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Book Development and Application of Crash Severity Models for Highway Safety

Download or read book Development and Application of Crash Severity Models for Highway Safety written by and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first edition of the Highway Safety Manual has provided methods and procedures for estimating total crashes, crashes by type, and crashes by severity at the site level, project level and corridor level. Crash prediction models are critical in the entire safety management system recommended by HSM, including network screening, economic analysis, project prioritization, and safety effectiveness evaluation. NCHRP Web-Only Document 351: Development and Application of Crash Severity Models for Highway Safety: Conduct of Research Report, from TRB's National Cooperative Highway Research Program, is supplemental to NCHRP Research Report 1047: Development and Application of Crash Severity Models for Highway Safety: User Guidelines. The document seeks to identify gaps and opportunities in the current severity prediction/estimation procedures within the HSM, to develop and validate new severity models to address the gaps and opportunities, and to develop a guidance document that includes protocols for the use and application of severity-based models in a format suitable for possible adoption in the HSM.

Book Development and Application of Crash Severity Models for Highway Safety

Download or read book Development and Application of Crash Severity Models for Highway Safety written by John Naylor Ivan and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This report presents guidelines on evaluating crash severity estimation models for use in different site conditions. The guidelines will be of interest to state departments of transportation (DOTs) seeking more informed model application, broader acceptance of model results, and, ultimately, improved safety decision making. The guidelines could also be applied to existing crash prediction models and serve to improve pertinent models and model elements in the Highway Safety Manual (HSM) and its associated tools." -- publisher's website

Book Highway Safety Manual

Download or read book Highway Safety Manual written by and published by AASHTO. This book was released on 2010 with total page 886 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The Highway Safety Manual (HSM) is a resource that provides safety knowledge and tools in a useful form to facilitate improved decision making based on safety performance. The focus of the HSM is to provide quantitative information for decision making. The HSM assembles currently available information and methodologies on measuring, estimating and evaluating roadways in terms of crash frequency (number of crashes per year) and crash severity (level of injuries due to crashes). The HSM presents tools and methodologies for consideration of 'safety' across the range of highway activities: planning, programming, project development, construction, operations, and maintenance. The purpose of this is to convey present knowledge regarding highway safety information for use by a broad array of transportation professionals"--p. xxiii, vol. 1.

Book Highway Safety Analytics and Modeling

Download or read book Highway Safety Analytics and Modeling written by Dominique Lord and published by Elsevier. This book was released on 2021-02-27 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Highway Safety Analytics and Modeling comprehensively covers the key elements needed to make effective transportation engineering and policy decisions based on highway safety data analysis in a single. reference. The book includes all aspects of the decision-making process, from collecting and assembling data to developing models and evaluating analysis results. It discusses the challenges of working with crash and naturalistic data, identifies problems and proposes well-researched methods to solve them. Finally, the book examines the nuances associated with safety data analysis and shows how to best use the information to develop countermeasures, policies, and programs to reduce the frequency and severity of traffic crashes. Complements the Highway Safety Manual by the American Association of State Highway and Transportation Officials Provides examples and case studies for most models and methods Includes learning aids such as online data, examples and solutions to problems

Book State Trunk Highway Safety and Geometrics  Technical Report

Download or read book State Trunk Highway Safety and Geometrics Technical Report written by David A. Woldseth and published by . This book was released on 1998 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Roadside Design Guide

    Book Details:
  • Author : American Association of State Highway and Transportation Officials. Task Force for Roadside Safety
  • Publisher :
  • Release : 1989
  • ISBN :
  • Pages : 560 pages

Download or read book Roadside Design Guide written by American Association of State Highway and Transportation Officials. Task Force for Roadside Safety and published by . This book was released on 1989 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Crash Severity Modeling in Transportation Systems

Download or read book Crash Severity Modeling in Transportation Systems written by Azad Salim Abdulhafedh and published by . This book was released on 2016 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling crash severity is an important component of reasoning about the issues that may affect highway safety. A better understanding of the factors underlying crash severity can be used to reduce the degree of crash severity injury, locate road hazardous sites, and adopt suitable countermeasures. In order to provide insights on the mechanism and behavior of the crash severity injury, a variety of statistical approaches have been utilized to model the relationship between crash severity and potential risk factors. Many of the traditional approaches for analyzing crash severity are limited in that they are based on the assumption that all observations are independent of each other. However, given the reality of vehicle movement in networked systems, the assumption of independence of crash incidence is not likely valid. For instance, spatial and temporal autocorrelations are important sources of dependency among observations that may bias estimates if not considered in the modeling process. Moreover, there are other aspects of vehicular travel that may influence crash severity that have not been explored in traditional analysis approaches. One such aspect is the roadway visibility that is available to a driver at a given time that can impact their ability to react to changing traffic conditions, a characteristics known as sight distance. Accounting for characteristics such as sight distance in crash severity modeling involve moving beyond statistical analysis and modeling the complex geospatial relationships between the driver and the surrounding landscape. To address these limitations of traditional approaches to crash severity modeling, this dissertation first details a framework for detecting temporal and spatial autocorrelation in crash data. An approach for evaluating the sight distance available to drivers along roadways is then proposed. Finally, a crash severity model is developed based upon a multinomial logistic regression approach that incorporates the available sight distance and spatial autocorrelation as potential risk factors, in addition to a wide range of other factors related to road geometry, traffic volume, driver's behavior, environment, and vehicles. To demonstrate the characteristics of the proposed model, an analysis of vehicular crashes (years 2013-2015) along the I-70 corridor in the state of Missouri (MO) and on roadways in Boone County MO is conducted. To assess existing stopping sight distance and decision sight distance on multilane highways, a geographic information system (GIS)-based viewshed analysis is developed to identify the locations that do not conform to AASHTO (2011) criteria regarding stopping and decision sight distances, which could then be used as potential risk factors in crash prediction. Moreover, this method provides a new technique for estimating passing sight distance along two-lane highways, and locating the passing zones and no-passing zones. In order to detect the existence of temporal autocorrelation and whether it's significant in crash data, this dissertation employs the Durbin-Watson (DW) test, the Breusch-Godfrey (LM) test, and the Ljung-Box Q (LBQ) test, and then describes the removal of any significant amount of temporal autocorrelation from crash data using the differencing procedure, and the Cochrane-Orcutt method. To assess whether vehicle crashes are spatially clustered, dispersed, or random, the Moran's I and Getis-Ord Gi* statistics are used as measures of spatial autocorrelation among vehicle incidents. To incorporate spatial autocorrelation in crash severity modeling, the use of the Gi* statistic as a potential risk factor is also explored. The results provide firm evidence on the importance of accounting for spatial and temporal autocorrelation, and sight distance in modeling traffic crash data.

Book Development of Safety Performance Functions for Two lane Roads Maintained by the Virginia Department of Transportation

Download or read book Development of Safety Performance Functions for Two lane Roads Maintained by the Virginia Department of Transportation written by Nicholas J. Garber and published by . This book was released on 2010 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, significant effort and money have been invested to enhance highway safety. As available funds decrease, the allocation of resources for safety improvement projects must yield the maximum possible return on investment. Identifying highway locations that have the highest potential for crash reduction with the implementation of effective safety countermeasures is therefore an important first step in achieving the maximum return on safety investment. This study was undertaken to develop safety performance functions (SPFs) for use in Virginia in conjunction with SafetyAnalyst, a computerized analytical tool that can be used for prioritizing safety projects. A safety performance function is a mathematical relationship (model) between frequency of crashes by severity and the most significant causal factors of crashes for a specific type of road. Although the SafetyAnalyst User's Manual recommends four SPFs for two-lane segments, these SPFs were developed using data from Ohio. Because the transferability of these SPFs to other states could not be guaranteed by the developers of the four recommended SPFs, it is necessary to calibrate or develop valid SPFs for each state using appropriate data from the state. In this study, annual average daily traffic (AADT) was used as the most significant causal factor for crashes, emulating the SPFs currently suggested by Safety Analyst. SPFs for two-lane roads in Virginia were developed for total crashes and combined fatal plus injury crashes through generalized linear modeling using a negative binomial distribution for the crashes. Models were developed for urban and rural areas separately, and in order to account for the different topographies in Virginia, SPFs were also separately developed for three regions in Virginia. A total of 139,635 sites were identified for use in this study. Each site is a segment of a rural or urban two-lane road without an intersection for which AADT data were available for the years 2003 through 2007 inclusive and no change in facility type had occurred over that period. A comparative analysis based on the Freeman-Tukey R2 coefficient was then conducted between the relevant Ohio SPFs suggested for use in the SafetyAnalyst User's Manual and those specifically developed in this study for Virginia to determine which set of models better fit the Virginia data. In general, the results indicated that the SPFs specifically developed for Virginia fit the Virginia data better. The final step in this methodology was to illustrate the value of SPFs developed through an analysis of sample sites and the need of the sites for safety improvement based on SPFs as compared to crash rates. The results indicated that prioritization using the empirical Bayes method that incorporates the SPFs resulted in a higher potential for reduction in crashes than did prioritization using crash rates. The effective use of SafetyAnalyst will facilitate the identification of sites with a high potential for safety improvement, which, in turn, with the implementation of appropriate safety improvements, will result in a considerable reduction in crashes and their severity.

Book Highway Safety

    Book Details:
  • Author :
  • Publisher :
  • Release : 2001
  • ISBN :
  • Pages : 101 pages

Download or read book Highway Safety written by and published by . This book was released on 2001 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transportation Research Record contains the following papers: Incorporating crash risk in selecting congestion-mitigation strategies : Hampton Roads area (Virginia) case study (Garber, NJ and Subramanyan, S); Development of artificial neural network models to predict driver injury severity in traffic accidents at signalized intersections (Abdelwahab, HT and Abdel-Aty, MA); Transferability of models that estimate crashes as a function of access management (Miller, JS, Hoel, LA, Kim, S and Drummond, KP); Sensor-friendly vehicle and roadway cooperative safety systems : benefits estimation (Misener, JA, Thorpe, C, Ferlis, R, Hearne, R, Siegal, M and Perkowski, J); Interstate highway crash injuries during winter snow and nonsnow events (Khattak, AJ and Knapp, KK); Simulation of road crashes by use of systems dynamics (Mehmood, A, Saccamanno, F and Hellinga, B); Longitudinal analysis of fatal run-off-road crashes, 1975 to 1997 (McGinnis, RG, Davis, MJ and Hathaway, EA); Injury severity in multivehicle rear-end crashes (Khattack, AJ); Computing and interpreting accident rates for vehicle types driver groups (Hauer, E); Geographics information system-based accident data management for Mexican federal roads (Mendoza, A, Mayoral, EF, Vicente, JL and Quintero, FL); Bayesian identification of high-risk intersections for older drivers via gibbs sampling (Davis, GA and Yang, S); Automated accident detection system (Harlow, C and Wang, Y); Evaluation of inexpensive global positioning system units to improve crash location data (Graettinger, AJ, Rushing, TW and McFadden, J).

Book Preliminary Analysis of the National Crash Severity Study

Download or read book Preliminary Analysis of the National Crash Severity Study written by United States. National Highway Traffic Safety Administration and published by . This book was released on 1979 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study investigates the fatalities on the National Crash Severity Study (NCSS) of towaway, passenger car accidents. The analysis is in three stages. First, NCSS fatalities are compared to the fatally-injured occupants reported on the Fatal Accident Reporting System (FARS), as a tool for evaluating the representativeness of the NCSS data. Second, estimates of the probability of fatality for NCSS are computed for various conditions, such as the incidence of fire and the sex of the occupant. Third, in cases where two factors are highly correlated, such as is the case for rollover and ejection, modeling techniques are used to help quantify the effects of each variable. The results of this study suggest the following preliminary conclusions: (1) FARS and NCSS have similar distributions of many variables. These include urbanization, size of vehicles, type damage to vehicle, occupant seating location, sex, and restraint use. Differences resulting from the investigative methods and geographical areas of the two studies are identified and assessed. (2) On the NCSS file, many variables are associated with a much higher rate of fatality. These include (a) at the accident level: the number of vehicles involved, urbanization, and the incidence of fire or explosion; (b) at the vehicle level: the change of velocity at impact, the direction of the impacting force, and vehicle damage area; and (c) at the occupant level: seating position, age, sex, ejection, entrapment, and restraint use. (3) Rollover and ejection, which often occur together, are each independently associated with a higher rate of fatality. Of the two factors, ejection appears more related to a higher probability of fatality than does rollover alone. NCSS is the best currently-available source of accident data for analyzing injury-related factors. This report attempts to describe the accidents occurring in the NCSS sampling areas, and suggest ideas for further research.

Book Road Traffic Crash Severity Prediction Using Multi State Data

Download or read book Road Traffic Crash Severity Prediction Using Multi State Data written by Thomas M. England and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The socioeconomic burden of road traffic crashes is immense. Safer roads and vehicular mechanisms to reduce distracted driving help reduce collisions. Additionally, computational models can be used to understand the reasons for crashes and devise interventions. We study models predicting the severity of a crash based on the data reported at the crash scene. Many U.S. states have developed traffic safety programs to make the anonymized crash data publicly available. These datasets aid researchers in the creation of predictive models for crashes. While many states make data from collisions publicly available, each state reports data differently. There is a lack of standardization. As a result, it is difficult for researchers to develop machine learning algorithms to process data from multiple states without adequate preprocessing. Currently, the vast majority of projects in this field of study utilize a dataset of a single city, road, or state. This limits the use of the developed model to a region. This project aims to create a large crash database that will allow researchers to develop algorithms that utilize data from across the country. Additionally, we want to examine if the use of data from multiple states is effective in increasing the accuracy of machine learning models. In order to achieve these goals, we develop software to find common data categories from state reports and combine them into one large dataset. The data categories were selected based on reports from previous projects that identified variables having a large impact on model accuracy. In order to test the effectiveness of the new multi-state dataset, we used two models (neural network-based and decision tree-based) to predict crash injury severity. We trained and tested these models on datasets from a single state, combined two-state datasets, and a combined multi-state dataset. The results of this research reveal that there is a drop in accuracy when data from multiple states are combined. This trend is present in both the models tested, with the trend being more pronounced in the decision tree. There are some cases in the neural network model where multi-state data lead to a higher accuracy compared to the single-state experiments. We also observe a downward trend between neural network accuracy and the distance between the states present in the dataset. This implies that the closer the states are together geographically, the better the accuracy will be using the neural network model. In the decision tree model, there is a positive correlation between overall accuracy and the number of features present in the dataset. This observation means that the more features states have in common, the better the accuracy will be for a decision tree classifier. The software artifacts from this project are open-sourced.

Book Development of Crash Prediction Models for Short term Durations

Download or read book Development of Crash Prediction Models for Short term Durations written by Mohamed Ahmed Abdel-Aty and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Crash prediction methods, which are used to identify crash hotspots or crash severity, consist of safety performance functions (SPFs), crash modification factors, and severity distribution functions. These tools use annual average daily traffic data along with geometric and operational characteristics to predict the annual average crash frequency. [This report] provides roadway safety practitioners within state departments of transportation with short-term crash prediction models to be used for estimating safety performance."--Publisher's website.

Book Work Zone Crash Analysis and Modeling to Identify Factors Associated with Crash Severity and Frequency

Download or read book Work Zone Crash Analysis and Modeling to Identify Factors Associated with Crash Severity and Frequency written by Sunanda Dissanayake and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The safe and efficient flow of traffic through work zones must be established by improving work zone conditions. Therefore, identifying the factors associated with the severity and the frequency of work zone crashes is important. According to current statistics from the Federal Highway Administration, 2,372 fatalities were associated with motor vehicle traffic crashes in work zones in the United States during the four years from 2010 to 2013. From 2002 to 2014, an average of 1,612 work zone crashes occurred in Kansas each year, making it a serious concern in Kansas. The objectives of this study were to analyze work zone crash characteristics, identify the factors associated with crash severity and frequency, and to identify recommendations to improve work zone safety. Work zone crashes in Kansas from 2010 to 2013 were used to develop crash severity models. Ordered probit regression was used to model the crash severities for daytime, nighttime, multi-vehicle and single-vehicle work zone crashes and for work zones crashes in general. Based on severity models, drivers from 26 to 65 years of age were associated with high crash severities during daytime work zone crashes and driver age was not found significant in nighttime work zone crashes. The use of safety equipment was related to reduced crash severities regardless of the time of the crash. Negative binomial regression was used to model the work zone crash frequency using work zones functioned in Kansas in 2013 and 2014. According to results, increased average daily traffic (AADT) was related to higher number of work zone crashes and work zones in operation at nighttime were related to a reduced number of work zone crashes. Findings of this study were used to provide general countermeasure ideas for improving safety of work zones" (page ii).

Book Highway and Traffic Safety

Download or read book Highway and Traffic Safety written by National Research Council (U.S.). Transportation Research Board and published by . This book was released on 2000 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transportation Research Record contains the following papers: Method for identifying factors contributing to driver-injury severity in traffic crashes (Chen, WH and Jovanis, PP); Crash- and injury-outcome multipliers (Kim, K); Guidelines for identification of hazardous highway curves (Persaud, B, Retting, RA and Lyon, C); Tools to identify safety issues for a corridor safety-improvement program (Breyer, JP); Prediction of risk of wet-pavement accidents : fuzzy logic model (Xiao, J, Kulakowski, BT and El-Gindy, M); Analysis of accident-reduction factors on California state highways (Hanley, KE, Gibby, AR and Ferrara, T); Injury effects of rollovers and events sequence in single-vehicle crashes (Krull, KA, Khattack, AJ and Council, FM); Analytical modeling of driver-guidance schemes with flow variability considerations (Kaysi, I and Ail, NH); Evaluating the effectiveness of Norway's speak out! road safety campaign : The logic of causal inference in road safety evaluation studies (Elvik, R); Effect of speed, flow, and geometric characteristics on crash frequency for two-lane highways (Garber, NJ and Ehrhart, AA); Development of a relational accident database management system for Mexican federal roads (Mendoza, A, Uribe, A, Gil, GZ and Mayoral, E); Estimating traffic accident rates while accounting for traffic-volume estimation error : a Gibbs sampling approach (Davis, GA); Accident prediction models with and without trend : application of the generalized estimating equations procedure (Lord, D and Persaud, BN); Examination of methods that adjust observed traffic volumes on a network (Kikuchi, S, Miljkovic, D and van Zuylen, HJ); Day-to-day travel-time trends and travel-time prediction form loop-detector data (Kwon, JK, Coifman, B and Bickel, P); Heuristic vehicle classification using inductive signatures on freeways (Sun, C and Ritchie, SG).

Book Modeling Crash Severity and Speed Profile at Roadway Work Zones

Download or read book Modeling Crash Severity and Speed Profile at Roadway Work Zones written by Zhenyu Wang and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: Work zone tends to cause hazardous conditions for drivers and construction workers since work zones generate conflicts between construction activities and the traffic, therefore aggravate the existing traffic conditions and result in severe traffic safety and operational problems. To address the influence of various factors on the crash severity is beneficial to understand the characteristics of work zone crashes. The understanding can be used to select proper countermeasures for reducing the crash severity at work zones and improving work zone safety. In this dissertation, crash severity models were developed to explore the factor impacts on crash severity for two work zone crash datasets (overall crashes and rear-end crashes). Partial proportional odds logistic regression, which has less restriction to the parallel regression assumption and provides more reasonable interpretations of the coefficients, was used to estimate the models. The factor impacts were summarized to indicate which factors are more likely to increase work zone crash severity or which factors tends to reduce the severity. Because the speed variety is an important factor causing accidents at work zone area, the work zone speed profile was analyzed and modeled to predict the distribution of speed along the distance to the starting point of lane closures. A new learning machine algorithm, support vector regression (SVR), was utilized to develop the speed profile model for freeway work zone sections under various scenarios since its excellent generalization ability. A simulation-based experiment was designed for producing the speed data (output data) and scenario data (input data). Based on these data, the speed profile model was trained and validated. The speed profile model can be used as a reference for designing appropriate traffic control countermeasures to improve the work zone safety.

Book Development of Crash Severity Model for Predicting Risk Factors in Work Zones for Ohio

Download or read book Development of Crash Severity Model for Predicting Risk Factors in Work Zones for Ohio written by Vanishravan Katta and published by . This book was released on 2013 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work zones are given priority by most government agencies nationwide because of the need for maintenance, rehabilitation, and advancement of the existing road networks. This results in large number of work zones and has had an inevitable impact on the regular traffic flows and traffic safety issues. The main objective of the study is to find the risk factors affecting crash severity (dependent variable) in work zones in the state of Ohio. Year 2010 data was collected from Ohio Department of Traffic Safety in the form of an excel spreadsheet. A total of 24 different independent variables which has 12,275 crash records were used in the development of the Crash Severity Model (CSM). The following steps were employed for the development of CSM. First, the Pearson chi-square statistics test was done to find the variables that have a significant relationship among themselves and the dependent variable. Second, the insignificant variables left from step 1 were selected which were found to have significant effect on crash severity in other studies and they were also added along with the significant variables found in step 1 for the development of the regression model. A total of 21 variables were found to have a significant relationship with the dependent variable. Three variables were selected from step 2 based on literatures. A binomial logit model was used to predict crash severity. Results of binary logistic regression showed that forty four categories of seventeen variables were found to be predictive of the fatal/injury crash severity type and also showed that the model fits to the data well with a prediction ability of 72.8 percent.

Book Annual Awards

    Book Details:
  • Author : United States. Federal Highway Administration
  • Publisher :
  • Release : 1970
  • ISBN :
  • Pages : 28 pages

Download or read book Annual Awards written by United States. Federal Highway Administration and published by . This book was released on 1970 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: