Download or read book A Two stage Model for Predicting Crash Rate by Severity Types written by S M A Bin al Islam and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Novel Approach to Modeling and Predicting Crash Frequency at Rural Intersections by Crash Type and Injury Severity Level written by Jun Deng (Writer on transportation) and published by . This book was released on 2013 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: Safety at intersections is of significant interest to transportation professionals due to the large number of possible conflicts that occur at those locations. In particular, rural intersections have been recognized as one of the most hazardous locations on roads. However, most models of crash frequency at rural intersections, and road segments in general, do not differentiate between crash type (such as angle, rear-end or sideswipe) and injury severity (such as fatal injury, non-fatal injury, possible injury or property damage only). Thus, there is a need to be able to identify the differential impacts of intersection-specific and other variables on crash types and severity levels. This thesis builds upon the work of Bhat et al., (2013b) to formulate and apply a novel approach for the joint modeling of crash frequency and combinations of crash type and injury severity. The proposed framework explicitly links a count data model (to model crash frequency) with a discrete choice model (to model combinations of crash type and injury severity), and uses a multinomial probit kernel for the discrete choice model and introduces unobserved heterogeneity in both the crash frequency model and the discrete choice model, while also accommodates excess of zeros. The results show that the type of traffic control and the number of entering roads are the most important determinants of crash counts and crash type/injury severity, and the results from our analysis underscore the value of our proposed model for data fit purposes as well as to accurately estimate variable effects.

Download or read book Estimation of Crash Type Frequency Accounting for Misclassification in Crash Data written by Asif Mahmud and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Individual crash types have different underlying causes and thus the relationships between roadway/traffic characteristics and crash frequency are likely to differ across unique crash types. Two statistical methods -- univariate and multivariate formulations -- have been widely used so far by researchers in estimating the impact of contributing factors on different crash types. Addressing the limitations of these methods, recently a two-stage approach has been proposed in which one model is estimated to predict the total crash frequency and its prediction is combined with another model which predicts the proportions of different crash types. More efficient one-stage joint models, in which both the frequency and proportion models are estimated simultaneously and predictions are provided more directly, have also been proposed for macro-level analysis. This study investigates the performance of this joint modeling paradigm in analyzing unique crash type frequencies on individual road segments. Moreover, this study also proposes the use of a multinomial logit (MNL) model to estimate the proportion of different collision types, which has never been done in safety literature. This study compares the performance of all these methods in predicting crash frequency by crash type on two-way two-lane urban-suburban collector roadway segments in Pennsylvania. While the methodologies of crash type frequency estimation are well-established, less focus has been given on the quality of the crash dataset they are applied on. Crash misclassification (MC) -- e.g., a crash of one type or severity being mistakenly miscategorized as another -- is a relatively common problem in transportation safety. Crash frequency models for individual crash categories estimated using datasets with MC errors could result in biased parameter estimates and thus lead to ineffective countermeasure planning. This study proposes a novel methodological formulation to directly account for this MC error and incorporates it into the two most common count data models used for crash frequency prediction: Poisson and Negative Binomial (NB) regression. The proposed framework introduces probabilistic MC rates among different crash types and modifies the likelihood function of the count models accordingly. The study also demonstrates how this approach can be integrated into reformulated models that express each count model as a discrete choice model. The capability of the proposed models to estimate true parameters, given the existence of MC error, is examined via simulation analysis. Then, the proposed models are applied to empirical data to examine the presence of MC in crash data and further examine the robustness of the proposed models. Lastly, the ability of the proposed models in accounting for underreporting, another acute problem in crash data, is examined through comparing its performance with that from established frameworks.

Download or read book Cross section Fatal Crash Type Prediction Models written by Hong Zhu and published by . This book was released on 2010 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rural two-lane highway in the southeastern United States is frequently associated with a disproportionate number of serious and fatal crashes. The major research objectives are to investigate the relations between probabilities of fatal crash type occurrence and potential contributing factors from road geometric design characteristics and roadside, environmental features. This dissertation analyzes the regional fatal crash database and successfully develops statistical models to examine the relations and provided meaningful research findings. This dissertation contributes to current traffic safety analysis by directly examining the connection between major fatal crash type occurrence and roadway geometrics, roadside characteristics, and environmental conditions through a regional case study. This study effort addresses the less understood relationship between fatal crash types and road features compared to other crash measures, such as crash frequency, crash rate, and injury severity. The developed fatal crash type prediction models not only demonstrate strong connections between crash types and road characteristics, but also provide a quantitative assessment tool for countermeasures in terms of reduction of fatal crash type occurrence. Since most countermeasures are more effective at mitigating certain type of crashes, the information revealed from the crash type prediction models help clarify the relationship between candidate countermeasures and expected crash reductions.

Download or read book A Novel Approach to Modeling and Predicting Crash Frequency at Rural Intersections by Crash Type and Injury Severity Level written by Jun Deng (Writer on transportation) and published by . This book was released on 2015 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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.

Download or read book Exploration of Advances in Statistical Methodologies for Crash Count and Severity Prediction Models written by Kai Wang and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This report first describes the use of different copula based models to simultaneously estimate the two crash indicators: injury severity and vehicle damage. The Gaussian copula model outperforms the other copula based model specifications (i.e. Gaussian, Farlie-Gumbel-Morgenstern (FGM), Frank, Clayton, Joe and Gumbel copula models), and the results indicate that injury severity and vehicle damage are highly correlated, and the correlations between injury severity and vehicle damage varied with different crash characteristics including manners of collision and collision types. This study indicates that the copula-based model can be considered to get a more accurate model structure when simultaneously estimating injury severity and vehicle damage in crash severity analyses. The second part of this report describes estimation of cluster based SPFs for local road intersections and segments in Connecticut using socio-economic and network topological data instead of traffic counts as exposure. The number of intersections and the total local roadway length were appropriate to be used as exposure in the intersection and segment SPFs, respectively. Models including total population, retail and non-retail employment and average household income are found to be the best both on the basis of model fit and out of sample prediction. The third part of this report describes estimation of crashes by both crash type and crash severity on rural two-lane highways, using the Multivariate Poisson Lognormal (MVPLN) model. The crash type and crash severity counts are significantly correlated; the standard errors of covariates in the MVPLN model are slightly lower than the other two univariate crash prediction models (i.e. Negative Binomial model and Univariate Poisson Lognormal model) when the covariates are statistically significant; and the MVPLN model outperforms the UPLN and NB models in crash count prediction accuracy. This study indicates that when simultaneously predicting crash counts by crash type and crash severity for rural two-lane highways, the MVPLN model should be considered to avoid estimation error and to account for the potential correlations among crash type counts and crash severity counts.

Download or read book Improved Prediction Models for Crash Types and Crash Severities written by and published by . This book was released on 2021 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: The release of the Highway Safety Manual (HSM) by the American Association of State Highway and Transportation Officials (AASHTO) in 2010 was a landmark event in the practice of road safety analysis. Before it, the United States had no central repository for information about quantitative road safety analysis methodology. The TRB National Cooperative Highway Research Program's NCHRP Web-Only Document 295: Improved Prediction Models for Crash Types and Crash Severities describes efforts to develop improved crash prediction methods for crash type and severity for the three facility types covered in the HSM—specifically, two‐lane rural highways, multilane rural highways, and urban/suburban arterials. Supplemental materials to the Web-Only Document include Appendices A, B, and C (Average Condition Models, Crash Severities – Ordered Probit Fractional Split Modeling Approach, and Draft Content for Highway Safety Manual, 2nd Edition).

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.

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.

Download or read book Selecting Exposure Measures for Predicting Crash Rates on Two lane Rural Highways written by Xiao Qin and published by . This book was released on 2002 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Identifying Effective Geometric and Traffic Factors to Predict Crashes at Horizontal Curve Sections written by Hojr Momeni and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Driver workload increases on horizontal curves due to more complicated navigation compared to navigation on straight roadway sections. Although only a small portion of roadways are horizontal curve sections, approximately 25% of all fatal highway crashes occur at horizontal curve sections. According to the Fatality Analysis Reporting System (FARS) database, fatalities associated with horizontal curves were more than 25% during last years from 2008 to 2014, reinforcing that investigation of horizontal curve crashes and corresponding safety improvements are crucial study topics within the field of transportation safety. Improved safety of horizontal curve sections of rural transportation networks can contribute to reduced crash severities and frequencies. Statistical methods can be utilized to develop crash prediction models in order to estimate crashes at horizontal curves and identify contributing factors to crash occurrences, thereby correlating to the primary objectives of this research project. Primary data analysis for 221 randomly selected horizontal curves on undivided two-lane two-way highways with Poisson regression method revealed that annual average daily traffic (AADT), heavy vehicle percentage, degree of curvature, and difference between posted and advisory speeds affect crash occurrence at horizontal curves. The data, however, were relatively overdispersed, so the negative binomial (NB) regression method was utilized. Results indicated that AADT, heavy vehicle percentage, degree of curvature, and long tangent length significantly affect crash occurrence at horizontal curve sections. A new dataset consisted of geometric and traffic data of 5,334 horizontal curves on the entire state transportation network including undivided and divided highways provided by Kansas Department of Transportation (KDOT) Traffic Safety Section as well as crash data from the Kansas Crash and Analysis Reporting System (KCARS) database were used to analyze the single vehicle (SV) crashes. An R software package was used to write a code and combine required information from aforementioned databases and create the dataset for 5,334 horizontal curves on the entire state transportation network. Eighty percent of crashes including 4,267 horizontal curves were randomly selected for data analysis and remaining 20% horizontal curves (1,067 curves) were used for data validation. Since the results of the Poisson regression model showed overdispersion of crash data and many horizontal curves had zero crashes during the study period from 2010 to 2014, NB, zero-inflated Poisson (ZIP), and zero-inflated negative binomial (ZINB) methods were used for data analysis. Total number of crashes and severe crashes were analyzed with the selected methods. Results of data analysis revealed that AADT, heavy vehicle percentage, curve length, degree of curvature, posted speed, difference between posted and advisory speed, and international roughness index influenced single vehicle crashes at 4,267 randomly selected horizontal curves for data analysis. Also, AADT, degree of curvature, heavy vehicle percentage, posted speed, being a divided roadway, difference between posted and advisory speeds, and shoulder width significantly influenced severe crash occurrence at selected horizontal curves. The goodness-of-fit criteria showed that the ZINB model more accurately predicted crash numbers for all crash groups at the selected horizontal curve sections. A total of 1,067 horizontal curves were used for data validation, and the observed and predicted crashes were compared for all crash groups and data analysis methods. Results of data validation showed that ZINB models for total crashes and severe crashes more accurately predicted crashes at horizontal curves. This study also investigated the effect of speed limit change on horizontal curve crashes on K-5 highway in Leavenworth County, Kansas. A statistical t-test proved that crash data from years 2006 to 2012 showed only significant reduction in equivalent property damage only (EPDO) crash rate for adverse weather condition at 5% significance level due to speed limit reduction in June 2009. However, the changes in vehicles speeds after speed limit change and other information such as changes in surface pavement condition were not available. According to the results of data analysis for 221 selected horizontal curves on undivided two-lane highways, tangent section length significantly influenced total number of crashes. Therefore, providing more information about upcoming changes in horizontal alignment of the roadway via doubling up warning sings, using bigger sings, using materials with higher retroreflectivity, or flashing beacons were recommended for horizontal curves with long tangent section lengths and high number of crashes. Also, presence of rumble strips and wider shoulders significantly and negatively influenced severe SV crashes at horizontal curve sections; therefore, implementing rumble strips and widening shoulders for horizontal curves with high number of severe SV crashes were recommended.

Download or read book Safe Mobility written by Dominique Lord and published by Emerald Group Publishing. This book was released on 2018-04-18 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book increases the level of knowledge on road safety contexts, issues and challenges; shares what can currently be done to address the variety of issues; and points to what needs to be done to make further gains in road safety.

Download or read book Analyzing Crash Frequency and Severity Data Using Novel Techniques written by Gaurav Satish Mehta and published by . This book was released on 2014 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing safe travel from one point to another is the main objective of any public transportation agency. The recent publication of the Highway Safety Manual (HSM) has resulted in an increasing emphasis on the safety performance of specific roadway facilities. The HSM provides tools such as crash prediction models that can be used to make informed decisions. The manual is a good starting point for transportation agencies interested in improving roadway safety in their states. However, the models published in the manual need calibration to account for the local driver behavior and jurisdictional changes. The method provided in the HSM for calibrating crash prediction models is not scientific and has been proved inefficient by several studies. To overcome this limitation this study proposes two alternatives. Firstly, a new method is proposed for calibrating the crash prediction models using negative binomial regression. Secondly, this study investigates new forms of state-specific Safety Performance Function SPFs using negative binomial techniques. The HSM's 1st edition provides a multiplier applied to the univariate crash prediction models to estimate the expected number of crashes for different crash severities. It does not consider the distinct effect unobserved heterogeneity might have on crash severities. To address this limitation, this study developed a multivariate extension of the Conway Maxwell Poisson distribution for predicting crashes. This study gives the statistical properties and the parameter estimation algorithm for the distribution. The last part of this dissertation extends the use of Highway Safety Manual by developing a multivariate crash prediction model for the bridge section of the roads. The study then compares the performance of the newly proposed multivariate Conway Maxwell Poisson (MVCMP) model with the multivariate Poisson Lognormal, univariate Conway Maxwell Poisson (UCMP) and univariate Poisson Lognormal model for different crash severities. This example will help transportation researchers in applying the model correctly.

Download or read book Vehicle Crash Mechanics written by Matthew Huang and published by CRC Press. This book was released on 2002-06-19 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: Governed by strict regulations and the intricate balance of complex interactions among variables, the application of mechanics to vehicle crashworthiness is not a simple task. It demands a solid understanding of the fundamentals, careful analysis, and practical knowledge of the tools and techniques of that analysis. Vehicle Crash Mechanics s

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

Download or read book Statistical and Econometric Methods for Transportation Data Analysis written by Simon Washington and published by CRC Press. This book was released on 2020-01-30 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book's website (with databases and other support materials) can be accessed here. Praise for the Second Edition: The second edition introduces an especially broad set of statistical methods ... As a lecturer in both transportation and marketing research, I find this book an excellent textbook for advanced undergraduate, Master’s and Ph.D. students, covering topics from simple descriptive statistics to complex Bayesian models. ... It is one of the few books that cover an extensive set of statistical methods needed for data analysis in transportation. The book offers a wealth of examples from the transportation field. —The American Statistician Statistical and Econometric Methods for Transportation Data Analysis, Third Edition offers an expansion over the first and second editions in response to the recent methodological advancements in the fields of econometrics and statistics and to provide an increasing range of examples and corresponding data sets. It describes and illustrates some of the statistical and econometric tools commonly used in transportation data analysis. It provides a wide breadth of examples and case studies, covering applications in various aspects of transportation planning, engineering, safety, and economics. Ample analytical rigor is provided in each chapter so that fundamental concepts and principles are clear and numerous references are provided for those seeking additional technical details and applications. New to the Third Edition Updated references and improved examples throughout. New sections on random parameters linear regression and ordered probability models including the hierarchical ordered probit model. A new section on random parameters models with heterogeneity in the means and variances of parameter estimates. Multiple new sections on correlated random parameters and correlated grouped random parameters in probit, logit and hazard-based models. A new section discussing the practical aspects of random parameters model estimation. A new chapter on Latent Class Models. A new chapter on Bivariate and Multivariate Dependent Variable Models. Statistical and Econometric Methods for Transportation Data Analysis, Third Edition can serve as a textbook for advanced undergraduate, Masters, and Ph.D. students in transportation-related disciplines including engineering, economics, urban and regional planning, and sociology. The book also serves as a technical reference for researchers and practitioners wishing to examine and understand a broad range of statistical and econometric tools required to study transportation problems.