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    Highway Safety Analytics and Modeling

    Highway Safety Analytics and Modeling

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    Bog E-bog
    • Format
    • Bog, paperback
    • Engelsk

    Beskrivelse

    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.

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  • Vægt880 g
    • coffee cup img
    10 cm
    book img
    15,1 cm
    22,9 cm

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    Data collection Human factors Machine learning Confidence intervals Statistics Support vector machines Goodness-of-fit Exploratory data analysis Model selection Outlier analysis Time series data Variable Selection Poisson process Heatmap Variability Binary logistic regression Hotspots Odds Ratio Kernel density estimation Hypothesis testing Spatial Data Analysis Correlation coefficient Association rules Dirichlet process Maximum Likelihood Data Aggregation Clustering analysis Bayesian networks Bar graphs Pie charts Sliding Window Neural network Histogram Sensitivity analysis Hazardous Sites Cross-sectional study Geographically weighted regression Before-after studies Box-and-whisker plot Bayesian method Before-after method with survival analysis Central Tendency Before-after method with control group Cell Transmission Model Crashdata Crash data Conditional logistic regression Crash-frequency models Crash-frequency model data-driven methods Decision Tree Model Generalized order logistic Continuous risk profile Goodness-of-logic Conway-Maxwell Contour plot Crash-severity model Crash variance Functional form Getis G Geospatial Methods Data issues Highway safety Highway safety researchers Extreme value models Naïve method Nested Logit Model Model transferability Naïve adjustment method Fundamental Diagram Moran's I Ordinal probit Multinomial Logit Model Hierarchical Bayesian Model Policy-based decision Post encroachment time Highway fatalities Global highway safety Random parameters (mixed) logit Poisson-lognormal Poisson trials Random Parameters Screening evaluation methods Roadway data Site selection bias Scatterplots Relative Risk Surrogate safety measures Safety pyramid Traffic conflicts technique traffic engineers Modeling objectives Surrogate safety assessment model Negative binomial or Poisson-gamma Network screening Peak searching Modeling issues Panel study Spatial Autoregressive Model Population Pyramid Traffic flow data Propensity score method Proportional Odds Model Real-time crash prediction Reducing crashes sample size calculations Sample size determination Time to collision

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