| 31. |
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| 32. |
- Laureshyn, Aliaksei
(författare)
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Application of automated video analysis to road user behaviour
- 2010
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The successful planning, design and management of a traffic system is impossible without knowledge of how the traffic environment affects the behaviour of road users and how the behaviour is related to the main qualities of the traffic system (e.g. safety, efficiency). Automated video analysis is a promising tool for traffic behaviour research in that it enables collection of micro-level behaviour data for large populations of road users and provides a detailed description of their motion. This thesis describes the tests done with an automated video analysis system developed at Lund University. The system was used in two large scale studies with the main task of detecting the presence of road users of a particular type. Accuracy of position and speed estimates were tested in a study specially designed for that purpose. The thesis also elaborates on the problem of relating the behaviour of road users to safety and proposes organising all the elementary events in traffic (defined here as encounters between two road users) into a severity hierarchy. The process of an encounter is described with a set of continuous safety indicators that can handle the various approach angles and transfer between being and not being on a collision course. When an objective measure for an encounter severity is found, the severity hierarchies may be used not only for describing safety but also for studying the balance between safety and other qualities valued by road users.
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| 33. |
- Laureshyn, Aliaksei, et al.
(författare)
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Automated video analysis as a tool for analysing road user behaviour
- 2006
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Ingår i: Proceedings of ITS World Congress, London, 8-12 October 2006.
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Konferensbidrag (refereegranskat)abstract
- At Lund University an automated video analysis system is being developed that can be applied for studying the behaviour of road users in complex traffic environments. It is stressed that system must be capable of handling all the categories of road users, i.e. vehicles, pedestrians and cyclists. Common problems like detection and tracking of moving objects, occlusion by foreground objects, ground-plane co-ordinates estimation, smoothing of the scattered data and estimation of speed and acceleration profiles are discussed and some solution proposed.
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| 34. |
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| 35. |
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| 36. |
- Laureshyn, Aliaksei, et al.
(författare)
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Evaluation of traffic safety, based on micro-level behavioural data: theoretical framework and first implementation.
- 2010
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Ingår i: Accident Analysis and Prevention. - : Elsevier BV. - 1879-2057 .- 0001-4575. ; 42:6, s. 1637-1646
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Tidskriftsartikel (refereegranskat)abstract
- A traffic encounter between individual road users is a process of continuous interplay over time and space and may be seen as an elementary event with the potential to develop into an accident. This paper proposes a framework for organising all traffic encounters into a severity hierarchy based on some operational severity measure. A severity hierarchy provides a description of the safety situation and trade-off between safety and efficiency in the traffic system. As a first approach to study the encounter process, a set of indicators is proposed to describe an encounter. These indicators allow for a continuous description even if the relationship between the road users changes during the process (e.g., when they are on a collision course or leave it). Automated video analysis is suggested as a tool that will allow data collection for validation of the proposed theories.
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| 37. |
- 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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| 38. |
- Laureshyn, Aliaksei, et al.
(författare)
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From Speed Profile Data to Analysis of Behaviour
- 2009
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Ingår i: IATSS Research. - 0386-1112. ; 33:2, s. 88-98
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Tidskriftsartikel (refereegranskat)abstract
- Classification of speed profiles is necessary to allow interpretation of automatic speed measurements in terms of road user behaviour. Aggregation without considering variation in individual profile shapes easily leads to aggregation bias, while classification based on exogenous criteria runs the risk of loosing important information on behavioural (co-) variation. In this paper we test how three pattern recognition techniques (cluster analysis, supervised learning and dimension reduction) can be applied to automatically classify the shapes of speed profiles of individual vehicles into interpretable types, with a minimum of a priori assumptions. The data for the tests is obtained from an automated video analysis system and the results of automated classification are compared to the classification by a human observer done from the video. Normalisation of the speed profiles to a constant number of data points with the same spatial reference allows them to be treated as multidimensional vectors. The k-means clustering algorithm groups the vectors (profiles) based on their proximity in multidimensional space. The results are satisfactory, but still the least successful among the tested techniques. Supervised learning (nearest neighbour algorithm tested) uses a training dataset produced beforehand to assign a profile to a specific group. Manual selection of the profiles for the training dataset allows better control of the output results and the classification results are the most successful in the tests. Dimension reduction techniques decrease the amount of data representing each profile by extracting the most typical “features”, which allows for better data visualisation and simplifies the classification procedures afterwards. The singular value decomposition (SVD) used in the test performs quite satisfactorily. The general conclusion is that pattern recognition techniques perform well in automated classification of speed profiles compared to classification by a human observer. However, there are no given rules on which technique will perform best.
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| 39. |
- Laureshyn, Aliaksei, et al.
(författare)
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In search of the severity dimension of traffic events: Extended Delta-V as a traffic conflict indicator
- 2017
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Ingår i: Accident Analysis & Prevention. - : Elsevier BV. - 1879-2057 .- 0001-4575. ; 98, s. 46-56
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Tidskriftsartikel (refereegranskat)abstract
- Most existing traffic conflict indicators do not sufficiently take into account the severity of the injuries resulting from a collision had it occurred. Thus far, most of the indicators that have been developed express the severity of a traffic encounter as their proximity to a collision in terms of time or space.This paper presents the theoretical framework and the first implementation of Extended Delta-V as a measure of traffic conflict severity in site-based observations. It is derived from the concept of Delta-V as it is applied in crash reconstructions, which refers to the change of velocity experienced by a road user during a crash. The concept of Delta-V is recognised as an important predictor of crash outcome severity.The paper explains how the measure is operationalised within the context of traffic conflict observations. The Extended Delta-V traffic conflict measure integrates the proximity to a crash as well as the outcome severity in the event a crash would have taken place, which are both important dimensions in defining the severity of a traffic event. The results from a case study are presented in which a number of traffic conflict indicators are calculated for interactions between left turning vehicles and vehicles driving straight through a signalised intersection. The results suggest that the Extended Delta-V indicator seems to perform well at selecting the most severe traffic events. The paper discusses how the indicator overcomes a number of limitations of traditional measures of conflict severity. While this is a promising first step towards operationalising an improved measure of traffic conflict severity, additional research is needed to further develop and validate the indicator.
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| 40. |
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