Development of a New Procedure for Assessing Road Signs Maintenance Priorities for the Tuscan Road Network

Abstract

Road network safety management is a challenging process for Road Administrations (RAs) in Italy. It requires planning their activities, identifying operational actions, and implementing maintenance activities. For an effective road management system, all these activities should be based on a replicable monitoring procedure which relies on technical criteria to identify critical sites requiring attention. To develop and implement a reliable and effective maintenance strategy, Road Administrations need inexpensive and user-friendly procedures that can be applied to the entire road network. Road signs and road markings plays an important role in providing visual guidance for road users, which in turn influences road safety. This paper proposes and discusses a standardized and systematic monitoring procedure for the condition assessment of road signs and markings. The procedure will be applied to identify damaged, old, or unreadable signs and markings and a section of a two-way two-lane rural road has been used to test and calibrate the proposed procedure.

Keywords

road signs road markings monitoring maintenance decision tools

Introduction

Every year, the lives of about 1.3 million people are cut short as a result of road traffic accidents, and between 20 and 50 million others suffer serious injuries and live with negative long-term health consequences. This burden, in addition to inflicting pain and suffering on injured people and their families, also has a significant economic impact on society, costing most countries 3% of their gross domestic product (World Health Organization, 2018). In 2019, about 22,700 people died and over 1.2 million people were seriously injured on the European road network (European Commission, 2020). In Italy, the situation is slightly more serious; in 2019, there were about 172,183 road accidents resulting in more than 3000 fatalities and over 240,000 people severely injured (ACI-ISTAT, 2020). Although road safety is improving and the number of accidents, fatalities, and injuries decreased slightly during the last 10 years, progress in this field is considered slow (European Commission, 2019).

Among the set of initiatives proposed by the European Road Safety Policy Orientations 2011-2020, the EU strategic action plan on Road Safety (European Commission, 2018) aims to reduce the number of crashes and their severity through “road infrastructure safety management”, which represents a systematic and proactive approach that helps to appropriately target road investments and maintenance. In this context, the media often identify the lack of maintenance as a leading factor in a perceived increase in accident rates on our roads. Statistical information relating to these types of accidents are inconsistent due to the large difference in the recorded consequences of accidents. Indeed, the effects of poorly maintained road signage have varying consequences, ranging from damage to the road or vehicles to fatalities. Based on the Italian data of 2019, about 13.8% of all accidents are associated with the non-compliance of road signs and/or road markings (hereinafter referred to as road signage) (ACI-ISTAT, 2020), although the dataset did not provide any additional information about the efficiency and condition of road signage. More recently, the lack of attention to road signage and the inability to scan the road have been reported as major causes of traffic accidents (Lee, 2008).

The Regional Road Safety Monitoring Centre (CMRSS) of the Tuscan Region publishes estimates of perceived road safety based on a survey of road users. Analysis of the latest survey data highlights that the absence or the inappropriateness of road signage is perceived as a risk by about 10% of the surveyed road users (which includes pedestrians, cyclists, PTW,¹ and 4-wheeled vehicles users). This represents a 2% increase in this risk perception from the previous survey conducted in 2016(Regione Toscana, 2018). Therefore, one of the most cost-effective, and often underestimated, ways to increase road safety would be measures to improve road signage elements, such as road signs and markings. In fact, since the cognitive processes of decision-making while driving are mainly based on visual inputs (the driver visually receives more than 90% of the information while driving), road safety depends mainly on the timeliness of the information the driver receives, which is mostly transmitted by road signs and road markings (Babic, Babic, Cajner, et al., 2020). Hence, providing clear and readable travel routes allows for safer and more comfortable driving and lower accident rates (Mosböcka & Burghardt, 2016). From this perspective, the concept of “self-explanatory roads” ((Theeuwes & Godthelp, 1995)(Weller et al., 2008)(Mackie et al., 2013)Theeuwes, 1998; Weller et al., 2008; Mackie et al., 2013), has now become one of the leading principles in road design worldwide. According to this concept, roads should be designed in such a way that road users immediately know how to behave and what to expect. To let a road be “self-explaining” various measures may be adopted that also involve traditional and non-traditional road signage (Babic et al., 2020; Jamson & Mrozek, 2017).

However, the safety effects provided by road signage are not only the result of adequate design but also the efficiency of maintaining its performance over time. During the daytime, the surface, colours, and symbols of road signage should remain readable without fading or degrading, while during the nighttime, they should be able to reflect the light from approaching headlights back to the driver. This requires road signage to be inspected and maintained regularly and replaced when its visual performance is reduced below acceptable levels or following any damage (Wali et al., 2019).

Several studies have shown that the drivers’ ability to react appropriately decreases when road signs are poorly visible or comprehended, and consequently there is a recorded increase in the risk of driving errors (Al-Madani, 2000). Elvik (1999), analysed the relationship between road signs and their impact on safety and found that the conspicuity and visibility of road signs are precursors of their readability. Smadi et al. (2008) conducted a before-after study to evaluate the relationship between retroreflectivity of road markings and the probability of an accident. The results of their research showed statistical significance, especially concerning very low retroreflective values. Furthermore, the findings of a more recent study (Carlson et al., 2013) confirmed the positive safety effects of maintaining proper retroreflectivity of road markings.

Focusing on the Italian situation, research conducted on the condition of road signage by Centro Studi 3M (2007) showed that its overall quality is seriously inadequate, with increased age-related deterioration of all road signage. This means that if the “information given by the road signs and/or road markings” becomes unreadable, road signage as a whole fails to perform its basic function, thus creating an increasingly hazardous road environment for all users and especially for drivers who are unfamiliar with the road. On the basis of this evidence, it appears that road signage must first be visible in order to be clearly legible. Visibility will become even more important with the advent of Autonomous Vehicles (AVs) in the near future. Indeed, the condition of the road signage, stands out as one of the most important infrastructural needs for deployment of AVs, as significant deterioration (e.g., lane markings are faded or otherwise physically deteriorated) or unusual use of road signs can confuse AVs, leading to possible accidents.

For all of these reasons, sign maintenance should be a priority for Road Administrations (RAs). However, when the RA’s budget is limited, the maintenance backlog of traffic signs grows, which means that many signs on the road have faded colours, insufficient contrast between the surface and the symbols, or no longer retain sufficient retro-reflective properties to remain clearly visible and well readable to users both day and night. Consequently, the RAs must implement programs to replace old or damaged road signs and markings. The first type of action could be developing a strategy for replacing road signage at predetermined time intervals, in line with manufacturers' warranties. At the same time, RAs also need to prioritise road signage maintenance by evaluating the performance of the main in-service elements and then defining a work plan for the replacement of non-performing road signage. The first action allows RAs to schedule their maintenance program relatively easily, while immediately considering the intervention cost. On the other hand, some elements of road signage may lose their efficiency before the end of the warranty period due to specific conditions and should be immediately replaced, while some others may continue to perform well even after a few years and replacing them can be a waste of resources. Under these circumstances, it seems preferable to continuously monitor the performances of road signage. Different actions involve different management costs. Costs and performance influence the administrator’s choice, especially with regards to the time planning of the maintenance (European Union Road Federation, 2015). However, improving road signage provides outstanding benefits at a minimal cost. Carlson and Wagner (2012) calculated that the cost/benefit ratio could even reach 60. Therefore, selecting an appropriate strategy (including material performances, proper positioning, etc.) can yield additional benefits in terms of safety, durability, environmental friendliness, and cost-performance ratio.

For all these reasons, a complex process such as road management requires solid organizational criteria based on step-by-step operative procedures from monitoring and planning to the implementation of maintenance interventions; a repeatable and reliable process that will allow the RAs to identify and prioritize critical sites. These actions can be facilitated by tools that identify the intervention strategy that optimizes maintenance activities in terms of minimizing the number of accidents within the limitations of the available budget. To this end, this paper describes a project by the Department of Civil and Environmental Engineering (DICeA) of the University of Florence and funded by the Tuscan Region, aimed at providing RAs and road engineers with an optimized decision support tool for monitoring and screening the entire road network that is practical, economical, and user-friendly. In order to optimize the RA’s resources, this tool will make it possible to assess and classify the condition of road signage along the entire road network to guide future maintenance activities based on the actual condition of road signs and markings.

The proposed methodology includes only the activities to evaluate the condition of the road signage (in terms of identifying damaged, old, or unreadable road signs). It does not assess compliance with applicable standards or the design and adequacy of the installation (e.g., judging if the road sign has been installed at the right location). It is therefore important to point out that the monitoring procedure provided doesn’t include “functional monitoring”, which represents an important activity for the RAs, and that is driven by the improvement of the road environment through accurate planning and design effort. To test and calibrate the process, the tool has been applied to a stretch of SR 2 “Via Cassia”, which is a “two-way two-lane” rural road of high cultural and historical significance.

Overview of Road Signage Requirements

The Vienna Convention on Road Signs and Signals (UN 1968) represents the first EU document that standardizes road signage to increase safety, readability, and comprehension for all road users. The fundamental principle of the document is the need for road signage uniformity, clarity and simplicity. The convention encourages the use of shapes and symbols, instead of words, as much as possible, and limits the differences between countries to avoid confusion or misunderstanding when a driver is in a country other than their own. In Italy, as in other European Countries, the installation and use of road signage is governed by national standards, which in turn are based on the Vienna Convention: the Road Code and related regulation (Ministry of Infrastructure and Transport, 1992a; Ministry of Infrastructure and Transport, 1992b). These standards identify signs, devices, and markings, as well as their meanings, their denomination and their main technical characteristics in terms of shape, dimension, colour, material, refraction, and lighting. Some other technical characteristics are described, without specific standards or references, in the manufacturers’ technical manuals or the specific technical standard (UNI EN, 2008; UNI EN, 2016; UNI EN, 2018). In Italy, the selection of road signage and their application criteria and dimensions, as required by the Road Code, are based solely on speed limits (relating to the road type) and visibility distance. Furthermore, this regulation specifies that all road signage must be efficient during its in-service life which requires RAs and road operators to monitor the performance of in-service road signage and promptly replace, reintegrate, remove, and/or repair all elements that are determined to be wholly or partially inefficient or no longer meet the purpose for which they were designed (Ministry of Infrastructure and Transport, 1992a). However, because the available literature doesn’t provide clear and systematic methods for assessing the condition of road signage, different RAs often base their assessment on experience rather than a systematic management system. Consequently, maintenance is not typically based on a measured decrease in performance but occurs only when road signage has been damaged or removed (Pietrantonio, 2014).

Road users correctly perceive road signs and markings if they are visible and readable (UN, 1968; Ministry of Infrastructure and Transport, 1992a; Mazzotta et al., 2014). This occurs when road signage is properly maintained over time and the purpose of the monitoring process is to acquire detailed knowledge of the parameters necessary to properly characterize the in-service features and life expectancy of the road signage (Machado & Rasdorf, 2020). The condition of each road sign and marking and its associated performance level, can be described by parameters summarized in Table 1 (Ministry of Infrastructure and Transport, 2001; PIARC, 2012; Ministry of Infrastructure and Transport, 2011; Ministry of Infrastructure and Transport, 2012).

Table 1.

Road Signs and Markings Characteristics.

Features	Vertical sign	Horizontal sign
Film performance	Retroreflection	Retroreflection
Film performance	Luminance	Luminance
Visibility	Uncontrolled vegetation	Uncontrolled vegetation
	Clean	Clean
	Vandalism	Vandalism
Support condition	Perpendicolarity	—
	Integrity	Integrity
	Orientation	Orientation
	Rusty	—

The items listed in Table 1 are the main ones that can change or deteriorate over time and which, therefore, must be taken into consideration during a monitoring procedure aimed at assessing the condition of the road signage. It is, therefore, appropriate to specify that no other parameters have been indicated, such as the choice of the road signage colour which is based on the standards, as well as the size and content provided which are decided by the designers.

Visibility (and consequently readably) is the main parameter that should be maintained throughout the in-service life of each element of road signage to ensure that drivers receive the information necessary to navigate the specific road environment. In general, it can be influenced by various elements (as indicated in Table 1) and must be guaranteed both during nighttime and daytime.

Visibility isn’t defined by the Road Code, which instead refers, both for technical specifications and for measuring methods, to the technical standards EN UNI 12,889-1: 2008 (for fixed vertical road signs) (UNI EN, 2008) and EN UNI 1436:2018 (for road markings) (UNI EN, 2018). Retroreflectivity represents the ability of a material to redirect light beams that reach its surface back towards the source and is the main parameter that allows drivers to read and understand the message within the road signage during nighttime, and to correctly carry out the required manoeuvre. The source is represented by the vehicle’s headlights which illuminate the road signs or markings. Due to its importance, the assessment of a sign’s retroreflectivity has therefore become the main parameter for the evaluation of road signage deterioration (Howe, 2006; Harris et al., 2009).

The quantification of in-service retroreflectivity is particularly difficult because of the influence of factors such as the vehicle’s headlights and/or position compared to the road signage (Hawkins et al., 2003). Various studies define different methodologies to evaluate retroreflectivity based on objective measurements during the road signage’s in-service life while others provide empirical models to estimate retroreflectivity based on the road signage’s initial characteristics or, simply, by assuming a linear reduction over time (Harris et al., 2009; Bahar et al., 2006; Cottrell & Hanson, 2001; (Federal Highway Administration, 2013) FKWA, 2013). However, they all indicate that the problem is not the measurement of absolute values of retroreflectivity for in-service road signage, but the absence of any maintenance thresholds that would define whether the in-service road signage performance is appropriate (or not) for the intended function.

During the daytime, visibility is enhanced by the reflective capacity of the material, which improves the colour and the brightness contrast within the road signage. The daytime visibility performance for an element of road signage can be determined using one, or both, of the following indicators: (a) luminance coefficient in diffused lighting conditions (Qd), and (b) chromatic coordinates and luminance factor (β). The technical standards previously discussed define the requirements, and the threshold related to the parameters allows to quantify the luminance for vertical sign and horizontal marking, respectively (UNI EN, 2008; UNI EN, 2016; UNI EN, 2018).

Retroreflectivity and luminance are not the only factors that influence the visibility of road signage. While visibility is affected by attributes such as colour, luminance performance, and retroreflectivity of the signage, its placement plays an equally important role; it must be clearly visible against the provided background, as well as located in a prominent position (Porathe & Strand, 2011).

Visibility can also be affected by uncontrolled vegetation that may partially or totally hide the road sign, and fast-growing weeds that can quickly obscure road markings. Although road signage does not typically require regular cleaning because periodic rainfall keeps it clean, localized conditions can negatively impact visibility due to the buildup of dirt, grime, mildew, or mold. Therefore, cleaning is an important and relatively cheap maintenance operation that can improve road signage readability (Hugh & McGee, 2010). Graffiti removal is a different aspect of cleaning maintenance that should not be overlooked (Immanemi et al., 2007).

The support on which a vertical road sign is installed also plays an often overlooked but still important role. Specifically, it mainly consists of a vertical post (sometimes stiffened and supported) onto which the informational road sign is fixed. The post guarantees the correct position and orientation of the road sign panel. It can become a hazard when it is either struck by a vehicle or when it does not allow for the information within the road sign to be read (Hugh & McGee, 2010).

Definition of a New Procedure for Assessing the Road Sign and Marking Conditions

Overview of the Procedure

This study proposes a new approach to assess the condition of road signs and markings on the Italian road network. It could provide RAs with a proactive procedure based on a timely and objective evaluation of the condition of road signage and markings. The procedure, consisting of three steps, is summarized in Figure 1.

Figure 1.

Conceptualization of the procedure.

The fulcrum of the Inspection step is “road inspection”, where physical inspections are carried out two or three times at different speeds to obtain information about the road signs and markings along with the road. The fulcrum of “data post-processing” step is the evaluation of the indices that quantify the condition of signs and markings along with the road network. Multiple algorithms are defined that provide the RAs with an overall evaluation of road signs and marking conditions and distress within the road section considered. The indices also make it possible to compare the condition of road signage section by section within the entire road network. The procedure will allow the RAs to identify the section(s) where maintenance is required and assign priorities to repair the signs and marking within the road stretch.

Road Segmentation Process

The road segmentation represents the first sub-step of the inspection phase. Different segmentation criteria and section lengths can be defined in relation to different objective but the proposed procedure suggests the use of 100-meter lengths because the existing Italian database was usually organized with road sections starting and ending in well-known locations and contains numerous consecutive 100-meter segments. The segment length can be defined by the RAs as desired, but it is recommended that the section length reflect homogeneous conditions along the entire section (iRAP, 2013).

Although the results obtained for an entire segment may vary, the selection of different lengths doesn’t affect the evaluation of a single element, and thus the reliability of the overall methodology. For example, shorter segments provide detailed information but are generally poorly manageable in network analysis/screening; conversely, the use of longer road segments distributes the effect of a single road sign/marking evaluation. Therefore, the segment length must be defined in advance, based on monitoring goals and the same criteria needs to be applied for the entire network to obtain homogeneous and comparable results. Specific consideration has to be given to the segmentation of intersections which should include the entire intersection area. Therefore, each intersection needs to be evaluated in its own road section, whose length is affected only by the intersection configuration and geometry.

Road Inspection

In the second sub-step, damaged road signs and markings can be detected through periodic inspections rather than relying on different inputs, such as citizen alerts or police notifications (e.g. as a consequence of a crash). The reactive approach (e.g. after an alert) is far too common and does not allow the RAs to act promptly to manage its road network based on objective criteria.

Inspection has been identified as the most effective method to identify important maintenance problems for road signage (Machado & Rasdorf, 2020; Hugh & McGee, 2010), employing three main types of assessment:

• nighttime inspection,

• daytime inspection, and

• instrumental measurement.

This assessment aims to provide a methodology for carrying out visual inspections that do not differ markedly from standard road safety inspections or other visual inspections for the monitoring of road infrastructure. Using this methodology, it is possible to:

• assess the visibility/conspicuity of the road signage;

• identify damage;

• identify obstructions;

• evaluate poor placement (design evaluation);

• identify any other factors that might degrade the value of the road signage along the road stretch.

However, although visual inspections (without the use of instrumental measurement) represent the most complete monitoring procedure, they are also the most subjective. Therefore, inspectors require adequate training to ensure that they understand the monitoring goals and how inspection procedures are designed to achieve them. For this reason, inspections must follow a pre-defined procedure, which includes:

• training: each inspector should be qualified via appropriate training. Currently, no monitoring training programs are available, and each RA will need to organise specific training that aims to provide an understanding of what to look for (maintenance condition) and how to detect road signage deficiencies;

• checklists: RAs will need to provide checklists to the inspectors during the training course. During the inspection, each inspector will follow the methodology provided in the checklist which will allow for a more objective and uniform evaluation of specific parameters;

• professional skills and experience: RAs will need to identify both the critical and desired skills that inspectors should have to carry out their duties. Inspections can be conducted by a single inspector or by a team. Teams improve the quality of the inspection but are more costly. During the inspection, the road must be travelled in both directions at the posted speed limit and a speed below 30 km/h. Each inspection should be supported by the use of a high-definition camera to record the time and location of any issues and/or damages observed. All observations and judgements obtained during the inspection should be used to support the post-processing activities and for defining the overall condition of signs and markings.

There are a large number of documents regarding the evaluation of road signs and markings conditions that can inform the checklist. Due to the importance of road signage in road perception and road safety, the topic is addressed by both road safety and road maintenance documents (Ministry of Infrastructures and Transports, 2001; PIARC, 2012; Ministry of Infrastructures and Transports, 2011; Ministry of Infrastructures and Transports, 2012; Hugh & McGee, 2010). RAs can develop area-specific checklists from the available inventory and can include site-specific requirements concerning the environments to be inspected.

Checklist and Maintenance Condition Rating

Based on the procedure proposed in this paper, the data obtained from the inspections allowed the definition of various indices for each element type (road sign/road marking). These indicators are defined by considering an overall evaluation of each element characteristics.

In terms of “driver readability”, road signs and markings are evaluated using the following parameters:

1. luminance;

2. retroreflectivity;

3. visibility/readability;

4. cleanliness: dirt and/or vandalism;

5. condition of the sign support.

While road signs are punctual elements, and therefore require a set of indicators for the evaluation of each element, road markings can be both punctual (i.e., arrows, zebra crossing, STOP, etc.) or continuous elements (i.e., centerlines, edge lines, etc.). For the latter, the continuous elements must be divided into sections, using the same segmentation criterion previously described (see 3.2). Therefore, the evaluation of continuous road markings should be carried out on “homogeneous sections of markings” to improve the reliability of the procedure. If the road markings are not homogenous inside the analyzed road section, the inspector should assign an average rating based on observation for the entire section (e.g., intersection).

Several checklists have been proposed for the evaluation of the five listed parameters (luminance, retro-reflectivity, uncontrolled vegetation, cleanliness, support conditions, etc.). No checklist can be considered exhaustive, nor inclusive of all the information necessary for road signage inspections, but it should instead be considered as an aid to describe and quantify the main deficiencies. Figures 2 and 3 present two examples of checklists for the evaluation of retroreflectivity and luminance. The checklists are divided into two parts: in the first, images help the inspector to understand what needs to be evaluated qualitatively. In the second part, a short description of the possible road signage conditions is provided, with associated grading. The condition and the rating are to be recorded by the inspector for each road sign (still in a qualitative manner) (Figure 2) or for each punctual or continuous road marking (Figure 3).

Figure 2.

Example of check list: nighttime condition.

Figure 3.

Example of check list: daytime condition

At the end of the monitoring phase, each parameter considered will be characterized by a different “assessment” expressed by a “maintenance condition rating”, ranging from 0 to 2, which corresponds to a different qualitatively maintenance condition, as expressed in the checklists (Figure 2 and Figure 3) and summarized in Table 2. The first three ratings of Table 2 describe an evaluation of the qualitative conditions. These describe a situation that is considered still readable for traffic safety, which however may not be optimal (i.e. fair or poor condition). The last condition “R” which stands for “in need of repair” characterizes all cases that require an immediate restoration/replacement intervention and, therefore, do not contribute to the definition of the “priority list” because it could strongly affect road safety (e.g., unreadable STOP sign).

Table 2.

Maintenance Condition Rating.

Maintenance condition	Rating
Good	0
Fair	1
Poor	2
Need to repair	R

By this assessment the RAs obtain a large amount of data ranging from 0 to 2, which will be used for the evaluation of four indices:

• the single road sign condition index;

• the single road marking condition index;

• the global road sign condition index; and

• the global road marking condition index.

“Condition Indices” Evaluation

Single Road Sign Condition Index

The single road sign condition index (IS_el) is based on the assessment of the performance of each road sign. The index value is determined by using all the parameters which determine the correct perception of the sign. This approach allows an adequately programmed maintenance action for both the single road element being assessed (i.e., the rating (0–2) of every single parameter, e.g., luminance) but also the group of shared indicators (e.g., readability with standard illumination, sign support, panel cleanliness etc.) as shown in Table 3. The table summarizes all the proposed parameters for assessment of the road signs, as a function of the macro-category within which they are being grouped.

Table 3.

Parameters Included Within Each Macro-Categories – Road Signs.

Macro-categories	Indicators
Film performance	Retroreflectivity
Film performance	Luminance
Visibility condition	Limited visibility due vegetation
	Clean due vegetation
	Clean due to vandalism
Structural support condition	Support verticality
	Support integrity
	Support orientation
	Rusty support

The road sign condition index IS_el can be determined by the following equation (1).

I S_{e l} = \frac{\sum_{k = 1}^{m} \frac{\sum_{i = 1}^{n_{k}} I S_{k i}}{n_{k}}}{m}

(1)

where:

- IS_ki is the rating of the ith sign of the kth macro-category

- n_k is the number of indicators within the kth macro-category (i.e. retro-reflectivity and luminance with reference to film performances macro-category)

- m = number of macro-category

Global Road Signs Condition Index

A global road sign condition index (IS_global) is proposed. This index describes a global evaluation of all road signs within the specific road segment or section. This is an important step in order to compare different road sign maintenance conditions, section by section, throughout the entire road network, to optimize and schedule the maintenance activity.

According to the algorithm shown in equation (2), the “IS_global” evaluation includes all the IS_el values previously determined for each road sign within a homogeneous section. The algorithm takes into account the different consequences of reduced visibility for different types of signs (e.g. a sign of “danger for wild animals” that is not visible, has a different impact on road safety if compared to a sign of “stop and give priority”). For this reason, a weighting factor p_n is given to each different type of road sign.

I S_{g l o b a l} = \frac{\sum_{n = 1}^{N} p_{n} \cdot I S_{e l, n}}{\sum_{n = 1}^{N} p_{n}}

(2)

where:

- IS_el,n is the nth road sign condition index;

- p_n is the level of hazard associated with the “unreadable” nth element; and

- N is the total number of the single road elements within the homogenous section.

The definition of p_n associated with each road sign is based on its effects on road safety. Existing literature describes the effects on road safety of the different types of road signs or markings (see, for example, Babic et al., 2020; Veneziano & Knapp, 2016), but there has been little work on how the different road signs affect road safety, or which types of sign damage can have a greater impact on risk (McCaethy et al., 2013). Based on the information provided by a road sign, and with the prescriptive information provided in the Italian Road Code on the performance of the film (Ministry of Infrastructures and Transports, 1992a), the following weightings are presented in Table 4.

Table 4.

Dangerousness Associated With the Poor Condition of Road Signs.

Sign Type^a	Weight (p_n)
Warning of danger signs and Priority signs - class 1	6
Regulatory signs excluding Priority signs - class 2	4
Informative signs and others	1

^aThe sign types considered are the ones defined in the Vienna Convention on Road Signs and Marking (United Nation Publication, 1968)

Considering IS_el as a probability index associated with a road sign that is poorly maintained, and the hazard level, p_n as the consequences associated with its condition, the global indicator is actually a risk indicator. Therefore, the assignment of priority ranking for maintenance interventions, on the basis of values obtained for the global indices, is based on the risk associated with the decrease in the average performance of all the road signs within each homogeneous section. This includes both the level of damage on the road sign and its effects on road safety, as well as the overall number of road signs in poor condition within the same road segment.

Single Road Marking Condition Index

Road markings are evaluated using the same procedure proposed for road signs, but with the inclusion of the previously mentioned concept of “markings homogeneous sections”. This means that for continuous road markings, an average evaluation should be assigned for the overall section condition (e.g. edge line not visible in most parts of the section).

The algorithm proposed for the evaluation of the local road marking condition index IM_el is shown in equation (3).

I M_{e l} = \frac{\sum_{k = 1}^{m} \frac{\sum_{i = 1}^{n_{k}} I M_{k i}}{n_{k}}}{m}

(3)

where:

- IM_ki is the rating of the ith local road marking of the kth macro-category

- n_k is the number of indicators within the kth macro-category “visibility”

- m = number of macro-category (in this case equal to 1)

The proposed evaluation does not differ from the one proposed for road signs, due to the need to consider one by one all road markings regardless of their length. Table 5 summarizes the indicators selected for the “visibility” macro-category.

Table 5.

Parameters Included Within Each Macro-Categories - Road Markings

Macro-categories	Indicators
Visibility	Retroreflectivity
Visibility	Luminance

Global Road Marking Section Index

The global road marking section index (IM_global) includes ratings of both the punctual road marking and the rating associated with the continuous road marking, with reference to the relative extension of a homogeneous road section. This ensures that one element that is longer than another, has a greater weight on the estimation of the global indicator.

IM_global can be determined from equation (4).

I M_{g l o b a l} = \frac{\sum_{n = 1}^{N} p_{n} \cdot l_{n} \cdot I M_{e l, n}}{\sum_{n = 1}^{N} p_{n} \cdot l_{n}}

(4)

where:

- IM_el,n is the nth road marking condition index (local or continuous)

- l_n is the length of the nth continuous road marking [m]

- p_n is the hazard level associated with the nth road marking

- N is the total number of the local/continuous road markings within the homogenous section, regardless of their length.

The proposed methodology considers the punctual road markings included within equation (3) as having an idealized length of 0.3 m which is the same distance provided by the technical standard (UNI, 2018), which the observer has to maintain to evaluate its retroreflectivity.

The risk associated with low performance of road markings can be defined by three categories, which are a function of the information provided to drivers. In the following tables, the weightings for each marking group are defined for continuous and punctual road markings respectively (see Table 6 and 7). The values are provided with reference to the type of road marking considered, such as lane/edge line and/or transversal lines and symbols.

Table 6.

Dangerousness Associated with the Poor Condition of Continuous Road Markings

Sign type	Weight (p_n)
Edge line	6
Lane line	4
Other road marking	1

Table 7.

Dangerousness Associated with the Poor Condition of Punctual Road Markings

Sign Type	Weight (p_n)
Transversal line (STOP, priority line, zebra crossing, etc,)	6
Dangerous/attention symbols	4
Arrows and indication marking	1

Definition of the Priority List

The priority list (for each element and/or for each road section) defines the degradation of road signs and markings to build a solid, simple, and reliable procedure for RAs both to assess and compare the condition of road signage, section by section. within their road network. The procedure allows the RAs to screen their network and develop a list of maintenance priorities to plan interventions in an accurate and timely manner.

In this context, it is important to understand what and how each rating is considered within the overall assessment. It should be noted that every time an “R” rating (in need of repair) is assigned, the evaluation of the element will not influence the definition of the global index value, and therefore the priority list for planning maintenance interventions. Indeed, in these cases, each element (punctual or continuous) receiving an “R” rating represents an “alert to the RAs” that will require immediate maintenance. On the other hand, when the rating is within the range 0–2, the section by section comparison between the global indices makes it possible to determine the “relative average risk” connected to the "failure" of the in-service signs.

Three priority ranges for both global indices, IS_global and IM_global, are proposed, as shown below:

1. Low intervention priority: index <0.5

2. Medium intervention priority: 0.5 ≤ index <1.5

3. High intervention priority: index ≥ 1.5

The third category, “high intervention priority,” does not have an upper limit; therefore, when the global index exceeds 1.5, immediate action is indicated. This being noted, it should be understood that the higher the global index values, the higher is the urgency of maintenance.

The priority list is a decisive step for optimizing maintenance activities, both for program planning and performing immediate repairs, as it will enable the RAs’ to allocate resources in a manner that best improves the efficiency and safety of the road network. The overall assessment provides the RAs with four different lists: two priority lists of road signs and markings respectively, and two “R” lists, prioritised by the urgency of maintenance of road signage.

A Practical Application of the Proposed Procedure

SR2 Cassia

The Via Cassia (SR 2) is an ancient consular road that still connects Rome and Florence and is one of the most famous rural, two-way two-lane roads located in the southern Tuscany region of Italy. Due to the road’s historical and continuing importance, the section between Florence and San Casciano in Val di Pesa was selected for this case study. The section analyzed, shown in Figure 4, is approximately 10 km in length and runs from km 281+600 (located outside the urban village of San Casciano in Val di Pesa) to km 292+300 (inside the urban area of Florence).

Figure 4.

SR 2 analysed road segment.

The SR2 runs through a hilly environment, characterized by numerous small radius curves and includes a section along the River Greve where it maintains a low curvature ratio. The road geometry is quite complex with many curves of different radii and many driveways. The average carriageway width is 6.95 m with very narrow or no shoulders, and close marginal elements (wider shoulders are present only in the last section analysed). In the final part of the selected segment, the road passes through different urban contexts, reaching an important junction with two roads of a higher functional class.

Tuscan Regional Database

The Italian Road Code (Ministry of Infrastructures and Transports, 1992a) requires that all information regarding road layout and properties are included in a local or national database, which constitutes the "road cadastre”. The Tuscany region has a regional road database that was previously analysed to carry out the monitoring activity. It contains information relating to the location (GPS coordinates) of road signs and markings and some attributes relating to the type of road signage (e.g., articles and figures defined in the DPR 495/92 and road position) as summarized in Table 8.

Table 8.

Regional Database (Tuscan Region).

Signs and Markings
Attributes	Description
ID	Progressive number
Location	Road name and GPS coordinates (beginning/end) or progressive km (beginning/end)
Identification code	Identification code (articles and figure from DPR 495/92)

However, to build an effective monitoring procedure, the consistency of the Tuscan database needs to be improved. Because missing information about road signs or markings doesn’t allow for the correct evaluation of each element, nor the evaluation of the condition of a global section (e.g., information relating to road signage removed by mistake, or significantly damaged), should be recorded and included in the database and frequently updated (Osichenko & Spielhofer, 2018). Moreover, the information included in the road signage database must be suitably assessed and defined homogeneously (see Table 9), as it is a fundamental element for the monitoring application and development.

Table 9.

Information Should be Included in the Regional Database.

Signs and Markings
Attributes	Description
Roadside position	Left, right or above
Shoulder offset	Distance from the sign of the shoulder
Height	Height from the pavement surface
Dimension	Height and width of the panel
Reflective properties	Efficiency (I, II, III)
Material type	Paint, thermoplastic
Installation	date
Support type	Material and dimension

The information summarized in Table 9 when combined with that in Table 8, constitutes a reasonable, albeit non-exhaustive, example of the level of information required to suitably evaluate the condition of road signage. The knowledge concerning all the elements that are present on the roadside, including their condition (damaged or not), represents the starting point for the development of a user-friendly “screening” tool that will support the RAs in their decision-making processes for the maintenance and repair of road signage and markings.

Monitoring Procedure and Data Collection

Monitoring is the core of the “screening tool” and combined with the maintenance interventions, represents the most expensive element, in terms of work and budget. Therefore, a complete and up-to-date cadastre plays an important role in speeding up the procedure. Three diffused inspections (in addition to a supplementary punctual one) were carried out on the SR 2 by three inspectors trained on what and how to record the data and equipped with checklists as previously described (see Figures 2 and 3). These inspections included:

• a daytime inspection carried out at a speed compliant within the posted speed limit;

• a daytime inspection conducted by car at a speed not exceeding 30 km/h. During this inspection, each inspector recorded all the information independently. Where the number of road signs or markings was sufficiently small, the procedure could be carried out without recording or stopping the car. In all other areas it was important to record what the inspectors said, or to stop the car to allow for an appropriate analysis of every element giving the rate equal to 0, 1, 2 or R, with reference to the conditions observed;

• a nighttime inspection conducted by car at a speed not exceeding 30 km/h. During this inspection, performed in the same conditions as the daytime one, each inspector recorded their “rating” in relation to the retroreflectivity of road signs and markings; and

• one punctual inspection inside an urban context, where the number of road signs and markings is too large for an evaluation by car. Here, the inspectors used the same checklist used for the rural context.

During the monitoring activities, the inspectors took as many photos and videos as possible in order to accurately conduct post-processing in a remote location. At the end of the inspection, the checklists were completed, and an example is shown in Table 10 which summarizes the ratings given by each inspector for each road sign. The post-processing can be considered complete when all the road signage characteristics are evaluated with reference to the inspection results.

Table 10.

Inspection Results Format

	Films performances		Visibility			Support condition
Type of road sign	Retroreflectivity	Luminance	Uncontrolled vegetation	Clean	Vandalism	Perpendicolarity	Integrity	Orientation	Rusty
Obstacle	0	0	0	0	2	0	0	2	0
Pedestrian crossing	R	0	0	2	2	0	0	0	0
Hazard: intersection	R	0	R	0	0	0	0	0	0
….	0	1	1	1	0	2	0	2	0

Results and Discussion

During the inspection of the selected section of the Via Cassia (SR 2) every road sign or marking (punctual or not) was characterized by its condition and the resulting evaluations were used to calculate the single condition and global condition indices, IS_el, IS_global, IM_el, and IM_global. The global results are presented together, with some specific examples, to allow the RAs and their road engineers to better understand the usefulness of the proposed procedure to quickly define where and how to intervene according to the condition of road signage and the available budget. The bar chart in Figure 5 represents the values obtained for the global indices along the SR2. The chart is organized according to the intervention priority list (km by km). In both cases, there are no sections that have been classified as “high intervention priority”, with all global indices rated less than 1.5. Generally, road signs were found to be in poorer condition than road markings and in most of the sections analyzed, the RA was replacing the markings during the inspections.

Figure 5.

Global indices of the homogeneous section.

Figures 6 and 7 display the same road signs during daytime and nighttime conditions together with the rating received. Although in this case, the given “rating” is the same both during the day and at night, the rating assigned during different inspections could change. The road signage may not perform as anticipated under differing lighting conditions, providing erroneous or illegible information to the road user. It is important to remember that the “R” rating does not affect the global evaluation score and is only included for elements that need to be repaired immediately. Despite the presence of road signs requiring replacement, this section occupies the sixth position in the ranking, compared to 13 elements and 3 elements for road signs and markings respectively.

Figure 6.

Low visibility of the sign below the viaduct due to the luminance and dirty – daytime inspection.

Figure 7.

Low visibility of the sign below the viaduct due to the retroreflectivity – nighttime inspection.

The parameters defined in the proposed procedure are not exhaustive; the precision of the methodology proposed could be improved by including a greater number of variables (characteristics monitored) such as road signs too close together or the presence of inconsistent information given by road signs and markings. However, increasing the number of variables evaluated would likely result in an increase in workload, either during inspection or post-processing, with a resulting increase in time and cost.

Based on this case study, an upside of the procedure is that it doesn’t require any specialized equipment for evaluating the condition of each element which will maximize its usefulness to even the smallest and less financially endowed RAs. On the other hand, the procedure doesn’t produce a totally objective evaluation of the condition of the road signage. However, this can be overcome to some degree by comparing the sections in a network to identify the sections where road signage is the most damaged.

Conclusions

The procedure described in this paper will provide RAs and their road engineers with a systematic monitoring procedure for the condition of road signs and markings. To implement the procedure, a useful, economical, and user-friendly “screening” tool has been developed that can be applied to the entire road network and be used to identify damaged, old, or unreadable signs and markings on the road network.

All inspections proposed could be conducted by car, using a high-resolution camera, or on foot; by-car inspection is suggested for nighttime and wherever the number of road signs and markings isn’t excessive. In this context, the use of the camera recordings allows technicians to post-process the survey carried out along the road with videos and pictures used to confirm the inspector’s assessment. Otherwise, and especially within urban areas or where the environment is very complex, and where it is possible to perform the inspection safely, the research suggests that more accurate inspections would be conducted on foot. In either case, to improve reliability, inspections should be conducted using checklists, where inspectors can find questionnaires, examples, and qualitative ratings for each element to be inspected.

It is important to note that the methodology proposed represents only one procedure that the RAs will need to manage their road signs and markings. Within this context, the proposed monitoring could represent a first step in assessing the condition of road signs and markings along with the road network itself. The procedure proposed directly responds to the needs of RAs for a user-friendly and inexpensive assessment tool that can be used in a consistent and effective manner to identify damaged or old and unreadable road signage and markings. Due its flexibility, it can be easily integrated into a wider monitoring procedure that also manages other aspects of safety on the entire road network.

In the case study discussed, the procedure was carried out on a 10 km section of the Via Cassia (SR 2). Inspections were conducted to validate, and revise as necessary, each step of the procedure described in this paper. All the inspections were conducted by a group of trained inspectors to estimate all the proposed indices. A road segmentation of 100 m was selected but this length could be adjusted according to the requirements of the RAs. The proposed procedures and algorithms can be easily applied to segments of differing lengths, with a suggested minimum of 50 m. Road sections excessively long may be inappropriate because, if the road signage is not homogeneous within the length, the average evaluation (global index) may hide locations with specific issues. The results provide the RAs with two different lists of priority, for road signs and markings respectively, and two separate lists identifying the elements that require immediate replacement (which were rated “R”).

To disseminate the proposed monitoring procedure more broadly, the authors would like to stress the importance of applying the methodology to a large number of different type roads within the entire Italian road network which includes roads that significantly differ from each other due to their intrinsic characteristics. Additionally, repeating the SR 2 assessment using different inspectors with different professional skills and experience, and including a wider number of sections, will help to identify problems and limitations and improve the replicability of the procedure.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Regione Toscana.

ORCID iDs

Monica Meocci

Andrea Paliotto

Note

Author Biographies

Monica Meocci is a researcher on Highway, Airport and Railway Engineering at the University of Florence (Italy), Department of Civil and Environmental Engineering. Her studies and work focus on vulnerable road users, road design and improvement in road maintenance techniques. Great interest is also aroused by the analysis of road materials performance to optimize the road configuration with reference to durability and maintenance. She is a member of the PIARC TC 3.1B and TC 4.1. She is responsible for SWALK project concerning pedestrian safety and for CIMABUHE project based on the innovation in monitoring road anomalies. She is a reviewer for several Scientific Journals on transport and road safety topics.

Valentina Branzi is a scientific laboratory technician at the Department of Civil and Environmental of the University of Florence (Italy). Since 2011, she is the technical manager of the LaSIS Lab (Road Safety and Accident Reconstruction Laboratory). Her studies and work focus on road design, environmental impact assessments for transportation systems, road safety and “human factor”, with particular focus on the evaluation of the driver behaviour and performance in relation to issues related to road design and traffic management. She is a reviewer for several European and Italian conferences on transport and road safety topics.

Andrea Paliotto is a PhD student at the Department of Civil and Environmental Engineering of the University of Florence. He participated in several European Research Projects, such as PRACT, Skillfull, CoEXist, and National Research Project such as the Tuscany Region CMRSS, with a focus on road safety and road monitoring and maintenance. He is a member of PIARC TC 3.1B Committee on road safety. His studies and work focus on “human factor” and driver behaviour with reference to the road geometry and configuration.

Lorenzo Domenichini is a full professor of Highway, Airport and Railway Engineering at the University of Florence (Italy), Department of Civil and Environmental Engineering. He was the Director of the LaSIS Lab (Road Safety and Accident Reconstruction Laboratory). He is president of the PIARC TC 3.1B “Design of Road Infrastructure”. His studies and work focus on road safety, road design and maintenance. He was responsible for several European Research Projects. In 2018-2019 he was responsible for the CMRSS project investigating maintenance decision-making process tools based on network monitoring and screening.

Francesca La Torre is a full professor of Highway, Airport and Railway Engineering at the University of Florence (Italy), Department of Civil and Environmental Engineering. Her studies and work focus on road safety and road design, with specific reference to the Vehicle Restraint System. She was responsible for several European Research Projects on road safety and road design. She is a member of the USA Task Force in developing the Highway Safety Manual (NCHRP). She is a member of the CEDR Task Group “Road Safety” and coordinator of the “Forgiving Roadsides” Working Group.

References

ACI-ISTAT . (2020). Incidenti stradali in Italia anno 2019 — stima preliminare (in Italian Language). December 2020.

Al-Madani

H. M. N.

(2000). Influence of drivers’ comprehension of posted signs on their safety related characteristics. Accident Analysis and Prevention, 32(4), 575–581. https://doi.org/10.1016/s0001-4575(99)00084-6

Babic

Fiolic

Babic

Gates

(2020). Road markings and their impact on driver behaviour and road safety: A systematic review of current findings. Journal of Advanced Transportation, 2020(1), 1–19. https://doi.org/10.1155/2020/7843743

Babić

Cajner

Sruk

Fiolić

(2020). Effect of road markings and traffic signs presence on young driver stress level, eye movement and behaviour in night-time conditions: A driving simulator study. Safety, 6(2), 24, https://doi.org/10.3390/safety6020024

Bahar

Masliah

Erwin

Tan

Hauer

(2006). Pavement marking materials: real-word relationship between retroreflectivity and safety over time. NCHRP Web-Only Document 92.

Carlson

Park

E. S.

Kang

D. H.

(2013). Investigation of longitudinal pavement marking retroreflectivity and safety. Journal of the Transportation Research Board, 2337(1), 59–66. https://doi.org/10.3141/2337-08

Carlson

Wagner

(2012). An evaluation of the effectiveness of wider edge line pavement markings. Report from Texas Transportation Institute for American Glass Bead Manufacturer’s Association.

Centro Studi 3M . (2007). La seconda ricerca sullo stato della segnaletica stradale in Italia. (in Italian language).

Cottrell

B. H.

Hanson

R. A.

(2001). Determining the effectiveness of pavement marking materials. VTRC Report 01-R9. Virginia Transportation Research Council, Virginia Department of Transportation.

10.

Elvik

(1999). Modern technologies in road traffic signs. Available: http://www.crp.pt/docs/A28S38-66.pdf. Last access 13.04.2021

11.

European Commission . (2018). Strategic action plan on road safety. European Commission.

12.

European Commission (2019). EU road safety policy framework 2021-2030 - next steps towards “vision zero”. Available: https://ec.europa.eu/transport/road_safety/sites/roadsafety/files/move-2019-01178-01-00-en-tra-00_3.pdf. Last access 20.04.2021.

13.

European Commission . (2020). Road safety: Europe’s roads are getting safer but progress remains too slow. Available: https://ec.europa.eu/transport/media/news/2020-06-11-road-safety-statistics-2019_en. Last access 13.04.2021.

14.

European Union Road Federation . (2015). Improved signage for better roads: An ERF position paper towards improving traffic signs in European roads. European Union Road Federation.

15.

Federal Highway Administration . (2013). Maintaining traffic sign retroreflectivity: Revised 2013 (Publication N. FHWA-SA-07-020). US Department of Transportation.

16.

Harris

Rasdorf

Hummer

(2009). A control sign facility design to meet the new FHWA minimum sign retroreflectivity standards. Public Works Management & Policy, 14(2), 174–194. https://doi.org/10.1177/1087724x09350226

17.

Hawkins

Jr. Carlson

P. J.

Schertz

Opiela

(2003). Workshops on nighttime visibility of traffic signs: Summary of workshop findings. Federal Highway Administration.

18.

Howe

S. J.

(2006). Assessment of road signs for retroreflectivity. In: Mathew

Kennedy

Tan

Anderson

(Eds.) Engineering asset management. Springer.

19.

Hugh

McGee

H.W.

(2010). Maintenance of signs and sign supports. In: A guide for local Highway and street maintenance personnel. U.S. Department of Transportation. Federal Highway Administration.

20.

Immanemi

Rasdorf

Hummer

Yeom

(2007). Field investigation of highway sign damage rates and inspector accuracy. Public Works Management & Policy, 11(4), 266–278. https://doi.org/10.1177/1087724X07299882.

21.

International Road Assessment Programme (iRAP) (2013). Smoothed star ratings, iRAP methodology fact sheet # 8. iRAP.

22.

Jamson

Mrozek

(2017). Is three the magic number? The role of ergonomic principles in cross country comprehension of road traffic signs. Ergonomics, 60(7), 1024–1031. https://doi.org/10.1080/00140139.2016.1245874

23.

Lee

J. D.

(2008). Fifty years of driving safety research. Human Factors, 50(3), 521–528. https://doi.org/10.1518/001872008x288376

24.

Machado

Rasdorf

(2020). Analysis of three sign management program case studies. Public Works & Policy, 25(1), 51–74. https://doi.org/10.1177/1087724x19862285

25.

Mackie

H.W.

Charlton

S.G.

Baas

P.H

Villasenor

P.C.

(2013). Road user behaviour changes following a self-explaining roads intervention. Accident Analysis & Prevention, 50, 742–750. DOI:10.1016/j.aap.2012.06.026

26.

Mazzotta

Vignali

Irali

(2014). Evaluation of the readability of road signs and roadside elements using Mobile Eye tracking device. Research Gate.

27.

McCaethy

Liang

Park

McFadden

Triew

(2013). Risk-based method for development and management of a traffic sign inventory for local agencies. Public Works Management & policy, 18(1), 82–95. https://doi.org/10.1177/1087724x12461144

28.

Ministry of Infrastructures and Transports . (1992a). Nuovo codice della strada, D.L. 30 Aprile 1992 n.285 e successive modificazioni. gazzetta ufficiale della repubblica Italiana, n. 114. MIT, Via G. Caraci 36, Roma in Italian language.

29.

Ministry of Infrastructures and Transports . (1992b). Regolamento di Esecuzione e di Attuazione del Nuovo Codice della Strada. D.P.R. n.495 del 16.12.1992. MIT, Via G. Caraci 36, Roma in Italian language.

30.

Ministry of Infrastructures and Transports . (2001). Linee guida per Le analisi di sicurezza delle strade. Circolare n.3699 del 08/06/2001. MIT, Via G. Caraci 36, Roma in Italian language.

31.

Ministry of Infrastructures and Transports . (2011). Gestione della Sicurezza delle Infrastrutture stradali. Decreto Legislativo n.35 del 15/03/2011. MIT, Via G. Caraci 36, Roma in Italian language.

32.

Ministry of Infrastructures and Transports . (2012). Linee guida per la Gestione della Sicurezza delle Infrastrutture stradali. Decreto ministeriale n.137 del 02/05/2012. MIT, Via G. Caraci 36, Roma in Italian language.

33.

Mosböcka

Burghardt

T. E.

(2016). The importance of road markings for road safety and modern traffic management. In 1st European Road Infrastructure Congress, Leeds, UK, 18–20 October 2016.

34.

Osichenko

Spielhofer

(2018) Monitoring and inventory of road signs and road markings. State of the art – a review of existing methods and systems, Proceedings of 7th Transport Research Arena TRA 2018, April 16–19, 2018, Vienna, Austria

2018

35.

PIARC - World Road Association . (2012). Road safety inspection guidelines for safety checks of existing roads. PIARC.

36.

Pietrantonio

(2014). A basic theory for the design of road signage elements. ReaserchGate.

37.

Porathe

Strand

(2011). Which sign is more visible? Measuring the visibility of traffic signs through the conspicuity index method. European Transportation Research Review, 2(1), 35–45. https://doi.org/10.1007/s12544-011-0050-9

38.

Smadi

Souleyrette

R. R.

Ormand

D. J.

Hawkins

(2008). Pavement marking retroreflectivity: Analysis of safety effectiveness. Journal of the Transportation Research Board, 2056(1), 17–24. https://doi.org/10.3141/2056-03

39.

Regione Toscana . (2018). I comportamenti di guida e il rischio di incidente stradale 2018. (in Italian Language).

40.

Theeuwes

Godthelp

(1995). Self-explaining roads. Safety Science, 19, 217–225.

41.

UNI EN

12899-1:2008 (2008). Segnaletica verticale permanente per il traffico stradale - segnali permanenti. Ente Nazionale Italiano di Unificazione.

42.

UNI EN

11480:2016 (2016). Linea guida per la definizione di requisiti tecnico-funzionali della segnaletica verticale (permanente) in applicazione alla UNI EN 12899-1:2008. Ente Nazionale Italiano di Unificazione.

43.

UNI EN

1436:2018 (2018). Materiali per la segnaletica orizzontale – prestazioni della segnaletica orizzontale per gli utenti della strada e metodi di prova. Ente Nazionale Italiano di Unificazione.

44.

United Nation Publication . (1968). Convention on road signs and Signals. United Nation Publication.

45.

Veneziano

Knapp

(2016). Sign effectiveness guide. Institute of Transport, IHRB Project TR-686.

46.

Wali

S. B.

Abdullah

M. A.

Hannan

M. A.

Hussain

Samad

S. A.

Ker

P. J.

Mansor

M. B.

(2019). Vision-based traffic sign detection and recognition systems: Current trends and challenges. Sensors (Basel), 19(9),Article 2093. https://doi.org/10.3390/s19092093

47.

Weller

Schlag

Friedel

Rammin

(2008). Behaviourally relevant road categorisation: A step towards self‐explaining rural roads. Accident Analysis and Prevention, 40, 1581–1588.

48.

Word Health Organization . (2018). Global status report on road safety 2018. Word Health Organization