Development And Validation Of Volume To Capacity Based Accident Prediction Models

This study is focused on the relationship between accidents and the traffic/geometric capacity of highways. By using regression analyses, this research is conducted to quantify the effects of traffic-to-capacity associations upon the number of accidents on different highway types. A concept of modified capacity is introduced where some variables such as surface rates, surface types, shoulder condition, inside shoulder type and conditions, and others are taken into consideration together with the main explanatory power, namely daily V$sb{-}$C ratios. An analysis of section lengths is conducted to investigate the influence of section lengths on the composition and explanatory power of the prediction models. For such, several section length cutoff points are analyzed and, based on the model's variations, a minimum section length is recommended for each highway type. The data sets are then constituted of sections with lengths equal or greater than the suggested cutoff points. Prediction models are generated based on four years of data analysis (1985, 1986, 1987, and 1988), where yearly, common-section, and averaged models are created. The averaged models are validated based on other averaged three-year models which are generated from the data sets for the years 1989, 1990, and 1991. The model validation is also based on existing models when prediction models for the specific highway types hereby analyzed exist from other authors. Following, daily V$sb{-}$C and six-year averaged models are created according to the capacity calculated on the Highway Capacity Manual and the geometric models developed for each highway type. Capacity is calculated on a daily basis to comply with the daily characteristics of the traffic flow. Geometric and Daily V$sb{-}$C accident prediction models are then recommended for rural and urban interstate highways, rural and urban two-lane highways, and urban multilane divided and undivided highways.

This collection contains 92 papers covering traffic congestion and traffic safety issues presented at the Traffic Congestion and Traffic Safety in the 21st Century conference, held in Chicago, Illinois, June 8-11, 1997.

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.

Model Validation and Uncertainty Quantification, Volume 3. Proceedings of the 33rd IMAC, A Conference and Exposition on Balancing Simulation and Testing, 2015, the third volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Structural Dynamics, including papers on: Uncertainty Quantification & Model Validation Uncertainty Propagation in Structural Dynamics Bayesian & Markov Chain Monte Carlo Methods Practical Applications of MVUQ Advances in MVUQ & Model Updating

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.

This book gathers papers presented at the second installment of the International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD-2019), which was held on July 08–11, 2019 in Marrakech, Morocco. It offers comprehensive coverage of recent advances in big data, data analytics and related paradigms. The book consists of fifty-two chapters, each of which shares the latest research in the fields of big data and data science, and describes use cases and applications of big data technologies in various domains, such as social networks and health care. All parts of the book discuss open research problems and potential opportunities that have arisen from the rapid advances in big data technologies. In addition, the book surveys the state of the art in data science, and provides practical guidance on big data analytics and data science. Expert perspectives are provided by authoritative researchers and practitioners from around the world, who discuss research developments and emerging trends, present case studies on helpful frameworks and innovative methodologies, and suggest best practices for efficient and effective data analytics. Chiefly intended for researchers, IT professionals and graduate students, the book represents a timely contribution to the growing field of big data, which has been recognized as one of the leading emerging technologies that will have a major impact on various fields of science and various aspects of human society over the next several decades. Therefore, the content in this book is an essential tool to help readers understand current developments, and provides them with an extensive overview of the field of big data analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use big data, such as management and finance, medicine and health care, networks, the Internet of Things, big data standards, benchmarking of systems, and others. In addition to a diverse range of applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modeling of high-dimensional data are also covered. The varied collection of topics addressed introduces readers to the richness of the emerging field of big data analytics.

With major implications for applied physics, engineering, and the natural and social sciences, the rapidly growing area of environmental fluid dynamics focuses on the interactions of human activities, environment, and fluid motion. A landmark for the field, this two-volume handbook presents the basic principles, fundamental flow processes, modeling techniques, and measurement methods used in the field, along with critical discussions of environmental sustainability related to engineering aspects. The first volume provides a comprehensive overview of the fundamentals, and the second volume explores the interactions between engineered structures and natural flows.