prometa, 2023; Ministarstvo Unutarnjih Poslova: Zagreb, Croatia, 2024. (In Croatian)
  41. Ranking EU Progress on Road Safety. 17th Road Safety Performance Index Report; European Transport Safety Council: Brussels, Belgium, 2023; Available online: https://etsc.eu/wp-content/uploads/ETSC-17th-PIN-Annual-Report-DIGITAL-1.pdf (accessed on 27 June 2024).
  42. Wijnen, W.; Weijermars, W.; Schoeters, A.; van den Berghe, W.; Bauer, R.; Carnis, L.; Elvik, R.; Martensen, H. An analysis of official road crash cost estimates in European countries. Saf. Sci. 2019, 113, 318–327. [Google Scholar] [CrossRef]
  43. Albalate, D.; Fernández, L.; Yarygina, A. The road against fatalities: Infrastructure spending vs. regulation? Accid. Anal. Prev. 2013, 59, 227–239. [Google Scholar] [CrossRef]
  44. Diependaele, K. Non-compliance with pedestrian traffic lights in Belgian cities. Transport. Res. Part F Traffic Psychol. Behav. 2019, 67, 230–241. [Google Scholar] [CrossRef]
Sustainability 16 06653 g001
Figure 1. Location of sections for measurements according to ZTV M 02.
Figure 1. Location of sections for measurements according to ZTV M 02.
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Figure 2. Test vehicle with side-mounted retroreflectometer.
Figure 2. Test vehicle with side-mounted retroreflectometer.
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Figure 3. Average year-to-year RL and Qd of RMs tested at spot locations.
Figure 3. Average year-to-year RL and Qd of RMs tested at spot locations.
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Figure 4. Line lengths of RMs with RL > 220 mcd/m2/lx (full acceptance range) and average RL.
Figure 4. Line lengths of RMs with RL > 220 mcd/m2/lx (full acceptance range) and average RL.
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Table 1. Number of measurement sections according to ZTV M 02.
Table 1. Number of measurement sections according to ZTV M 02.
Length of Longitudinal Lines Applied in One Day [km]Area of the Other Markings Applied in One Day [m2]Number of Measurement Sections
<1<1201
1–5120–6002
>5–10>600–12003
>10>12004
Table 2. Requirements for RL and Qd [mcd/m2/lx] of RMs in Croatia.
Table 2. Requirements for RL and Qd [mcd/m2/lx] of RMs in Croatia.
Marking TypeType I (Paints—Thin Layer Applications)Type II (Thermoplastic, Cold Plastic, Tape—Thick Layer Applications)
Line ConditionNew or RenewedUsedNew or RenewedUsed
ParameterRLQdRLQdRLQdRLQd
Minimum required value200130100100300160150130
Verification range (a)180–220110–15090–11090–110270–330140–180130–170110–150
(a) If the average RL or Qd was within the verification range, confirmation measurements were to be performed. If values were below the verification range, the marking job was to be rejected. The verification range was abandoned in 2019.
Table 3. Selected information about the roads with the analysed RMs.
Table 3. Selected information about the roads with the analysed RMs.
RoadAnalysed Line Lengths [km] (a)Annually Average Daily Traffic (AADT)
Light VehiclesHeavy VehiclesWeight-Adjusted AADT (b)
D3633–4939634226917
D5540–4852284868630
D3059–7255505819617
D3726–3647435468565
D780–91583161410,129
D284–8739835507833
(a) Length variations of the analysed RMs were due to the different lengths of renewals in particular years, exclusion of sections undergoing construction, regions obscured from dynamic testing by stopped or overtaken vehicles, etc. (b) Weight adjustment per standard ONR 22440-1 [30].
Table 4. Retroreflectivity (RL) [mcd/m2/lx]; results from static testing 2003–2013.
Table 4. Retroreflectivity (RL) [mcd/m2/lx]; results from static testing 2003–2013.
RoadLineYearRL Change 2003–2013
20032004200520062007200820092010201120122013
D36Centre142223242252261271272285290305308117%
Right edge18920423724725326026426828628829054%
Left edge16423524124825126026226728128828976%
D30Centre19825226226627828628529631132532664%
Right edge25625826226626926228429729830130218%
Left edge20821622523825626726627632131232255%
D37Centre18819824829421028827025131230831568%
Right edge21623023524125021926827125626727226%
Left edge24025625225626426628229429228829222%
D7Centre18921922828929029530030731331031869%
Right edge22026228026326725027127928528829032%
Left edge23925526430627223227828529329029423%
D2Centre19022124729327927028128726929329857%
Right edge21125727127227824526226726628028334%
Left edge19022629027327326126927127327627746%
D55Centre20124425025526126128528227129128943%
Right edge18720723623524822425426226726526743%
Left edge17619523123324124423924424624823936%
Percentage passing (RL > 220 mcd/m2/lx)22%67%100%100%94%94%100%100%100%100%100%–
Percentage for verification (180 ≤ RL ≤ 220 mcd/m2/lx)61%33%0%0%6%6%0%0%0%0%0%–
Percentage failing
(RL < 180 mcd/m2/lx)		17%0%0%0%0%0%0%0%0%0%0%–
Average RL20023125026326125927227728529029346%
Table 5. Daytime visibility (Qd) [mcd/m2/lx]; results from static testing 2003–2013.
Table 5. Daytime visibility (Qd) [mcd/m2/lx]; results from static testing 2003–2013.
RoadLineYearQd Change 2003–2013
20032004200520062007200820092010201120122013
D36Centre1551571591631671711711761691691678%
Right edge14915414915816116616716918017818121%
Left edge15416314415015516116917316917617816%
D30Centre14915415316016716917016216017617618%
Right edge13815315415715314515616817217017527%
Left edge13916216416717015015815916816616821%
D37Centre1561481401671691721411681671691709%
Right edge13714511614414612015015317517117427%
Left edge11011912914314915215515217017818063%
D7Centre13813913915816217816917017217117427%
Right edge14419515514615316616416616716918126%
Left edge1681571461611681811741781791771808%
D2Centre14014113415416916516816516216816921%
Right edge13518514114115616716516917817517327%
Left edge13416114814716016917016417317117430%
D55Centre15716216216517118118719420319019625%
Right edge13714715215916416518018518817818233%
Left edge1641801621441581691801771871731799%
Percentage passing (Qd > 130 mcd/m2/lx)33%67%44%67%89%83%94%100%100%100%100%–
Percentage for verification (110 ≤ Qd ≤ 130 mcd/m2/lx) (a)67%33%56%33%11%17%6%0%0%0%0%–
Average Qd14515714715516116416617017417417722%
(a) Failures (i.e., Qd < 110 mcd/m2/lx) were not recorded.
Table 6. Results from dynamic testing of RL between 2015 and 2022.
Table 6. Results from dynamic testing of RL between 2015 and 2022.
RoadYear20152016201720182019202020212022Multi-Year Average
D36Distance RL < 180 mcd/m2/lx5.70 km (17.4%)2.30 km (5.0%)22.05 km (47.7%)29.65 km (62.0%)4.15 km (8.7%)6.55 km (13.6%)1.45 km (2.9%)15.45 km (31.8%)10.91 km (24%)
Distance 180 ≤ RL ≤ 220 mcd/m2/lx6.30 km (19.2%)2.75 km (6.0%)12.45 km (26.9%)7.60 km (15.9%)4.85 km (10.1%)5.65 km (11.8%)2.50 km (5.2%)6.75 km (13.9%)6.1 km (14%)
Distance RL > 220 mcd/m2/lx20.80 km (63.4%)41.10 km (89.0%)11.75 km (25.4%)10.55 km (22.1%)38.95 km (81.2%)35.70 km (74.6%)44.50 km (91.9%)26.35 km (54.3%)28.71 km (63%)
Average RL [mcd/m2/lx]242264184163269274319215241
D30Distance RL < 180 mcd/m2/lx3.80 km (6.4%)3.40 km (5.7%)14.00 km (23.5%)11.60 km (19.5%)3.15 km (5.4%)12.85 km (21.2%)2.30 km (3.8%)19.00 km (31.6%)8.76 km (15%)
Distance 180 ≤ RL ≤ 220 mcd/m2/lx9.35 km (15.7%)11.45 km (19.2%)20.55 km (34.5%)17.40 km (29.2%)9.35 km (16.1%)8.55 km (14.1%)2.00 km (3.3%)3.25 km (5.4%)10.23 km (17%)
Distance RL > 220 mcd/m2/lx46.30 km (77.9%)44.65 km (75.1%)25.05 km (42.0%)30.65 km (51.3%)45.50 km (78.5%)39.00 km (64.7%)56.40 km (92.9%)37.85 km (63.0%)40.67 km (68%)
Average RL [mcd/m2/lx]262254212225282249315250256
D2Distance RL < 180 mcd/m2/lx5.50 km (6.4%)7.30 km (8.6%)2.25 km (2.7%)0.75 km (0.9%)0.45 km (0.5%)12.15 km (14.4%)4.05 km (4.7%)4.90 km (5.7%)4.66 km (6%)
Distance 180 ≤ RL ≤220 mcd/m2/lx7.25 km (8.5%)11.40 km (13.4%)4.15 km (4.9%)1.95 km (2.3%)1.30 km (1.5%)12.85 km (15.2%)5.45 km (6.4%)8.80 km (10.4%)6.64 km (8%)
Distance RL > 220 mcd/m2/lx72.70 km (85.1%)66.15 km (78.0%)78.65 km (92.4%)81.55 km (96.8%)83.15 km (98.0%)59.05 km (70.4%)76.15 km (88.9%)71.35 km (83.9%)73.59 km (87%)
Average RL [mcd/m2/lx]258260330310307240298292287
D7Distance RL < 180 mcd/m2/lx3.50 km (3.9%)0.25 km (0.3%)0.15 km (0.2%)5.65 km (6.4%)3.00 km (3.4%)2.35 km (2.5%)37.80 km (42.1%)21.75 km (24.1%)9.3 km (10%)
Distance 180 ≤ RL ≤220 mcd/m2/lx5.70 km (6.3%)0.45 km (0.5%)1.10 km (1.2%)19.90 km (22.4%)27.65 km (31.0%)11.55 km (12.7%)22.70 km (25.3%)35.90 km (39.7%)15.61 km (17%)
Distance RL > 220 mcd/m2/lx81.0 km (89.8%)89.60 km (99.2%)88.35 km (98.6%)63.15 km (71.2%)58.30 km (65.6%)76.75 km (84.8%)29.35 km (32.6%)32.70 km (36.2%)64.9 km (72%)
Average RL [mcd/m2/lx]281408333240234264193205270
D37Distance RL < 180 mcd/m2/lx8.95 km (26.8%)7.00 km (21.0%)12.60 km (37.5%)7.50 km (30.2%)6.60 km (19.1%)7.60 km (23.1%)3.00 km (9.1%)5.55 km (16.5%)7.35 km (23%)
Distance 180 ≤ RL ≤ 220 mcd/m2/lx9.30 km (27.8%)14.45 km (43.3%)11.20 km (33.3%)9.35 km (37.7%)3.20 km (9.2%)6.10 km (18.5%)2.45 km (7.5%)7.50 km (22.3%)7.94 km (25%)
Distance RL > 220 mcd/m2/lx15.15 km (45.4%)11.95 km (35.7%)9.80 km (29.2%)7.95 km (32.1%)24.85 km (71.7%)19.10 km (58.4%)27.40 km (83.4%)20.60 km (61.2%)17.1 km (52%)
Average RL [mcd/m2/lx]208219172199268235293227228
D55Distance RL < 180 mcd/m2/lx0.95 km (2.0%)1.25 km (2.7%)3.05 km (6.5%)0.85 km (1.8%)1.10 km (2.3%)0.35 km (0.9%)2.55 km (5.4%)3.35 km (7.2%)1.68 km (4%)
Distance 180 ≤ RL ≤220 mcd/m2/lx3.45 km (7.4%)3.20 km (6.9%)3.90 km (8.4%)6.50 km (13.9%)4.00 km (8.6%)3.80 km (9.5%)4.05 km (8.6%)7.15 km (15.3%)4.5 km (10%)
Distance RL > 220 mcd/m2/lx42.45 km (90.6%)42.25 km (90.4%)39.70 km (85.1%)39.25 km (84.3%)41.35 km (89.1%)35.55 km (89.6%)40.60 km (86.0%)36.20 km (77.5%)39.66 km (87%)
Average RL [mcd/m2/lx]282347329311260261268249288
Averages for all roadsDistance RL < 180 mcd/m2/lx28.4 km (8%)21.5 km (6%)54.1 km (15%)56 km (16%)18.4 km (5%)41.8 km (12%)51.1 km (14%)70 km (19%)42.68 km (12%)
Distance 180 ≤ RL ≤220 mcd/m2/lx41.3 km (12%)43.7 km (12%)53.3 km (15%)62.7 km (18%)50.3 km (14%)48.5 km (14%)39.1 km (11%)69.3 km (19%)51.05 km (14%)
Distance RL > 220 mcd/m2/lx278.4 km (80%)295.7 km (82%)253.3 km (70%)233.1 km (66%)292.1 km (81%)265.1 km (75%)274.4 km (75%)225 km (62%)264.65 km (74%)
Average RL [mcd/m2/lx]256292260241270254281240262
Table 7. Distances of RMs with grossly substandard retroreflectivity (RL < 100 mcd/m2/lx).
Table 7. Distances of RMs with grossly substandard retroreflectivity (RL < 100 mcd/m2/lx).
Year20152016201720182019202020212022Range
D362.25 km (6.86%)0.05 km (0.11%)0.85 km (1.84%)7.80 km (16.32%)0.05 km (0.10%)0.05 km (0.10%)<0.05 km2.60 km (5.36%)0.00–7.80 km (0.00–16.32%)
D300.40 km (0.67%)0.05 km (0.08%)0.15 km (0.25%)0.30 km (0.50%)0.15 km (0.26%)3.50 km (5.79%)0.70 km (1.15%)6.30 km (10.48%)0.05–6.30 km (0.08–10.48%)
D20.25 km (0.29%)<0.05 km0.05 km (0.06%)<0.05 km<0.05 km1.30 km (1.55%)0.45 km (0.53%)1.30 km (1.53%)0.00–1.30 km (0.00–1.55%)
D70.30 km (0.33%)0.05 km (0.06%)<0.05 km0.10 km (0.11%)<0.05 km<0.05 km0.35 km (0.39%)<0.05 km0.00–0.35 km (0.00–0.39%)
D371.00 km (2.99%)0.10 km (0.30%)1.00 km (2.98%)0.50 km (2.02%)0.75 km (2.16%)0.55 km (1.68%)0.55 km (1.67%)1.10 km (3.27%)0.10–1.10 km (0.30–3.27%)
D550.05 km (0.11%)<0.05 km<0.05 km<0.05 km<0.05 km0.05 km (0.13%)<0.05 km<0.05 km0.00–0.05 km (0.00–0.13%)
Table 8. Road accidents in Croatia.
Table 8. Road accidents in Croatia.
YearAll AccidentsFatalitiesInjuries
NumberRate per 100,000 ResidentsRate per 100,000 VehiclesNumberRate per 100,000 ResidentsRate per 100,000 VehiclesSeverity (a)NumberRate per 100,000 ResidentsRate per 100,000 VehiclesSeverity (a)
200392,1022074558270115.842.50.76%26,153589158528%
201334,02179918493688.620.01.08%15,27435983045%
202334,60489818222747.114.40.79%14,20436874841%
Change 2003–2013−63%−61%−67%−48%−46%−53%42%−42%−39%−48%58%
Change 2013–20232%12%−1%−26%−17%−28%−27%−7%3%−10%−9%
Change 2003–2023−62%−57%−67%−61%−55%−66%4%−46%−38%−53%45%
(a) For the purpose of this report, severity is defined as the proportion of accidents ending with a fatality or an injury to all accidents. Calculations are not adjusted for accidents with multiple victims.
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Babić, D.; Fiolić, M.; Babić, D.; Burghardt, T.E. Systematic Testing of Road Markings’ Retroreflectivity to Increase Their Sustainability through Improvement of Properties: Croatia Case Study. Sustainability 2024, 16, 6653. https://doi.org/10.3390/su16156653

AMA Style

Babić D, Fiolić M, Babić D, Burghardt TE. Systematic Testing of Road Markings’ Retroreflectivity to Increase Their Sustainability through Improvement of Properties: Croatia Case Study. Sustainability. 2024; 16(15):6653. https://doi.org/10.3390/su16156653

Chicago/Turabian Style

Babić, Darko, Mario Fiolić, Dario Babić, and Tomasz E. Burghardt. 2024. "Systematic Testing of Road Markings’ Retroreflectivity to Increase Their Sustainability through Improvement of Properties: Croatia Case Study" Sustainability 16, no. 15: 6653. https://doi.org/10.3390/su16156653

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