Methodological considerations with data uncertainty in road safety analysis.

The analysis of potential influencing factors that affect the likelihood of road accident occurrence has been of major interest for safety researchers throughout the recent decades. Even though steady methodological progresses were made over the years, several impediments pertaining to the statistical analysis of crash data remain. While issues related to methodological approaches have been subject to constructive discussion, uncertainties inherent to the most fundamental part of any analysis have been widely neglected: data. This paper scrutinizes data from various sources that are commonly used in road safety studies with respect to their actual suitability for applications in this area. Issues related to spatial and temporal aspects of data uncertainty are pointed out and their implications for road safety analysis are discussed in detail. These general methodological considerations are exemplary illustrated with data from Austria, providing suggestions and methods how to overcome these obstacles. Considering these aspects is of major importance for expediting further advances in road safety data analysis and thus for increasing road safety.

[1]  Md. Tazul Islam,et al.  Effects of spatial correlation in random parameters collision count-data models , 2015 .

[2]  C. Daly,et al.  A Statistical-Topographic Model for Mapping Climatological Precipitation over Mountainous Terrain , 1994 .

[3]  D. Lord,et al.  Investigation of Effects of Underreporting Crash Data on Three Commonly Used Traffic Crash Severity Models , 2011 .

[4]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[5]  S Yagar,et al.  A temporal analysis of rain-related crash risk. , 1993, Accident; analysis and prevention.

[6]  R. Tibshirani Regression Shrinkage and Selection via the Lasso , 1996 .

[7]  Jianming Ma P.E. Bayesian Analysis of Underreporting Poisson Regression Model with an Application to Traffic Crashes on Two-Lane Highways , 2009 .

[8]  Julia B Edwards,et al.  WEATHER-RELATED ROAD ACCIDENTS IN ENGLAND AND WALES: A SPATIAL ANALYSIS / , 1996 .

[9]  Michael B. Lowry,et al.  Spatial interpolation of traffic counts based on origin–destination centrality , 2014 .

[10]  Margaret M. Peden,et al.  World Report on Road Traffic Injury Prevention , 2004 .

[11]  D. Eisenberg The mixed effects of precipitation on traffic crashes. , 2004, Accident; analysis and prevention.

[12]  S. Schubert,et al.  MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications , 2011 .

[13]  F. Giorgi,et al.  Regional Dynamical Downscaling and the Cordex Initiative , 2015 .

[14]  A. Sterl,et al.  The ERA‐40 re‐analysis , 2005 .

[15]  R. Steinacker,et al.  A Mesoscale Data Analysis and Downscaling Method over Complex Terrain , 2006 .

[16]  Lynn A. Sherretz,et al.  An Analysis of the Relationship Between Rainfall and the Occurrence Of Traffic Accidents , 1978 .

[17]  Russell G. Congalton,et al.  Global Land Cover Mapping: A Review and Uncertainty Analysis , 2014, Remote. Sens..

[18]  Trevor Hastie,et al.  Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.

[19]  R. Reynolds,et al.  The NCEP/NCAR 40-Year Reanalysis Project , 1996, Renewable Energy.

[20]  Michele Brunetti,et al.  HISTALP—historical instrumental climatological surface time series of the Greater Alpine Region , 2007 .

[21]  A. Degaetano,et al.  Spatial Interpolation of Daily Maximum and Minimum Air Temperature Based on Meteorological Model Analyses and Independent Observations , 2007 .

[22]  J. Abatzoglou Development of gridded surface meteorological data for ecological applications and modelling , 2013 .

[23]  Reinhold Steinacker,et al.  Data Quality Control Based on Self-Consistency , 2011 .

[24]  Hoong Chor Chin,et al.  Application of Poisson Underreporting Model to Examine Crash Frequencies at Signalized Three-Legged Intersections , 2005 .

[25]  P. Jones,et al.  A European daily high-resolution gridded data set of surface temperature and precipitation for 1950-2006 , 2008 .

[26]  Paul P Jovanis,et al.  Using naturalistic driving data to explore the association between traffic safety-related events and crash risk at driver level. , 2014, Accident; analysis and prevention.

[27]  Joseph E. Hummer,et al.  Comparison of mobile and manual data collection for roadway components , 2011 .

[28]  Sabrina Giordano,et al.  hmmm: An R Package for Hierarchical Multinomial Marginal Models , 2014 .

[29]  Dominique Lord,et al.  The statistical analysis of highway crash-injury severities: a review and assessment of methodological alternatives. , 2011, Accident; analysis and prevention.

[30]  Peter Bühlmann Regression shrinkage and selection via the Lasso: a retrospective (Robert Tibshirani): Comments on the presentation , 2011 .

[31]  Chandra R. Bhat,et al.  Analytic methods in accident research: Methodological frontier and future directions , 2014 .

[32]  K. Richards,et al.  Homogenization of surface temperature data in High Mountain Asia through comparison of reanalysis data and station observations , 2016 .

[33]  T. Haiden,et al.  The Integrated Nowcasting through Comprehensive Analysis (INCA) System and Its Validation over the Eastern Alpine Region , 2011 .

[34]  Kira Hyldekær Janstrup,et al.  Road Safety Annual Report 2017 , 2017 .

[35]  George Yannis,et al.  A review of the effect of traffic and weather characteristics on road safety. , 2014, Accident; analysis and prevention.

[36]  Andrew P Tarko,et al.  Markov switching negative binomial models: an application to vehicle accident frequencies. , 2008, Accident; analysis and prevention.

[37]  Yingjie Xia,et al.  Towards improving quality of video-based vehicle counting method for traffic flow estimation , 2016, Signal Process..

[38]  F. Zhao,et al.  Using Geographically Weighted Regression Models to Estimate Annual Average Daily Traffic , 2004 .

[39]  Fred L. Mannering,et al.  The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives , 2010 .

[40]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[41]  Benedikt Bica,et al.  INCA-CE: a Central European initiative in nowcasting severe weather and its applications , 2012 .

[42]  F Mannering,et al.  Effect of roadway geometrics and environmental factors on rural freeway accident frequencies. , 1995, Accident; analysis and prevention.

[43]  Kara M. Kockelman,et al.  Spatial prediction of traffic levels in unmeasured locations: applications of universal kriging and geographically weighted regression , 2013 .

[44]  Christoph Matulla,et al.  Regional, seasonal and predictor-optimized downscaling to provide groups of local scale scenarios in the complex structured terrain of Austria , 2005 .

[45]  C. Schär,et al.  Reconstruction of Mesoscale Precipitation Fields from Sparse Observations in Complex Terrain , 2001 .

[46]  Panagiotis Ch. Anastasopoulos Random parameters multivariate tobit and zero-inflated count data models: addressing unobserved and zero-state heterogeneity in accident injury-severity rate and frequency analysis , 2016 .

[47]  Bhagwant Persaud,et al.  Accident Prediction Models With and Without Trend: Application of the Generalized Estimating Equations Procedure , 2000 .

[48]  C. Farmer Reliability of Police-Reported Information for Determining Crash and Injury Severity , 2003, Traffic injury prevention.

[49]  Pengjun Zheng,et al.  An Investigation on the Manual Traffic Count Accuracy , 2012 .

[50]  Weixu Wang,et al.  Application of generalized estimating equations for crash frequency modeling with temporal correlation , 2014, Journal of Zhejiang University SCIENCE A.

[51]  R. Bivand,et al.  Tools for Reading and Handling Spatial Objects , 2016 .

[52]  Martin Garnowski,et al.  On factors related to car accidents on German Autobahn connectors. , 2011, Accident; analysis and prevention.

[53]  José Manuel Gutiérrez,et al.  On the Use of Reanalysis Data for Downscaling , 2012 .

[54]  B. Boudevillain,et al.  A high-resolution rainfall re-analysis based on radar–raingauge merging in the Cévennes-Vivarais region, France , 2016 .

[55]  R. Steinacker,et al.  A new concept for high resolution temperature analysis over complex terrain , 2006 .

[56]  J. Apt,et al.  Quantifying sources of uncertainty in reanalysis derived wind speed , 2016 .

[57]  Jochen Köhler,et al.  Prediction of road accidents: A Bayesian hierarchical approach. , 2013, Accident; analysis and prevention.

[58]  George Yannis,et al.  Explaining the road accident risk: weather effects. , 2013, Accident; analysis and prevention.

[59]  R. Tibshirani,et al.  Regression shrinkage and selection via the lasso: a retrospective , 2011 .

[60]  Dominique Lord,et al.  Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory. , 2005, Accident; analysis and prevention.

[61]  Toshiyuki Yamamoto,et al.  Underreporting in traffic accident data, bias in parameters and the structure of injury severity models. , 2008, Accident; analysis and prevention.

[62]  Cynthia Burch,et al.  A Comparison of KABCO and AIS Injury Severity Metrics Using CODES Linked Data , 2014, Traffic injury prevention.

[63]  A S Hakkert,et al.  Risk of a road accident in rainy weather. , 1988, Accident; analysis and prevention.

[64]  Comparison of NCEP‐NCAR and ERA‐Interim over Australia , 2016 .

[65]  Daiheng Ni Traffic Sensing Technologies , 2016 .

[66]  Edward Cripps,et al.  Bayesian Analysis of Uncertainty in the GlobCover 2009 Land Cover Product at Climate Model Grid Scale , 2016, Remote. Sens..

[67]  Rowan Fealy,et al.  Comparison of ERA‐40, ERA‐Interim and NCEP/NCAR reanalysis data with observed surface air temperatures over Ireland , 2011 .

[68]  R. Benestad Empirical-statistical downscaling in climate modeling , 2004 .

[69]  Jean-Louis Martin,et al.  Relationship between crash rate and hourly traffic flow on interurban motorways. , 2002, Accident; analysis and prevention.

[70]  Simon Washington,et al.  On the significance of omitted variables in intersection crash modeling. , 2012, Accident; analysis and prevention.

[71]  D. Noyce,et al.  Rainfall effect on single-vehicle crash severities using polychotomous response models. , 2010, Accident; analysis and prevention.

[72]  Sudeshna Mitra,et al.  Sun glare and road safety: An empirical investigation of intersection crashes , 2014 .

[73]  Srinivas Reddy Geedipally,et al.  Analysis of crash severities using nested logit model--accounting for the underreporting of crashes. , 2012, Accident; analysis and prevention.

[74]  R Kulmala,et al.  Measuring the contribution of randomness, exposure, weather, and daylight to the variation in road accident counts. , 1995, Accident; analysis and prevention.

[75]  Suzanne J Wilson,et al.  Validity of using linked hospital and police traffic crash records to analyse motorcycle injury crash characteristics. , 2012, Accident; analysis and prevention.

[76]  C. Frei,et al.  Comparison of six methods for the interpolation of daily, European climate data , 2008 .

[77]  Manfred J. Lexer,et al.  Climate change scenarios at Austrian National Forest Inventory sites , 2002 .

[78]  Linda Ng Boyle,et al.  Emerging research methods and their application to road safety. , 2013, Accident; analysis and prevention.

[79]  Damien Sulla-Menashe,et al.  A Global Land Cover Climatology Using MODIS Data , 2014 .

[80]  C. Frei Interpolation of temperature in a mountainous region using nonlinear profiles and non‐Euclidean distances , 2014 .

[81]  S. Washington,et al.  Statistical and Econometric Methods for Transportation Data Analysis , 2010 .

[82]  Charles P Compton,et al.  Injury severity codes: a comparison of police injury codes and medical outcomes as determined by NASS CDS Investigators. , 2005, Journal of safety research.

[83]  C. Frei,et al.  Daily temperature grids for Austria since 1961—concept, creation and applicability , 2015, Theoretical and Applied Climatology.

[84]  Ramesh S. V. Teegavarapu,et al.  Geo-spatial grid-based transformations of precipitation estimates using spatial interpolation methods , 2012, Comput. Geosci..

[85]  Rob Jamieson,et al.  Sensitivity of DEM, slope, aspect and watershed attributes to LiDAR measurement uncertainty. , 2016 .

[86]  Haris N. Koutsopoulos,et al.  A Synthesis of emerging data collection technologies and their impact on traffic management applications , 2011 .

[87]  C. Daly,et al.  Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States , 2008 .

[88]  Naveen Eluru,et al.  Evaluating alternate discrete outcome frameworks for modeling crash injury severity. , 2013, Accident; analysis and prevention.

[89]  V. Sisiopiku,et al.  Relationship Between Volume-to-Capacity Ratios and Accident Rates , 1997 .

[90]  Geert Wets,et al.  Studying the effect of weather conditions on daily crash counts using a discrete time-series model. , 2008, Accident; analysis and prevention.

[91]  G. Pegram,et al.  Interpolation of daily rainfall networks using simulated radar fields for realistic hydrological modelling of spatial rain field ensembles , 2014 .

[92]  T. Wigley,et al.  Downscaling general circulation model output: a review of methods and limitations , 1997 .

[93]  Ahmed E. Radwan,et al.  Modeling traffic accident occurrence and involvement. , 2000, Accident; analysis and prevention.

[94]  Torsten Hothorn,et al.  Model-based Boosting 2.0 , 2010, J. Mach. Learn. Res..

[95]  Andrea K. Kaiser-Weiss,et al.  Methodologies to characterize uncertainties in regional reanalyses , 2015 .

[96]  Frank E. Harrell,et al.  Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis , 2001 .

[97]  A. Männik,et al.  High resolution re-analysis for the Baltic Sea region during 1965–2005 period , 2011 .

[98]  Timo Vihma,et al.  Validation of atmospheric reanalyses over the central Arctic Ocean , 2012 .

[99]  C. Kobayashi,et al.  The JRA-55 Reanalysis: General Specifications and Basic Characteristics , 2015 .

[100]  Zengyun Hu,et al.  Evaluation of reanalysis, spatially interpolated and satellite remotely sensed precipitation data sets in central Asia , 2016 .

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

[102]  Fred Mannering,et al.  Impact of roadside features on the frequency and severity of run-off-roadway accidents: an empirical analysis. , 2002, Accident; analysis and prevention.

[103]  P. Rietveld,et al.  The impact of climate change and weather on transport: An overview of empirical findings , 2009 .

[104]  K. Schulz,et al.  Statistical Downscaling of ERA-Interim Forecast Precipitation Data in Complex Terrain Using LASSO Algorithm , 2014 .