Due to the dynamic nature and complexity of road traffic, road safety is one of the most demanding social challenges. Therefore, contemporary road safety strategies incorporate a multidisciplinary and comprehensive approaches to address this problem and improve the safety of each individual element, i.e., the human, vehicle, and road. Traffic control devices are an important part of road infrastructure, among which road markings and road signs play a significant role. In general, road markings and signs represent basic means of communication between the road authorities and road users and, as such, provide road users with necessary information about the rules, warnings, obligations, and other information related to the upcoming situations and road alignment. The aim of this entry is to briefly present the main functions and characteristics of road markings and signs, and their role in road safety. In addition, practical issues and future trends and directions regarding road markings and signs are discussed.

As part of an overall traffic signalling system, traffic signs warn the traffic participants, give information about the restrictions, prohibitions and obligations and provide additional information needed for a safe and undisturbed traffic flow. The traffic sign quality is expressed by its retroreflection and it is particularly pronounced in conditions of reduced visibility. The aim of this paper is to analyse how traffic signs quality affects the frequency of traffic accidents in low visibility conditions. For this purpose, traffic accidents and the quality of traffic signs were analysed on 130 state roads in the Republic of Croatia between 2013 and 2015. In the analysis several variables were used: the number of traffic accidents occurred under reduced visibility conditions, length of the road, AADT (Annual Average Daily Traffic) and the number of traffic signs that do not meet the minimum prescribed values of retroreflection. Statistical analysis showed a positive correlation between the accidents and unsatisfactory traffic signs, i.e. that with the increase in the number of traffic sings that do not have a satisfactory level of retroreflection, an increase in the number of accidents in reduced visibility conditions is expected.

Motorcyclist safety remains a significant problem, and the overall safety of motorcyclists has been improved at a much slower rate in the last decade compared to passenger and commercial vehicles. Because motorcyclists are not protected by the vehicle frame, fatalities or severe injuries are often related to hitting a roadside object or safety barrier. The main objective of this study is to investigate relations between the presence and type of road safety barriers and the consequences of motorcycle crashes on rural roads. For this purpose, we analysed Croatian rural road-crash data from 2015–2019, tested several factors as single predictors, and combined them using binary logistic regression. The results show that run-off-road crashes and nighttime driving are significant risk factors. There was no significant positive impact of the presence of safety barriers on the crash consequences due to the unsuitability of the barriers for motorcyclists, which proves the fact that the functionality of existing safety barriers should be upgraded. The results of this study could be further used by researchers, road designers, and experts to improve road infrastructure safety on rural roads.

Speeding is one of the main contributing factors to road crashes and their severity; therefore, this study aims to investigate the complex dynamics of speeding and uses a multivariable analysis framework to explore the diverse factors contributing to exceeding vehicle speeds on rural roads. The analysis encompasses diverse measured variables from Croatia’s secondary road network, including time of day and supplementary data such as average summer daily traffic, roadside characteristics, and settlement location. Measuring locations had varying speed limits ranging from 50 km/h to 90 km/h, with traffic volumes from very low to very high. In this study, modeling of influencing factors on speeding was carried out using conventional and more advanced methods with speeding as a binary dependent variable. Although all models showed accuracy above 74%, their sensitivity (predicting positive cases) was greater than specificity (predicting negative cases). The most significant factors across the models included the speed limit, distance to the nearest intersection, roadway width, and traffic load. The findings highlight the relationship between the variables and speeding cases, providing valuable insights for policymakers and law enforcement in developing measures to improve road safety by determining locations where speeding is expected and planning further measures to reduce the frequency of speeding vehicles.