Metro passenger behaviors and their relations to metro incident involvement. (September 2015)

• Record Type: Journal Article
• Authors: Wan, Xin; Li, Qiming; Yuan, Jingfeng; Schonfeld, Paul M.
• Is Part Of: Accident analysis and prevention. Volume 82(2015)
• Page Start: 90
• Page End: 100
• Publication Date: 2015-09
• Subjects: Rail transit safety -- Passenger behaviors -- Incidents -- Violations -- Errors; Accidents -- Prevention -- Periodicals; Accident Prevention -- Periodicals; Accidents -- Prévention -- Périodiques; 363.106
• DOI: 10.1016/j.aap.2015.05.015
• Languages: English
• ISSNs: 0001-4575

Abstract

Highlights: Metro passenger behavior questionnaire is developed and validated on Chinese samples. Transgressions, self-willed inattentions and abrupt violations are differentiated. Importance hierarchy and affected entities of passenger behaviors are measured. Effects of demographic and riding variables on different behaviors are examined. Transgressions and abrupt violations are predictors of incident involvement. Abstract: The frequent incidents caused by metro passengers in China suggest that it is necessary to explore the classification and effects of passenger behaviors and their relations to incident involvement. A metro passenger behavior questionnaire (MPBQ) and a metro station staff questionnaire (MSSQ), both comprising 32 behavior items, were developed and surveyed on a sample of metro passengers ( N = 579) and metro staff ( N = 99). Using the MPBQ, the self-reported frequency of each aberrant behavior was measured and subjected to explanatory factor analysis, which revealed a three-factor solution on the 28 retained behavior items: transgressions, self-willed inattentions and abrupt violations. ANOVA was used to examine the effects of demographic and riding profile variables on different types of behaviors. The MSSQ was used to collect metro staff opinions on behavior frequency, severity and entities that might be affected, given that a specific behavior occurred. An importance hierarchy was established over the 32 identified behaviors to determine the most important riding behaviors. Finally, logistic regression showed that riding time, number of stops experienced by a passenger and, more importantly, transgressions and abrupt violations, were significant predictors of incident involvement. The possible explanations and implications of the findings might help in understanding passenger behaviors and targeting metro safety interventions in ways that promote safer operations.