Analysis of motorcyclist injury severities in motorcyclist violation crash on suburban roads of China: accommodating temporal instability and the unobserved heterogeneity in means and variances

被引:0
作者
Ye, Yuntao [1 ]
He, Jie [1 ]
Yan, Xintong [1 ]
机构
[1] Southeast Univ, Sch Transportat, 2 Si Pai Lou, Nanjing 210096, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Motorcyclist injury severity; traffic violation; temporal instability; random parameters logit model; heterogeneity in means and variances; SINGLE-VEHICLE; LOGIT ANALYSIS; BEHAVIOR; DRIVERS; FAULT;
D O I
暂无
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
This study analysed motorcyclist violation (MV) crashes on suburban roads of China to investigate how determinants affect MV crash injury severity and explore the temporal stability of determinants. Crash data from Xi'an, China (2015-2018) were utilized to investigate three MV crash injury categories: no injury, minor injury and severe injury. Motorcyclist-related, crash-related, roadway-related, environment-related and time-related characteristics were analysed utilizing a group of random parameters multinomial logit models with heterogeneity in means and variances. The temporal instability was measured by performing likelihood ratio tests. Marginal effects were calculated to further illustrate the temporal variations of these factors. The study found an overall temporal instability, with some violations like alcohol-impaired riding, speeding, and unlicensed riding having significant effects on MV crash injury severity. Additionally, the study revealed a significant risk compensation mechanism of riders under adverse riding conditions. The findings provided insights and recommendations for suburban motorcycle crash prevention strategies.
引用
收藏
页码:145 / 159
页数:15
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共 57 条
  • [31] Unobserved heterogeneity and the statistical analysis of highway accident data
    Mannering, Fred
    Shankar, Venky
    Bhat, Chandra R.
    [J]. ANALYTIC METHODS IN ACCIDENT RESEARCH, 2016, 11 : 1 - 16
  • [32] Changes in motorcycle-related injuries and deaths after mandatory motorcycle helmet law in a district of Vietnam
    Ninh Thi Ha
    Ederer, David
    Van Anh Ha Vo
    An Van Pham
    Mounts, Anthony
    Nolen, Leisha D.
    Sugerman, David
    [J]. TRAFFIC INJURY PREVENTION, 2018, 19 (01) : 75 - 80
  • [33] Crash harm before and during the COVID-19 pandemic: Evidence for spatial heterogeneity in Tennessee
    Patwary, A. Latif
    Khattak, Asad J.
    [J]. ACCIDENT ANALYSIS AND PREVENTION, 2023, 183
  • [34] An analysis of motorcycle injury and vehicle damage severity using ordered probit models
    Quddus, MA
    Noland, RB
    Chin, HC
    [J]. JOURNAL OF SAFETY RESEARCH, 2002, 33 (04) : 445 - 462
  • [35] Severity of motorcycle crashes in Calgary
    Rifaat, Shakil Mohammad
    Tay, Richard
    de Barros, Alexandre
    [J]. ACCIDENT ANALYSIS AND PREVENTION, 2012, 49 : 44 - 49
  • [36] A hybrid Machine learning and statistical modeling approach for analyzing the crash severity of mobility scooter users considering temporal instability
    Sadeghi, Matin
    Aghabayk, Kayvan
    Quddus, Mohammed
    [J]. ACCIDENT ANALYSIS AND PREVENTION, 2024, 206
  • [37] Severity of motorcycle crashes in Dar es Salaam, Tanzania
    Salum, Jimoku Hinda
    Kitali, Angela E.
    Bwire, Hannibal
    Sando, Thobias
    Alluri, Priyanka
    [J]. TRAFFIC INJURY PREVENTION, 2019, 20 (02) : 189 - 195
  • [38] Probabilistic models of motorcyclists' injury severities in single- and multi-vehicle crashes
    Savolainen, Peter
    Mannering, Fred
    [J]. ACCIDENT ANALYSIS AND PREVENTION, 2007, 39 (05) : 955 - 963
  • [39] Examination of factors determining fault in two-vehicle motorcycle crashes
    Schneider, William H.
    Savolainen, Peter T.
    Van Boxel, Dan
    Beverley, Rick
    [J]. ACCIDENT ANALYSIS AND PREVENTION, 2012, 45 : 669 - 676
  • [40] The impact of weekday, weekend, and holiday crashes on motorcyclist injury severities: Accounting for temporal influence with unobserved effect and insights from out-of-sample prediction
    Se, Chamroeun
    Champahom, Thanapong
    Jomnonkwao, Sajjakaj
    Kronprasert, Nopadon
    Ratanavaraha, Vatanavongs
    [J]. ANALYTIC METHODS IN ACCIDENT RESEARCH, 2022, 36