Traffic volume and collisions involving transit and nontransit vehicles

Ragland, David R; Hundenski, R J; Holman, Barbara L.; Fisher, Jonathan

doi:10.1016/0022-4375(94)90023-x

Cited by 3 publications

(4 citation statements)

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“…SPECIAL ISSUE: TRANSIT OPERATORS-OBSERVATIONAL IOB ANALYSIS a function of the number of vehicles on the street (Ragland, Hundenski, Holman, & Fisher, 1992). The authors found increased risk for collision in the morning shift because of increased traffic density during that time.…”

Section: Alternative Explanations For Resultsmentioning

confidence: 99%

“…First, traffic density, which varied between different shifts and transit lines, might have been responsible for the association between stressors and accidents. It has been argued that collision accidents in bus drivers are SPECIAL ISSUE: TRANSIT OPERATORS-OBSERVATIONAL IOB ANALYSIS a function of the number of vehicles on the street (Ragland, Hundenski, Holman, & Fisher, 1992). The authors found increased risk for collision in the morning shift because of increased traffic density during that time.…”

Section: Alternative Explanations For Resultsmentioning

confidence: 99%

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Objective stress factors, accidents, and absenteeism in transit operators: A theoretical framework and empirical evidence.

Greiner

Krause²,

Ragland³

et al. 1998

Journal of Occupational Health Psychology

121

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The authors used observational job analysis as a conceptually based technique to measure stress factors unbiased by worker appraisal with 81 transit driving tasks on 27 transit lines. Stressor dimensions included work barriers that interfere with task performance due to poor technical-organizational design, time pressure, time binding (autonomy over time management), and monotonous conditions. Line-specific average stressor values were assigned to 308 transit operators who mainly worked the particular line. Logistic regression analyses showed associations for high work barriers and sickness absences (odds ratio [OR] = 3.8, p = .05). There were elevated risks for work accidents for high time pressure operators (OR = 4.0, p = .04) and for the medium time-binding group (OR = 3.3, p = .04) and significant (alpha = .20) unadjusted interaction terms for barriers and time pressure in predicting accidents and absences, and barriers and time binding in predicting absences. Findings suggest guaranteed rest breaks and flexible timing for accident prevention and removal of work barriers for reducing absenteeism.

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Section: Alternative Explanations For Resultsmentioning

confidence: 99%

Section: Alternative Explanations For Resultsmentioning

confidence: 99%

Objective stress factors, accidents, and absenteeism in transit operators: A theoretical framework and empirical evidence.

Greiner

Krause²,

Ragland³

et al. 1998

Journal of Occupational Health Psychology

121

View full text Add to dashboard Cite

show abstract

“…Lastly, a number of measures have been employed or suggested to represent risk exposure. Such measures include vehicle hours and miles; passenger movements and stops served; route length, traffic volume, and number of intersections per route; and the extent of on-street parking (Cheung et al, 2008;Jovanis et al, 1991;Ragland et al, 1992).…”

Section: Review Of Safety Researchmentioning

confidence: 99%

Analysis of Bus Collision Incidents Using Transit ITS and other Archived Operations Data

Strathman¹,

Wachana

Callas³

2010

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This report analyzes factors contributing to bus operations safety incidents at TriMet, the transit provider for the Portland Oregon metropolitan region. The analysis focuses on 4,631 collision and non-collision incidents that occurred between 2006 and 2009. Empirical analysis of these incidents draws on a wide array of operator-level data recovered by transit ITS technologies in combination with information from TriMet's human resources, scheduling, and customer relations databases. Incident frequencies are estimated in relation to operators' demographic characteristics, employment status, assigned work characteristics, service delivery and performance indicators, temporal factors, and customer information. Apart from identifying factors that are empirically related to the frequency of safety incidents, the findings offer insights into operations policies and practices that hold promise for improving safety.

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“…There are two general effects of this trend. First, increased traffic congestion can result in increased risk of collisions between transit vehicles and nontransit vehicles (Ragland, 1993; Ragland, Hundenski, Holman, & Fisher, 1992), increased exposure to motor vehicle fumes (Zuskin, Mustajbegovic, & Schachter, 1994), and increased psychophysiological activity (Evans & Carrere, 1991). Second, increasing traffic congestion creates barriers to transit vehicles, thereby reducing the potential efficiency of transit (Greiner, Ragland, Krause, Syme, & Fisher, 1997; OECD-ECMT, 1995; Rescue Muni, 1997).…”

Section: Policies Affecting the Transit System Environment: Interface...mentioning

confidence: 99%

Studies of health outcomes in transit operators: Policy implications of the current scientific database.

Ragland¹,

Krause²,

Greiner³

et al. 1998

Journal of Occupational Health Psychology

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Urban transit operators' medical symptoms and conditions exceed other occupational groups, resulting partly from working conditions. Medical outcomes among operators have an impact on the transit system, including on performance, work attendance, and medical costs. This is exacerbated by external economic and political pressures in which expected service often exceeds the system's capacity in a congested, chaotic urban environment. A vicious cycle of poor working environment, reduced health and well-being among operators, and lowered efficiency and increased costs often results. Operator-health policies focusing solely on individuals are not sufficient to address these problems. A broader approach is needed, acknowledging the relationship between health of the system and health of employees, including redesigning the interface between transit systems and the urban environment and organizational change within companies. This comprehensive approach recognizes the dynamic reciprocity among the transit operators, the transit system, and the larger community.

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Traffic volume and collisions involving transit and nontransit vehicles

Cited by 3 publications

References 0 publications

Objective stress factors, accidents, and absenteeism in transit operators: A theoretical framework and empirical evidence.

Objective stress factors, accidents, and absenteeism in transit operators: A theoretical framework and empirical evidence.

Analysis of Bus Collision Incidents Using Transit ITS and other Archived Operations Data

Studies of health outcomes in transit operators: Policy implications of the current scientific database.

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