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The last ten years have seen explosive growth in the technology available to the collision analyst, changing the way reconstruction is practiced in fundamental ways. The greatest technological advances for the crash reconstruction community have come in the realms of photogrammetry and digital media analysis. The widespread use of scanning technology has facilitated the implementation of powerful new tools to digitize forensic data, create 3D models and visualize and analyze crash vehicles and environments. The introduction of unmanned aerial systems and standardization of crash data recorders to the crash reconstruction community have enhanced the ability of a crash analyst to visualize and model the components of a crash reconstruction. Because of the technological changes occurring in the industry, many SAE papers have been written to address the validation and use of new tools for collision reconstruction. Collision Reconstruction Methodologies Volumes 1-12 bring together seminal SAE technical papers surrounding advancements in the crash reconstruction field. Topics featured in the series include: • Night Vision Study and Photogrammetry • Vehicle Event Data Recorders • Motorcycle, Heavy Vehicle, Bicycle and Pedestrian Accident Reconstruction The goal is to provide the latest technologies and methodologies being introduced into collision reconstruction - appealing to crash analysts, consultants and safety engineers alike.
Promoting human health and safety by reducing exposures to risks and harms through regulatory interventions is among the most important responsibilities of the government. Such efforts encompass a wide array of activities in many different contexts: improving air and water quality; safeguarding the food supply; reducing the risk of injury on the job, in transportation, and from consumer products; and minimizing exposure to toxic chemicals. Estimating the magnitude of the expected health and longevity benefits and reductions in mortality, morbidity, and injury risks helps policy makers decide whether particular interventions merit the expected costs associated with achieving these benefits and inform their choices among alternative strategies. Valuing Health for Regulatory Cost-Effectiveness Analysis provides useful recommendations for how to measure health-related quality of- life impacts for diverse public health, safety, and environmental regulations. Public decision makers, regulatory analysts, scholars, and students in the field will find this an essential review text. It will become a standard reference for all government agencies and those consultants and contractors who support the work of regulatory programs.
This report presents the results of an analysis effort undertaken to address the following research question: What sensor(s) can be cost effectively added to vehicles on a wide scale to significantly improve our understanding and modeling of naturalistic near-crash/pre-crash driver performance? Current sensor and computer technology allows for the efficient collection and storage of driver and vehicle performance data on board vehicles. Crash data recorders or black boxes exist today on many vehicles though they are limited in number of recorded parameters and storage capacity. However, their capability is increasing. Recent field operational tests of advanced-technology crash avoidance systems and naturalistic driving data collection efforts have employed comprehensive data acquisition systems to characterize driver and vehicle performance as well as the driving environment. These projects gathered data on driver exposure to various environmental factors and on driver encounters with driving conflicts, near-crashes, and actual crashes. Unfortunately, the in-vehicle data acquisition packages in these projects cost over $10,000 per vehicle. It would be advantageous to build and install a very small, inexpensive package under $1,000 in a vehicle fleet of 5,000 or more. The presence of low-cost near-crash/crash event data recorders (EDRs) on thousands of vehicles would enable a more accurate assessment of safety benefits for intelligent vehicle crash avoidance technologies, and would greatly improve the quality of data in national crash databases such as the National Automotive Sampling System (NASS) Crashworthiness Data System (CDS) and General Estimates System (GES).
"This SAE Special Publication presents papers from the sessions Safety Test Methodology and Structural Crashworthiness held during the SAE 2006 World Congress, held April 3-6, 2006 in Detroit, Michigan, USA."--Pref.
The previous edition of this useful text on epidemiologic methods for studying injuries and evaluating interventions to prevent them provides specific objectives for research in the various stages of injury control planning and implementation, including the types of data needed to reach the objectives. Using a progressive, step-by-step analysis, it illustrates how to pose research questions and design the best research studies to answer those questions. This new edition will update all chapters and include new examples of studies. The chapters will also be organized into more precise topic areas for ease of reference. The chapter on policy analysis would be dissolved and topic treated as part of other chapters.
There are approximately 4,000 fatalities in crashes involving trucks and buses in the United States each year. Though estimates are wide-ranging, possibly 10 to 20 percent of these crashes might have involved fatigued drivers. The stresses associated with their particular jobs (irregular schedules, etc.) and the lifestyle that many truck and bus drivers lead, puts them at substantial risk for insufficient sleep and for developing short- and long-term health problems. Commercial Motor Vehicle Driver Fatigue, Long-Term Health and Highway Safety assesses the state of knowledge about the relationship of such factors as hours of driving, hours on duty, and periods of rest to the fatigue experienced by truck and bus drivers while driving and the implications for the safe operation of their vehicles. This report evaluates the relationship of these factors to drivers' health over the longer term, and identifies improvements in data and research methods that can lead to better understanding in both areas.