**1. Introduction**

Road traffic crashes are the eighth leading cause of death globally with an estimated 1.35 million killed and 50 million injured each year [1]. Speed management has a long association with road safety and is enshrined within contemporary international road safety strategies such as the safe systems approach [2,3]. Such strategies are founded upon the basis that the consequences of crashes at higher speeds are a simple matter of physics: the greater the change in velocity, the greater the energy dissipation and, subsequently, the higher the severity of injury [4]. On this basis, understanding the relationships between drivers, vehicles, road infrastructure, and speed continues to be an important goal of road safety research.

Early case-control studies in speed research suggested that the greater the differential in the speed of a vehicle from the average of all the traffic, the higher the risk of a crash [5,6]. Self-reporting studies have also found that drivers found to be travelling faster are more likely to have a history of crashes [7]. More recent research has tended to look at the road level (including segments, sections, intersections, and corridors), rather than individual driver level, not least because of the difficulties of categorically associating speed as a causation factor in individual crashes [8]. The question then becomes one of how the frequency and severity of the crashes vary with mean speed, to which the answer has been extensively explored; before-and-after studies of measures, such as changes in the posted speed limit, traffic calming interventions, or increased enforcement have resulted in linear, power, and asymptotic relationships associating higher mean speeds with increased crash rates [9–14]. Therefore, from the point of view of the road designer, road features that result in unintended increases in mean speed are unlikely to be desirable.

**Citation:** Llewellyn, R.; Cowie, J.; Fountas, G. Solar-Powered Active Road Studs and Highway Infrastructure: Effect on Vehicle Speeds. *Energies* **2021**, *14*, 7209. https://doi.org/10.3390/en14217209

Academic Editors: Marek Guzek, Rafał Jurecki and Wojciech Wach

Received: 17 October 2021 Accepted: 30 October 2021 Published: 2 November 2021

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**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

In several countries across the world, reflective road studs are used as a measure to assist drivers in low light by highlighting road features, such as lanes, carriageway edges, curvature, and junctions. They rely on the reflection of the vehicle's headlight beam back to the driver to provide a preview of oncoming features. However, such a system is limited in range by the power of the vehicle headlights and can be further affected by weather and the physical condition of the studs themselves. Active Road Studs (also known as Internally Illuminated Raised Pavement Markers) are a recent development which seeks to address such issues. The studs feature high-powered LEDs which significantly increase the preview time of the road ahead and have been suggested as being of assistance to drivers in several road scenarios [15,16]. They have also been shown to have a positive impact on driver confidence [17]. However, if increased confidence were to result in a corresponding increase in speed, this could potentially compromise any road safety gains made. On this basis, the effect of active road studs on vehicle speeds in the context of other road features is of particular interest.

The relationship between active road studs and speed has been the subject of several simulator studies exploring the behaviour of drivers with and without their implementation. One such study investigated thirty-six participants split evenly across three age groups over a 37 km generic, rural, single carriageway route, with matching sections of no studs, passive (i.e., traditional reflective) studs, and active studs [18]. The simulation showed statistically significant increases in mean speed along the route between the nostud and the passive- or active-stud sections. However, no statistically significant difference was found between passive and active road studs. Looking at corners alone, the same results were found for right-hand curves. For left-hand curves, an increase was found in mean speed for the youngest and oldest driver groups. Drivers were also found to brake more strongly for both studded conditions on corners, but there was no significant difference in braking between active and passive studs.

A later simulator study compared the speed of drivers on a route with no studs, active studs on curves, and full road lighting on curves [19]. In this case, the studs were activated by an approaching vehicle and switched off once the vehicle had passed. The distance between studs was also varied; larger distances between studs were applied on the approach, with smaller distances on the curve itself. Twenty participants drove the route, comprising sixteen straight and sixteen curved sections. On the straight sections, higher mean speeds were recorded with both the stud and the lighting treatment when compared with the unlit route; however, no significant difference was found between the mean speeds of the studded and lit conditions. Overall, faster speeds were found on the approach to curves than within them. Noting that this study was based on right-hand driving, in right-hand curves no differences between the three speeds were found. For left-hand curves, the speed on the approaches was higher with the lighting than with the studs or no treatment.

Regarding the speed effects of active road studs in real-world applications, a beforeand-after video study of an undefined length of road was undertaken between two bends in Victoria, Australia [20,21]. The reductions in mean speed before and after installation in each direction were found to be 1.2 km/h (0.7 mph) and 3.1 km/h (1.9 mph), respectively. However, the change was only statistically significant in the latter case, and the methods of control for other confounding factors were not detailed. A review of the literature, practitioner feedback, and manufacturers undertaken in the United States included speed effects on highway junctions and links in its scope [22]. Whilst the reporting of reduced speed was suggested as a possible outcome in the review, it notes that the data were limited and could not be considered conclusive.

The research to date on the relationship between active road studs and speed is limited to simulator-based studies or very small field installations. Furthermore, the focus of the existing work has been on plain tangent and curve sections and has not covered potential mean-speed changes at other road features, such as junction approaches, merges, and dual carriageway sections. The present work attempts to address this gap in knowledge. On this basis, the aim of this research was to measure the choice of speed by drivers, using real-world rural junctions and links and to determine whether changes in the speed of vehicles may be associated with the installation of active road studs when compared to other road features. Building on the findings of previous studies, the stated hypothesis is that the implementation of active road studs results in no change in speed when compared to their traditional reflective equivalent and that other road features are associated with differences in mean speed. The objectives were to:


The work described here forms part of a larger study investigating the effects of active road studs on driver behaviour, such as lane discipline, gap acceptance, and driver confidence. The focus in this element is the effect of active road studs on vehicle speeds. Section 2 describes the materials and methods adopted, including the background to the case study chosen, the procedure used for obtaining the speed and infrastructure data, and the statistical methods used for the analysis. Section 3 states the results of the route and individual site surveys and the development of the linear regression model. The findings are discussed in the context of the existing literature in Section 4, with conclusions and implications for practitioners identified in Section 5.

#### **2. Materials and Methods**

#### *2.1. Case Study Background*

The A1 trunk road (a route of national strategic importance) runs between Edinburgh and London in the UK. The road is constructed to dual carriageway or motorway standard for most of its length, but the section straddling the border between Scotland and England is more mixed in its composition. It also carries a lower volume of traffic than other parts of the route. Although complying with modern alignment standards due to extensive upgrading in the latter half of the 20th century, it mainly consists of single carriageway, with a posted speed limit of 60 mph (97 km/h). Short sections of 2 + 1 carriageway and higher speed 70 mph (113 km/h) dual carriageway are provided at intervals to provide overtaking opportunities. The speed limits for heavy goods vehicles (HGVs) are 20 mph lower than the posted limit at 40 mph (64 km/h) and 50 mph (80 km/h) for the single and dual carriageway sections, respectively. The route is particularly rural in nature, carrying national strategic traffic along with linking local towns and villages. During the hours of darkness, there is very little ambient light due to its location away from major population centres. Street lighting is provided at certain points, but the route is predominantly unlit.

The case study for this research is a 20 km section of the A1 in Scotland immediately north of its border with England. The route here has a modest crash rate relative to other Scottish trunk roads; this has been associated with fixed-enforcement-camera treatment [23]. Nevertheless, local communities have continued to raise safety concerns, prompting a review by the national roads authority. The review found that the legibility of the route during hours of darkness, particularly around junctions, could be problematic. An improvement scheme was proposed [24] comprising the installation of 4200 solar-powered active road studs to highlight the approaches to nine junctions and two intermediate carriageway sections. The active road studs were effectively a like-for-like replacement of the reflective road studs which were already in situ. In accordance with the UK traffic sign regulations, white, red, amber, and green studs were used to indicate the centreline, nearside and offside edge lines, and the merge/diverge sections, respectively. Examples of typical active road stud installations implemented as part of the scheme are shown in Figure 1.

**Figure 1.** Example active stud installations: (**a**) dual to single carriageway merge; (**b**) single carriageway curve; (**c**) single carriageway junction; (**d**) dual carriageway junction.

#### *2.2. Methodological Considerations*

Two methods were considered for the measurement of speeds on the treated section of the route. The first option was the use of automatic traffic counters. Such counters have the benefit of being able to record a large amount of data over a continuous period, resulting in a large sample size and coverage of a range of conditions. With careful installation, they can be installed relatively inconspicuously to avoid any potential influence on the results. However, as an observer is not usually continuously present, confounding factors, such as incidents and inclement weather conditions, can mean collected speed data may not be fully representative. The accuracy of the automatic traffic counters can also be affected by irregular vehicle trajectories, detector spacing, scanning time, and multiple vehicles in the detection zone [25,26]. The traffic counters also record the speeds of all vehicles passing, irrespective of flow density. As a result, individual recorded speeds may be affected due to the presence of other vehicles and may not reflect a true speed choice by the drivers.

The alternative method considered for measuring speeds was a manual radar survey. Such surveys are labour-intensive and are more limited in the choice of location due to the need for the observer to remain inconspicuous whilst not compromising the safety of the survey staff or other road users. They can also be prone to human error or bias, particularly where the observer is inexperienced. However, manual speed surveys allow for a truer representation of free mean speeds to be recorded as the observer can exercise judgement regarding whether speeds are likely to be by choice; for example, this can be achieved

by recording speeds only where a certain headway between vehicles is exceeded and by the monitoring of other factors, such as the illumination of brake lights. Other benefits of the continuous presence of an observer include the monitoring of weather conditions and the accounting for any unusual incidents during the survey period. On this basis and in the interests of potentially greater precision, the manual radar survey was selected as the preferred method for this work.
