Alejandra Medina-Flintsch

Probe Vehicles Used to Measure Road Ride Quality: Pilot Demonstration

New vehicle technology is leading to efficient methods for assessing the condition of the National Highway System. The use of simple sensors such as accelerometers, installed in vehicles, could provide a cost-effective way to assess ride quality for pavement management. A pilot study compared data gathered from accelerometers with the current state-of-the-art practices for measuring ride quality. After a review of relevant previous studies involving probe vehicles, this study assessed the use of probe vehicles’ acceleration measurements to evaluate the pavement profile. The repeatability of acceleration measurements with cross-correlation and standard deviation was obtained. With visual methods and the coherence function, acceleration measurements were compared with profile measurements obtained from inertial profilers. The literature review reinforced the view that using probe vehicles for pavement condition data collection would be promising and that measuring pavement condition with typical onboard sensors could provide a cost-effective way to collect data for pavement management. Probe vehicles are most practically used in pavement management applications to describe ride quality by using vehicle accelerometers and the Global Positioning System. The pilot study confirmed that the acceleration runs were repeatable. Visual inspection of the acceleration and profile plots suggested that the acceleration profiles and smoothness measurements were similar. Analysis with the coherence function also confirmed this strong relationship. The tested methodology provides a practical way to evaluate smoothness while providing a wider base of coverage compared with that of inertial profilers.

New approach for managing pavement friction and reducing road crashes

Evaluation of crash count data as a function of roadway characteristics allows departments of transportation (DOTs) to predict expected average crash risks to assist in identifying segments that could benefit from various treatments. Crash risk is modeled using negative binomial regression, as a function of annual average daily traffic (AADT) and other variables. For this paper, a crash study was carried out for the Interstate, primary, and secondary routes in the Salem District of Virginia. The data used in the study included the following information obtained from Virginia DOT records: 2010 to 2012 crash data, 2010 to 2012 AADT, and horizontal radius of curvature. In addition, tire–pavement friction, or skid resistance, was measured with a continuous friction measurement, fixed-slip device called a GripTester. Negative binomial regression was used to relate the crash data to the AADT, skid resistance, and horizontal radius of curvature. To determine which of the variables to include in the final models, researchers performed the Akaike information criterion test. By mathematically combining the information acquired from the negative binomial regression models and the information contained in the crash counts, researchers empirically estimated the parameters of each network’s true average crash risks with the empirical Bayes approach. The new estimated average crash risks were then used to rank segments according to their empirically estimated crash risk and to prioritize segments according to their expected crash reduction if a friction treatment were applied.

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.

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

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

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.

Cost–Benefit Analysis of Four Large Truck Advanced Safety Technologies

INTRODUCTIONnThis 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.nnnMETHODSnThe 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.nnnRESULTSnThis 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.nnnCONCLUSIONSnBCA 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.