Author: John A. GreenPublisher:
ISBN:
Category : Accidents
Languages : en
Pages : 59
Book Description
Characteristics of Large-truck Accidents as Represented in Texas Accident Data at HSRI.
Author: John A. GreenPublisher:
ISBN:
Category : Accidents
Languages : en
Pages : 59
Book Description
Characteristics of Large-Truck Accidents as Represenated in Texas Accident Data at HSRI
Author: John A. Greensome characteristics of light-truck accidents in texas
Author: john a. greenLarge Truck Accident Causation. Final Report
Author: J. P. EicherExamination of Truck Accidents on Urban Freeways
Author: Brian Lee BowmanPublisher:
ISBN:
Category : Tractor trailer combinations
Languages : en
Pages : 108
Book Description
The objective of this study was to determine the nature and extent of urban freeway accidents involving trucks, over 10,000 lb gross vehicle weight, and their consequences as a function of vehicle type and traffic and roadway characteristics. The study was limited to urban freeways and expressways with large total volumes (minimum 100,000 average daily traffic) and a significant percentage of large truck traffic (minimum 5%). The primary tasks involved a review of the literature, and the analysis of accident and operational data from selected urban freeway sites. A total of 2,221 verified truck accidents were included in the study occurring during 3.75 years on 46.5 miles of freeway. The study determined the characteristics of truck accidents, developed comparisons between truck and passenger vehicle accidents, and estimated the operational and economic consequences of truck accidents. An estimate of the total annual cost of urban freeway accidents was determined to be 634,000 dollars per freeway mile. Applying this estimate to the total 2,497 Interstate and freeway miles, with volumes greater than 100,000 vehicles per day, that exist nationwide results in a nationwide annual cost of 1.6 billion dollars due to truck accidents on urban freeways.
Large-truck Crash Causation Study
Author: Marc StarnesTraffic and Geometric Characteristics Affecting the Involvement of Large Trucks in Accidents: Accident characteristics and fault tree analysis
Author: Nicholas J. GarberPublisher:
ISBN:
Category : Roads
Languages : en
Pages :
Book Description
Recent trends indicate that vehicle miles traveled for large trucks is increasing at a higher rate than for other vehicles. The resulting competition between large trucks and other vehicles for highway space can be expected to result in more multi-vehicle collisions involving large trucks. The likelihood of these collisions causing severe injuries to vehicle occupants will also increase with the trend towards the use of smaller automobiles and heavier and larger trucks. In order to develop countermeasures that will alleviate this problem, it is first necessary to identify the characteristics of large-truck accidents and the role of traffic and geometric variables in such accidents. This study investigated the major factors associated with large truck accidents including the effect of highway facility type and highway geometry, and the development of mathematical models relating the factors with accident rates and probability of occurrence. This first volume documents the methodology of the study, the results of a statistical analysis of large-trucks historical accident data, the results of a fault tree analysis. This second volume gives a detailed description of the development of the regression and logistic models.
Large-Truck Crash Causation Study
Author: National Highway Traffic Safety AdministrationPublisher: CreateSpace
ISBN: 9781492398738
Category : Transportation
Languages : en
Pages : 56
Book Description
The Large-Truck Crash Causation Study (LTCCS) is a data collection project conducted by the National Highway Traffic Safety Administration (NHTSA) and the Federal Motor Carrier Safety Administration (FMCSA) of the United States Department of Transportation (USDOT). NHTSA's National Center for Statistics and Analysis (NCSA) worked together with FMCSA to develop the LTCCS, which was conducted within the National Automotive Sampling System (NASS) that NCSA operates. The tables in this report were created through the use of the data collected in the LTCCS. While the LTCCS collected data on approximately 1,000 variables, the tables presented in this report comprise only a sample of these variables. The complete LTCCS variable database can be used jointly to examine a large number of issues surrounding large-truck crashes. One section in the report focuses on “crash-level” variables, which provide counts of crashes that occurred under certain characteristics (i.e., crash counts stratified according to how many vehicles were in the crash). The next section includes tables that are presented at the “vehicle level.” These tables thus provide counts of the number of vehicles involved in certain types of crashes (i.e., vehicle counts that have been stratified by the injury severity of the person most severely injured in each vehicle). The tables in the following section are presented at the “driver level.” These tables display counts of drivers that were involved in certain crash scenarios (i.e., the number of drivers involved in the crashes, stratified by the age of the driver). The appendix includes tables and computer programs for calculating standard errors and confidence intervals using LTCCS data.
Statistics of Truck Accidents: an Addendum to a Study of Longer and Wider Trucks on the Texas Highway System. Interim Report
Author: Ted Chira-ChavalaSpatial and Temporal Effects of Large Truck-Involved Crash Injury Severities
Author: Jasmine PahukulaPublisher:
ISBN:
Category : Crash injuries
Languages : en
Pages : 84
Book Description
Large truck-involved crashes have a significant impact on both the economy and society. They are associated with high injury severities, high crash costs and contribute to congestion in urban areas. Past studies have investigated the contributing factors of large truck-involved crashes, however a study isolating the spatial and temporal effects is lacking. This thesis aims to bridge that gap as well as provide practical applications to improve safety from a large truck perspective through two new frameworks. This thesis contains two standalone documents, each detailing the spatial and temporal transferability framework, separately. These frameworks provide additional information that can be utilized in the development of planning tools to ultimately improve safety. Random parameters logit models (i.e. mixed logit models) were utilized to help identify the contributing factors of large truck-involved crashes. One advantage of the mixed logit model is that it can account for the unobserved heterogeneity in the model which relaxes the independence of irrelevant alternatives (IIA) property. A series of log likelihood ratio tests were utilized to determine if transferability, spatial or temporal, was warranted. The first document details the spatial transferability framework which is demonstrated through a case study on large truck-involved crashes in urban areas in Oregon and Texas. Strict regulations imposed on the trucking industry limits the variability of heavy-vehicle configurations and enhance the standards for truck drivers (as opposed to passenger vehicle drivers). Encouraging consistency between large trucks is one way to improve safety and has also lead to the investigation of commonalities between large truck-involved crashes in two spatially distributed regions. The results of the log-likelihood ratio tests indicate that spatial transferability is not warranted between Oregon and Texas. Key differences were non-driver or 'uncontrollable' characteristics (e.g. weather, light conditions and time of day) while driver related characteristics (e.g. gender, age and restraint use) had similar impacts. Since the major differences include non-driver characteristics, perhaps a regional model with similar 'uncontrollable' characteristics is warranted. The second document illustrates the temporal transferability framework which is applied to large truck-involved crashes in urban areas in Texas. Traffic patterns, light conditions and driver behavior vary throughout the day and consequently can have a varied impact on large truck-involved crashes. The results of the log likelihood ratio tests indicate that temporal transferability is warranted and the database was divided into five time periods to be analyzed separately. Traffic flow, light conditions, surface conditions, month and percentage of trucks on the road were among the significant differences between the crash factors of each time period. The two proposed transferability frameworks, spatial and temporal, provide new information that can be integrated into safety planning tools and more sharply guide decision-makers. For example, the results of this thesis can help to pinpoint temporal or spatial-related countermeasures. In addition the results of this thesis can help in the allocation of limited resources (i.e. help prioritize projects), minimize economic loss and help decision makers improve safety from a large truck perspective (e.g. modify trucking regulations). Finally, this thesis provides a foundation for future research. As indicated in Chapter 2, a future study to evaluate the feasibility of a regional large truck-involved crash model between neighboring regions and the development of a national crash data reporting standard are potential ideas for future research. Chapter 3 stressed the importance of time of day on large truck-involved crashes which can serve as the basis to study the safety and economic impacts of time of day shifts of truck freight movements to off-peak periods. In summary, this thesis involves original research that expands the literature and provides a new foundation to analyze large truck-involved crashes.