Andreas Hula , Apostolos Ziakopoulos , Ángel Losada , Andrea Schaub , Peter Saleh , George Yannis
{"title":"基于轨迹的交叉口冲突局部特征判定指标:微空间分析","authors":"Andreas Hula , Apostolos Ziakopoulos , Ángel Losada , Andrea Schaub , Peter Saleh , George Yannis","doi":"10.1016/j.aap.2025.108155","DOIUrl":null,"url":null,"abstract":"<div><div>Real world behaviour data is the most reliable reference to assess road safety in a specific road infrastructure context. However, its collection and implementation for road safety research in a rapid and portable manner is still challenging, facing data protection issues and the complexities to set up constant tracking mechanisms with their own power supply. To tackle these limitations, the Mobility Observation Box (MOB) provides a flexible data collection, to be used in subsequent video analysis. Object detection and tracking allow for the derivation of movement trajectories, which in turn allow to derive quantitative indicators of road safety relevant behaviour, namely well-established Surrogate Safety Measures (SSMs), such as Post-Encroachment-Time (PET), Time-to-Closest-Approach (TCA) and Time-to-Collision-(TTC) alongside a number of indicators like maximum speed of two interaction partners, the angle they approach each other in and the minimum distance they had at one point in their interaction. To facilitate potential MOB uses, this study leverages over 51 h of naturalistic video data at a busy Vienna intersection to advance road safety research by (i) employing random parameters binary modelling of the likelihood of critical conflict occurrence and (ii) Gaussian generalized additive spatial modelling to identify key factors influencing the absolute values of conflict angles on critical conflicts only. Within the examined intersection, specific speed and acceleration effects were determined, together with the respective heterogeneity-in-means, as well as significant categorical effects of different road user types. All road user types were ultimately less likely to be involved in safety–critical conflicts compared to cars in both leading (firstly detected) and following (secondly detected) roles, with the exception of cyclists in the leading role. Within the micro-spatial analysis, the kinematic parameters of the second road user only (speed, max acceleration and max deceleration), the duration of the interaction as well as intersection-specific local effects related to the position of the leading road user were all found to influence the transformed absolute value of the angles of critical conflicts.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"220 ","pages":"Article 108155"},"PeriodicalIF":5.7000,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Trajectory-based indicators to determine the local character of intersection conflicts: A micro-spatial analysis\",\"authors\":\"Andreas Hula , Apostolos Ziakopoulos , Ángel Losada , Andrea Schaub , Peter Saleh , George Yannis\",\"doi\":\"10.1016/j.aap.2025.108155\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Real world behaviour data is the most reliable reference to assess road safety in a specific road infrastructure context. However, its collection and implementation for road safety research in a rapid and portable manner is still challenging, facing data protection issues and the complexities to set up constant tracking mechanisms with their own power supply. To tackle these limitations, the Mobility Observation Box (MOB) provides a flexible data collection, to be used in subsequent video analysis. Object detection and tracking allow for the derivation of movement trajectories, which in turn allow to derive quantitative indicators of road safety relevant behaviour, namely well-established Surrogate Safety Measures (SSMs), such as Post-Encroachment-Time (PET), Time-to-Closest-Approach (TCA) and Time-to-Collision-(TTC) alongside a number of indicators like maximum speed of two interaction partners, the angle they approach each other in and the minimum distance they had at one point in their interaction. To facilitate potential MOB uses, this study leverages over 51 h of naturalistic video data at a busy Vienna intersection to advance road safety research by (i) employing random parameters binary modelling of the likelihood of critical conflict occurrence and (ii) Gaussian generalized additive spatial modelling to identify key factors influencing the absolute values of conflict angles on critical conflicts only. Within the examined intersection, specific speed and acceleration effects were determined, together with the respective heterogeneity-in-means, as well as significant categorical effects of different road user types. All road user types were ultimately less likely to be involved in safety–critical conflicts compared to cars in both leading (firstly detected) and following (secondly detected) roles, with the exception of cyclists in the leading role. Within the micro-spatial analysis, the kinematic parameters of the second road user only (speed, max acceleration and max deceleration), the duration of the interaction as well as intersection-specific local effects related to the position of the leading road user were all found to influence the transformed absolute value of the angles of critical conflicts.</div></div>\",\"PeriodicalId\":6926,\"journal\":{\"name\":\"Accident; analysis and prevention\",\"volume\":\"220 \",\"pages\":\"Article 108155\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2025-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Accident; analysis and prevention\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0001457525002416\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ERGONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accident; analysis and prevention","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0001457525002416","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ERGONOMICS","Score":null,"Total":0}
Trajectory-based indicators to determine the local character of intersection conflicts: A micro-spatial analysis
Real world behaviour data is the most reliable reference to assess road safety in a specific road infrastructure context. However, its collection and implementation for road safety research in a rapid and portable manner is still challenging, facing data protection issues and the complexities to set up constant tracking mechanisms with their own power supply. To tackle these limitations, the Mobility Observation Box (MOB) provides a flexible data collection, to be used in subsequent video analysis. Object detection and tracking allow for the derivation of movement trajectories, which in turn allow to derive quantitative indicators of road safety relevant behaviour, namely well-established Surrogate Safety Measures (SSMs), such as Post-Encroachment-Time (PET), Time-to-Closest-Approach (TCA) and Time-to-Collision-(TTC) alongside a number of indicators like maximum speed of two interaction partners, the angle they approach each other in and the minimum distance they had at one point in their interaction. To facilitate potential MOB uses, this study leverages over 51 h of naturalistic video data at a busy Vienna intersection to advance road safety research by (i) employing random parameters binary modelling of the likelihood of critical conflict occurrence and (ii) Gaussian generalized additive spatial modelling to identify key factors influencing the absolute values of conflict angles on critical conflicts only. Within the examined intersection, specific speed and acceleration effects were determined, together with the respective heterogeneity-in-means, as well as significant categorical effects of different road user types. All road user types were ultimately less likely to be involved in safety–critical conflicts compared to cars in both leading (firstly detected) and following (secondly detected) roles, with the exception of cyclists in the leading role. Within the micro-spatial analysis, the kinematic parameters of the second road user only (speed, max acceleration and max deceleration), the duration of the interaction as well as intersection-specific local effects related to the position of the leading road user were all found to influence the transformed absolute value of the angles of critical conflicts.
期刊介绍:
Accident Analysis & Prevention provides wide coverage of the general areas relating to accidental injury and damage, including the pre-injury and immediate post-injury phases. Published papers deal with medical, legal, economic, educational, behavioral, theoretical or empirical aspects of transportation accidents, as well as with accidents at other sites. Selected topics within the scope of the Journal may include: studies of human, environmental and vehicular factors influencing the occurrence, type and severity of accidents and injury; the design, implementation and evaluation of countermeasures; biomechanics of impact and human tolerance limits to injury; modelling and statistical analysis of accident data; policy, planning and decision-making in safety.