Statistical Methods In Highway Safety Analysis

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.

This Transportation Research Record contains 28 papers dealing with statistical methods in highway safety research; highway safety data, analysis, and evaluation; occupant protection; and systematic reviews and meta-analysis. The papers address such topics as risk and crash prediction models, crashes on freeways and at signalized intersections, multivehicle crash prediction, speed and safety, red light running crashes, freeway lane closures, ramp design, accident exposure, rumble strip benefits, collisions with median trees, intersection safety, accident reconstruction, safety effects of speed limit changes, geometric design and head-on crashes, deer-vehicle crashes, sport utility vehicle rollover, vehicle occupancy and crash risk, a logit model for studying injury severity, abdominal injuries in rail passengers, healthy transport policies, and meta-analysis.

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

"TRB's Transportation Research Record: Journal of the Transportation Research Board, No. 2515, explores 15 papers related to statistical methods and highway safety performance, including: Multivariate Full Bayesian Hot Spot Identification and Ranking: New Technique; Modeling Crash Rates for a Mountainous Highway by Using Refined-Scale Panel Data; Exploring Piecewise Linear Effects of Crash Contributing Factors with a Novel Poisson-Mixed Multivariate Adaptive Regression Splines Model; Classification of Gaps at Uncontrolled Intersections and Midblock Crossings Using Support Vector Machines; Safety Impacts of a Statewide Centerline Rumble Strip Installation Program; Evaluation of the Safety Effectiveness of the Conversion of Two-Lane Roadways to Four-Lane Divided Roadways: Bayesian Versus Empirical Bayes; Is Horizontal Curvature a Significant Factor of Safety in Rural Multilane Highways?; Developing Calibration Factors for Crash Prediction Models with Consideration of Crash Recording Threshold Change; Empirical Bayes Before-After Study on Safety Effect of Narrow Pavement Widening Projects in Texas; Transferability and Calibration of Highway Safety Manual Performance Functions and Development of New Models for Urban Four-Lane Divided Roads in Riyadh, Saudi Arabia; Safety Analysis of Freeway Segments with Random Parameters; Strength of the Variable: Calculating and Evaluating Safety Performance Function Calibration Factors for the State of Ohio; Statistical Evaluation of Different Sample Sizes for Local Calibration Process in the Highway Safety Manual; Results and Lessons from Local Calibration Process of the Highway Safety Manual for the State of Maryland; Validation Technique Applied to Oregon Safety Performance Function Arterial Segment Models." -- Publisher's description

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).

Covers empirical approaches to outlier detection in intelligent transportation systems data, modeling of traffic crash-flow relationships for intersections, profiling of high-frequency accident locations by use of association rules, analysis of rollovers and injuries with sport utility vehicles, and automated accident detection at intersections via digital audio signal processing.