Feasibility of developing training programs designed to improve deficient driver factors. Volume II: identifying accident avoidance behaviors: a guide for accident investigators. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Training program for accident investigation and coding in the National Crash Severity Study. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

The National Accident Sampling System - a status report. Volume III: implementation of NASS subsystems.

Mode of access: Internet.

Accident investigation technician instructor training institute. Volume 1. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Highway collision investigation training program. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

NASS investigator training - evaluation of the first training cycle. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Tracking rail safety : incident and accident investigation in Australia

Scoping Project: Currently no national or structured learning framework available in Aus or NZ Current Project: Develop a national training program & capability framework for rail incident investigators - Establish the potential market demand - Define the curricula for a multi-level national training program - Explore training providers & delivery options

Keep ahead of the workforce development curve through the establishment of standardised training for rail incident investigators

The Australasian rail industry lacks a consistently accepted standard of minimal training necessary to perform rail incident investigations. Current Australasian courses do not offer the breadth of development required for a comprehensive career pathway in incident investigation (Biggs, Banks & Dovan, 2012; Short, Kains & Harris, 2010).

Accident, provocation and jury reforms

In 2008, there were a number of areas in the criminal law in Queensland in which there was law reform activity. These include jury reform, accident and provocation.

Research participation of individuals with dementia : decisional capacity, informed consent, and considerations for nurse investigators

Decisional capacity is a precious component of personhood and is progressively diminished in dementia. Conducting research with individuals with dementia demands a commitment to ensure the quest for knowledge does not overwhelm the rights of those it is intended to protect. The purposes of this article are to describe current understandings of the concept of decisional capacity, describe recent regulatory developments related to the consideration of additional protections for decisionally impaired adults, and provide recommendations for nurse investigators working with this vulnerable group.

Systems-based accident analysis in the led outdoor activity domain : application and evaluation of a risk management framework

Safety-compromising accidents occur regularly in the led outdoor activity domain. Formal accident analysis is an accepted means of understanding such events and improving safety. Despite this, there remains no universally accepted framework for collecting and analysing accident data in the led outdoor activity domain. This article presents an application of Rasmussen's risk management framework to the analysis of the Lyme Bay sea canoeing incident. This involved the development of an Accimap, the outputs of which were used to evaluate seven predictions made by the framework. The Accimap output was also compared to an analysis using an existing model from the led outdoor activity domain. In conclusion, the Accimap output was found to be more comprehensive and supported all seven of the risk management framework's predictions, suggesting that it shows promise as a theoretically underpinned approach for analysing, and learning from, accidents in the led outdoor activity domain.

Development of accident modification factors on intersection crash maneuvers

In order to estimate the safety impact of roadway interventions engineers need to collect, analyze, and interpret the results of carefully implemented data collection efforts. The intent of these studies is to develop Accident Modification Factors (AMF's), which are used to predict the safety impact of various road safety features at other locations or in upon future enhancements. Models are typically estimated to estimate AMF's for total crashes, but can and should be estimated for crash outcomes as well. This paper first describes data collected with the intent estimate AMF's for rural intersections in the state of Georgia within the United Sates. Modeling results of crash prediction models for the crash outcomes: angle, head-on, rear-end, sideswipe (same direction and opposite direction) and pedestrian-involved crashes are then presented and discussed. The analysis reveals that factors such as the Annual Average Daily Traffic (AADT), the presence of turning lanes, and the number of driveways have a positive association with each type of crash, while the median width and the presence of lighting are negatively associated with crashes. The model covariates are related to crash outcome in different ways, suggesting that crash outcomes are associated with different pre-crash conditions.

Empirical investigation of interactive highway safety design model accident prediction algorithm : Rural intersections

One major gap in transportation system safety management is the ability to assess the safety ramifications of design changes for both new road projects and modifications to existing roads. To fulfill this need, FHWA and its many partners are developing a safety forecasting tool, the Interactive Highway Safety Design Model (IHSDM). The tool will be used by roadway design engineers, safety analysts, and planners throughout the United States. As such, the statistical models embedded in IHSDM will need to be able to forecast safety impacts under a wide range of roadway configurations and environmental conditions for a wide range of driver populations and will need to be able to capture elements of driving risk across states. One of the IHSDM algorithms developed by FHWA and its contractors is for forecasting accidents on rural road segments and rural intersections. The methodological approach is to use predictive models for specific base conditions, with traffic volume information as the sole explanatory variable for crashes, and then to apply regional or state calibration factors and accident modification factors (AMFs) to estimate the impact on accidents of geometric characteristics that differ from the base model conditions. In the majority of past approaches, AMFs are derived from parameter estimates associated with the explanatory variables. A recent study for FHWA used a multistate database to examine in detail the use of the algorithm with the base model-AMF approach and explored alternative base model forms as well as the use of full models that included nontraffic-related variables and other approaches to estimate AMFs. That research effort is reported. The results support the IHSDM methodology.