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Cross Section Fatal Crash Type Prediction Models
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Book Synopsis Cross-section Fatal Crash Type Prediction Models by : Hong Zhu
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.
Book Synopsis A Predictive Median Barrier Warrant to Reduce Cross-median Crashes by : Andrew W. Ooms
Download or read book A Predictive Median Barrier Warrant to Reduce Cross-median Crashes written by Andrew W. Ooms and published by . This book was released on 2010 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Defining New Exposure Measures for Crash Prediction Models by Type of Collision by :
Download or read book Defining New Exposure Measures for Crash Prediction Models by Type of Collision written by and published by . This book was released on 2007 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Modeling of Transport Demand by : V.A Profillidis
Download or read book Modeling of Transport Demand written by V.A Profillidis and published by Elsevier. This book was released on 2018-10-23 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modeling of Transport Demand explains the mechanisms of transport demand, from analysis to calculation and forecasting. Packed with strategies for forecasting future demand for all transport modes, the book helps readers assess the validity and accuracy of demand forecasts. Forecasting and evaluating transport demand is an essential task of transport professionals and researchers that affects the design, extension, operation, and maintenance of all transport infrastructures. Accurate demand forecasts are necessary for companies and government entities when planning future fleet size, human resource needs, revenues, expenses, and budgets. The operational and planning skills provided in Modeling of Transport Demand help readers solve the problems they face on a daily basis. Modeling of Transport Demand is written for researchers, professionals, undergraduate and graduate students at every stage in their careers, from novice to expert. The book assists those tasked with constructing qualitative models (based on executive judgment, Delphi, scenario writing, survey methods) or quantitative ones (based on statistical, time series, econometric, gravity, artificial neural network, and fuzzy methods) in choosing the most suitable solution for all types of transport applications. Presents the most recent and relevant findings and research - both at theoretical and practical levels - of transport demand Provides a theoretical analysis and formulations that are clearly presented for ease of understanding Covers analysis for all modes of transportation Includes case studies that present the most appropriate formulas and methods for finding solutions and evaluating results
Book Synopsis Development of Accident Prediction Models and Improvement Strategies by : Yiu-Kuen Michael Lau
Download or read book Development of Accident Prediction Models and Improvement Strategies written by Yiu-Kuen Michael Lau and published by . This book was released on 1989 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Measuring the Goodness-of-fit of Accident Prediction Models by : Shaw-Pin Miaou
Download or read book Measuring the Goodness-of-fit of Accident Prediction Models written by Shaw-Pin Miaou and published by . This book was released on 1996 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: In developing accidents-flow-roadway design models, the R-squared goodness-of-fit measure has been used by traffic safety engineers and researchers for many years to (1) determine the quality and usability of a model; (2) select covariates (or explanatory variables) for inclusion in the model; (3) make a decision as to whether it would be worthwhile to collect additional covariates; and (4) compare the relative quality of models from different studies. Through computer simulations, this study demonstrated the pitfalls of using R-squared to make these decisions and comparisons. Other goodness-of-fit criteria such as the Akaike Information Criterion, scaled deviance, and Pearson's X-squared statistics were also introduced and evaluated. Based on limited simulation results, one of the alternative criteria called R-squared-alpha was recommended for evaluating and comparing the quality of accident prediction models when sample size is large. Finally, the interrelated and complementary nature of two approaches that have traditionally been used to develop the relationship between run-off-the-road accident frequency and roadside hazards (i.e., accident-based approach and encroachment-based approach) were studied and demonstrated using data from a Federal Highway Administration and Transportation Research Board roadway cross-section design data base. It was suggested that exploring the complementary nature of these two approaches could be a viable avenue to reduce data collection cost.
Book Synopsis Statistical Methods in Highway Safety Analysis by : Bhagwant Naraine Persaud
Download or read book Statistical Methods in Highway Safety Analysis written by Bhagwant Naraine Persaud and published by . This book was released on 2001 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: TRB's National Cooperative Highway Research Program (NCHRP) Synthesis 295: Statistical Methods in Highway Safety Analysis focus on the type of safety analysis required to support traditional engineering functions, such as the identification of hazardous locations and the development and evaluation of countermeasures. Analyses related specifically to driver and vehicle safety are not covered, but some statistical methods used in these areas are of relevance and are summarized where appropriate.
Book Synopsis Crash Prediction Models on Truck-related Crashes on Two-lane Rural Highways with Vertical Curves by : Srutha Vavilikolanu
Download or read book Crash Prediction Models on Truck-related Crashes on Two-lane Rural Highways with Vertical Curves written by Srutha Vavilikolanu and published by . This book was released on 2008 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: "According to Federal Motor Carrier Safety Administration (FMCSA), truck involvement in fatal crashes is more on rural areas than on urban areas. The Fatality Analysis Reporting System (FARS) encyclopedia also indicates that truck involvement in fatal crashes are approximately 12% of the total fatal crashes in the nation and 14 % in The State of Ohio. One area for potential concern is the role of vertical curves on truck crashes. In the design of vertical curves stopping distance, grade and length of the curve are important factors taken into consideration. Vehicle operations on vertical curves are influenced by the grade of the curve, stopping sight distance and vehicle speed. These factors may create operational issues for vehicles traveling on vertical curves and in turn increase the likelihood for crashes. Truck specific studies in the past have focused on geometric roadway factors associated with crashes on vertical curves. Most of the research studies are focused on crest curve truck crashes, and little research has been done on crashes on vertical sag curves. The main research goal of the study is to develop prediction models to evaluate the impact of geometry, traffic volumes and speed on truck-related crashes on two-lane rural vertical curves. The accomplishment of the research goal is achieved by setting five objectives. The first objective is to develop three crash prediction models using negative binomial regression model. These models are 1. Full model - for all vertical curves 2. Reduced model I - for crest curves only and 3. Reduced model II - for sag curves only. The dataset includes 1,935 vertical curve segments with 205 truck crashes from 2002-2006. In second and third objective, Full Bayes approach is used to enhance the results obtained in the Reduced Models I and II. These results are then compared to the initial models. The fourth objective is evaluating the vertical curve variables which are statistically significant with truck-related crashes. These results show that higher grade change for the length of the vertical curve, total width in the range of 24 to 26ft, more number of passenger cars and trucks, increases the truck-related crashes on both crest and sag curves. Low speed limit on crest curves and high speed limit on sag curves increases truck-related crashes which may seem counter intuitive. The fifth objective is to provide suggestions on effective methods to reduce truck related crashes and improve safety. Some potential areas for design improvement may include flattening of steep vertical curves, advisory speed signs and increasing the roadway width on rural vertical curves in Ohio."--Abstract.
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 Synopsis Transportation Cyber-Physical Systems by : Lipika Deka
Download or read book Transportation Cyber-Physical Systems written by Lipika Deka and published by Elsevier. This book was released on 2018-07-30 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transportation Cyber-Physical Systems provides current and future researchers, developers and practitioners with the latest thinking on the emerging interdisciplinary field of Transportation Cyber Physical Systems (TCPS). The book focuses on enhancing efficiency, reducing environmental stress, and meeting societal demands across the continually growing air, water and land transportation needs of both people and goods. Users will find a valuable resource that helps accelerate the research and development of transportation and mobility CPS-driven innovation for the security, reliability and stability of society at-large. The book integrates ideas from Transport and CPS experts and visionaries, consolidating the latest thinking on the topic. As cars, traffic lights and the built environment are becoming connected and augmented with embedded intelligence, it is important to understand how smart ecosystems that encompass hardware, software, and physical components can help sense the changing state of the real world. Bridges the gap between the transportation, CPS and civil engineering communities Includes numerous examples of practical applications that show how diverse technologies and topics are integrated in practice Examines timely, state-of-the-art topics, such as big data analytics, privacy, cybersecurity and smart cities Shows how TCPS can be developed and deployed, along with its associated challenges Includes pedagogical aids, such as Illustrations of application scenarios, architecture details, tables describing available methods and tools, chapter objectives, and a glossary Contains international contributions from academia, government and industry
Book Synopsis Introducing Multilevel Modeling by : Ita G G Kreft
Download or read book Introducing Multilevel Modeling written by Ita G G Kreft and published by SAGE. This book was released on 1998-04-07 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first accessible and practical guide to using multilevel models in social research. Multilevel approaches are becoming increasingly important in social, behavioural, and educational research and it is clear from recent developments that such models are seen as being more realistic, and potentially more revealing, than ordinary regression models. While other books describe these multilevel models in considerable detail none focuses on the practical issues and potential problems of doing multilevel analyses that are covered in Introducing Multilevel Modeling. The authors' approach is user-oriented and the formal mathematics and statistics are kept to a minimum. Other key features include the use of worked examples using real data sets, analyzed using the leading computer package for multilevel modeling - "MLn." Discussion site at: http: \www.stat.ucla.eduphplibw-agoraw-agora.phtml?bn=Sagebook Data files mentioned in the book are available from: http: \www.stat.ucla.edu deleeuwsagebook
Book Synopsis Vehicle Crash Mechanics by : Matthew Huang
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
Book Synopsis A Novel Approach to Modeling and Predicting Crash Frequency at Rural Intersections by Crash Type and Injury Severity Level by : Jun Deng (Writer on transportation)
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.
Book Synopsis Identifying Effective Geometric and Traffic Factors to Predict Crashes at Horizontal Curve Sections by : Hojr Momeni
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.
Book Synopsis Improved Prediction Models for Crash Types and Crash Severities by :
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).
Book Synopsis Real-time Crash Prediction of Urban Highways Using Machine Learning Algorithms by : Mirza Ahammad Sharif
Download or read book Real-time Crash Prediction of Urban Highways Using Machine Learning Algorithms written by Mirza Ahammad Sharif and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Motor vehicle crashes in the United States continue to be a serious safety concern for state highway agencies, with over 30,000 fatal crashes reported each year. The World Health Organization (WHO) reported in 2016 that vehicle crashes were the eighth leading cause of death globally. Crashes on roadways are rare and random events that occur due to the result of the complex relationship between the driver, vehicle, weather, and roadway. A significant breadth of research has been conducted to predict and understand why crashes occur through spatial and temporal analyses, understanding information about the driver and roadway, and identification of hazardous locations through geographic information system (GIS) applications. Also, previous research studies have investigated the effectiveness of safety devices designed to reduce the number and severity of crashes. Today, data-driven traffic safety studies are becoming an essential aspect of the planning, design, construction, and maintenance of the roadway network. This can only be done with the assistance of state highway agencies collecting and synthesizing historical crash data, roadway geometry data, and environmental data being collected every day at a resolution that will help researchers develop powerful crash prediction tools. The objective of this research study was to predict vehicle crashes in real-time. This exploratory analysis compared three well-known machine learning methods, including logistic regression, random forest, support vector machine. Additionally, another methodology was developed using variables selected from random forest models that were inserted into the support vector machine model. The study review of the literature noted that this study's selected methods were found to be more effective in terms of prediction power. A total of 475 crashes were identified from the selected urban highway network in Kansas City, Kansas. For each of the 475 identified crashes, six no-crash events were collected at the same location. This was necessary so that the predictive models could distinguish a crash-prone traffic operational condition from regular traffic flow conditions. Multiple data sources were fused to create a database including traffic operational data from the KC Scout traffic management center, crash and roadway geometry data from the Kanas Department of Transportation; and weather data from NOAA. Data were downloaded from five separate roadway radar sensors close to the crash location. This enable understanding of the traffic flow along the roadway segment (upstream and downstream) during the crash. Additionally, operational data from each radar sensor were collected in five minutes intervals up to 30 minutes prior to a crash occurring. Although six no-crash events were collected for each crash observation, the ratio of crash and no-crash were then reduced to 1:4 (four non-crash events), and 1:2 (two non-crash events) to investigate possible effects of class imbalance on crash prediction. Also, 60%, 70%, and 80% of the data were selected in training to develop each model. The remaining data were then used for model validation. The data used in training ratios were varied to identify possible effects of training data as it relates to prediction power. Additionally, a second database was developed in which variables were log-transformed to reduce possible skewness in the distribution. Model results showed that the size of the dataset increased the overall accuracy of crash prediction. The dataset with a higher observation count could classify more data accurately. The highest accuracies in all three models were observed using the dataset of a 1:6 ratio (one crash event for six no-crash events). The datasets with1:2 ratio predicted 13% to 18% lower than the 1:6 ratio dataset. However, the sensitivity (true positive prediction) was observed highest for the dataset of a 1:2 ratio. It was found that reducing the response class imbalance; the sensitivity could be increased with the disadvantage of a reduction in overall prediction accuracy. The effects of the split ratio were not significantly different in overall accuracy. However, the sensitivity was found to increase with an increase in training data. The logistic regression model found an average of 30.79% (with a standard deviation of 5.02) accurately. The random forest models predicted an average of 13.36% (with a standard deviation of 9.50) accurately. The support vector machine models predicted an average of 29.35% (with a standard deviation of 7.34) accurately. The hybrid approach of random forest and support vector machine models predicted an average of 29.86% (with a standard deviation of 7.33) accurately. The significant variables found from this study included the variation in speed between the posted speed limit and average roadway traffic speed around the crash location. The variations in speed and vehicle per hour between upstream and downstream traffic of a crash location in the previous five minutes before a crash occurred were found to be significant as well. This study provided an important step in real-time crash prediction and complemented many previous research studies found in the literature review. Although the models investigate were somewhat inconclusive, this study provided an investigation of data, variables, and combinations of variables that have not been investigated previously. Real-time crash prediction is expected to assist with the on-going development of connected and autonomous vehicles as the fleet mix begins to change, and new variables can be collected, and data resolution becomes greater. Real-time crash prediction models will also continue to advance highway safety as metropolitan areas continue to grow, and congestion continues to increase.
Book Synopsis Journal of Transportation and Statistics by :
Download or read book Journal of Transportation and Statistics written by and published by . This book was released on 2004 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt:
