Federal Motor Carrier Safety Administration Research Articles

Spatio-Temporal Assessment of Heavy-Duty Truck Incident and Inspection Data

Vehicular incidents, especially those involving tractor trailers, are increasing in number every year. These events are extremely costly for fleets, in terms of damage or loss of property, loss of efficiency, and certainly in terms of loss of life. Although the U.S. Department of Transportation (DOT) is responsible for performing inspections, and fleet managers are encouraged to maintain their fleet and participate in regular inspections, it is uncertain whether these inspections are occurring at a frequency that is necessary to prevent incidents. The Federal Motor Carrier Safety Administration (FMCSA) of the DOT manages and maintains the Motor Carrier Management Information System (MCMIS) dataset, which contains all incident and inspection data regarding commercial vehicles in the U.S. The purpose of this preliminary analysis was to explore the MCMIS dataset through spatiotemporal analyses, to uncover findings that may hint at potential improvements in the DOT inspection process and highlight location-specific trends in the dataset. These analyses are novel, as previous research using the MCMIS dataset only examined the data at the state or county level, not at a national scale. The results from the analyses pinpointed specific major metropolitan areas, namely Harris County (Houston), Texas, and three of the New York boroughs (Kings, Queens, and the Bronx), which were found to have increasing incident rates during the study period (2016–2020). An overview of potential causal factors contributing to this increase are provided as well as an overview of the inspection process, and suggestions for improvement relative to the highlighted locations in Texas and New York are also provided. Ultimately, it is suggested that the incorporation of advanced technology and automation may prove beneficial in reducing the occurrence of events that lead to incidents and may also help in the inspection process.

Timber Transportation Crash and Vehicle Defect Rates in the US South

Highlights Crash rates among southern log truck fleets were 176% higher than log truck fleets in the Lake States. Vehicle and driver out-of-service rates were similar among log trucks in the US South, Northeast, Lake States, and West. The age and condition of log trucks did not explain elevated crash rates in the US South. Abstract. The US South harvests more than 200 million tonnes of timber annually, nearly all of which is transported from forests to mills by truck. Log truck fleets in the US South have been struggling with rising liability insurance premiums. The goal of this study was to compare crash rates and the condition of log trucks operating in the US South to log trucks operating in other US regions and trucks in other industries. A sample of inspection and crash data were collected from the Federal Motor Carrier Safety Administration. Vehicle and driver out-of-service rates, vehicle defect rates, and crash rates among log truck fleets in the US South were compared to log trucks in other US regions and to 50 large non-log truck fleets. Crash rates among southern log truck fleets were 176% higher than log truck fleets in the Lake States and 48% higher than 50 large non-log truck fleets. Vehicle and driver out-of-service rates were similar among log truck fleets in each region (p > 0.25), but southern logging business fleets had higher vehicle out-of-service rates than 50 large non-log truck fleets (p = 0.02). Driver education, technology implementation, improved fleet maintenance practices, and weight limit parity on interstate highways may improve timber transportation safety. Keywords: Log trucks, Logging accidents, Logging safety, Timber harvesting, Wood supply chain.

A case and framework for expanding the use of model‐free evidence

A case and framework for expanding the use of model‐free evidence

The Electronic Logging Device Mandate and Costs for Refrigerated Citrus


 
 
 
 
 
 
 Speedy truck transportation is required to get products like fresh produce from the farm to the grocery store before it spoils. The Electronic Logging Device (ELD) Mandate from the Federal Motor Carrier Safety Administration could significantly affect trucking costs for agricultural producers. This 6-page publication written by Tara Wade, Shellye Suttles, and Derek Farnsworth and published by the UF/IFAS Food and Resource Economics Departmentuses truck shipment data to analyze transportation costs and identifies potential future effects of the ELD Mandate.https://edis.ifas.ufl.edu/fe1086
 
 
 
 
 
 

Sleep Apnea Screening for Commercial Drivers: A Retrospective Comparison of the 2016 FMCSA MRB Recommendations and the 2006 Joint Task Force Consensus Guidelines.

Compare the 2016 Federal Motor Carrier Safety Administration (FMCSA) and 2006 Joint Task Force (JTF) Guidelines for commercial drivers' obstructive sleep apnea (OSA) screening. Retrospective review of all commercial driver medical examinations performed in 2017 at an academic occupational medicine clinic. Screening criteria from both the JTF and FMCSA were applied, separately, and jointly. Statistical tests were applied as appropriate. Applying the FMCSA or JTF criteria separately to 706 commercial drivers, the positive OSA screening yields were 15.7% and 16.9%, respectively. Using both criteria produced an overall positive OSA screen yield of 20.1%. Positive predictive values for applying both guidelines ranged from 72.7% to 95.5%. The combined use of the 2016 FMCSA and 2006 JTF OSA screening criteria in series has a higher screening yield than using either guideline individually.

Gibrat’s law in the trucking industry

The distribution of firm size in the trucking industry is highly skewed, with a few firms accounting for a disproportionate share of transport. The distribution is also highly disperse so that firms have no characteristic size. This paper demonstrates that the distribution of firms sizes can be well approximated by the Zipf distribution. Such a distribution is consistent with a random growth process that is independent of firm size (Gibrat’s law). We use data from the Federal Motor Carrier Safety Administration in 2016 to demonstrate that the Zipf distribution provides a fit that is as good or better than other competing distributions, strongly supporting the model of random growth.

The Pre-Registry Commercial Driver Medical Examination: Screening Sensitivity and Certification Lengths for Two Safety-Related Medical Conditions.

Use independent diagnostic data to analyze the screening effectiveness of the pre-Registry commercial driver medical examination (CDME) for obstructive sleep apnea (OSA), and its sensitivity for hypertension; analyze certification lengths where relevant. CDME screening results for 1668 drivers were compared to polysomnogram diagnostic test results, and CDME screening results were evaluated for 1155 drivers with at least one insurance claim with a hypertension diagnostic code. Any CDME documentation of the medical condition was considered as detection by screening. CDME sensitivity was 20.7% for moderate OSA (AHI ≥ 15). While sensitivity was 77.5% for hypertension, 93.3% of drivers with Stage 3 hypertension were certified, contrary to Federal Motor Carrier Safety Administration standards. The pre-Registry CDME was ineffective in screening commercial drivers for OSA. Screening was better for hypertension; incorrect certifications were given to many hypertensive drivers.

Diabetes in the Workplace: the Hazards of Hypoglycemia.

The effects of hypoglycemia can result in injury, including at work. Our goal was to review the recent medical literature regarding hypoglycemia and occupational injuries and provide guidance to clinicians asked to render opinions regarding fitness for work duties in individuals with diabetes. Recent studies contain conflicting conclusions regarding the occupational risks posed by workers with diabetes. However, the US Federal Motor Carrier Safety Administration concluded there was sufficient evidence to change the rule that previously disqualified commercial drivers with insulin-treated diabetes. Blanket employment policies that disqualify workers with diabetes are unnecessary in many occupational fields. In assessing occupational risks and fitness for duty in workers with diabetes, it is important to perform an individualized assessment of the worker and consider the risk factors for hypoglycemia, information from the treating clinician, essential functions of the job, and, if needed, availability of reasonable accommodations.

1256-P: Assessing Truck Drivers with Diabetes: The Clinician's Role

In 2018 the Department of Transportation (DOT) published a new rule on the requirements for medical certification of commercial motor vehicle (CMV) drivers with insulin-treated diabetes mellitus. This rule eliminates significant obstacles for those drivers, thus potentially enabling thousands of drivers to pursue careers that had previously been unavailable to them. This poster reviews the process of CMV medical certification for drivers with insulin-treated diabetes and provides resources and guidance for the assessment process. The new rule requires an assessment by a treating clinician (defined as a healthcare professional who manages, and prescribes insulin for, treatment of the individual’s diabetes mellitus as authorized by the healthcare professional’s applicable state licensing authority). The components of this assessment include: • A minimum of 3 months of blood glucose self-monitoring records measured with a glucometer that stores all readings from which data can be downloaded. • Hypoglycemia history. • Hemoglobin A1C measurements. • Complications of diabetes. The treating clinician completes an assessment form to determine whether the driver meets the physical qualification standards of the Federal Motor Carrier Safety Administration (FMCSA) to operate a CMV. Additional assessment by the treating clinician may be required if the driver has recently experienced a motor vehicle accident or severe hypoglycemic episode. The treating clinician is required to attest the driver maintains a “stable insulin regimen” and “proper control of his/her diabetes mellitus.” The American Diabetes Association provides a useful online calculator to assess the risk of a diabetes related motor vehicle accident (professional.diabetes.org/RADD) Although the rule requires an opinion from a treating clinician, the final decision on medical certification for any individual CMV driver is made by a certified medical examiner listed on the National Registry of Certified Medical Examiners. Disclosure D. Lorber: None. K. Hathaway: None.

FAST DASH: Program overview and key findings from initial technology evaluations

One focus of the U.S. Federal Motor Carrier Safety Administration (FMCSA) is to provide leadership in the testing and evaluation of promising safety technologies developed for use in commercial motor vehicles (CMVs). To this end, a program was developed by FMCSA to conduct independent, short-turnaround evaluations of promising safety technologies. Vendors who had promising safety technologies, focused in the commercial vehicle domain, were solicited to participate and submit an application. One technology was selected by FMCSA for each evaluation cycle (lasting approximately 18 months). The technology was tested in both static and dynamic conditions, after which a trucking fleet, and its drivers, were brought in to test the technology in a field operational test (FOT) lasting approximately 6 weeks. During the FOT, 15–20 trucks were instrumented with the technology and other data collection equipment, including sensors and video cameras. A study was then conducted during which drivers used the technology in their revenue-producing operations. Initially, often for the first 2 months, the technology collected data but did but not actively present alerts to the driver. Following this baseline period, a four-month intervention period was conducted. Each evaluation has resulted in more than 1,000,000 km of driving data including continuous video data. Data analyses focused on understanding the efficacy of the technology in terms of (i) safety improvements, (ii) challenges to implementation (e.g., unintended consequences), and (iii) user acceptance (including driver, fleet manager, and other fleet personnel as appropriate). The technology vendors who applied for the first three evaluations can be classified into the following general categories: fatigue/drowsiness, fleet management, visibility safety systems, cell phone policy/enforcement, and other systems. Three technology evaluations were completed in the first 5 years of (i) a blind spot detection and warning system, (ii) an onboard monitoring system, and (iii) a novel mirror technology. High-level results of each of these three evaluations are highlighted in the paper.

Reconciling Alternative Theories for the Safety of Owner–Operators

Motor carrier safety is an important concern of shippers, carriers, policy makers, consignees, insurance providers, and the motoring public. One aspect of carrier safety that has garnered substantial attention is whether carriers making greater use of owner–operators are more or less safe vis‐à‐vis carriers making greater use of employee drivers. Currently, conflicting theoretical predictions exist regarding the direction of this relationship. In this article, we offer a reconciliation of the alternative theoretical predictions by developing a coherent theory that merges sociological rational choice theory and theory regarding motor carrier safety. We subject our theory to empirical testing by fitting a series of seemingly unrelated regression models to a vector of safety measures tracked as part of the Federal Motor Carrier Safety Administration's Compliance, Safety, and Accountability program. Our results are consistent with our proposed theory of owner—operator safety and provide meaningful theoretical and managerial implications and directions for future research.

A Time-Series Analysis of Motor Carrier Safety Behaviors

Multiple stakeholders are impacted by motor carrier operating safety, including truck drivers, motor carriers, insurance companies, shippers, and the general public. I develop and test theory in this article about motor carriers' longitudinal performance on three categories of safety behaviors associated with accident rates—Unsafe Driving, Hours-of-Service Compliance, and Vehicle Maintenance—as tracked by the Federal Motor Carrier Safety Administration as part of the Compliance, Safety, and Accountability (CSA) program. I specifically draw on fundamental concepts from sociological agency theory and resource dependency theory to develop a middle-range theory that generates previously untested hypotheses about carriers' longitudinal safety performance for these classes of safety behaviors following the CSA program's inception. The hypotheses are investigated by fitting a series of multivariate latent curve models to four years of panel data for 484 big for-hire vehicle carriers operating in the United States. The empirical findings confirm the theoretical expectations and persist during robustness testing. These findings have significant consequences for academics, motor carrier executives, purchasers of motor carrier transportation services, and policymakers.

Commercial truck crash injury severity analysis using gradient boosting data mining model

IntroductionTruck crashes contribute to a large number of injuries and fatalities. This study seeks to identify the contributing factors affecting truck crash severity using 2010 to 2016 North Dakota and Colorado crash data provided by the Federal Motor Carrier Safety Administration. MethodTo fulfill a gap of previous studies, broad considerations of company and driver characteristics, such as company size and driver’s license class, along with vehicle types and crash characteristics are researched. Gradient boosting, a data mining technique, is applied to comprehensively analyze the relationship between crash severities and a set of heterogeneous risk factors. ResultsTwenty five variables were tested and 22 of them are identified as significant variables contributing to injury severities, however, top 11 variables account for more than 80% of injury forecasting. The relative variable importance analysis is conducted and furthermore marginal effects of all contributing factors are also illustrated in this research. Several factors such as trucking company attributes (e.g., company size), safety inspection values, trucking company commerce status (e.g., interstate or intrastate), time of day, driver’s age, first harmful events, and registration condition are found to be significantly associated with crash injury severity. Even though most of the identified contributing factors are significant for all four levels of crash severity, their relative importance and marginal effect are all different. ConclusionsFor the first time, trucking company and driver characteristics are proved to have significant impact on truck crash injury severity. Some of the results in this study reinforce previous studies’ conclusions. Practical applicationsFindings in this study can be helpful for transportation agencies to reduce injury severity, and develop efficient strategies to improve safety.

Nothing good happens after dark: the influence of temporal factors on motor carrier crash severity

Motor carrier safety is a topic of great importance for both industry and makers of public policy. Regulatory agencies, such as the Federal Motor Carrier Safety Administration (FMCSA), regularly publish data detailing the circumstances surrounding roadway accidents. FMCSA’s Large Truck and Bus Crash Facts (LTBCF) data demonstrate an increase in accidents during daylight hours and on weekdays. Roadway risks are ever-present but differ by time of day and day of the week. These differences may potentially engender crashes of different severities at different times. This study analyzes FMCSA LTBCF data to determine when crashes of different severities are more likely to occur. Findings indicate that crashes resulting in property damage are more likely to occur during the day and on weekdays. However, fatal and injury crashes are significantly more likely during nights and weekends. Recommendations to improve safety outcomes are provided along with suggestions for future research.

A Multivariate Time‐Series Examination of Motor Carrier Safety Behaviors

Motor carriers’ operational safety affects multiple stakeholders including truck drivers, motor carriers, insurance companies, shippers, and the general public. In this article, I devise and test theory regarding motor carriers’ longitudinal performance for three classes of safety behaviors linked to carriers’ accident rates—Unsafe Driving, Hours‐of‐Service Compliance, and Vehicle Maintenance—tracked by the Federal Motor Carrier Safety Administration as part of the Compliance, Safety, and Accountability (CSA) program. Specifically, I draw on core concepts from sociological agency theory and resource dependency theory to devise middle‐range theory that generates never‐before‐tested hypotheses regarding carriers’ longitudinal safety performance for these classes of safety behaviors after the start of the CSA program. The hypothesized predictions are tested by fitting a series of multivariate latent curve models to four years of panel data for a random sample of 484 large, for‐hire motor carriers operating in the United States. The empirical findings corroborate the theoretical predictions and remain after robustness testing. These findings have important implications for scholars, motor carrier managers, procurers of motor carrier transportation services, and public policy makers.

Driver Exposure - Impact of Idle Reduction Technologies

Long-haul truck drivers spend extended periods of time in the cabin of trucks, both while driving and during rest periods. Drivers rest in the truck cabin with the truck engine idling to provide air conditioning or heating. Past studies indicate that in-cab particulate matter (PM) concentrations are higher during truck idling than at other times. The exposure of drivers to pollutants in the truck cabin during idling/rest periods has emerged as an area of concern, due to short-term impacts such as drowsiness, fatigue, and long-term health impacts such as heart disease and lung cancer. Idle reduction is also being promoted as an emissions reduction strategy and fuel saving measure for trucks. Idle reduction technologies (IRTs) are commercially available to provide drivers with heating and cooling in the truck cabin. However, there is limited knowledge on the impact of IRTs on driver exposure to diesel exhaust. This study, performed for the Federal Motor Carrier Safety Administration, examined how effective IRTs are in reducing driver exposure to diesel exhaust, while considering their cost-effectiveness. The study focused on diesel-powered IRTs, specifically auxiliary power units and fuel operated heaters and their impact on particulate matter of 2.5 micrometers or less. A test protocol was developed to assess in-cab exposures of diesel-powered IRTs against baseline conditions, and for the truck engine idling. The testing included field data collection across 24 trucks stops in three states to establish representative ambient PM2.5 concentrations at truck stops, for use in the laboratory testing stage. Laboratory testing was conducted in an environmentally controlled test chamber to assess in-cab PM2.5 levels under baseline conditions, compared to the truck idling and use of different IRTs. Five trucks, ranging from Model Year (MY) 2006 to 2014 were tested. A cost analysis was also conducted to assess cost-effectiveness and payback period for various IRTs. The results indicated that both IRTs and idling the truck engine reduced in-cab PM2.5 level compared to ambient levels. It was also found that all trucks post-MY2007 did not exhibit self-pollution, i.e., in-cab PM2.5 levels did not increase on account of the truck or IRT’s own emissions. Keeping in mind overall emissions and fuel consumption benefits, the findings support the use of idle reduction technologies to reduce in-cab PM2.5 levels. The cost analysis indicated that all IRTs are economically feasible (with payback period under two years), with fuel operated heaters showing the shortest payback period.

Management of Obstructive Sleep Apnea in Commercial Motor Vehicle Operators: Recommendations of the AASM Sleep and Transportation Safety Awareness Task Force.

The American Academy of Sleep Medicine Sleep and Transportation Safety Awareness Task Force responded to the Federal Motor Carrier Safety Administration and Federal Railroad Administration Advance Notice of Proposed Rulemaking and request for public comments regarding the evaluation of safety-sensitive personnel for moderate-to-severe obstructive sleep apnea (OSA). The following document represents this response. The most salient points provided in our comments are that (1) moderate-to-severe OSA is common among commercial motor vehicle operators (CMVOs) and contributes to an increased risk of crashes; (2) objective screening methods are available and preferred for identifying at-risk drivers, with the most commonly used indicator being body mass index; (3) treatment in the form of continuous positive airway pressure (CPAP) is effective and reduces crashes; (4) CPAP is economically viable; (5) guidelines are available to assist medical examiners in determining whether CMVOs with moderate-to-severe OSA should continue to work without restrictions, with conditional certification, or be disqualified from operating commercial motor vehicles.

Developing and Testing a Dynamic Theory of Motor Carrier Safety

Developing an understanding of the longitudinal relationships between different measures of motor carrier safety is important to advance theory and practice regarding this significant supply chain management and public policy issue. In this article, we combine core principles from several theoretical traditions to propose a dynamic theory of motor carrier safety that specifies the longitudinal relationships between three core measures of safety publically reported by the Federal Motor Carrier Safety Administration: unsafe driving, hour‐of‐service compliance, and vehicle maintenance. We test this theory using four years of longitudinal data on motor carrier safety for a random sample of large, for‐hire motor carriers. Results from fitting a vector multivariate autoregressive moving average time‐series model are largely consistent with the theory we propose. We describe the implications of our research for supply chain management theory and practice, summarize limitations, and suggest directions for future research.

The impact of new entrants and the new entrant program on motor carrier safety performance

Due to the importance of the recent Federal Motor Carrier Safety Administration requirement that all motor carriers participate in the New Entrant Safety Assurance Program (NESAP), the purpose of this study is to examine the relationship of the NESAP to motor carrier safety performance. Our study finds that carriers who entered the industry before the NESAP program (e.g., more experienced carriers) have significantly better safety performance in comparison to new entrant carriers. We also demonstrate that new entrants who successfully complete the requirements of the NESAP have significantly better safety performance than new entrants who fail to complete the program successfully. The implications of the study are also discussed.

Analysis of Truck Accidents Using Structural Equation Models

Abstract Many researchers and practitioners in the trucking industry have expressed concerns with the implementation of Compliance, Safety and Accountability (CSA), which is a safety management initiative created by the Federal Motor Carrier Safety Administration (FMCSA). CSA assigns Behavior Analysis Safety Improvement Categories (BASIC) scores to carriers, based on driver and vehicle performance. This technique of assigning BASIC scores to carriers is a cause of concern for many stakeholders in the industry. This article presents a structural equation model (SEM) to understand the relationship between the BASIC scores and crash records of the carriers. Exogenous variables are Unsafe Driving, Fatigue Driving, Driver Fitness, Controlled Substances/Alcohol, and Vehicle Maintenance. Crash-Per-Million-Miles is the endogenous variable in the SEM. We observed existence of a latent variable driver characteristic, which in turn influences three of the exogenous variables. Based on the SEM model output we concluded that four of the exogenous variables—Unsafe Driving, Fatigue Driving, Driver Fitness, and Controlled Substances/Alcohol—have significant influence on the endogenous variable.