Observing the observation of (vulnerable) road user behavior and safety: a scoping review into current practices

The main strength of behavioral observation studies is that naturalistic data is collected without the road users’ knowledge that they are being observed for research purposes. It enables the observation and identification of behavioral and situational processes that contribute to unsafe traffic events, while minimizing the influence of behavioral adaptation effects. Such studies have already been reported since the 1930s, but an overview of the current extent, range and nature of this type of research is lacking. Therefore, a scoping review evaluating all peer-reviewed journal articles published in English was conducted in order to a) investigate their purposes, b) identify common topics and behavioral indicators, c) examine study characteristics and d) prevent duplicate research efforts. In total, 600 journal articles found in three major databases were included in this review. The majority of the studies collected data of car drivers (81%), while pedestrians, cyclists and motorcyclists were found in 23%, 9% and 5% of the studies respectively. The main goal of behavioral observation is to observe what happens at selected locations (51%), followed by the evaluation of a specific safety improving treatment (38%) and the development of behavioral models (10%). Most common research topics were crossing, yielding and red-light running behavior for pedestrians and cyclists and yielding and speeding for car drivers. Speed and red-light-running were two of the indicators that have been measured most. With regard to study characteristics, four main research designs were identified: single observation, before-after studies, with-without and crosssectional setups. Some difficulties in determining truck-involvement, characteristics of the observation period and sample sizes were encountered. Finally, because the use of video cameras to capture behavioral observations has become the major data collection technique in recent years, the current efforts to improve and further develop automated video-analysis software tools can prove to be a valuable asset in behavioral observation studies and traffic safety evaluation in general.This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 635895 (InDeV- In-Depth-understanding of accident causation for Vulnerable road users). This publication reflects only the authors’ views. The European Commission is not responsible for any use that may be made of the information it contains.behavioral observation; scoping review; traffic safety; vulnerable road User

Exploration of a method to validate surrogate safety measures with a focus on vulnerable road users

Abstract Background. Traditional crash-based analysis of road safety at individual sites has its shortcomings due to low numbers and the random nature of crashes at individual sites and the related statistical issues, as well as the under-reporting of crashes and lack of information on contributing factors and the process preceding crashes. To get around the problem, road safety analysis based on surrogate measures of safety, i.e. not based on crashes, can be used. However, the question whether surrogate measures are valid indicators for safety remains unanswered and only a few attempts have actually been made to carry out proper large-scale validation studies. Aim. This work presents a methodological approach for a large-scale validation study of surrogate safety indicators focusing on vulnerable road users. With only one site analyzed so far, it presents the exploration of the data and of the performance of the technical tools used in the study. Method. Video-filming and consequent video analysis are used to measure the surrogate safety indicators. In the first step, the video is “condensed” using a watchdog software RUBA that selects situations with an encounter of a cyclist or pedestrian and a motor vehicle. At a later stage, the trajectories of the individual road users are produced using a semi-automated tool T-Analyst and several surrogate safety indicators are tested to set a severity score for an encounter. The performance of the surrogate indicators will be compared to the expected number of accidents at each site and availability of the data for developing a safety performance function (SPF) that is country-, manoeuvreand type of VRU-specific are explored. Results & Conclusion. From methodological perspective, limited accident data available seriously complicates building a reliable SPF (“ground truth”) against which the surrogate safety measures could be validated; some other, “indirect” methods of validation might be required. We present also the performance of the software tools and applicability of the various surrogate safety indicators that were tested

Review of current study methods for VRU safety. Part 1 – Main report

The report presents the results of a review of the study methods related to vulnerable road user safety that are used today and aims to link accident causation factors to VRU accident risk. The review covered the following categories of study methods: epidemiological studies based on accident and injury data; in-depth accident investigations; naturalistic driving studies; behavioural observations; traffic conflict studies; and self-reported accident studies. The review consisted of two parts: a systematic literature review and a questionnaire survey. A scoping review of the available scientific literature was conducted that covered four types of safety-related studies: naturalistic driving studies, behavioural observations, traffic conflict studies and self-reported accidents. In total, over one thousand publications were included in the scoping reviews. Full reports on the results of the four reviews are published as separate parts of this report. Questionnaires were sent out to all InDeV partners to obtain information and a critical appraisal of the currently used study methods related to VRU safety. The survey results show that epidemiological studies based on accident and injury records form the basis of traffic safety assessment in every partner country. General accident reports help identify the time trends of accident occurrence and to compare the safety situation among countries and cities. Benchmarking between countries can help monitor progress towards the targets for traffic safety improvement and to assess the relative importance of problems. While the exact causes of accidents cannot be determined, the contributing factors can often be deduced. Identification of dangerous locations is performed using black spot analysis and network safety analysis. Both are important and useful for VRU safety assessment – black spots identify dangerous intersections and road crossings and network analysis identifies dangerous road links. The exposure measures used should be appropriate for VRUs and should include pedestrian and bicycle volumes in addition to motorised traffic volumes. The European CARE accident database was set up with a comprehensive structure and scope of information as defined in the CADaS glossary. The advantage of using CARE for safety research is that it is a disaggregate database, i.e. detailed cross-classification analyses can be made. However, not all countries provide all data according to the guidelines. The possibilities of safety analysis would be greatly improved if the guidelines were followed by all countries.The literature review and survey on accident data quality conducted among InDeV partners show that despite efforts to harmonise the definitions of injury road accidents and their severity at the European level, differences exist both in the definitions and their interpretation. Even in the case of the fundamental definition of “road accident/injury accident”, the definitions used by some countries differ slightly from the CARE database standard. Data on fatalities are quite comparable between the InDeV partner countries: the 30-day road accident fatality definition is used. CARE definitions of injury severity are applied in only 3 out of 7 countries. There are also considerable differences among countries in terms of accident data collection and data verification procedures, which results in varying levels of underreporting of the different accident categories. In all InDeV partner countries, accident data are collected on a paper form and transferred to a computer database. The information on injury severity is gathered from ambulances, hospitals or the road users involved in the accidents. This information is verified based on hospital information after a period ranging between 30 days and one year. In Sweden, data verification is performed automatically via the STRADA database, which links the police database with hospital registries. In almost all InDeV partner countries, data quality control is carried out after the data is transferred to a computer database. Cross-checking for consistency of information is used in some countries. The in-depth investigation study is a good tool to examine accident scenarios and to find accident/injury contributing factors. However, valid knowledge can be obtained only if the number of cases, the period of time and the number of variables are sufficient. The comparison of different in-depth databases is difficult due to the application of different investigation criteria. The drawbacks include the study’s retrospective view (compared to video-documented crashes) and the introduction of uncertainties in the process of data collection and encoding due to interpretation. In general, in-depth investigations are time- and cost-consuming, but highly effective in terms of the knowledge that can be gained from the investigation of individual accidents.A review of naturalistic studies shows that this method can provide important insights into the understanding of the causation factors of accidents with VRUs. These studies can also be used to identify the locations where vulnerable road users are involved in accidents. So far, naturalistic data from VRUs have mostly been collected via equipped motorcycles or bicycles. Accidents and critical situations were detected based on kinematic triggers such as acceleration, rotation, etc. only in few cases. The potential for such detection was shown through studies of falls among the elderly. In order to examine accident causation it is necessary to collect additional information from road users, e.g. via a questionnaire that is sent to them after the accident. Another limitation of naturalistic studies is that data is typically collected from only one of the road users involved in the accident.Behavioural observation studies are an important tool to understand the causes of accidents that involve VRUs because such studies provide insight into the situational and behavioural processes that lead to an accident. The survey that was carried out among partner countries provides an overview of the behavioural observation studies conducted there and identifies the topics that were addressed. A review of about 600 publications on road user behavioural observation studies shows that these are mainly used to monitor traffic events and to evaluate safety improvement measures. Behavioural observations seem very useful to examine how road users interact with each other or navigate through a crossing. Most studies involving VRUs were found to take place at some kind of crossing. Many studies were not adequately documented with respect to the observation periods and sample size. Certain topics were found not to have been the subject of much research, for example powered two-wheelers. The observation and analysis of traffic conflicts as surrogates for accidents has two main advantages: conflicts occur more frequently than accidents and observing them allows better understanding of the processes that may lead to accidents. The basic theory behind the use of traffic conflicts for safety analysis is the assumption of continuity in the severity of all events that take place in a traffic environment. There is a relationship between the severity and frequency of events, i.e. injury accidents are rare, while normal interactions are frequent. As severe traffic conflicts are close to real accidents in terms of the process of their development, observations of these conflicts can be used to understand the mechanism of accident development. The scoping review of literature shows an increase in the use of traffic conflict studies, in particular those that use video analysis tools. The review also shows that there is a considerable number of validation studies on the relationship between conflicts and accidents, although most of these are quite old. Recently, new indicators with high potential have been suggested and there is a clear need for new validation studies that use video analysis tools. Emerging technologies open up new possibilities for the wider use of site-based traffic conflict studies. Nevertheless, a combination of conflict studies with other types of behavioural observations and accident analyses provides better insight into road safety problems.The self-reported accident study method is highly relevant as it allows to gain knowledge on accident causation as well as the events that led to the accident. This method allows to obtain information on accidents that are not reported to the police, thus making it possible to estimate the level of underreporting. A systematic literature review shows that the practice for collecting self-reported accidents varies and most studies focus on car accidents. Self-reported accidents are used to evaluate safety measures, estimate the total number of accidents and to identify accident causation factors. Self-reported accident data are typically collected via online or paper questionnaires where respondents are asked to recall their accidents from a period ranging from one month to 5 years. A survey among InDeV partners showed that the use of the self-reporting method is not very common in their countries. While the method has relevance and seems a promising way of gaining knowledge on accident causation factors, the level of underreporting and socioeconomic factors, it is still quite untested. Careful consideration of methodological challenges and issues is required before conclusions on underreporting can be drawn based on self-reports alone.Based on the review of road safety analysis methods, several general recommendations for improving VRU safety assessment are put forward. The standard definition of injury accidents adopted by the EC (CARE database) covers virtually all traffic accidents involving VRUs with the exception of single pedestrian accidents (falls). It is recommendable to include this additional category in VRU safety assessment studies as well as in economic calculations of total accident costs.There is no clear definition of what constitutes an “injury” suffered by the victims of a road accident. Since the occurrence of an “injury” is one of the preconditions for the classification of a collision as an accident, there is a grey area between “slight injury” and “property damage only” accidents. The term “injury” should be defined for the sake of consistency. The determination of injury severity in road accident victims poses considerable challenges. The EC’s current efforts have not yet produced a reliable system of reporting the numbers of the severely injured in different countries. The proposed criterion of serious injury based on MAIS3+ levels is difficult to implement and has its disadvantages. There is a need to harmonise not just the definitions of injury and its severity but also the procedures for accident data collection and verification among the EU countries. A review of the current procedures should be conducted and common guidelines worked out. However, this type of study is beyond the scope of the InDeV project and should be undertaken by the EC. One way of improving police accident data quality is to verify these data using hospital/medical records. When comparing police-reported numbers of traffic accident victims with hospital data, one should bear in mind the differences in definitions and the scope of available information. Guidelines for the integration of police and medical data based on best practices (e.g. the STRADA system in Sweden) would be very useful. Overall, there is a lack of appropriate exposure measures for the calculation of safety indicators for VRUs. It is a serious problem; the local population can be used for the calculation and comparison of fatality rates in cities and regions. When analysing and identifying black spots at intersections and road crossings, pedestrian and bicycle volumes should be used in addition to motorised traffic volumes. In an effort to obtain improved results, an integrated approach to VRU safety assessment is proposed. The study methods discussed in this report differ in terms of the approach, data collection method and the specific aims. However, the various methods often complement each other in terms of the results that can be achieved with a specific objective in mind. This complementarity is presented in the form of a matrix, where seven specific aims are listed against six assessment methods. The matrix should help to decide which combination of methods to use in order to achieve a specific objective. The use of a mix of different methods can often produce more accurate, more comprehensive and faster assessments