Analytic Methods in Accident Research Analytic Methods in Accident Research RSS feedThis is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Contrasting case-wise deletion with multiple imputation and latent variable approaches to dealing with missing observations in count regression models
Publication date: Available online 17 August 2019Source: Analytic Methods in Accident ResearchAuthor(s): Amir Pooyan Afghari, Simon Washington, Carlo Prato, Md Mazharul HaqueAbstractMissing data can lead to biased and inefficient parameter estimates in statistical models, depending on the missing data mechanism. Count regression models are no exception, with missing data leading to incorrect inferences about the effects of explanatory variables. A convenient approach for dealing with missing data is to remove observations with incomplete records prior to the analysis - often referred to as case-wise deletion. Removing inco...
Source: Analytic Methods in Accident Research - August 17, 2019 Category: Accident Prevention Source Type: research

An exploratory investigation of public perceptions towards safety and security from the future use of flying cars in the united states
This study aims at investigating public perceptions towards the safety and security implications that will arise after the future introduction of flying cars in the traffic fleet. In this context, we focus on individuals’ opinions about possible safety benefits and concerns as well as about policy measures that can potentially enhance the security of flying car. Due to the emergent nature and lack of public exposure of this technology, individuals’ perceptions and opinions regarding flying cars might be subject to several layers of unobserved heterogeneity, such as shared unobserved variations across interrelated perce...
Source: Analytic Methods in Accident Research - July 14, 2019 Category: Accident Prevention Source Type: research

Time-of-day variations and temporal instability of factors affecting injury severities in large-truck crashes
Publication date: Available online 5 July 2019Source: Analytic Methods in Accident ResearchAuthor(s): Ali Behnood, Fred L. ManneringAbstractUsing the data from large-truck crashes in Los Angeles over an eight-year period (January 1, 2010 to December 31, 2017), the variation in the influence of factors affecting injury severities during different time periods of the day (morning and afternoon) and from year to year is studied. To capture potential unobserved heterogeneity, random parameters logit models with heterogeneity in the means and variances of the random parameters were estimated considering three possible crash inj...
Source: Analytic Methods in Accident Research - July 6, 2019 Category: Accident Prevention Source Type: research

Analyzing road crash frequencies with uncorrelated and correlated random-parameters count models: An empirical assessment of multilane highways
Publication date: Available online 22 June 2019Source: Analytic Methods in Accident ResearchAuthor(s): Tariq Usman Saeed, Thomas Hall, Hiba Baroud, Matthew J. VolovskiAbstractRecent literature on highway safety research has focused on methodological advances to minimize misspecifications and the potential for erroneous estimates and invalid statistical inferences. To further these efforts, this study carries out an empirical assessment of uncorrelated and correlated random-parameters count models for analyzing road crash frequencies on multilane highways considering two crash severities; injury and no-injury. The empirical...
Source: Analytic Methods in Accident Research - June 24, 2019 Category: Accident Prevention Source Type: research

Bayesian hierarchical modeling of the non-stationary traffic conflict extremes for crash estimation
Publication date: Available online 14 June 2019Source: Analytic Methods in Accident ResearchAuthor(s): Lai Zheng, Tarek Sayed, Mohamed EssaAbstractA Bayesian hierarchical modeling (BHM) approach is used to model non-stationary traffic conflict extremes of different sites together for crash estimation. The hierarchical structure has three layers, a data layer that is modeled with a generalized extreme value (GEV) distribution, a latent Gaussian process layer that relates parameters of GEV to covariates and the unobserved heterogeneity, and a prior layer with prior distributions to characterize the latent process. The propos...
Source: Analytic Methods in Accident Research - June 15, 2019 Category: Accident Prevention Source Type: research

Publisher’s Note
Publication date: June 2019Source: Analytic Methods in Accident Research, Volume 22Author(s): (Source: Analytic Methods in Accident Research)
Source: Analytic Methods in Accident Research - June 12, 2019 Category: Accident Prevention Source Type: research

A marginalized random effects hurdle negative binomial model for analyzing refined-scale crash frequency data
In this study, a marginalized random effects hurdle negative binomial (MREHNB) model was developed in which the hurdle modelling structure handles the excessive zeros issue and site-specific random effect terms capture the factors associated with unobserved heterogeneity. Moreover, the marginalized inference approach was first introduced here to obtain the marginal mean inference for the overall population rather than subject-specific estimations. Empirical analyses were conducted based on data from the Shanghai urban expressway system, and the MREHNB model was compared with the HNB (hurdle negative binomial) and the REHNB...
Source: Analytic Methods in Accident Research - May 15, 2019 Category: Accident Prevention Source Type: research

The effects of driver fatigue, gender, and distracted driving on perceived and observed aggressive driving behavior: A correlated grouped random parameters bivariate probit approach
This study aims to provide further insights in the variations of these two behavioral components arising from driver’s fatigue, gender as well as internal and external distractions (such as, rushing to destination, listening to music and solving logical problems) during the driving task. To identify how the factors determining perceived and observed aggressive behavior may vary across groups of drivers associated with such sources of aggressive driving, survey and simulation data are statistically analyzed. Separate models of perceived and observed aggressive driving behavior are estimated for fatigued and non-fatigued, ...
Source: Analytic Methods in Accident Research - May 4, 2019 Category: Accident Prevention Source Type: research

The effects of driver fatigue, gender, and distracted driving on perceived and observed aggressive driving behavior: A correlated grouped random parameters bivariate probit approach
This study aims to provide further insights in the variations of these two behavioral components arising from driver’s fatigue, gender as well as internal and external distractions (such as, rushing to destination, listening to music and solving logical problems) during the driving task. To identify how the factors determining perceived and observed aggressive behavior may vary across groups of drivers associated with such sources of aggressive driving, survey and simulation data are statistically analyzed. Separate models of perceived and observed aggressive driving behavior are estimated for fatigued and non-fatigued, ...
Source: Analytic Methods in Accident Research - April 12, 2019 Category: Accident Prevention Source Type: research

Combining driving simulator and physiological sensor data in a latent variable model to incorporate the effect of stress in car-following behaviour
Publication date: June 2019Source: Analytic Methods in Accident Research, Volume 22Author(s): Evangelos Paschalidis, Charisma F. Choudhury, Stephane HessAbstractCar-following models, which are used to predict the acceleration-deceleration decisions of drivers in the presence of a closely spaced lead vehicle, are critical components of traffic microsimulation tools and useful for safety evaluation. Existing car-following models primarily account for the effects of surrounding traffic conditions on a driver’s decision to accelerate or decelerate. However, research in human factors and safety has demonstrated that driving d...
Source: Analytic Methods in Accident Research - April 10, 2019 Category: Accident Prevention Source Type: research

A statistical assessment of temporal instability in the factors determining motorcyclist injury severities
This study explores the temporal instability of factors affecting motorcyclist-injury severities in single-vehicle motorcycle crashes in Florida. Two data sources are used; one covers the 2012 to 2016 crash histories of Florida motorcyclists who were newly licensed in 2012, and the second covers motorcycle crashes that occur on horizontal curves in Florida from 2005 to 2015. In the first dataset (2012 new riders), temporal changes may result from riders gaining experience as well as general temporal shifts. In the second dataset, rider experience is unknown (thus becoming a source of potential unobserved heterogeneity) but...
Source: Analytic Methods in Accident Research - April 7, 2019 Category: Accident Prevention Source Type: research

A preliminary investigation of the effectiveness of high visibility enforcement programs using naturalistic driving study data: A grouped random parameters approach
Publication date: Available online 22 February 2019Source: Analytic Methods in Accident ResearchAuthor(s): Sarvani Sonduru Pantangi, Grigorios Fountas, Md Tawfiq Sarwar, Panagiotis Ch. Anastasopoulos, Alan Blatt, Kevin Majka, John Pierowicz, Satish B. MohanAbstractThis paper seeks to assess the effectiveness of high-visibility enforcement (HVE) programs in terms of reducing aggressive driving behavior. Using Strategic Highway Research Program 2 (SHRP2) Naturalistic driving study (NDS) data, behavioral reactions of drivers before, during, and after the conduct of high-visibility enforcement programs are analyzed, in order t...
Source: Analytic Methods in Accident Research - February 23, 2019 Category: Accident Prevention Source Type: research

A hierarchical Bayesian spatiotemporal random parameters approach for alcohol/drug impaired-driving crash frequency analysis
In this study, hierarchical Bayesian random parameters models with various spatiotemporal interactions are developed to address this issue. Selected for analysis are the yearly county-level alcohol/drug impaired-driving related crash counts data of three different injury severities including minor injury, major injury, and fatal injury in Idaho from 2010 to 2015. The variables, including daily vehicle miles traveled (DVMT), the proportion of male (MALE), unemployment rate (UR), and the percentage of drivers of 25 years and older with a bachelor's degree or higher (BD), are found to have significant impacts on crash frequ...
Source: Analytic Methods in Accident Research - February 9, 2019 Category: Accident Prevention Source Type: research

Comprehensive evaluation of signal-coordinated arterials on traffic safety
Publication date: Available online 31 January 2019Source: Analytic Methods in Accident ResearchAuthor(s): Yingfei Fan, Guopeng Zhang, Jian Ma, Jaeyoung Lee, Teng Meng, Xiaoning Zhang, Xinguo JiangAbstractMany cities have adopted signal coordination schemes to improve the operational efficiency of arterials. Through providing a “green wave”, the coordinated signals allow vehicles to pass consecutive intersections with fewer stops. Conventionally, studies focused mainly on the efficiency aspect of signal coordination. From a safety perspective, there are few studies devoted to investigating spatial heterogeneity and homo...
Source: Analytic Methods in Accident Research - January 31, 2019 Category: Accident Prevention Source Type: research

A multilevel generalized ordered probit fractional split model for analyzing vehicle speed
Publication date: Available online 31 December 2018Source: Analytic Methods in Accident ResearchAuthor(s): Tanmoy Bhowmik, Shamsunnahar Yasmin, Naveen EluruAbstractVehicle operating speed plays a significant role in many fields of transportation engineering including safety, operation, design and management. The current research effort contributes to literature on examining vehicle speed on arterial roads methodologically and empirically. Specifically, we propose and estimate a panel mixed generalized ordered probit fractional split (PMGOPFS) model to examine critical factors contributing to vehicle operating speed on road...
Source: Analytic Methods in Accident Research - January 1, 2019 Category: Accident Prevention Source Type: research