| 1. |
- Kamaluddin, Noor Azreena, et al.
(författare)
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Modelling of motorcyclists' risky behaviour at an urban T-junction using generalised linear model : An exploratory study
- 2023
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Ingår i: IATSS Research. - : Elsevier BV. - 0386-1112. ; 47:1, s. 94-104
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Tidskriftsartikel (refereegranskat)abstract
- Motorcyclists represent the greatest share of recorded traffic crashes and fatalities in Malaysia. The association between motorcyclists' behaviour and traffic conflict occurrence was assessed at a typical stop-regulated T-Junction in an urban area of Kuala Lumpur, Malaysia. Traffic activities were filmed over four months and the behaviour of motorcyclists entering the main road from the minor road was observed from recorded video sequences. Situations ending in a traffic conflict were compared to similar interactive situations not ending with a conflict. In total, 447 sets of interactions of motorcyclists and other motorists at the T-Junction were analysed where 242 interactions ended in conflicts (three of them ended with traffic crashes). The generalised linear model with a binomial response and link logit was adopted to assess the association of motorcyclists' behavioural variables with the probability of conflict occurrence. The significant behavioural variables were classified into categories according to the statistical variation of the value they can assume in the dataset. The motorcyclist's entering angle was the most significant contributory factor in the probability of traffic conflict. The findings can be helpful in deciding on road safety countermeasures. The results could feed into the decisions of policymakers to structure the education and licensing process.
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| 2. |
- Laureshyn, Aliaksei, et al.
(författare)
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Exploration of a method to validate surrogate safety measures with a focus on vulnerable road users
- 2017
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Ingår i: Proceedings of the Road Safety & Simulation International Conference, 17-19 October 2017.
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 3. |
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| 4. |
- Madsen, Tanja, et al.
(författare)
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Comparison of two simulation methods for testing of algorithms to detect cyclist and pedestrian accidents in naturalistic data
- 2017
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Naturalistic studies can potentially be used to detect accidents of vulnerable road users and thus overcome the large degree of under-reporting in the official accident records. In this study, simulated cycling and walking accidents were performed by a stuntman and with a crash test dummy to test how they differ from each other and the potential implications of using simulated accidents as an alternative to real accidents. The study consisted of simulations of common accident types for cyclists and pedestrians, such as tripping over a curb or falling of the bike after hitting an obstacle. Motion data in terms of acceleration and rotation as well as the state of the screen (turned on/off) was collected via an Android smartphone to use as indicators for the motion patterns during accidents. The results show that dummy data have a distinct peak at the moment of the fall as a result of not being able to break the fall. As opposed to this, the stuntman arranges himself in a way to reduce the impact when hitting the ground. In real accidents, motion patterns will probably lie in-between these two types.
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| 5. |
- Olszewski, Piotr, et al.
(författare)
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Review of current study methods for VRU safety. Part 1 – Main report
- 2016
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- 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 econom
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| 6. |
- Varhelyi, Andras, et al.
(författare)
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Surrogate safety measures and traffic conflict observations.
- 2018. - first
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Ingår i: How to analyse accident causation? : A handbook with focus on vulnerable road users - A handbook with focus on vulnerable road users. - 9789089130648 ; , s. 95-128
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Bokkapitel (refereegranskat)abstract
- The chapter primarily focuses on observing traffic conflicts (also known as near-accidents) as a site-based road safety analysis technique. Traffic conflicts are a type of surrogate safety measure. The term surrogate indicates that non-accident-based indicators are used to assess VRU safety instead ofthe more traditional approach focusing on accidents (see chapter 2). The theory underpinning surrogate safety measures is briefly described, followed by a discussion on the characteristics of the traffic conflict technique. Next, guidelines for conducting traffic conflict observations using trained human observers or video cameras are presented. Chapter 4 concludes with examples of the use of the traffic conflict technique in road safety studies focusing on VRUs.
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| 7. |
- Yastremska-Kravchenko, Oksana, et al.
(författare)
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What constitutes traffic event severity in terms of human danger perception?
- 2022
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Ingår i: Transportation Research Part F: Traffic Psychology and Behaviour. - : Elsevier BV. - 1369-8478. ; 90, s. 22-34
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Tidskriftsartikel (refereegranskat)abstract
- This study focuses on the severity gradation of non-collision events. Earlier theoretical work has suggested that a proper severity measure for an event should reflect the risk of personal injury, which is often split into two components, including the risk of a collision and the potential consequences had the collision taken place. While a great number of severity measures have been suggested, most of them fail to address both components, thus resulting in counter-intuitive event gradations and inconclusive outcomes in validation studies. Conversely, it has been shown that human observers often show very good agreement when given a task to rank traffic situations by their severity or level of danger. The aim of this study is to investigate in depth how human judgements of the severity of traffic situations can be expressed by means of objective safety indicators. In this study, a set of video-recorded traffic situations, in which a cyclist passes straight through an intersection while a left or right-turning motor vehicle crosses the cyclist's path, were analysed. Binary logistic regression was used to develop models assessing the most important traffic severity indicators associated with human feelings of danger. The results showed that the initial conditions of a traffic event, defined as a start of an evasive action, contain the most important information for explaining its severity. Moreover, variables related to both proximity and collision consequences are important and should be integrated into severity measures.
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