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Developing a Random Parameters Negative Binomial-Lindley Model to analyze highly over-dispersed crash count data
Publication date: June 2018 Source:Analytic Methods in Accident Research, Volume 18 Author(s): Mohammad Razaur Rahman Shaon, Xiao Qin, Mohammadali Shirazi, Dominique Lord, Srinivas Reddy Geedipally The existence of preponderant zero crash sites and/or sites with large crash counts can present challenges during the statistical analysis of crash count data. Additionally, unobserved heterogeneity in crash data due to the absence of important variables could negatively impact the estimated model parameters. The traditional negative binomial (NB) model with fixed parameters might not adequately handle highly over-dispers...
Source: Analytic Methods in Accident Research - April 25, 2018 Category: Accident Prevention Source Type: research

Analysis of vehicle accident-injury severities: A comparison of segment- versus accident-based latent class ordered probit models with class-probability functions
Publication date: June 2018 Source:Analytic Methods in Accident Research, Volume 18 Author(s): Grigorios Fountas, Panagiotis Ch. Anastasopoulos, Fred L. Mannering Using information from 1990 single-vehicle accidents that occurred between 2011 and 2013 in the state of Washington, the injury severity level of the most severely injured vehicle occupant is studied using two latent class modeling approaches: segment-based and accident-based latent class ordered probit model with class-probability functions. The segment-based latent class ordered probit framework allows explanatory parameters to vary across unobserved group...
Source: Analytic Methods in Accident Research - April 24, 2018 Category: Accident Prevention Source Type: research

A Comprehensive joint econometric model of motor vehicle crashes arising from multiple sources of risk
This study first postulates, and then demonstrates empirically, that crash occurrence may be more complex than can be adequately captured by a single equation regression model. The total crash count recorded at a transport network location (e.g. road segment) may arise from multiple simultaneous and inter-dependent sources of risk, rather than one. Each of these sources may uniquely contribute to the total observed crash count. For instance, a site’s crash occurrence may be dominated by contributions from driver behaviour issues (e.g. speeding, impaired driving), while another site’s crashes might arise predominately f...
Source: Analytic Methods in Accident Research - April 4, 2018 Category: Accident Prevention Source Type: research

Multivariate random parameters zero-inflated negative binomial regression for analyzing urban midblock crashes
Publication date: March 2018 Source:Analytic Methods in Accident Research, Volume 17 Author(s): Chenhui Liu, Mo Zhao, Wei Li, Anuj Sharma Urban midblock crashes are influenced mainly by traffic operation and roadway geometric features. In this paper, 10-year crash data from 1,506 directional urban midblock segments in Nebraska were analyzed using the multivariate random parameters zero-inflated negative binomial model to account for unobserved heterogeneity produced by correlations across segments, correlations across crash collision types, excessive zero crashes, and over dispersion. The multivariate random paramete...
Source: Analytic Methods in Accident Research - March 15, 2018 Category: Accident Prevention Source Type: research

Using the multivariate spatio-temporal Bayesian model to analyze traffic crashes by severity
Publication date: March 2018 Source:Analytic Methods in Accident Research, Volume 17 Author(s): Chenhui Liu, Anuj Sharma Unobserved heterogeneity across space, time, and crash type is often non-negligible in crash frequency modeling. When multiple crash types with spatial and temporal features are analyzed, multivariate spatio-temporal models should be considered. For this study, we analyzed the yearly county-level fatal, major injury, and minor injury crashes in Iowa from 2006 to 2015 using a multivariate spatio-temporal Bayesian model. The model adopted a multivariate spatial structure, a multivariate temporal struct...
Source: Analytic Methods in Accident Research - February 21, 2018 Category: Accident Prevention Source Type: research

Temporal instability and the analysis of highway accident data
Publication date: March 2018 Source:Analytic Methods in Accident Research, Volume 17 Author(s): Fred Mannering Virtually every statistical analysis of highway safety data is predicated on the assumption that the estimated model parameters are temporally stable. That is, the assumption that the effect of the determinants of accident likelihoods and resulting accident-injury severities do not change over time. This paper draws from research previously conducted in fields such as psychology, neuroscience, economics, and cognitive science to build a case for why we would not necessarily expect the effects of explanatory var...
Source: Analytic Methods in Accident Research - November 1, 2017 Category: Accident Prevention Source Type: research

The effects of neighborhood characteristics and the built environment on pedestrian injury severity: A random parameters generalized ordered probability model with heterogeneity in means and variances
Publication date: December 2017 Source:Analytic Methods in Accident Research, Volume 16 Author(s): Chunfu Xin, Rui Guo, Zhenyu Wang, Qing Lu, Pei-Sung Lin Transportation infrastructure facilities and pedestrian/driver behaviors are associated with neighborhood characteristics and the built environment. However, the effects of neighborhood characteristics and the built environment on pedestrian injury severity are not well documented. To investigate and quantify the effects of neighborhood characteristics and built environment on pedestrian injury severity, a random parameters generalized ordered probit model with he...
Source: Analytic Methods in Accident Research - October 21, 2017 Category: Accident Prevention Source Type: research

Gas dynamic analogous exposure approach to interaction intensity in multiple-vehicle crash analysis: Case study of crashes involving taxis
This study aims to propose a novel Gas Dynamic Analogous Exposure (GDAE) to model multiple-vehicle crash frequency. We analogize the meeting frequency of vehicles with the meeting frequency of gas molecules because both systems consider the numbers of the meetings of discrete entities. A meeting frequency function of vehicles is derived based on the central idea of the classical collision theory in physical chemistry with consideration of constrained vehicular movement by the road alignments. The GDAE is then formulated on the basis of the major factors that contribute to the meeting frequency of vehicles. The proposed GDA...
Source: Analytic Methods in Accident Research - October 18, 2017 Category: Accident Prevention Source Type: research

Exploring spatio-temporal effects in traffic crash trend analysis
This study addresses the limitations of existing studies by exploring multiple models that best fit the spatial and temporal correlations. In this study, we used Bayesian spatio-temporal models to investigate regional crash frequency trends, and explored the effects of omitting spatial or temporal trends in spatio-temporal correlated data. The fast Bayesian inference approach, integrated nested Laplace approximation, was used to estimate parameters. It was found that fatal crashes showed decreasing trends in all Iowa counties from 2006 to 2015, but the decreasing rates varied by counties. Among all the covariates investiga...
Source: Analytic Methods in Accident Research - October 14, 2017 Category: Accident Prevention Source Type: research

Impact of road-surface condition on rural highway safety: A multivariate random parameters negative binomial approach
Publication date: December 2017 Source:Analytic Methods in Accident Research, Volume 16 Author(s): Sikai Chen, Tariq Usman Saeed, Samuel Labi Recent studies have begun to shed more light on the crashes experienced on rural roads by examining the influence of a road’s pavement surface condition. In a bid to contribute to this growing body of knowledge and to facilitate comprehensive evaluation of pavement maintenance projects, this paper explores the safety effects of the pavement condition of rural roads. The paper tests the hypotheses that pavement roughness generally has a non-trivial residual impact on safety out...
Source: Analytic Methods in Accident Research - September 21, 2017 Category: Accident Prevention Source Type: research

Investigating the effect of spatial and mode correlations on active transportation safety modeling
Publication date: December 2017 Source:Analytic Methods in Accident Research, Volume 16 Author(s): Ahmed Osama, Tarek Sayed This paper describes the development of macro-level crash models for active modes of transportation incorporating spatial and mode correlation effects. The models are based on data from 134 traffic analysis zones (TAZs) in the City of Vancouver. Five years of cyclist and pedestrian crash data, as well as traffic exposure and large GIS data, were used to establish the macro-level crash models. The GIS data included land use, built environment, socioeconomic, bike network, and pedestrian network ind...
Source: Analytic Methods in Accident Research - September 14, 2017 Category: Accident Prevention Source Type: research

Crash modeling for intersections and segments along corridors: A Bayesian multilevel joint model with random parameters
Publication date: December 2017 Source:Analytic Methods in Accident Research, Volume 16 Author(s): Saif A. Alarifi, Mohamed A. Abdel-Aty, Jaeyoung Lee, Juneyoung Park Previous highway safety studies have focused on either intersections or roadway segments while some researchers have analyzed safety at the corridor-level. The corridor-level analysis, which aggregates intersections and roadway segments, may allow us to understand the safety problems in the wider perspective. However, it would result in losing some of the specific characteristics of intersections or roadway segments. Therefore, we proposed a multilevel ...
Source: Analytic Methods in Accident Research - August 30, 2017 Category: Accident Prevention Source Type: research

Determinants of bicyclist injury severities in bicycle-vehicle crashes: A random parameters approach with heterogeneity in means and variances
Publication date: December 2017 Source:Analytic Methods in Accident Research, Volume 16 Author(s): Ali Behnood, Fred Mannering This paper investigates risk factors that significantly contribute to the injury severity of bicyclists in bicycle/motor-vehicle crashes while systematically accounting for unobserved heterogeneity within the crash data. Using the data from Los Angeles over a seven-year period (January 1, 2010 to December 31, 2016) a random parameters multinomial logit model of bicyclist-injury severity, with heterogeneity in parameter means and variances, is estimated to explore the effects of a wide range of ...
Source: Analytic Methods in Accident Research - August 19, 2017 Category: Accident Prevention Source Type: research

Occupant injury severities in hybrid-vehicle involved crashes: A random parameters approach with heterogeneity in means and variances
Publication date: September 2017 Source:Analytic Methods in Accident Research, Volume 15 Author(s): Puttipan Seraneeprakarn, Shuaiqi Huang, Venkataraman Shankar, Fred Mannering, Narayan Venkataraman, John Milton Differences in hybrid and non-hybrid vehicle design, and potential differences in driver-related behavior among owners of these vehicle types, can potentially have interesting implications for safety-related policies. To study possible differences in hybrid and non-hybrid occupant injury severities in motor vehicle crashes, this paper uses a sample of hybrid-vehicle-involved crashes and estimates a mixed lo...
Source: Analytic Methods in Accident Research - June 23, 2017 Category: Accident Prevention Source Type: research

Multivariate space-time modeling of crash frequencies by injury severity levels
Publication date: September 2017 Source:Analytic Methods in Accident Research, Volume 15 Author(s): Xiaoxiang Ma, Suren Chen, Feng Chen Road traffic crashes threaten thousands of drivers every day and significant efforts have been put forth to reduce the number and mitigate the impacts of traffic crashes. Although the last decade has witnessed substantial methodological improvements in crash prediction modelling, several methodological challenges still remain in terms of predicting crash frequencies of different injury severity levels. These challenges include spatial correlation and/or heterogeneity, temporal correla...
Source: Analytic Methods in Accident Research - June 20, 2017 Category: Accident Prevention Source Type: research