The intercoder agreement when using the Driving Reliability and Error Analysis Method in road traffic accident investigations

被引:9
|
作者
Warner, Henriette Wallen [1 ]
Sandin, Jesper [1 ]
机构
[1] Chalmers Univ Technol, S-41296 Gothenburg, Sweden
关键词
Intercoder agreement; Traffic accidents; Causation analysis; DREAM;
D O I
10.1016/j.ssci.2009.12.022
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Many different classification schemes have been used in the analysis of road traffic accidents but the agreement between coders using the same classification scheme is rarely tested and/or reported. As a high intercoder agreement is a prerequisite for a study's validity, this is a serious shortcoming. The aim of the present study was, therefore, to test the intercoder agreement of the Driving Reliability and Error Analysis Method (DREAM) version 3.0 by letting seven coders from different European countries analyse and classify the causes of the same four accident scenarios. The results showed that the intercoder agreement for genotypes (contributing factors) ranges from 74% to 94% with an average of 83%, while for phenotypes (observable effects) it ranges from 57% to 100% with an average of 78%. The results also showed that weaknesses in classification schemes, methods, training of coders as well as in presentation of accident information can be identified by testing the intercoder agreement. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:527 / 536
页数:10
相关论文
共 40 条
  • [21] Conflict Situations and Driving Behavior in Road Traffic - An Analysis Using Eyetracking and Stress Measurement on Car Drivers
    Sawilla, Swenja
    Keller, Christine
    Schlegel, Thomas
    HCI IN MOBILITY, TRANSPORT, AND AUTOMOTIVE SYSTEMS. DRIVING BEHAVIOR, URBAN AND SMART MOBILITY, MOBITAS 2020, PT II, 2020, 12213 : 86 - 103
  • [22] The synthesis of human-error analysis using the cognitive reliability and error analysis method and fault-tree analysis
    Zupancic, J
    Marn, J
    STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING, 2002, 48 (08): : 418 - 437
  • [23] Distracted when Using Driving Automation: A Quantile Regression Analysis of Driver Glances Considering the Effects of Road Alignment and Driving Experience
    He, Dengbo
    Kanaan, Dina
    Donmez, Birsen
    FRONTIERS IN FUTURE TRANSPORTATION, 2022, 3
  • [24] A traffic dynamic operation risk assessment method using driving behaviors and traffic flow Data: An empirical analysis
    Yang, Haiyi
    Zhao, Xiaohua
    Luan, Sen
    Chai, Shushan
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 249
  • [25] Using error analysis method for division of highway accident responsibility based on computer simulation technology
    Liu Q.
    Advances in Transportation Studies, 2019, 2 (Special Issue): : 133 - 140
  • [26] ANALYSIS OF FIVE FACTORS INFLUENCING ROAD TRAFFIC ACCIDENT OCCURRENCE IN CHINA (1990-2018) BY THE VECTOR AUTOREGRESSIVE AND VECTOR ERROR CORRECTION MODELS
    Sun, Bo
    Wu, Lei
    Wei, Ming
    JOURNAL OF NONLINEAR AND CONVEX ANALYSIS, 2022, 23 (09) : 1761 - 1773
  • [27] Evaluation method using chaotic analysis for the model of vehicles' behavior in road traffic system
    Itakura, N
    Fukeda, A
    Honda, N
    Yikai, K
    MATHEMATICAL AND COMPUTER MODELLING, 2001, 33 (6-7) : 771 - 782
  • [28] Traffic Accident Traits and Driver Characteristics Implication on Road Accidents using Descriptive Analysis: A Cross Sectional Study in Sulaymaniyah, Iraq
    Abdulla, Raza
    Qader, Bakhtiyar
    Sdiq, Karwan
    ENGINEERING TECHNOLOGY & APPLIED SCIENCE RESEARCH, 2023, 13 (02) : 10372 - 10376
  • [29] An improved software reliability prediction model by using high precision error iterative analysis method
    Jabeen, Gul
    Luo, Ping
    Afzal, Wasif
    SOFTWARE TESTING VERIFICATION & RELIABILITY, 2019, 29 (6-7):
  • [30] Innovative prediction and causal analysis of accident vehicle towing probability using advanced gradient boosting techniques on extensive road traffic scene data
    Zhang, Ronghui
    Liu, Yang
    Wang, Zihan
    Chen, Junzhou
    Zeng, Qiang
    Zheng, Lai
    Zhang, Hui
    Pei, Yulong
    ACCIDENT ANALYSIS AND PREVENTION, 2025, 211