Performance Assessment of an Onboard Monitoring System for Commercial Motor Vehicle Drivers: A Field Operational Test
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Summary
This report details a Field Operational Test (FOT) conducted by the Federal Motor Carrier Safety Administration (FMCSA) to evaluate the safety benefits of Onboard Monitoring Systems (OBMS) for commercial motor vehicle drivers. The study aimed to determine if OBMS technology, which provides real-time feedback and facilitates manager-led coaching based on recorded Safety-Critical Events (SCEs), could reduce at-risk behaviors and improve overall driver safety. The research was motivated by the need to reduce crash severity and frequency among large trucks and motorcoaches, building upon previous shorter-term studies by extending the observation period to 12 months. The experimental design involved four operational fleets: two trucking firms (Fleets A and H) and two motorcoach companies (Fleets D and E). A total of 156 vehicles were instrumented with OBMS and Data Acquisition Systems, involving 317 commercial drivers. The study spanned three phases: a one-month baseline, a nine-month intervention phase where feedback and coaching were provided, and a two-month withdrawal phase. In the trucking fleets, drivers were divided into feedback and control groups, while all drivers in the motorcoach fleets received feedback. Data analysis employed both driver-level methods (binary logit regression and repeated measures ANOVA) and fleet-level methods (cumulative binomial distribution) to assess changes in SCE rates. Additionally, questionnaires were administered to drivers and safety managers to gauge attitudes toward the technology, and crash data were analyzed using negative binomial regression. The findings indicated that OBMS implementation generally reduced critical event rates, though effectiveness varied by fleet and coaching consistency. Approximately 95% of recorded events were low-severity, with speeding being the most common issue in Fleets A and E, while seatbelt non-compliance and distraction dominated in Fleets D and H, respectively. Fleet E demonstrated a continual decrease in low-severity events, attributed to timely coaching within one week of an event. In contrast, Fleets A, D, and H utilized more sporadic coaching, which was less efficient. Fleet H showed a statistically significant decrease in both high- and low-severity event rates during the intervention and withdrawal phases. Regarding crash reduction, Fleet H experienced a significant 59.8% decrease in crash rates (from 12.5 to 5.0 crashes per million vehicle miles traveled), whereas Fleet A showed no statistically significant change. Driver attitudes were generally ambivalent or neutral, with feedback group drivers reporting lower satisfaction over time compared to control group drivers and safety managers, who held consistently positive views. The study concludes that OBMS can improve driver performance and safety, particularly when supported by timely and consistent coaching from safety managers. The persistence of reduced event rates in the withdrawal phase suggests that behavioral changes may endure after the intervention ends. However, the effectiveness of the system is heavily dependent on carrier-specific implementation strategies, such as the frequency of coaching and the ability to accurately identify drivers. The results imply that while OBMS is a viable tool for enhancing commercial fleet safety, its impact on crash reduction may require longer evaluation periods to fully manifest across all fleets. Future research should focus on optimizing coaching protocols and extending study durations to better assess long-term efficacy.
Key finding
Onboard monitoring systems with real-time feedback and coaching significantly reduced safety-critical event rates and crash rates in commercial fleets, with effectiveness contingent upon the timeliness of safety manager coaching.
Methodology
field_study
Sample size: 317
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
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.
- in vehicle coaching
- dms validation
- exposure measurement
- naturalistic crash near crash
- telematics ubi feedback
- truck driver fatigue
Information type
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- Applied Guidance: countermeasure evaluation
- Empirical Findings: observational prevalence
- Methodological Resource: dataset resource