Confounding Factors of Commercial Motor Vehicles in Safety Critical Events

Hernandez, Salvador; Al-Bdairi, Nabeel Saleem Saad; Jessup, Eric L. · 2018 · ROSA P / Pacific Northwest Transportation Consortium (PacTrans) (UTC)

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Summary

This study addresses the limitations of prior quasi-experimental research on Commercial Motor Vehicle (CMV) hours-of-service (HOS) regulations, which identified increased crash odds with longer driving times but failed to account for confounding factors. Previous studies often attributed safety critical events (SCEs)—defined as crashes, near crashes, or crash-relevant events—solely to driver fatigue linked to time-on-task. However, factors such as time of day (TOD), traffic density, and circadian rhythms may create systematic bias. This research aimed to validate earlier findings by uncovering relationships between HOS observations and these confounding variables, specifically examining how operational constraints like parking availability and driver behaviors influence safety outcomes. The researchers conducted a survey of large truck drivers delivering goods in the Pacific Northwest, collecting data on demographics, driving habits, crash history, and perceptions of safety hazards. To analyze the heterogeneous data, the study employed advanced econometric methods, including random parameters binary logit models and multivariate probit approaches. The analytical framework focused on three primary areas: cell phone use while driving, lane-changing behavior, and the impact of finding safe and adequate parking on HOS compliance. The models controlled for unobserved heterogeneity and correlated error terms to isolate the specific effects of driver behavior and operational constraints on SCE likelihood. Key findings indicate that factors related to fatigue management and driving hours significantly influence safety outcomes. The study demonstrated that company policies restricting work hours and enabling drivers to take breaks when fatigued effectively reduce the likelihood of SCEs. Additionally, the analysis highlighted that distracted driving, particularly cell phone use, is a critical risk factor that carriers can mitigate through internal enforcement policies. The research also revealed that the lack of available parking often forces drivers to violate HOS limitations or drive while tired, creating a direct link between infrastructure constraints and safety risks. Lane-changing behavior was found to be influenced by traffic density and time of day, suggesting that crash causality is multifaceted rather than solely dependent on driving duration. The significance of this work lies in its validation of HOS-related studies while providing a more nuanced understanding of crash causation. By identifying confounding factors, the study offers actionable insights for federal regulators, trucking industry groups, and insurance companies. It suggests that strategic operational adjustments, such as delivery schedule modifications to avoid high-risk time-of-day interactions and improved parking infrastructure, can enhance safety beyond regulatory compliance. These findings support the development of targeted policies that address both driver fatigue and external operational pressures, ultimately reducing human and economic costs associated with CMV crashes.

Key finding

Restrictions on the number of hours worked and schedules that enable drivers to take breaks when fatigued are effective at reducing the likelihood of safety critical events, while cell phone use and lane-changing behavior were analyzed as key risk indicators.

Methodology

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Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• truck driver fatigue
• shift work driving
• bus coach
• exposure measurement
• traffic density
• sex gender

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: observational prevalence, crash risk outcomes, behavioral performance data