Using hierarchical tree-based regression model to predict train-vehicle crashes at passive highway-rail grade crossings.

This paper applies a nonparametric statistical method, hierarchical tree-based regression (HTBR), to explore train-vehicle crash prediction and analysis at passive highway-rail grade crossings. Using the Federal Railroad Administration (FRA) database, the research focuses on 27 years of train-vehicle accident history in the United States from 1980 through 2006. A cross-sectional statistical analysis based on HTBR is conducted for public highway-rail grade crossings that were upgraded from crossbuck-only to stop signs without involvement of other traffic-control devices or automatic countermeasures. In this study, HTBR models are developed to predict train-vehicle crash frequencies for passive grade crossings controlled by crossbucks only and crossbucks combined with stop signs respectively, and assess how the crash frequencies change after the stop-sign treatment is applied at the crossbuck-only-controlled crossings. The study results indicate that stop-sign treatment is an effective engineering countermeasure to improve safety at the passive grade crossings. Decision makers and traffic engineers can use the HTBR models to examine train-vehicle crash frequency at passive crossings and assess the potential effectiveness of stop-sign treatment based on specific attributes of the given crossings.

[1]  K K Knapp.  LITERATURE REVIEW OF HIGHWAY-RAILROAD GRADE CROSSING SIGHT DISTANCE ASSUMPTIONS , 1999 .

[2]  Matthew G Karlaftis,et al.  Effects of road geometry and traffic volumes on rural roadway accident rates. , 2002, Accident; analysis and prevention.

[3]  B D Ogden,et al.  Railroad-highway grade crossing handbook , 2007 .

[4]  G M McCollister,et al.  A model to predict the probability of highway rail crossing accidents , 2007 .

[5]  Eric C. Wigglesworth.  A human factors commentary on innovations at railroad–highway grade crossings in Australia , 2001 .

[6]  Simon Washington,et al.  Iteratively specified tree-based regression : theory and trip generation example , 2000 .

[7]  Stephen H Richards,et al.  Evaluation of Effectiveness of Stop-Sign Treatment at Highway–Railroad Grade Crossings , 2009 .

[8]  Dominique Lord,et al.  Application of Accident Prediction Models for Computation of Accident Risk on Transportation Networks , 2002 .

[9]  E Hauer,et al.  HOW TO ESTIMATE THE SAFETY OF RAIL-HIGHWAY GRADE CROSSINGS AND THE SAFETY EFFECTS OF WARNING DEVICES , 1987 .

[10]  Li-Yen Chang,et al.  Analysis of traffic injury severity: an application of non-parametric classification tree techniques. , 2006, Accident; analysis and prevention.

[11]  Randall Guensler,et al.  Effect of On-Ramp Geometric and Operational Factors on Vehicle Activity , 2005 .

[12]  Laurence R. Rilett,et al.  Improved Transition Preemption Strategy for Signalized Intersections near At-Grade Railway Grade Crossing , 2007 .

[13]  Shauna L. Hallmark,et al.  Characterizing on-road variables that affect passenger vehicle modal operation , 2002 .

[14]  J R Stewart,et al.  Applications of Classification and Regression Tree Methods in Roadway Safety Studies , 1996 .

[15]  M G Karlaftis,et al.  Heterogeneity considerations in accident modeling. , 1998, Accident; analysis and prevention.

[16]  Joyoung Lee,et al.  Accident Frequency Model Using Zero Probability Process , 2006 .

[17]  Fedel Frank Saccomanno,et al.  Evaluating factors affecting safety at highway-railway grade crossings , 2005 .

[18]  Trevor Hastie,et al.  The Elements of Statistical Learning , 2001 .

[19]  Chi-Kang Lee,et al.  Analysis of Accident Risk at Railroad Grade Crossing , 2008 .

[20]  Xuedong Yan,et al.  Analyses of Rear-End Crashes Based on Classification Tree Models , 2006, Traffic injury prevention.

[21]  Liping Fu,et al.  Estimating countermeasure effects for reducing collisions at highway-railway grade crossings. , 2007, Accident; analysis and prevention.

[22]  Seohoon Jin,et al.  Decision tree approaches for zero-inflated count data , 2006 .

[23]  H W McGee,et al.  SAFETY FEATURES OF STOP SIGNS AT RAIL-HIGHWAY GRADE CROSSINGS. VOLUME II. TECHNICAL REPORT , 1978 .

[24]  Liping Fu,et al.  Risk-Based Model for Identifying Highway-Rail Grade Crossing Blackspots , 2004 .

[25]  Jodi L Carson,et al.  An alternative accident prediction model for highway-rail interfaces. , 2002, Accident; analysis and prevention.

[26]  Simon Washington,et al.  Hierarchical Tree-Based Versus Ordinary Least Squares Linear Regression Models: Theory and Example Applied to Trip Generation , 1997 .

[27]  Li-Yen Chang,et al.  Data mining of tree-based models to analyze freeway accident frequency. , 2005, Journal of safety research.

[28]  Robert Tibshirani,et al.  The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.

[29]  Mohamed Abdel-Aty,et al.  Analysis of Types of Crashes at Signalized Intersections by Using Complete Crash Data and Tree-Based Regression , 2005 .

[30]  Xiao Qin,et al.  Variable Selection Issues in Tree-Based Regression Models , 2008 .

[31]  J. Friedman.  Multivariate adaptive regression splines , 1990 .

[32]  J. Freidman,et al.  Multivariate adaptive regression splines , 1991 .

[33]  Ronald W Eck,et al.  PHYSICAL AND OPERATIONAL CHARACTERISTICS OF RAIL-HIGHWAY GRADE CROSSINGS ON LOW-VOLUME ROADS , 1987 .

[34]  Wei-Yin Loh,et al.  Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..

[35]  Jutaek Oh,et al.  Bayesian methodology incorporating expert judgment for ranking countermeasure effectiveness under uncertainty: example applied to at grade railroad crossings in Korea. , 2006, Accident; analysis and prevention.

[36]  Archie Burnham.  Stop Sign Effectiveness at Railroad Grade Crossings (Abuse without Excuse) , 1995 .

[37]  David A Noyce,et al.  Enhanced Traffic Control Devices at Passive Highway-Railroad Grade Crossings , 1998 .

[38]  James Freeman,et al.  The experiences and perceptions of heavy vehicle drivers and train drivers of dangers at railway level crossings. , 2008, Accident; analysis and prevention.

[39]  M. Hadi,et al.  ESTIMATING SAFETY EFFECTS OF CROSS-SECTION DESIGN FOR VARIOUS HIGHWAY TYPES USING NEGATIVE BINOMIAL REGRESSION , 1995 .

[40]  Doohee Nam,et al.  Accident prediction model for railway-highway interfaces. , 2006, Accident; analysis and prevention.

[41]  G. V. Kass.  An Exploratory Technique for Investigating Large Quantities of Categorical Data , 1980 .

[42]  Richard A Raub.  Examination of Highway-Rail Grade Crossing Collisions Over 10 Years in Seven Midwestern States , 2006 .

[43]  Antoine G. Hobeika,et al.  TRUCK ACCIDENT MODELS FOR INTERSTATES AND TWO-LANE RURAL ROADS , 1993 .

[44]  H W McGee,et al.  TRAFFIC-CONTROL DEVICES FOR PASSIVE RAILROAD-HIGHWAY GRADE CROSSINGS , 2002 .