Steering or braking avoidance response in SHRP2 rear-end crashes and near-crashes: A decision tree approach.

OBJECTIVE: The paper presents a systematic analysis of drivers' crash avoidance response during crashes and near-crashes and developed a machine learning-based predictive model that can determine driver maneuver using pre-incident driver behavior and driving context. METHODS: We analyzed 286 naturalistic rear-end crashes and near-crashes from the SHRP2 naturalistic driving study. All the events were manually reduced using face video (face and forward) and kinematic responses. In this paper, we developed new reduction variables that enhanced the understanding of drivers' gaze behavior and roadway attention behavior during these events. These features reflected how the event criticality, measured using time to collision, related to drivers' pre-incident behavior (secondary behavior, gaze behavior), and drivers' perception of the event (physical reaction and maneuver). The imperative understanding of such relations was validated using a random forest- (RF) based classifier, which efficiently predicted if a driver was going to brake or change the lane as an avoidance maneuver. RESULTS: The RF presented in this paper effectively explored the nonlinear patterns in the data and was highly accurate (∼96 %) in its prediction. A further analysis of the RF model showed that six features played a pivotal role in the decision logic. These included the drivers' last glance duration before the event, last glance eccentricity, duration of 'eyes on road' immediately before the event, the time instance and criticality when the driver perceives the threat as well as acknowledge the threat, and possibility of an escape path in the adjacent lane. Using partial dependency plots, we also showed how different thresholds of these feature variables determined the drivers' maneuver intention. CONCLUSIONS: In this paper we analyzed driving context, drivers' behavior, event criticality, and drivers' response in a unified structure to predict their avoidance response. To the best of our knowledge, this is the first such effort where large-scale naturalistic data (crashes and near crashes) was analyzed for prediction of drivers' maneuver and determined key behavioral and contextual factors that contribute to this avoidance maneuver.

Reducing risky driving: Assessing the impacts of an automatically-assigned, targeted web-based instruction program.

INTRODUCTION: Transportation safety research has consistently shown driver behavior is the primary cause in the majority of crashes. This study evaluated the effectiveness of an automatically-assigned, targeted web-based instruction program to reduce risky driving behavior. METHOD: This quasi-experiment used a within-subjects, multiple-baseline stepwise ABC design; where "A" was the Phase I baseline, "B" was the Phase II driver awareness of program, and "C" was the Phase III WBI program. RESULTS: A significant reduction in rates of risky driving behaviors coincided with the implementation of the WBI program, even for those drivers who did not receive WBI but were included in the program. More specifically, excessive speeding was significantly reduced by 73.93% from baseline to intervention across all drivers. For those drivers who received WBI, the program coincided with statistically significant reductions in speeding, hard braking, and hard cornering. The first WBI course assigned and completed was the most impactful in reducing at-risk driving behavior. CONCLUSIONS: These results show that the automatically-assigned, targeted WBI program was an effective method in reducing risky driving behaviors, not only for those drivers that received training, but for all drivers. The authors hypothesize the reduction in risky driving behaviors was not the result of the WBI, but instead from the implicit feedback of being assigned a training courses, the development of implicit, non-specific goals to reduce risky driving behaviors that result in a WBI course assignment, and the resulting increased driver accountability created by the WBI program. Practical application: Through the use of an automatically-assigned, targeted WBI program, fleets may have fewer crashes and insurance claims. This reduction in crashes and insurance claims may result in lower insurance premiums and may help to prevent injuries and save lives.

Prevalence of operator fatigue in winter maintenance operations.

Similar to commercial motor vehicle drivers, winter maintenance operators are likely to be at an increased risk of becoming fatigued while driving due to long, inconsistent shifts, environmental stressors, and limited opportunities for sleep. Despite this risk, there is little research concerning the prevalence of winter maintenance operator fatigue during winter emergencies. The purpose of this research was to investigate the prevalence, sources, and countermeasures of fatigue in winter maintenance operations. Questionnaires from 1043 winter maintenance operators and 453 managers were received from 29 Clear Road member states. Results confirmed that fatigue was prevalent in winter maintenance operations. Over 70% of the operators and managers believed that fatigue has a moderate to significant impact on winter maintenance operations. Approximately 75% of winter maintenance operators reported to at least sometimes drive while fatigued, and 96% of managers believed their winter maintenance operators drove while fatigued at least some of the time. Furthermore, winter maintenance operators and managers identified fatigue countermeasures and sources of fatigue related to winter maintenance equipment. However, the countermeasures believed to be the most effective at reducing fatigue during winter emergencies (i.e., naps) were underutilized. For example, winter maintenance operators reported to never use naps to eliminate fatigue. These results indicated winter maintenance operations are impacted by operator fatigue. These results support the increased need for research and effective countermeasures targeting winter maintenance operator fatigue.

Analysis of bus drivers reaction to simulated traffic collision situations - eye-tracking studies.

OBJECTIVES: The aim of the study was to establish whether the driver's visual strategy may influence a driver's behavior to avoid a crash in a high-risk situation. Any published papers on drivers' visual strategies just before a crash were not found. MATERIAL AND METHODS: Tests were performed using a high-tech driving bus simulator. Participants comprised 45 men drivers, aged 43.5±7.9 years old, seniority as a bus driver of 13.3±8.6 years. The tests were preceded by medical examinations: general, neurological and ophthalmological. Each participant drove the same city route for approximately 40 min (entire route - ER). In the final phase, a collision situation was simulated (a phantom car blocked the participant's right of way). Driver's visual strategy was analyzed using the FaceLab device with 2 cameras during ER and just before collision. The field-of-view covered by camera 1 was divided into 8 regions, by camera 2 into 10 regions. The distribution of gazes in regions was a criterion of visual strategy. RESULTS: Thirty-five drivers completed the simulated driving test, 14 escaped the collision, 21 crashed. These groups differed only in resting systolic blood pressure before the test. The analysis of covariance, after adjusting to this factor, indicated that during the ER visual strategy recorded by camera 1 did not differ between groups, in camera 2 the drivers in the crash group fixed their gaze more frequently (p = 0.049) in region 3 (close part of the road in front of the windshield). Just before the collision drivers who escaped the collision fixed their gaze significantly more often in region 6 (left side of the road) in camera 1 and in region 6 (in front of the windshield,) and region 10 (right side) in camera 2. CONCLUSIONS: The visual strategy has an impact on the road safety. The analysis of visual strategies may be a useful tool for the training of drivers. Int J Occup Med Environ Health. 2019;32(2):161-74.

A synthetic approach to compare the large truck crash causation study and naturalistic driving data.

Truck crashes represent a significant problem on our nation's highways. There is a great opportunity to learn about crash causation by analyzing and comparing the Large Truck Crash Causation Study (LTCCS) and naturalistic driving (ND) data. These data sets provide in-depth information, but have contrasting strengths and weaknesses. The LTCCS contains information on high-severity crashes (crashes and fatal crashes), but relied on data collected during crash investigations. The LTCCS identified principal driver errors in the crash, such as the Critical Reason, but not detailed behaviors or scenario sequences. The ND data sets relate primarily to non-crashes that are detectable from dynamic vehicle events, such as hard braking, swerve, etc., provide direct video observations of the driver and the surrounding driving scene and precise information on driver inputs (kinematics) and captured events, and provide certain types of exposure data that cannot easily be obtained using crash reconstruction data. The ND data are collected continuously, thereby capturing both safety-critical events and normative driving (i.e., baseline). The current project evaluated large-truck crash data from the LTCCS and two large-truck ND data sets, the Naturalistic Truck Driving Study and the Drowsy Driver Warning System Field Operational Test. A synthetic risk ratio analysis on the associated factor, Following Too Closely, indicated that truck drivers in the LTCCS were 1.34 times more likely to be involved in a crash, than an ND crash-relevant conflict, if they were following too closely (i.e., tailgating). Given several caveats noted in the paper, this study suggests it's possible to use the ND data set to calculate the exposure of a given behavior and use the LTCCS data set to calculate the crash exposure to the same behavior.

Do the benefits outweigh the costs? Societal benefit-cost analysis of three large truck safety technologies.

Although research has found advanced safety technologies to be effective at preventing large truck crashes, limited empirical data exists regarding their cost effectiveness to the U.S. society. Without these data, carriers are hesitant to adopt costly technologies and government agencies are hesitant to create regulation mandating their use. The objective of this study was to provide scientifically-based estimates of the societal benefits and costs of large truck automatic emergency braking (AEB), lane departure warning (LDW), and video-based onboard safety monitoring (OSM). For each technology, benefit-cost analyses were performed for installing the technology on all large trucks (including retrofitting existing trucks) and for equipping new large trucks only. Sensitivity analyses examined three cost estimates (low, average, high; values technology-specific), two estimates of system efficacy (low and high; values technology-specific), and three discount rates (0%, 3%, 7%) for each technology. Equipping trucks with LDW and video-based OSM systems were found to be cost effective for all combinations of costs, efficacy, and discount rates examined, for both new and existing trucks. Results for AEB and were mixed. Only a $500 AEB system was cost effective when equipping new trucks and retrofitting existing trucks. However, all cost estimates were cost effective with a 28% efficacy rate when only equipping new large trucks. Overall, these data suggested all three technologies can be cost-effective for new large trucks provided the current costs and efficacy rates can be maintained or improved upon.

An observational study of the safety benefits of electronic logging devices using carrier-collected data.

OBJECTIVE: Fatigue has been shown to be a contributing factor in many large truck crashes. Long duty periods, irregular work schedules, and poor sleeping environments make fatigue a noteworthy concern in trucking operations. One way to limit fatigued driving is through prescriptive hours-of-service (HOS) regulations. This duty status information is typically recorded in written logs; however, more trucking companies are moving toward electronic HOS recorders. These devices were first marketed as productivity tools; however, more recently they have been touted for their safety benefits in reducing fatigued truck drivers (because falsifying electronic logs is difficult). METHODS: The purpose of the current study was to assess the benefits of electronic logging devices (ELDs) on safety and HOS violations in trucks as they operated during normal revenue service. Data on crashes, HOS violations, mileage, and onboard safety systems were obtained from participating motor carriers. Although the final data sets included data from 11 carriers representing medium and large carriers (including a total of 82,943 crashes, 970 HOS violations, and 224,034 truck-years that drove a total of 15.6 billion miles), the data set in the study was skewed toward larger, for-hire carriers and may not represent the overall U.S. trucking population. RESULTS: After controlling for calendar year, carriers in the data set, onboard safety system status, and long-haul/regional indicator, ELD-equipped trucks had a significantly lower total crash rate (11.7% reduction), preventable crash rate (5.1% reduction), driving-related HOS violation rate (53% reduction), and non-driving-related HOS violation rate (49% reduction) than trucks not equipped with ELDs. CONCLUSION: The results show a clear safety benefit, in terms of crash and HOS violation reductions, for trucks equipped with ELDs.

Benefit-cost analysis of lane departure warning and roll stability control in commercial vehicles.

INTRODUCTION: This paper presents the cost benefits of two different onboard safety systems (OSS) installed on trucks as they operated during normal revenue deliveries. Using a formal economic analysis approach, the study quantified the costs and benefits associated with lane departure warning (LDW) systems and roll stability control (RSC) systems. METHODS: The study used data collected from participating carriers (many of these crashes were not reported to state or Federal agencies), and the research team also reviewed each crash file to determine if the specific OSS would have mitigated or prevented the crash. The deployment of each OSS was anticipated to increase the safety of all road users, but impact different sectors of society in different ways. Benefits that were inherent in each group (e.g., industry, society) were considered, and different benefit-cost analyses (BCAs) were performed. RESULTS: This paper presents two BCAs: a BCA focused on the costs and benefits in the carrier industry by implementing each OSS, and a BCA that measured the societal benefits of each OSS. In addition, a BCA for a theoretical mandatory deployment option for each OSS is presented. CONCLUSIONS: BCA results for LDW and RSC clearly showed their benefits outweighed their costs for the carrier and society. Practical applications: Cost information is a crucial factor in purchasing decisions in carriers; similarly, regulators must consider the cost burden prior to mandating technologies. The results in this study provide carrier decision makers and regulators with information necessary to make an informed decision regarding RSC and LDW.

Nonadherence with Employer-Mandated Sleep Apnea Treatment and Increased Risk of Serious Truck Crashes.

STUDY OBJECTIVES: To evaluate the effect of an employer-mandated obstructive sleep apnea (OSA) program on the risk of serious preventable truck crashes. METHODS: Data are from the first large-scale, employer-mandated program to screen, diagnose, and monitor OSA treatment adherence in the US trucking industry. A retrospective analysis of cohorts was constructed: polysomnogram-diagnosed drivers (OSA positive n = 1,613, OSA negative n = 403) were matched to control drivers unlikely to have OSA (n = 2,016) on two factors affecting crash risk, experience-at-hire and length of job tenure; tenure was matched on the date of each diagnosed driver's polysomnogram. Auto-adjusting positive airway pressure (APAP) treatment was provided to all cases (i.e. OSA positive drivers); treatment adherence was objectively monitored. Cases were grouped by treatment adherence: "Full Adherence" (n = 682), "Partial Adherence" (n = 571), or "No Adherence" (n = 360). Preventable Department-of-Transportation-reportable crashes/100,000 miles were compared across study subgroups. Robustness was assessed. RESULTS: After the matching date, "No Adherence" cases had a preventable Department of Transportation-reportable crash rate that was fivefold greater (incidence rate ratio = 4.97, 95% confidence interval: 2.09, 10.63) than that of matched controls (0.070 versus 0.014 per 100,000 miles). The crash rate of "Full Adherence" cases was statistically similar to controls (incidence rate ratio = 1.02, 95% confidence interval: 0.48, 2.04; 0.014 per 100,000 miles). CONCLUSIONS: Nontreatment-adherent OSA-positive drivers had a fivefold greater risk of serious preventable crashes, but were discharged or quit rapidly, being retained only one-third as long as other subjects. Thus, the mandated program removed risky nontreatment-adherent drivers and retained adherent drivers at the study firm. Current regulations allow nonadherent OSA cases to drive at another firm by keeping their diagnosis private. COMMENTARY: A commentary on this article appears in this issue on page 961.

Efficacy of roll stability control and lane departure warning systems using carrier-collected data.

INTRODUCTION: Large truck crashes have significantly declined over the last 10 years, likely due, in part, to the increased use of onboard safety systems (OSS). Unfortunately, historically there is a paucity of data on the real-world efficacy of these devices in large trucks. The purpose of this study was to evaluate the two OSSs, lane departure warning (LDW) and roll stability control (RSC), using data collected from motor carriers. METHOD: A retrospective cohort approach was used to assess the safety benefits of these OSSs installed on Class 7 and 8 trucks as they operated during normal revenue-producing deliveries. Data were collected from 14 carriers representing small, medium, and large carriers hauling a variety of commodities. The data consisted of a total of 88,112 crash records and 151,624 truck-years that traveled 13 billionmiles over the observation period. RESULTS: The non-LDW cohort had an LDW-related crash rate that was 1.917 times higher than the LDW cohort (p=0.001), and the non-RSC cohort had an RSC-related crash rate that was 1.555 times higher than the RSC cohort (p<0.001). CONCLUSIONS: The results across analyses indicated a strong, positive safety benefit for LDW and RSC under real-world conditions. PRACTICAL APPLICATIONS: The results support the use of LDW and RSC in reducing the crash types associated with each OSS.

A safety self-management intervention for mining operations.

PROBLEM: This quasi-experimental field study examined the efficacy of a safety self-management process to increase safety-related work practices in mining operations. METHODS: After a 7-week baseline, 15 miners participated in a safety self-management training and education presentation. The participants in a prebehavior condition (n=8) recorded their intentions to engage in specific percentages of safety-related work behaviors before starting their shift for the day. In contrast, participants in a postbehavior condition (n=7) recorded their percentages of safety-related work behaviors after their shift for the day. RESULTS: During withdrawal (4 weeks), the miners did not complete any self-monitoring forms. Based on 10,905 behavioral observations, safety self-management was effective at increasing the frequency of safety-related behavior (p<.05). For the prebehavior condition, the mean percent safe score across three target behaviors increased 34.8% during intervention. Similarly, in the postbehavior condition, the mean percent safe score across three target behaviors increased 40.1% during intervention. IMPACT ON INDUSTRY: The results suggest that employees who work in relative isolation or have little oversight, compared to traditional industrial workers, may benefit from a process by which they can systematically observe themselves.

The Airline Lifesaver: a 17-year analysis of a technique to prompt the delivery of a safety message.

INTRODUCTION: The Airline Lifesaver (AL) is a 13.3 cm x 9.8 cm card any passenger can deliver to the attendant of a commercial airline in order to prompt the delivery of an important safety message. In particular, the AL requests the following safety--belt reminder be added to the regular announcements given at the end of the flight-"Now that you have worn a seat belt for the safest part of your trip, the flight crew would like to remind you to buckle-up during your ground transportation." METHOD: The AL card was handed to 1,258 flight attendants over a 17-year period and compliance with the request for the safety message was systematically tracked. Slightly more than one-third of the AL cards (n=460) included an incentive for making the announcement. RESULTS: Without the incentive, compliance to give the buckle-up reminder was 35.5% of 798 flights. With the incentive, compliance was significantly higher (i.e., 53.3%). IMPACT: The validity of the AL intervention is discussed with regard to its: (a) relevance to cognitive dissonance and consistency theory, and (b) broad-based applicability as a component of community-wide efforts to facilitate a safety-focused culture. The 17-year study also demonstrated a practical and cost-effective application of a behavior-based incentive program.

An assessment of commercial motor vehicle driver distraction using naturalistic driving data.

OBJECTIVE: This study analyzed naturalistic driving data from commercial trucks (3-axle and tractor-trailer/tanker) and buses (transit and motorcoach) during a 3-month period. METHODS: The data set contained 183 commercial truck and bus fleets comprising 13,306 vehicles and included 1085 crashes, 8375 near crashes, 30,661 crash-relevant conflicts, and 211,171 baseline events. Study results documented the prevalence of tertiary tasks and the risks associated with performing these tasks while driving. RESULTS: Results indicated the odds of involvement in a safety-critical event differed as a function of performing different cell phone-related subtasks while driving. Although the odds ratio for talking/listening on a cell phone while driving was found to not significantly increase the likelihood of involvement in a safety-critical event, other cell phone subtasks (e.g., texting, dialing, reaching) were found to significantly increase the odds of involvement in a safety-critical event. CONCLUSIONS: The results suggest that cell phone use while driving should not be considered a simple dichotomous task (yes/no). Consideration should instead be made for a set of discrete cell phone subtasks that are each associated with varying levels of risk. Several hypotheses are presented to explain why cell phone use while driving was found to not increase the likelihood of involvement in a safety-critical event.

Evaluating the 2003 revised hours-of-service regulations for truck drivers: the impact of time-on-task on critical incident risk.

On January 4th, 2004, the Federal Motor Carrier Safety Administration implemented a revised set of regulations concerning the hours-of-service (HOS) of commercial motor vehicle (CMV) drivers. One central component of the revised HOS regulations was a one-hour increase in allowable driving time, from 10 to 11h. The current study evaluated the impact of the additional driving-hour on critical incident risk. Data from a naturalistic truck driving study, which resulted in over 2 million driving miles of continuously collected data, were analyzed. Driving hour bins (hours 1 through 11) were created and the frequency of critical incidents for each hour, and trips (opportunities) per each hour, were identified. A relative frequency was then calculated (critical incidents divided by opportunities) for each hour and odds ratios were determined. Analyses found an elevated risk in the 1st driving-hour, but no consistent significant difference between hours 2 through 11. Analyses on time-of-day, where incident rates were calculated for each of the 24h in the day, were also conducted. The results found a strong positive correlation to national traffic density data. As an impact on U.S. national transportation policy, the results of this study do not support the hypothesis that there is an increased risk resulting from CMV drivers driving in the 11th driving-hour as compared to the 10th driving-hour, or any hour.