Jiajun Pang , Adam Krathaus , Irina Benedyk , Sheikh Shahriar Ahmed , Panagiotis Ch. Anastasopoulos
{"title":"影响雪灾事故发生的环境因素的时间不稳定性分析——基于均值和方差异质性的随机参数危险持续时间模型","authors":"Jiajun Pang , Adam Krathaus , Irina Benedyk , Sheikh Shahriar Ahmed , Panagiotis Ch. Anastasopoulos","doi":"10.1016/j.amar.2022.100215","DOIUrl":null,"url":null,"abstract":"<div><p><span>The present paper introduces the time between the start of a snowfall and the occurrence of a motor vehicle accident as a novel measure for evaluating motor vehicle safety during snowfalls. Detailed information of accidents that occurred during snowfalls between 2017 and 2020 in the state of New York are used to explore the accelerating or delaying effect of different factors on the time between the start of a snowfall and the occurrence of an accident. To that end, the hazard-based duration modeling framework is employed, and to account for multiple layers of unobserved heterogeneity, a random parameters with heterogeneity in means and variances approach is introduced – for this first time, to the authors’ knowledge. The temporal stability of the factors across the study period is investigated through conducting a series of systematic likelihood ratio tests, and the factors are not found to be temporally stable across the study years. Hence, separate year-specific models are estimated. The results show that a number of factors affect the time between the start of a snowfall and the occurrence of a motor vehicle accident such as: visibility conditions; concrete road sections; road sections with high </span>Pavement<span> Condition Index (PCI); roads with more than 4 lanes in both directions; locations in close proximity to bus stations; the period during the cold winter months (specifically February); the amount of accumulated snow on the ground before snowfall; the presence of ramps; and long time intervals between snowfalls (especially for heavy snow conditions and adverse visibility conditions). The findings from this paper are anticipated to offer insights to winter maintenance teams, transportation system operators, and users regarding accident-prone periods and locations during snowfalls.</span></p></div>","PeriodicalId":47520,"journal":{"name":"Analytic Methods in Accident Research","volume":"34 ","pages":"Article 100215"},"PeriodicalIF":12.5000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"A temporal instability analysis of environmental factors affecting accident occurrences during snow events: The random parameters hazard-based duration model with means and variances heterogeneity\",\"authors\":\"Jiajun Pang , Adam Krathaus , Irina Benedyk , Sheikh Shahriar Ahmed , Panagiotis Ch. Anastasopoulos\",\"doi\":\"10.1016/j.amar.2022.100215\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span>The present paper introduces the time between the start of a snowfall and the occurrence of a motor vehicle accident as a novel measure for evaluating motor vehicle safety during snowfalls. Detailed information of accidents that occurred during snowfalls between 2017 and 2020 in the state of New York are used to explore the accelerating or delaying effect of different factors on the time between the start of a snowfall and the occurrence of an accident. To that end, the hazard-based duration modeling framework is employed, and to account for multiple layers of unobserved heterogeneity, a random parameters with heterogeneity in means and variances approach is introduced – for this first time, to the authors’ knowledge. The temporal stability of the factors across the study period is investigated through conducting a series of systematic likelihood ratio tests, and the factors are not found to be temporally stable across the study years. Hence, separate year-specific models are estimated. The results show that a number of factors affect the time between the start of a snowfall and the occurrence of a motor vehicle accident such as: visibility conditions; concrete road sections; road sections with high </span>Pavement<span> Condition Index (PCI); roads with more than 4 lanes in both directions; locations in close proximity to bus stations; the period during the cold winter months (specifically February); the amount of accumulated snow on the ground before snowfall; the presence of ramps; and long time intervals between snowfalls (especially for heavy snow conditions and adverse visibility conditions). The findings from this paper are anticipated to offer insights to winter maintenance teams, transportation system operators, and users regarding accident-prone periods and locations during snowfalls.</span></p></div>\",\"PeriodicalId\":47520,\"journal\":{\"name\":\"Analytic Methods in Accident Research\",\"volume\":\"34 \",\"pages\":\"Article 100215\"},\"PeriodicalIF\":12.5000,\"publicationDate\":\"2022-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Analytic Methods in Accident Research\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2213665722000045\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytic Methods in Accident Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2213665722000045","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
A temporal instability analysis of environmental factors affecting accident occurrences during snow events: The random parameters hazard-based duration model with means and variances heterogeneity
The present paper introduces the time between the start of a snowfall and the occurrence of a motor vehicle accident as a novel measure for evaluating motor vehicle safety during snowfalls. Detailed information of accidents that occurred during snowfalls between 2017 and 2020 in the state of New York are used to explore the accelerating or delaying effect of different factors on the time between the start of a snowfall and the occurrence of an accident. To that end, the hazard-based duration modeling framework is employed, and to account for multiple layers of unobserved heterogeneity, a random parameters with heterogeneity in means and variances approach is introduced – for this first time, to the authors’ knowledge. The temporal stability of the factors across the study period is investigated through conducting a series of systematic likelihood ratio tests, and the factors are not found to be temporally stable across the study years. Hence, separate year-specific models are estimated. The results show that a number of factors affect the time between the start of a snowfall and the occurrence of a motor vehicle accident such as: visibility conditions; concrete road sections; road sections with high Pavement Condition Index (PCI); roads with more than 4 lanes in both directions; locations in close proximity to bus stations; the period during the cold winter months (specifically February); the amount of accumulated snow on the ground before snowfall; the presence of ramps; and long time intervals between snowfalls (especially for heavy snow conditions and adverse visibility conditions). The findings from this paper are anticipated to offer insights to winter maintenance teams, transportation system operators, and users regarding accident-prone periods and locations during snowfalls.
期刊介绍:
Analytic Methods in Accident Research is a journal that publishes articles related to the development and application of advanced statistical and econometric methods in studying vehicle crashes and other accidents. The journal aims to demonstrate how these innovative approaches can provide new insights into the factors influencing the occurrence and severity of accidents, thereby offering guidance for implementing appropriate preventive measures. While the journal primarily focuses on the analytic approach, it also accepts articles covering various aspects of transportation safety (such as road, pedestrian, air, rail, and water safety), construction safety, and other areas where human behavior, machine failures, or system failures lead to property damage or bodily harm.