Road Safety Performance Indicators Research Articles

Effective road safety measures in Greece

The paper presents road safety actions and measures proposed in the framework of the development of the Greek Strategic Road Safety Plan for the period 2021-2030. Five road safety pillars that concern all road crash factors are outlined. For each pillar, actions and particular measures are defined, adapted to the Greek reality and based on the principles of Vision Zero and the Safe System Approach. In total, 44 actions and 200 road safety measures are foreseen and implementation priorities are defined. Next, the framework for monitoring the implementation of actions is presented, taking into account the elements of the Safe System Approach. The use of a set of key performance indicators for road safety is proposed and the methodological framework for the collection of the necessary data and the calculation of road safety performance indicators is provided.

The Baseline project: Key Performance Indicators for Road Safety in EU countries, based on a common methodology for data collection and analysis

The European Commission has made grants available for supporting the collection of road safety performance indicators (called ‘KPIs’) within the EU. 18 EU Member States are participating in this project. For each of the eight KPIs considered, a common methodology for data collection and analysis has been developed by European experts; the methodological guidelines are available at the Baseline website (baseline.vias.be). Data collection and analysis is currently being finalized; the KPIs will be available in October 2022. They will constitute the basis for monitoring road safety progress at national and EU level, will facilitate the formulation of targets at European an national level, and will support decision makers on the most appropriate measures to be taken to improve road safety. Several EU countries have already integrated the monitoring of the KPIs in their road safety strategy.

Capturing long-memory properties in road fatality rate series by an autoregressive fractionally integrated moving average model with generalized autoregressive conditional heteroscedasticity: A case study of Florida, the United States, 1975–2018

Introduction: Time series models play an important role in monitoring and understanding the serial dynamics of road crash exposures, risks, outcomes, and safety performance indicators. The time-series methods applied in previous studies on crash time series analysis assume that the serial dependency decays rapidly or even exponentially. However, this assumption is violated in most cases because of the existence of long-memory properties in the crash time series data. Ignoring the long-memory dependency could result in biased understanding of the dynamics of road traffic crashes. Method: To fill this research gap, this study proposes an autoregressive fractionally integrated moving average model with generalized autoregressive conditional heteroscedasticity (ARFIMA-GARCH) to capture and accommodate the long-memory decencies in the road fatality rate time series. To further investigate how the factors influencing the fatality risks play a role in the long-memory dependence, the effects of exogenous variables are examined in this study. The analysis is conducted based on the road crash fatality data in Florida, USA over 44 years. Results’ Conclusions: The case analysis confirmed the existence of long-memory property in the crash fatality time series data by both the joint tests of Augmented Dickey-Fuller and the Phillips–Perron, and the integer order of differencing (≤0.5) in the proposed models. The model results reveal that gasoline price and alcohol consumption per capita is positively associated with road fatality risks, whereas unemployment rate and rural/urban road mileage are negatively related to the road fatality risks. Practical Applications: The significant influential factors are also found to account for the long-memory serial correlations between road traffic fatalities to some extent.

A multidimensional and multi-period analysis of safety on roads

This paper proposes a multidimensional and multi-period analysis of safety on roads. It aggregates different road safety performance indicators observed over different periods for which multicriteria and multi-period approaches are used. The criticality of a road depends on the interaction of various factors, such as human factors, causes of accidents and their severity levels, and the characteristics/states of the roads. Therefore, there is a need for a multidimensional view of risk and its consequences concerning traffic accidents. Furthermore, using the Multiple Criteria Decision Making/Aid methods (MCDM/A) allows the performance of roads in the multiple criteria to be considered according to the decision maker's preferences. On the other hand, the temporal approach reflects the performance of roads and their accidents in different periods, enabling the information on the temporal behavior of accidents to be aggregated to the result. Given that Brazil has a vast road network, there is thus the problem of prioritizing road segments to allocate resources for traffic accident prevention and mitigation actions, especially as these resources are usually limited and scarce. For that, a case study is developed in the state of Pernambuco in Brazil. Eleven road segments are analyzed. The strategic objective of the decision-maker is to have a broader view, initially, of the criticality of these road segments in terms of safety so that strategically he can allocate resources to prevent and mitigate the risks of traffic accidents. For this, the decision-maker considered eleven criteria. These represent the different dimensions that can influence traffic accidents, such as the damage (impacts) to human beings or other consequences resulting from traffic accidents and issues related to the characteristics/state of the road and its traffic. Five periods of time were considered to incorporate the temporal influence of these dimensions (2015 to 2019). As a result, it is seen that, for a more comprehensive assessment, it is essential to consider a multidimensional view of risk and a multi-period evaluation, thus incorporating more information into the decision model and thereby making its results more assertive.

Composite performance indicators for helmet and seat-belt enforcement as imprecise data

Objectives Composite road safety performance indicators (RSPIs) are useful tools in regional road safety planning. Among the indicators and data calculated by the World Health Organization (WHO), information on the effectiveness of law enforcement on various risk factors for road casualties were provided, which can be considered as qualitative indicators. The purpose of this study is to analyze the performance indicators related to the percentage of helmet and seat-belt use versus the qualitative enforcement scores attributed by WHO. Methods This analysis was performed for 30 member states of WHO and will show how and with what degree of efficiency the qualitative output of the enforcement score acts versus the input percentage of seat-belt and helmet use. The qualitative nature of the output index has led us to depart the traditional analysis of crisp numerical indicators related to road safety performance and to consider data as imprecise or fuzzy indices. In this study we used two methods including imprecise DEA-based CIs and fuzzy DEA-based CIs, respectively. Results Results show that the clear score achieved by the Imprecise DEA-based CI model is easy to interpret and use. Whereas, in the Fuzzy DEA-based CI model, the fuzzy indicator scores obtained based on the level of several probabilities are strong in capturing the uncertainties related to human behavior. Conclusions Both RSPIs are applicable with slight differences that were in the order of countries and the ease of reading the results. We also found that each method has different strengths and that the FDEA-based CIs method is more accurate and more in line with the inputs than the IDEA-based CIs method.

Polytrauma: The European Paradigm

This review of the literature aims to describe the main advantages and disadvantages of the trauma systems in Europe. Moreover, the purpose of this article is to present the last concepts regarding the management of the polytrauma patients and the newest sets of measures to prevent car crashes in European Union. The articles published regarding the management of the polytrauma patient and trauma systems were identified using PubMed search. Optimal management of major polytrauma requires a national trauma system which should detail every level of organization from the trauma centers to the every member of the trauma team. European trauma systems varies a lot depending on the country and the specialized trauma surgery training programs are more advanced in countries with complex trauma systems. Introducing road safety performance indicators for trauma management decreased the rate of deaths by car crashes in Europe.

Car drivers' road safety performance: A benchmark across 32 countries

The road safety performance of a country and the success of policy measures can be measured and monitored in different ways. In addition to the traditional road safety indicators based on the number of fatalities or injured people in road traffic crashes, complementary road safety performance indicators can be used in relation to vehicles, infrastructure, or road users' behaviour. The last-mentioned can be based on data from roadside surveys or from questionnaire surveys. However, results of such surveys are seldom comparable across countries due to differences in aims, scope, or methodology.This paper is based on the second edition of the E-Survey of Road Users' Attitudes (ESRA), an online survey carried out in 2018, and includes data from more than 35,000 road users across 32 countries. The objective is to present the main results of the ESRA survey regarding the four most important risky driving behaviours in traffic: driving under the influence (alcohol/drugs), speeding, mobile phone use while driving, and fatigued driving. The paper explores several aspects related to these behaviours as car driver, such as the self-declared behaviours, acceptability and risk perception, support for policy measures, and opinions on traffic rules and penalties.Results show that despite the high perception of risk and low acceptability of all the risky driving behaviours analysed, there is still a high percentage of car drivers who engage in risky behaviours in traffic in all the regions analysed. Speeding and the use of a mobile phone while driving were the most frequent self-declared behaviours. On the other hand, driving under the influence of alcohol or drugs was the least declared behaviour. Most respondents support policy measures to restrict risky behaviour in traffic and believe that traffic rules are not being checked regularly enough, and should be stricter.The ESRA survey proved to be a valuable source of information to understand the causes underlying road traffic crashes. It offers a unique database and provides policy makers and researchers with valuable insights into public perception of road safety.

Analyzing the Relationship between Road Safety Pillars and the World Health Organization Member States’ Mortality Rate using Structural Equation Modeling Approach

Road deaths phenomenon suggests the development of studies that consider the complex causal relationship between the factors that influence it at the compatible level with the definition of road safety policies. This paper analyzes the influence of 48 road safety performance indicators on the mortality rate of 175 World Health Organization Member States in 2016. Structural equation models were proposed to evaluate the proposition and use of latent variables that represent five major road safety policy areas and the influence on mortality rates. The proposed model structure indicated that management has a strategic role in public policies, having an indirect influence on reducing the mortality rate through safe vehicles, user safety, and safe roads and mobility. The results indicated that policies aimed at encouraging users’ safe behavior were the ones that had the greatest influence in reducing road deaths followed by policies in safer vehicles, road safety management, safer roads and mobility, and post-crash response.

Monitoring Of Road Safety Performance Indicators – Current Situation And Trends In The Republic Of Serbia

Republic of Serbia started to monitor road safety performance indicators (RSPIs) in 2013. After comprehensive study, Road Traffic Safety Agency and University of Belgrade – Faculty of Transport and Traffic Engineering have developed national methodology for monitoring RSPIs. This methodology is harmonized with several key EU projects, such as SAFETYNET and DACOTA, that means that data are comparable at international level. From autumn 2013 till nowadays, according to developed national methodology for RSPIs monitoring, every year, twice a year Republic of Serbia collecting data regard key RSPIs. Results are usually published at different national and international conferences, through different reports, fact sheets, as well at official web site of Road Traffic Safety Agency. In this paper we presenting methodology for monitoring key RSPIs in the Republic of Serbia, as well some of the key results – current situation and trends. According to that results of monitoring RSPIs data in the Republic of Serbia, several key policy documents were adopted, i.e. National Road Safety Strategy for the Republic of Serbia for the period 2016-2020 includes data about current state, trends and intermediate and final targets for RSPIs. Also this data will be used for monitoring and assessing of success (reaching targets) of national road safety strategy and effects of applied road safety measures. In the meantime, many Serbian municipalities have started to use RSPIs data for their local road safety strategies and to plan their road safety activities, to allocate funds, etc.

The Significance of the Development of Road Safety Performance Indicators Related to Driver Fatigue

Drivers’ fatigue, as a problem of the modern era, is causing more and more attention in the world, and special attention is given to this problem by transport companies in order to protect their workers, passengers and the economic stability of the company. According to the IRTAD report out of the 38 countries, 26 countries in their reports were accounted for the percentage of traffic accidents due to fatigue, pointing out that this percentage is much higher if traffic accidents with professional drivers.In this paper are defined road safety performance indicators related to the fatigue of professional drivers and their significance is shown. The development and monitoring of road safety performance indicators related to driver fatigue provides a wide range of options: allows monitoring of road safety indicators related to the fatigue due to commercial vehicle drivers’ – detect the problem, then allows comparisons and ranking transportation companies to the level of road safety from the aspect of driver fatigue.

Use of SafeFITS mathematical modeling in a road safety management system

The results of the work of the UNECE ITC on the development of the SafeFITS tool were reviewed, the indicators proposed in the framework of this tool for assessing the effectiveness of making management decisions in order to ensure road safety were analyzed and the possibility and relevance of its application in Ukraine were considered. Keywords: road safety, road traffic incident, road traffic fatalities and injuries, road safety performance indicators (RSPI), road safety management system.

Comparison of Self-reported and Observed Road Safety Performance Indicators

The first concept of road safety performance indicators was published by European Transport Safety Council, Brussels in 2001. Hungary has long and reliable time series of safety belt wearing and child safety seat usage rates in passenger cars. These rates are based on real roadside observations and representative sample, meeting the requirements of international road accident databases. The methodology of the data collection has been further developed during the recent years, but we paid attention to the possibility of comparison with the earlier data and consistent analysis of time series. Although the roadside observations could not have been organized in each year, the trends can be seen relatively well. Our initial hypothesis was that the self-reported data always show a bit "better" picture about the driving behaviour than the observed ones, since the people are not sure that their data will be handled in an anonym way. Based on these results we can say that the ESRA results are relatively good estimations of the real safety belt wearing rates.

Risk Indicators and Road Accident Analysis for the Period 2012–2016

Road accidents are a major societal issue for every country. The purpose of this paper is to assess the number of traffic and road accidents depending on a series of variables (collision mode, road configuration, conditions of occurrence, road category, type of vehicle involved, personal factors, and length of time of the driving license) in Romania from 2012–2016. The analysis of the road accident trend identifies the causes of accidents, road safety performance indicators, and risk indicators. Having these identified data, a framework is proposed for improving the road safety system and reducing accidents. The Romanian Police, the National Institute of Statistics (NIS) in Romania, and the European Commission provided the data used for this analysis. The data obtained from these databases are analysed and evaluated according to a series of variables. This paper will outline an informative image of road accidents and establish a framework for reducing their effects in road transport. As a result of the analysis, we have seen that the combination of vehicles and personal factors influences the number of traffic and road accidents.

A fuzzy decision-support system in road safety planning

The objective of this research was to develop a decision-support system to help road safety policy makers make the right choices in road safety planning based on the efficiency of previously implemented safety measures. The measures considered for each region in the study include performance indicators about police operations, treated black spots, freeway and highway facility supplies, speed control cameras, emergency medical services and road lighting projects. To this end, an inefficiency measure is calculated, defined by the proportion of fatality rates in relation to the combined measure of road safety performance indicators, which should be minimised. The relative inefficiency for each region is modelled using the data envelopment analysis (DEA) technique, which follows a benchmarking and target-setting process. In the next step, a fuzzy decision-making system is constructed to convert the information obtained from the DEA into a rule-based system that can be used by policy makers to evaluate the expected outcomes of certain alternative investment strategies in road safety. Using the resultant fuzzy decision-support system, policy makers can analyse alternative strategies in addition to those unique targets suggested by the DEA benchmarking and target-setting process.

Relationship between road safety and mobile photo enforcement performance indicators: A case study of the city of Edmonton

ABSTRACTMobile photo enforcement (MPE) programs are commonly implemented to regulate speed and improve road safety. However, most previous research focuses mainly on validating the safety effects of MPE, with very minimal discussion on the enforcement performance indicators (EPIs). Therefore, the goal of this study is to provide a better understanding of the relationship between the three selected EPIs (number of enforced sites, average check length, and number of issued tickets) and the program's safety outcomes. In total, 8 years (2005–2012) of monthly citywide data were collected and used in a generalized linear Poisson model. The results show that as the number of enforced sites and issued tickets increased, the number of speed-related collisions decreased. Also, as the average check length decreased, a greater reduction of speed-related collisions was observed. These results indicate that collision reductions were associated with a MPE program that promoted: higher spatial coverage (i.e., more enforceable locations), more frequent checks (i.e., shorter average check length), and more issued tickets. The marginal effects of enforcing 100 sites and issuing 10,000 tickets per month were calculated to be 47 and 140 fewer speed-related collisions, respectively.

A Hierarchical Aggregation Approach for Indicators Based on Data Envelopment Analysis and Analytic Hierarchy Process

This research proposes a hierarchical aggregation approach using Data Envelopment Analysis (DEA) and Analytic Hierarchy Process (AHP) for indicators. The core logic of the proposed approach is to reflect the hierarchical structures of indicators and their relative priorities in constructing composite indicators (CIs), simultaneously. Under hierarchical structures, the indicators of similar characteristics can be grouped into sub-categories and further into categories. According to this approach, we define a domain of composite losses, i.e., a reduction in CI values, based on two sets of weights. The first set represents the weights of indicators for each Decision Making Unit (DMU) with the minimal composite loss, and the second set represents the weights of indicators bounded by AHP with the maximal composite loss. Using a parametric distance model, we explore various ranking positions for DMUs while the indicator weights obtained from a three-level DEA-based CI model shift towards the corresponding weights bounded by AHP. An illustrative example of road safety performance indicators (SPIs) for a set of European countries highlights the usefulness of the proposed approach.

Benchmarking road safety performance: Identifying a meaningful reference (best-in-class)

For road safety improvement, comparing and benchmarking performance are widely advocated as the emerging and preferred approaches. However, there is currently no universally agreed upon approach for the process of road safety benchmarking, and performing the practice successfully is by no means easy. This is especially true for the two core activities of which: (1) developing a set of road safety performance indicators (SPIs) and combining them into a composite index; and (2) identifying a meaningful reference (best-in-class), one which has already obtained outstanding road safety practices. To this end, a scientific technique that can combine the multi-dimensional safety performance indicators (SPIs) into an overall index, and subsequently can identify the ‘best-in-class’ is urgently required. In this paper, the Entropy-embedded RSR (Rank-sum ratio), an innovative, scientific and systematic methodology is investigated with the aim of conducting the above two core tasks in an integrative and concise procedure, more specifically in a ‘one-stop’ way. Using a combination of results from other methods (e.g. the SUNflower approach) and other measures (e.g. Human Development Index) as a relevant reference, a given set of European countries are robustly ranked and grouped into several classes based on the composite Road Safety Index. Within each class the ‘best-in-class’ is then identified. By benchmarking road safety performance, the results serve to promote best practice, encourage the adoption of successful road safety strategies and measures and, more importantly, inspire the kind of political leadership needed to create a road transport system that maximizes safety.

Road Safety Outcome Model among Commercial Bus

Road safety outcome is a complex issue involving high number of risk factors and indicators that contributes to road accidents and their severity related to human-vehicle–road interactions. This requires a multi-dimensional model in order to fully understand the road safety situation especially among commercial bus drivers. This study identified some of the risk factors with the objective of establishing the relationship between them through a model for assessing the road safety outcome. The model was developed using data collected from 465 commercial bus drivers in Johor, Malaysia. The estimated model yielded significant relationship between the risk factors (Drivers, Vehicle and Road) and road safety outcomes. The statistical analysis of these risk factors shows that the model has significant fit to the data. The results therefore, yielded a road safety output guideline formula suitable for road safety performance indicator for safety practitioners and stakeholders. The study pointed out three critical risk factors (e.g. Drivers, Vehicle and Road) with their various levels of risk contributions as influence on road safety among commercial bus. Six recommendations based on this finding were made in an attempt to reduce commercial bus accidents.

A New Weighting Approach Based on Rough Set Theory and Granular Computing for Road Safety Indicator Analysis

The steadily increasing volume of road traffic has resulted in many safety problems. Road safety performance indicators may contribute to better understand current safety conditions and monitor the effect of policy interventions. A composite road safety performance indicator is desired to reduce the dimensions of selected risk factors. The essential step for constructing such a composite indicator is to assign a suitable weight to each indicator. However, no agreement on weighting and aggregation in the composite indicator literature has been reached so far. Granular computing is an emerging computing paradigm of information processing that makes use of granules in problem solving. Rough set theory is considered as one of the leading special cases of granular computing approaches. In this article, a new weighting approach based on rough set theory and granular computing is introduced for road safety indicator analysis. The proposed method is applied to a real case study of 21 European countries of which only the class information (not the real values) on all indicators is used to calculate the weights. Experimental evaluation shows that it is an efficient approach to combine individual road safety performance indicators into a composite one.

Development of Road Safety Performance Indicators for the European Countries

Purpose Safety performance indicators (SPIs) are measures reflecting the operational conditions of the road traffic system that influence the system’s safety performance. Within the EU funded SafetyNet project, SPIs were developed for seven road safety-related areas: alcohol and drugs; speed; protective systems; daytime running lights; vehicles (passive safety); roads and trauma management. The purpose was to develop meaningful SPIs that, given the available data, could be applied in Europe. Method A common procedure for the development of SPIs in each area was applied, starting with a definition of unsafe operational conditions of the traffic system and continuing with a conversion of this information into a measurable variable. Based on a literature survey, a relationship between the problem area and road safety was ascertained. Characteristics of the system's performance were analyzed aiming to select those which can be quantified. Examples of SPIs in use by different bodies and research studies were examined. Using the SPIs' concept suggested in each area, the data were collected in cooperation with national experts from 29 European countries, aiming to verify the applicability of the SPIs developed and to conduct country comparisons. Results The rationale behind the SPIs in each safety area was detailed, and the application of the developed SPIs to the European countries' comparisons was shown. For some areas, i.e. protective systems' use, sufficiently good data appeared to be available in Europe, while for other areas, i.e. speed and alcohol, data quantity and quality varied strongly. For passive vehicle safety, trauma management and roads, completely new approaches were developed for the SPIs' estimation. Conclusion Given the data are collected on a common basis, SPIs can become valuable tools in future knowledge- and data-driven policy-making in Europe.