Analyzing Heterogenous Effects of Contributing Factors Affecting
 Injury Severity of Helicopter Accidents

doi:10.16097/j.cnki.1009-6744.2024.02.032

Abstract

Abstract: The study explores the contributing factors affecting the injury severity of helicopter accidents based on the modeling exercises that capture unobserved heterogeneity. The data include 1241 helicopter accident records collected from the National Transportation Safety Board (NTSB) database, categorizing the accident information into temporal, flight, pilot, helicopter, and meteorological factors. Afterward, the study uses Chi-square tests to examine the statistical differences of factors' probability distributions across injury severities (property-damage-only, minor injury, and serious injury or fatal). Several mixed Logit models are developed to model the injury severity, which set the random parameters with diverse priori densities. Through a meticulous comparison, the optimal model is selected based on data fitting metrics. Further, the estimates of this model are used to analyze the effects of the contributing factors on injury severities and their heterogenous effects. The results indicate that unobserved heterogeneity can be found in modeling the injury severity of helicopter accidents. The mixed Logit model with independent normal and multivariate normal random parameters outperformances others in data-fitting. Among the factors, encountering IMC, loss of control in flight, fuel issues, low altitude operation or external loading (including contact with powerlines or trees), maneuvering or operation, approaching, elder pilots, pilots with helicopter instrument qualification, and accidents involving fire or explosion significantly increase the probability of serious injuries or fatalities. For the factor's heterogenous effects, the coefficients of weekend flight, elder pilots, and the use of 3-point restraints can be modeled as random parameters.

Key words: air transportation, accident severity, random parameter mixed Logit model, helicopter accident, contributing factors, unobserved heterogeneity

摘要： 提取美国国家运输安全委员会(NationalTransportationSafety Board, NTSB)数据库1241起直升机事故记录的关键信息，分析通用航空直升机事故后果严重性的影响因素及其影响异质性问题。首先，将事故记录中各项信息梳理为时间、飞行过程、飞行员、直升机和气象条件类因素，同时，采用卡方检验分析各因素在无伤事故、轻伤事故和重伤死亡事故分类下的分布差异；而后，基于不同先验概率分布的随机系数构建若干混合Logit模型，拟合事故严重性；最后，通过对比不同模型的拟合效果，根据最优模型的参数估计，分析不同事故严重性对应因素的影响机理和影响的异质性问题。结果表明：直升机事故严重性的统计建模存在明显的因素影响异质性问题；基于独立正态和多元正态分布的相关随机系数混合Logit模型拟合效果优于其他模型；影响因素中，出现仪表气象条件、空中失去控制、燃油问题、低空运行及挂载(含撞线/树)、运动及作业、进近、老年驾驶员、飞行员具有直升机仪表能力以及直升机起火爆炸等因素时，将显著增加重伤死亡事故的概率；异质性分析中，周末、老年飞行员和三点式座椅安全带等因素存在显著的影响异质性。

关键词: 航空运输, 事故严重性, 随机系数混合Logit模型, 直升机事故, 影响因素, 异质相关性

CLC Number:

ZHOUYue, JIANG Weian, FU Chuanyun, WEI Lin, YOU Yi. Analyzing Heterogenous Effects of Contributing Factors Affecting Injury Severity of Helicopter Accidents[J]. Journal of Transportation Systems Engineering and Information Technology, 2024, 24(2): 323-332.

周悦, 蒋维安, 付川云, 魏麟, 犹轶. 考虑因素异质影响的直升机事故严重性分析[J]. 交通运输系统工程与信息, 2024, 24(2): 323-332.

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References

[1]中华人民共和国交通运输部.2021年交通运输行业发展统计公报[R]. 北京: 中华人民共和国交通运输部, 2022. [Ministry of Transport of the People's Republic of China. Statistical communiqué of the People's Republic of China on the 2021 national transportation industry development[R]. Beijing: Ministry of Transport of the People's Republic of China, 2022.]

[2] FILGO A P G, SOUZA C A, SIQUEIRA E L, et al. An analysis of helicopter accident reports in Brazil from a human factors perspective[J]. Reliability Engineering & System Safety, 2019, 183: 39-46.

[3] XU Z, SALEH J H, SUBAGIA R. Machine learning for helicopter accident analysis using supervised classification: Inference, prediction, and implications[J]. Reliability Engineering & System Safety, 2020, 204: 107210.

[4]王畅, 程蒙,马帅.直升机尾桨失效事故案例分析[J]. 重庆交通大学学报(自然科学版),2022, 41(4): 489 494. [WANG C, CHENG M, MA S. Case study on accident caused by loss of tail-rotor effectiveness[J]. Journal of Chongqing Jiaotong University (Natural Science), 2022, 41(4): 489-494.]

[5]詹月玫.国内民用直升机撞线事故分析[J].直升机技术, 2023, 216: 64-67. [ZHAN Y M. Analysis of domestic civil helicopter collision with cables[J]. Helicopter Technique, 2023, 216: 64-67.]

[6] 王新野,潘盈朵,高文权,等.影响直升机飞行员飞入IMC的心理因素:一项基于三十年间NTSB事故报告的研究[J]. 心理科学,2022, 45(1): 156-163. [WANG X Y, PAN Y D, GAO W Q, et al. Mental factors of helicopter pilots flying into IMC: Based on NTSB accident reports in the past 30 years[J]. Journal of Psychological Science, 2022, 45(1): 156-163.]

[7] BLEDSOE B E, SMITH M G. Medical helicopter accidents in the United States: A 10-year review[J]. Journal of Trauma and Acute Care Surgery, 2004, 56(6): 1325-1329.

[8] RAO A H, MARAIS K. High risk occurrence chains in helicopter accident[J]. Reliability Engineering & System Safety, 2018, 170: 83-98.

[9] 王创业,李柯,郑懿,等.基于FTA-BN的应急救援直升机事故致因分析[J].武汉理工大学学报(信息与管理工程版), 2022, 44(2): 212-219. [WANG C Y, LI K, ZHENG Y, et al. Analysis of causation factors of emergency rescue helicopter accident based on FTA-BN [J]. Journal of WUT (Information & Management Engineering), 2022, 44(2): 212-219.]

[10] SUBAGIA R, SALEH J H, CHURCHWELL J S, et al. Statistical learning for turboshaft helicopter accidents using logistic regression[J]. Plos One, 2020, 15(1): e0227334.

[11] 高扬, 曹媛.基于关联规则挖掘的直升机事故/事件分析[J]. 安全与环境学报,2020,20(3): 849-856. [GAO Y, CAO Y. Analysis of the helicopter accidents based on the association rules mining[J]. Journal of Safety and Environment, 2020, 20(3): 849-856.]

[12] MANNERING F, SHANKAR V, BHAT C R. Unobserved heterogeneity and the statistical analysis of highway accident data[J]. Analytic Methods in Accident Research, 2016, 11: 1-16.

[13] 宋栋栋, 杨小宝,祖兴水,等.基于均值异质性随机参数Logit模型的城市道路事故驾驶员受伤严重程度研究[J]. 交通运输系统工程与信息, 2021, 21(3): 214 220. [SONG D D, YANG X B, ZU X S, et al. Examination of driver injury severity in urban crashes: A random parameters Logit model with heterogeneity in means approach[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(3): 214-220.]

[14] 周悦, 江欣国,付川云,等.基于混合Logit模型的出租车超速者运营因素分析[J].交通运输系统工程与信息, 2021, 21(3): 229-236. [ZHOU Y, JIANG X G, FU C Y, et al. Operational factors analysis for taxi speeders using mixed Logit model[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(3): 229-236.]

[15] 杨洋, 贺昆, 王云鹏,等.面向动态交通流的高速公路事故风险模型空间移植研究[J].交通运输系统工程与信息,2023, 23(3): 174-186. [YANG Y, HE K, WANG Y P, et al. Spatial transplantation for modeling of freeway traffic crash risk based on dynamic traffic flow[J]. Journal of Transportation Systems Engineering and Information Technology, 2023, 23(3): 174-186.]

Analyzing Heterogenous Effects of Contributing Factors Affecting Injury Severity of Helicopter Accidents

考虑因素异质影响的直升机事故严重性分析

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