Daniel Blower

Accident rates for heavy truck-tractors in Michigan

Accident rates of heavy truck-tractors are modelled using log-linear methods. The accident data used are a census of truck-tractor involvements in Michigan from May 1987 to April 1988. Travel data used to calculate the rates were produced by a survey of truck-tractors in Michigan covering the same time period. Both the accident and travel data were limited to Michigan-registered tractors operating in Michigan. Log-linear models of casualty and property-damage-only accident rates were developed using number of trailers, road type, area type, and time of day as predictor variables. Overall, differences between tractors with one and two trailers were not significant. Tractors with no trailers (bobtails) have significantly higher accident rates. Characteristics of the operating environment were found to have larger effects on the accident rate than tractor configuration (except for the bobtail). Rates varied by a factor of up to 6.8, depending on the road type. Casualty accident risk at night was 1.4 times the risk during the day. The risk of a casualty accident in rural areas was 1.6 times that of urban areas.

Type of Motor Carrier and driver history in fatal bus crashes

The Buses Involved in Fatal Accidents (BIFA) project collects detailed information about buses involved in fatal crashes. The BIFA project is supported by the Federal Motor Carrier Safety Administration. Using BIFA data for 1999 to 2005, this study focuses on factors associated with driver errors in fatal bus crashes involving different bus operator types. Five different carrier types were identified: school, transit, intercity, charter or tour, and other. Many factors were associated with driver error, including bus operation type, age, sex, hours driving, trip type, method of compensation, and previous driving record. A logistic regression model was used to model the probability of driver error. Bus operation type, previous violations, and previous crashes were significant parameters in the model. Prior driver violations and crashes both increased the probability that a driver would have been coded with an error in the crash. Transit and school bus drivers were the least likely to have contributed to the crash. Intercity operations were associated with an increase in the odds by 1.9 times, with a 95% confidence interval from 1.1 to 3.2 times. Charter and other bus operations were associated with significantly higher odds of driver error. The odds ratio for charter or tour bus operations was 1.7 (range of 1.2 to 2.4), and for other buses it was 2.6 (range of 1.9 to 3.6). The other factors were not significant.

Condition of Trucks and Truck Crash Involvement: Evidence from the Large Truck Crash Causation Study

This study, using the Large Truck Crash Causation Study (LTCCS), examined the relationship between the mechanical condition of heavy trucks and crash involvement. Two specific hypotheses were tested. First, trucks with defects and out-of-service (OOS) conditions were statistically more likely to be in the role of precipitating a crash than trucks with no defects or OOS conditions. Second, defects in specific systems, such as the brake system, were associated with crash roles in which those systems were primary mechanisms for avoiding the crash and physical mechanisms that link the vehicle defect with the crash role. Postcrash inspections showed that the condition of the trucks in the LTCCS was poor. Almost 55% of the vehicles had one or more mechanical violations. Almost 30% had at least one OOS condition. Of mechanical systems, violations in the brake system (36% of all) and the lighting system (19%) were the most frequent. Both driver and vehicle factors were found to contribute to crashes. A brake OOS condition increased the odds of the trucks being assigned the critical reason (a variable identifying the precipitating vehicle) by 1.8 times. Both hours of service violations and log OOS violations increased the odds by a larger amount—2.0 and 2.2 times respectively. In rear-end and cross-paths crashes, brake violations, especially violations related to adjustment, increased the odds of the trucks being the striking vehicle by 1.8 times.

Analysis of Crash Rates and Surrogate Events: Unified Approach

A preliminary study was done into the use and validation of crash surrogates, which are obtained from naturalistic driving studies for the detailed analysis of risk factors. The approach is based on a unified statistical analysis of crash data and surrogate events that uses a spatial referencing system and a common measure of exposure. Statistical methods based on a bivariate response and Bayesian update models were adapted to the joint analysis of crashes and surrogates. The study specifically addresses road-departure crashes involving a single vehicle. It is proposed that suitable surrogates be based on underlying continuous measures of disturbance in the drivers lateral control of the vehicle. Naturalistic driving data from a field operational test conducted in southeastern Michigan were spatially joined with highway data and crash data from the same area, and a set of candidate crash surrogates was tested. Analysis results indicated that simple lateral lane position did not provide a satisfactory surrogate, whereas estimated time to road departure was found to show the correct statistical dependencies, consistent with the crash data. The approach developed in the study provided a way to assess crash risk in a common framework and also to validate or invalidate candidate surrogates. When applied to data from the future SHRP 2 naturalistic driving study, the increased statistical power resulting from the much larger data set will provide more definitive conclusions about surrogate validity and factors influencing overall crash risk.

Benefits and Costs of Four Approaches to Improving Rollover Stability of Cargo Tank Motor Vehicles

Four broad approaches to decreasing the number of cargo tank rollovers were evaluated: driver training, electronic stability aids, improvements in design of the vehicle itself, and highway design. A study of rollover crash statistics confirmed many expectations, but a few of the factors were not as strong as might have been expected. The portion of rollovers that occur on freeways is 15% to 20%. A driver error of one kind or another (e.g., decision or performance error) figures in about three-fourths of cargo tank rollovers. Inattention and distraction account for about 15%. Evasive maneuvers were a factor in 5% to 10% of rollovers. Drivers must be trained to appreciate the diverse causes for rollovers and to anticipate the situations that lead to them. Adherence to viable work and rest schedules is crucial. Electronic stability aids automatically slow the truck when it rounds a curve too fast. They can be remarkably effective in preventing this scenario. However, crash statistics and anecdotal accounts consistently show many other factors that can lead to rollovers. Significant reductions in rollover rates can be achieved with modest changes in vehicle stability. Cargo tank trailers of improved stability are currently available for some cargoes. When mountainous terrain or other factors dictate highway designs that can contribute to rollovers, drivers need to be made aware through signage or dispatch instructions. A comprehensive benefit–cost analysis, conducted from a societal point of view during a 20-year window, projected that the improvements will be cost beneficial.

Determination of Events Leading to Sport Utility Vehicle Rollover

To determine the major event pathways that result in sport utility vehicle (SUV) rollover, researchers at the University of Michigan Transportation Research Institute examined SUV rollover cases selected from the National Automotive Sampling System crashworthiness data system files for 1999 to 2001. Selected SUVs included the Ford Explorer, Jeep Cherokee, Chevrolet Blazer, Toyota 4-Runner, and GMC Jimmy for model years 1989 to 2001. Researchers coded up to six pre-rollover events, along with the stability of the vehicle (tracking or skidding) after each event. In addition, crash avoidance and recovery maneuvers were recorded, along with the rollover initiation type, location of rollover initiation, direction of roll, number of quarter turns of roll, location of roll, and surface condition at rollover initiation. Approximately 34% of SUV rollovers began with a loss of control caused by tire saturation, and about 75 % of the loss-of-control cases were on icy, wet, or snowy roads. Of the SUVs that ran off the road as the first event, 47% returned to the road before rolling over, and of these, 76% were tracking (presumed under control) before initial road departure. Between 40% and 49% of SUV rollover crashes experienced yaw instability while still on the roadway before roll. These rollovers may be addressed by electronic stability control devices if such devices can increase the control limits of the vehicle.

Prevention of Tractor–Semitrailer Rollovers: Effectiveness of Electronic Stability Control Systems

This study estimated the effectiveness of electronic stability control systems and roll stability control systems in preventing rollovers of heavy-truck tractor–semitrailers. The study combined hardware-in-the-loop simulation with the analysis of independent crash data sets. Engineering and statistical techniques were used to estimate the probable safety benefits of stability control technologies for five-axle tractor–semitrailers. The conventional approach for assessing the safety benefits of vehicle technologies was to analyze crash data sets containing data on the safety performance of vehicles equipped with the technology of interest. Because the deployment of the stability technologies for large trucks was in its infancy, national crash databases did not yet have a sufficient amount of factual data that could be directly linked to the performance of the technologies. Therefore a novel method of examining the potential benefits of these systems was used. This study focused on untripped vehicle rollovers in curves through the examination of crash scenarios that would be likely to benefit from the technologies; the probable effectiveness of each technology was estimated. The analysis in this study did not have the advantage of examining representative crash data sets that contained identifiable data from vehicles equipped with the technologies. Therefore, the analysis was based on probable outcome estimates derived from hardware-in-the-loop simulation, field test experience, and expert panel assessment, and these methods were used to estimate the safety benefits from the national crash data population.

Comparison of Occupant Restraints Based on Injury-Producing Contact Rates

The study aims to evaluate the effectiveness of restraints in preventing injury-producing contacts of specific body regions, such as the head, chest, with specific interior components. Injury-producing contact rates are compared for four restraint configurations: unrestrained, three-point belted, driver air bag alone, and driver airbag plus three-point belt. The three-point belt provides substantial reductions in driver-injury rates for head/face and torso contacts with the glazing, pillar/rails, and steering assembly. The addition of the driver airbag to the three-point belt appears to offer further reductions in these injury rates.

Data and methods for studying commercial motor vehicle driver fatigue, highway safety and long-term driver health

This article summarizes the recommendations on data and methodology issues for studying commercial motor vehicle driver fatigue of a National Academies of Sciences, Engineering, and Medicine study. A framework is provided that identifies the various factors affecting driver fatigue and relating driver fatigue to crash risk and long-term driver health. The relevant factors include characteristics of the driver, vehicle, carrier and environment. Limitations of existing data are considered and potential sources of additional data described. Statistical methods that can be used to improve understanding of the relevant relationships from observational data are also described. The recommendations for enhanced data collection and the use of modern statistical methods for causal inference have the potential to enhance our understanding of the relationship of fatigue to highway safety and to long-term driver health.

Finite Element Approach to Identify the Potential of Improved Heavy-Truck Crashworthiness and Occupant Protection in Frontal Impacts

Interior crash protection has not yet received adequate attention for heavy trucks, as such protection did for automobiles. The goal of this pilot project was to determine the nature of truck crashes that would remain after full deployment of advanced collision avoidance technologies and to assess the crashes with respect to truck driver injury and prevention. Heavy-truck occupant safety was analyzed according to injury pattern and severity to help identify and characterize heavy-truck crashes to define opportunities for improved truck crashworthiness and reduce truck driver fatalities and injuries. A finite element (FE) model combining heavy-truck cabin structure, interior components, dummy, and passive restraint systems was developed to simulate a head-on crash into a rigid barrier at 35 mph, the impact conditions used with the NHTSA new car assessment program test. This crash also represented an impact condition that was overrepresented in real-world crash data and for which there was room for improvement in occupant safety. A full FE tractor semitrailer model was employed to collect the crash pulse resulting on the truck cab as outcome of the computer simulation, which was then applied to defined locations of the FE cab model. Acceleration data were collected from impact of different parts of the dummy with interior components of the occupant compartment to assist in the calculation of body injury levels. The researchers developed a comparative risk study to evaluate the effectiveness of passive safety restraints, which would lead to preliminary guidance on the effectiveness of the use of such occupant injury mitigation systems.