"I did not see that coming": A latent variable structural equation model for understanding the effect of road predictability on crashes along horizontal curves.

Driver anticipation plays a crucial role in crashes along horizontal curves. Anticipation is related to road predictability and can be influenced by roadway geometric design. Therefore, it is essential to understand which geometric design elements can influence anticipation and cause the road to be (un)predictable.

The usefulness of artificial intelligence for safety assessment of different transport modes.

Recent research in transport safety focuses on the processing of large amounts of available data by means of intelligent systems, in order to decrease the number of accidents for transportation users. Several Machine Learning (ML) and Artificial Intelligence (AI) applications have been developed to address safety problems and improve efficiency of transportation systems. However exchange of knowledge between transport modes has been limited.

Road-safety-II: Opportunities and barriers for an enhanced road safety vision.

Road safety research is largely focused on prediction and prevention of technical, human or organisational failures that may result in critical conflicts or crashes. Indicators of traffic risk aim to capture the passage to unsafe states. However, research in other industries has shown that it is meaningful to analyse safety along the whole spectrum of behaviours.

Towards common ethical and safe 'behaviour' standards for automated vehicles.

Automated vehicles (AVs) aim to dramatically improve traffic safety by reducing or eliminating human error, which remains the leading cause of road crashes. However, commonly accepted standards for the 'safe driving behaviour of machines' are pending and urgently needed. Unless a common understanding of safety as a design value is achieved, different manufacturers' driving styles may emerge, resulting in inconsistent, unpredictable and potentially unsafe 'behaviour' of AVs in certain situations.

Prediction of rear-end conflict frequency using multiple-location traffic parameters.

Traffic conflicts are heavily correlated with traffic collisions and may provide insightful information on the failure mechanism and factors that contribute more towards a collision. Although proactive traffic management systems have been supported heavily in the research community, and autonomous vehicles (AVs) are soon to become a reality, analyses are concentrated on very specific environments using aggregated data. This study aims at investigating -for the first time- rear-end conflict frequency in an urban network level using vehicle-to-vehicle interactions and at correlating frequency with the corresponding network traffic state.

Transport safety and human factors in the era of automation: What can transport modes learn from each other?

One of the main aims of introducing automation in transport is to improve safety by reducing or eliminating human errors; it is often argued however that this may induce new types of errors. There is different level of maturity with automation in different transport modes (road, aviation, maritime and rail), however no systematic research has been conducted on the lessons learned in different sectors, so that they can be exploited for the design of safer automated systems. The aim of this paper is to review the impact of key human factors on the safety of automated transport systems, with focus on relevant experiences from different transport sectors.

Predictors of accidents in people with mild cognitive impairment, mild dementia due to Alzheimer's disease and healthy controls in simulated driving.

Objectives: To examine the driving variables that predict accident probability in mild dementia due to Alzheimer's disease (AD), mild cognitive impairment (MCI) and healthy older control drivers in simulated driving. To compare the three groups in mean performance and in frequency of scores exceeding 1.5 SD from the mean.

A systematic cost-benefit analysis of 29 road safety measures.

Economic evaluations of road safety measures are only rarely published in the scholarly literature. We collected and (re-)analyzed evidence in order to conduct cost-benefit analyses (CBAs) for 29 road safety measures. The information on crash costs was based on data from a survey in European countries.

Review and ranking of crash risk factors related to the road infrastructure.

The objective of this paper is the review and comparative assessment of infrastructure related crash risk factors, with the explicit purpose of ranking them based on how detrimental they are towards road safety (i.e. crash risk, frequency and severity).

The European road safety decision support system on risks and measures.

The European Road Safety Decision Support System (roadsafety-dss.eu) is an innovative system providing the available evidence on a broad range of road risks and possible countermeasures. This paper describes the scientific basis of the DSS.

How many crashes are caused by driver interaction with passengers? A meta-analysis approach.

Introduction: Conversation and other interactions with passengers while driving induce a level of distraction to the person driving.

Method: This paper conducts a qualitative literature review on the effect of passenger interaction on road safety and then extends it by using meta-analysis techniques.

Results: The literature review indicates that the distraction due to passengers is a very frequent risk factor, with detrimental effects to various driving behavior and safety measures (e.

Meta-analysis of the effect of road work zones on crash occurrence.

There is strong evidence that work zones pose increased risk of crashes and injuries. The two most common risk factors associated with increased crash frequencies are work zone duration and length. However, relevant research on the topic is relatively limited.

Mild Cognitive Impairment and driving: Does in-vehicle distraction affect driving performance?

Objectives: In-vehicle distraction is considered to be an important cause of road accidents. Drivers with Mild Cognitive Impairment (MCI), because of their attenuated cognitive resources, may be vulnerable to the effects of distraction; however, previous relevant research is lacking. The main objective of the current study was to explore the effect of in-vehicle distraction on the driving performance of MCI patients, by assessing their reaction time at unexpected incidents and accident probability.

Towards an integrated approach of pedestrian behaviour and exposure.

In this paper, an integrated methodology for the analysis of pedestrian behaviour and exposure is proposed, allowing to identify and quantify the effect of pedestrian behaviour, road and traffic characteristics on pedestrian risk exposure, for each pedestrian and for populations of pedestrians. The paper builds on existing research on pedestrian exposure, namely the Routledge microscopic indicator, proposes adjustments to take into account road, traffic and human factors and extends the use of this indicator on area-wide level. Moreover, this paper uses integrated choice and latent variables (ICLV) models of pedestrian behaviour, taking into account road, traffic and human factors.

Relating traffic fatalities to GDP in Europe on the long term.

Modeling road safety development can provide important insight into policies for the reduction of traffic fatalities. In order to achieve this goal, both the quantifiable impact of specific parameters, as well as the underlying trends that cannot always be measured or observed, need to be considered. One of the key relationships in road safety links fatalities with risk and exposure, where exposure reflects the amount of travel, which in turn translates to how much travelers are exposed to risk.

Good practices on cost - effective road infrastructure safety investments.

The paper presents the findings of a research project aiming to quantify and subsequently classify several infrastructure-related road safety measures, based on the international experience attained through extensive and selected literature review and additionally on a full consultation process including questionnaire surveys addressed to experts and relevant workshops. Initially, a review of selected research reports was carried out and an exhaustive list of road safety infrastructure investments covering all types of infrastructure was compiled. Individual investments were classified according to the infrastructure investment area and the type of investment and were thereafter analysed on the basis of key safety components.

Latent risk and trend models for the evolution of annual fatality numbers in 30 European countries.

In this paper a unified methodology is presented for the modelling of the evolution of road safety in 30 European countries. For each country, annual data of the best available exposure indicator and of the number of fatalities were simultaneously analysed with the bivariate latent risk time series model. This model is based on the assumption that the amount of exposure and the number of fatalities are intrinsically related.

Road safety forecasts in five European countries using structural time series models.

Objective: Modeling road safety development is a complex task and needs to consider both the quantifiable impact of specific parameters as well as the underlying trends that cannot always be measured or observed. The objective of this research is to apply structural time series models for obtaining reliable medium- to long-term forecasts of road traffic fatality risk using data from 5 countries with different characteristics from all over Europe (Cyprus, Greece, Hungary, Norway, and Switzerland).

Methods: Two structural time series models are considered: (1) the local linear trend model and the (2) latent risk time series model.

Motorcycle riding under the influence of alcohol: results from the SARTRE-4 survey.

Riding a motorcycle under the influence of alcohol is a dangerous activity, especially considering the high vulnerability of motorcyclists. The present research investigates the factors that affect the declared frequency of drink-riding among motorcyclists in Europe and explores regional differences. Data were collected from the SARTRE-4 (Social Attitudes to Road Traffic Risk in Europe) survey, which was conducted in 19 countries.

Is road safety management linked to road safety performance?

This research aims to explore the relationship between road safety management and road safety performance at country level. For that purpose, an appropriate theoretical framework is selected, namely the 'SUNflower' pyramid, which describes road safety management systems in terms of a five-level hierarchy: (i) structure and culture, (ii) programmes and measures, (iii) 'intermediate' outcomes'--safety performance indicators (SPIs), (iv) final outcomes--fatalities and injuries, and (v) social costs. For each layer of the pyramid, a composite indicator is implemented, on the basis of data for 30 European countries.

Multilevel analysis in road safety research.

Hierarchical structures in road safety data are receiving increasing attention in the literature and multilevel (ML) models are proposed for appropriately handling the resulting dependences among the observations. However, so far no empirical synthesis exists of the actual added value of ML modelling techniques as compared to other modelling approaches. This paper summarizes the statistical and conceptual background and motivations for multilevel analyses in road safety research.

Exposure data and risk indicators for safety performance assessment in Europe.

The objective of this paper is the analysis of the state-of-the-art in risk indicators and exposure data for safety performance assessment in Europe, in terms of data availability, collection methodologies and use. More specifically, the concepts of exposure and risk are explored, as well as the theoretical properties of various exposure measures used in road safety research (e.g.

Road safety performance indicators for the interurban road network.

Various road safety performance indicators (SPIs) have been proposed for different road safety research areas, mainly as regards driver behaviour (e.g. seat belt use, alcohol, drugs, etc.

On statistical inference in time series analysis of the evolution of road safety.

Data collected for building a road safety observatory usually include observations made sequentially through time. Examples of such data, called time series data, include annual (or monthly) number of road traffic accidents, traffic fatalities or vehicle kilometers driven in a country, as well as the corresponding values of safety performance indicators (e.g.

A statistical analysis of the impact of advertising signs on road safety.

This research aims to investigate the impact of advertising signs on road safety. An exhaustive review of international literature was carried out on the effect of advertising signs on driver behaviour and safety. Moreover, a before-and-after statistical analysis with control groups was applied on several road sites with different characteristics in the Athens metropolitan area, in Greece, in order to investigate the correlation between the placement or removal of advertising signs and the related occurrence of road accidents.