Michigan traffic accident facts /

Description based on: Year 1953; title from cover.

Railroad employee accident investigation report.

Mode of access: Internet.

Causative factors and countermeasures for rural and suburban pedestrian accidents : accident data collection and analysis : appendices /

Mode of access: Internet.

Traffic Accident Facts for Michigan

Mode of access: Internet.

Railroad Accident Investigation

Title Varies: Investigation In the Matter of Making Accident Investigation Reports; Report In the Matter of Making Accident Investigation Reports

A redesign of a road traffic accident reporting system using business process simulation

Business process simulation (BPS) is used to evaluate the effect of the redesign of a police road traffic accident (RTA) reporting system. The new system aims to provide timely statistical analysis of traffic behaviour to government bodies and to enable more effective utilisation of traffic police personnel. The simulation method is demonstrated in the context of assisting process change enabled by the use of information systems in an organisation in which there had been a historically mixed pattern of success in this activity.

Rural road accident investigation and prevention in Iran

The objectives are to examine rural road accident data in order to develop a method by which high accident rate locations and accident causes can be identified, and also to develop proposals for improvements at such locations and to identify measures which will improve road safety throughout the country. The problem of road safety in Iran is an important issue, because of the tragic and unnecessary loss of life, and the enormous cost of accidents in the country. The resources available to deal with the problems are limited and must be allocated on priority basis. This study represents an initial effort to identify the extent of the problem in order to take remedial measures. A study was made of all the available road accident data collected by agencies related to road safety in Iran, and the major organisations responsible for road safety development were visited. The Vice Minister of Roads and Transportation selected for this study a 280 Km rural road in South West Iran. Mainly because of the lack of suitable maps and plans of the roads, it was not possible to accurately identify the location of accidents. Accident scene data was subsequently collected by the highway police and personally by the author. The data for the study road was then analysed to identify 'high accident rate' locations, and also to determine, as far as was possible, the reasons for the accidents. The study suggests specific improvements for each of the high accident rate locations examined (eg. the building of dual carriageways with central guard rails to reduce the risk of collision with oncoming vehicles, pedestrian facilities to allow pedestrians to cross dangerous roadsl]. In addition recommendations are made to guide and assist the major organisations responsible for road safety in Iran. These recommendations are: (al for improving accident data collection and storage (bl for subsequent analysis for taking remedial measures with a view to accident prevention

Estimation and prediction of average vehicle occupancies using traffic accident records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver’s age, and driver’s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Estimation and Prediction of Average Vehicle Occupancies using Traffic Accident Records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver¡¯s age, and driver¡¯s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Passenger vehicle median crossover and head-on collision with another passenger vehicle, Linden, New Jersey, May 1, 2003 /

"PB2006-916202."

Collision deformation classification training program : intermediate level /

Mode of access: Internet.

The effect of truck size and weight on accident experience and traffic operations. Volume 1: executive summary. Final report.

Federal Highway Administration, Washington, D.C.

The effect of truck size and weight on accident experience and traffic operations. Volume II: traffic operations. Final report.

Federal Highway Administration, Washington, D.C.