A Multivariate Approach For Modeling Driver Injury Severity By Body Region
Publication date: Available online 15 May 2020Source: Analytic Methods in Accident ResearchAuthor(s): Ahmed Kabli, Tanmoy Bhowmik, Naveen Eluru (Source: Analytic Methods in Accident Research)
Source: Analytic Methods in Accident Research - May 16, 2020 Category: Accident Prevention Source Type: research

Is an informed driver a better decision maker? A grouped random parameters with heterogeneity-in-means approach to investigate the impact of the connected environment on driving behaviour in safety-critical situations
Publication date: Available online 2 April 2020Source: Analytic Methods in Accident ResearchAuthor(s): Anshuman Sharma, Zuduo Zheng, Jiwon Kim, Ashish Bhaskar, Mazharul Haque (Source: Analytic Methods in Accident Research)
Source: Analytic Methods in Accident Research - April 3, 2020 Category: Accident Prevention Source Type: research

A temporal analysis of driver-injury severities in crashes involving aggressive and non-aggressive driving
Publication date: Available online 1 April 2020Source: Analytic Methods in Accident ResearchAuthor(s): Mouyid Islam, Fred Mannering (Source: Analytic Methods in Accident Research)
Source: Analytic Methods in Accident Research - April 1, 2020 Category: Accident Prevention Source Type: research

Analysis of injury severity of rear-end crashes in work zones: A random parameters approach with heterogeneity in means and variances
Publication date: Available online 23 March 2020Source: Analytic Methods in Accident ResearchAuthor(s): Miao Yu, Changjiang Zheng, Changxi Ma (Source: Analytic Methods in Accident Research)
Source: Analytic Methods in Accident Research - March 24, 2020 Category: Accident Prevention Source Type: research

Hierarchical Bayesian Modeling to Evaluate the Impacts of Intelligent Speed Adaptation Considering Individuals’ Usual Speeding Tendencies: A Correlated Random Parameters Approach
Publication date: Available online 25 February 2020Source: Analytic Methods in Accident ResearchAuthor(s): Kojiro Matsuo, Mitsuru Sugihara, Motohiro Yamazaki, Yasuhiro Mimura, Jia Yang, Komei Kanno, Nao Sugiki (Source: Analytic Methods in Accident Research)
Source: Analytic Methods in Accident Research - February 26, 2020 Category: Accident Prevention Source Type: research

The joint effect of weather and lighting conditions on injury severities of single-vehicle accidents
Publication date: Available online 26 February 2020Source: Analytic Methods in Accident ResearchAuthor(s): Grigorios Fountas, Achille Fonzone, Niaz Gharavi, Tom Rye (Source: Analytic Methods in Accident Research)
Source: Analytic Methods in Accident Research - February 26, 2020 Category: Accident Prevention Source Type: research

Statistical and machine-learning methods for clearance time prediction of road incidents: A methodology review
Publication date: Available online 24 February 2020Source: Analytic Methods in Accident ResearchAuthor(s): Jinjun Tang, Lanlan Zheng, Chunyang Han, Weiqi Yin, Yue Zhang, Yajie Zou, Helai Huang (Source: Analytic Methods in Accident Research)
Source: Analytic Methods in Accident Research - February 25, 2020 Category: Accident Prevention Source Type: research

A hierarchical Bayesian multivariate ordered model of distracted drivers’ decision to initiate risk-compensating behaviour
This study aims to fill this gap by developing a comprehensive multivariate ordered model in Bayesian framework for risk-compensating behaviour of distracted drivers. The multivariate setting captures the common unobserved factors between multiple types of risk-compensating behaviour. In addition, an instrumental variable is employed to account for the endogeneity between crash risk and driving behaviour. To capture the varying effects of exogenous factors as well as varying propensity of initiating risk-compensating behaviour, the model is specified with grouped random parameters and random thresholds. This model is then ...
Source: Analytic Methods in Accident Research - February 8, 2020 Category: Accident Prevention Source Type: research

Temporal stability of driver injury severities in animal-vehicle collisions: A random parameters with heterogeneity in means (and variances) approach
This study investigates the determinants of driver injury severity in animal-vehicle collisions while systematically accounting for unobserved heterogeneity in the data by using three methodological approaches: mixed logit model, mixed logit model with heterogeneity in means, and mixed logit model with heterogeneity in means and variances. Using the data from Washington state from January 1, 2012 to December 31, 2016, a wide range of factors that could potentially affect the injury severity of drivers were examined. Moreover, the temporal stability and transferability of the models were investigated through a series of lik...
Source: Analytic Methods in Accident Research - February 5, 2020 Category: Accident Prevention Source Type: research

On the causal effect of proximity to school on pedestrian safety at signalized intersections: A heterogeneous endogenous econometric model
Publication date: Available online 28 January 2020Source: Analytic Methods in Accident ResearchAuthor(s): Shahram Heydari, Luis Miranda-Moreno, Adrian J. HickfordAbstractPedestrian safety in proximity to schools is a major concern of transportation authorities, local governments, and residents. In fact, several countermeasures (e.g., school-zone speed limits) are usually in place around schools to provide a safer environment, especially for school-age children. Two questions arise here: (i) are transportation facilities in proximity to schools truly safer than other facilities given a variety of implemented road safety int...
Source: Analytic Methods in Accident Research - January 29, 2020 Category: Accident Prevention Source Type: research

An Exploratory analysis of traffic accidents and vehicle ownership decisions using a random parameters logit model with heterogeneity in means
In this study, we present a methodology that addresses a driver’s decisions pertaining to a damaged car following a traffic accident. The choice set includes three alternatives: to replace the damaged car with a new one, replace the damaged car with a used one, and repair the damaged car. A random parameter (mixed) logit model with heterogeneity in the means is specified and estimated to gain more insight into the driver’s decision-making process following a traffic accident.The estimation results of the random parameter (mixed) logit model with heterogeneity in the means indicate that a wide range of explanato...
Source: Analytic Methods in Accident Research - January 29, 2020 Category: Accident Prevention Source Type: research

Big Data, Traditional Data and the Tradeoffs between Prediction and Causality in Highway-Safety Analysis
Publication date: Available online 25 January 2020Source: Analytic Methods in Accident ResearchAuthor(s): Fred Mannering, Chandra R. Bhat, Venky Shankar, Mohamed Abdel-AtyAbstractThe analysis of highway accident data is largely dominated by traditional statistical methods (standard regression-based approaches), advanced statistical methods (such as models that account for unobserved heterogeneity), and data-driven methods (artificial intelligence, neural networks, machine learning, and so on). These methods have been applied mostly using data from observed crashes, but this can create a problem in uncovering causality sinc...
Source: Analytic Methods in Accident Research - January 25, 2020 Category: Accident Prevention Source Type: research

Incorporating Safety Reliability into Route Choice Model: Heterogeneous Crash Risk Aversions
In this study, a route choice model which accounts for both travelers’ safety concern—route safety reliability—and travel time concern is proposed. Route safety reliability (variability) is defined by the distribution of the travel crash risk cost (CRC) to represent the safety condition of travel routes. We further associate the travel safety variability due to stochastic crash occurrence with travelers’ crash risk aversion route choice behaviors, and postulate that travelers acquire the variability of route travel safety based on the past experience and factor it into their route choice in the form...
Source: Analytic Methods in Accident Research - January 25, 2020 Category: Accident Prevention Source Type: research

Driver Drowsiness Detection Using Mixed-effect Ordered Logit Model Considering Time Cumulative Effect
Publication date: Available online 25 January 2020Source: Analytic Methods in Accident ResearchAuthor(s): Xuxin Zhang, Xuesong Wang, Xiaohan Yang, Chuan Xu, Xiaohui Zhu, Jiaohua WeiAbstractDrowsy driving is one of the main causes of traffic crashes, a serious threat to road traffic safety. The effective early detection of a drowsiness state can help provide a timely warning for drivers, but previous studies have seldom considered the cumulative effect of drowsiness over time. The purpose of this study is therefore to establish a model to detect a driver's drowsiness level by considering individual differences combined with...
Source: Analytic Methods in Accident Research - January 25, 2020 Category: Accident Prevention Source Type: research

A Bivariate Bayesian Hierarchical Extreme Value Model for Traffic Conflict-based Crash Estimation
Publication date: Available online 22 January 2020Source: Analytic Methods in Accident ResearchAuthor(s): Lai Zheng, Tarek SayedAbstractThere are two main issues associated with traffic conflict-based crash estimation. First, there are several conflict indicators which were shown to inherently represent partial severity aspects of traffic events. Therefore, combining more than one conflict indicator can result in more comprehensive understanding on the underlying level of safety. Second, the conflict extremes characterized by the indicators, which are most related to crashes, are rare and heterogeneous in nature. These iss...
Source: Analytic Methods in Accident Research - January 22, 2020 Category: Accident Prevention Source Type: research

Hourly associations between weather factors and traffic crashes: non-linear and lag effects
In this study, we propose a novel distributed lag non-linear model (DLNM), integrated with case-crossover design, to evaluate the lag effect of weather on crash incidence. The proposed modelling framework could describe the non-linear relationship between weather and crash and the lag effects. Also, the possible over-dispersion and autocorrelation of the time-series weather and crash data can be controlled for. The model was estimated using an integrated meteorological, traffic and crash dataset in Hong Kong. For instances, high resolution data on temperature, humidity, rain intensity and wind speed in 1-hour interval was ...
Source: Analytic Methods in Accident Research - November 9, 2019 Category: Accident Prevention Source Type: research

A latent class approach for driver injury severity analysis in highway single vehicle crash considering unobserved heterogeneity and temporal influence
This study provided an insightful understanding of the time-varying effects of the significant factors on driver injury severity using marginal effect analysis, and the temporal indicators in the proposed model were found to enhance the model capability of temporal variation identification. (Source: Analytic Methods in Accident Research)
Source: Analytic Methods in Accident Research - November 9, 2019 Category: Accident Prevention Source Type: research

Do We Need Multivariate Modeling Approaches to Model Crash Frequency by Crash Types? A Panel Mixed Approach to Modeling Crash Frequency by Crash Types
Publication date: Available online 31 October 2019Source: Analytic Methods in Accident ResearchAuthor(s): Tanmoy Bhowmik, Shamsunnahar Yasmin, Naveen EluruAbstractIn safety literature, simulation-based multivariate framework is the most commonly employed approach for analyzing multiple crash frequency dependent variables. The current research effort contributes to literature on crash frequency analysis by suggesting an alternative and mathematically simpler approach for analyzing multiple crash frequency variables for the same study unit. The proposed recasts a multivariate distributional problem as a repeated measure univ...
Source: Analytic Methods in Accident Research - October 31, 2019 Category: Accident Prevention Source Type: research

Bayesian hierarchical modeling of traffic conflict extremes for crash estimation: A non-stationary peak over threshold approach
This study presents a Bayesian hierarchical model to estimate crashes from traffic conflict extremes in a non-stationary context. The model combines a peak over threshold approach with non-stationary thresholds in terms of regression quantiles and covariate-dependent parameters of the generalized Pareto distribution. The developed model was applied to estimate rear-end crashes from traffic conflicts of the same type collected from four signalized intersections. The conflicts were measured by the modified time to collision (MTTC) and traffic volume, shock wave area, average shock wave speed, and platoon ratio of each signal...
Source: Analytic Methods in Accident Research - October 18, 2019 Category: Accident Prevention Source Type: research

Bayesian hierarchical modeling traffic conflict extremes for crash estimation: A non-stationary peak over threshold approach
This study presents a Bayesian hierarchical model to estimate crashes from traffic conflict extremes in a non-stationary context. The model combines a peak over threshold approach with non-stationary thresholds in terms of regression quantiles and covariate-dependent parameters of the generalized Pareto distribution. The developed model was applied to estimate rear-end crashes from traffic conflicts of the same type collected from four signalized intersections. The conflicts were measured by the modified time to collision (MTTC) and traffic volume, shock wave area, average shock wave speed, and platoon ratio of each signal...
Source: Analytic Methods in Accident Research - October 2, 2019 Category: Accident Prevention Source Type: research

Modeling unobserved heterogeneity for zonal crash frequencies: a Bayesian multivariate random-parameters model with mixture components for spatially correlated data
This study applies mixture components in a multivariate random parameters spatial model for zonal crash counts. Three different modeling formulations are employed to demonstrate the effects of mixture components and spatial heterogeneity in the goodness-of-fit in a multivariate random parameter model. The models are built for injury (i.e., possible, non-incapacitating, incapacitating, and fatal injury) and non-injury crashes using the data from 738 traffic analysis zones (TAZs) in Hillsborough County of Florida during a three-year period. The Deviance Information Criteria (DIC) is used to evaluate the performances of these...
Source: Analytic Methods in Accident Research - September 12, 2019 Category: Accident Prevention Source Type: research

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 interrelat...
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-fatigu...
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-fatigu...
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 drivi...
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 ...
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

A flexible discrete density random parameters model for count data: Embracing unobserved heterogeneity in highway safety analysis
Publication date: December 2018Source: Analytic Methods in Accident Research, Volume 20Author(s): Shahram HeydariAbstractIn traffic safety studies, there are almost inevitable concerns about unobserved heterogeneity. As a feasible alternative to current methods, this article proposes a novel crash count model that can address asymmetry and multimodality in the data. Specifically, a Bayesian random parameters model with flexible discrete densities for the regression coefficients is developed, employing a Dirichlet process prior. The approach is illustrated on the Ontario Highway 401, which is one of the busiest North Americ...
Source: Analytic Methods in Accident Research - November 5, 2018 Category: Accident Prevention Source Type: research

Investigating varying effect of road-level factors on crash frequency across regions: A Bayesian hierarchical random parameter modeling approach
This study aims to quantitatively examine the variations in effect of road-level factors on crash frequency across different regions. Treating the hierarchical structure existing in the crash data that road entity nested within the geographic region, a hierarchical random parameter model, which allows the coefficients of road-level variables to vary with regions, is proposed. A Poisson lognormal model and a hierarchical random intercept model are also built for the purpose of comparison. A specific roadway facility type, urban two-lane two-way roadway segments in Florida, with crash and road level data including traffic vo...
Source: Analytic Methods in Accident Research - October 20, 2018 Category: Accident Prevention Source Type: research

Non-decreasing threshold variances in mixed generalized ordered response models: A negative correlations approach to variance reduction
This study highlights a potential limitation of these models, as applied in most empirical research, that the variances of the random thresholds are implicitly assumed to be in a non-decreasing order. This restriction is unnecessary and can lead to difficulty in estimation of random parameters in higher order thresholds. In this study, we investigate the use of negative correlations between random parameters as a variance reduction technique to relax the property of non-decreasing variances of thresholds in MGOR models. To this end, a simulation-based approach was used (where multiple datasets were simulated assuming a kno...
Source: Analytic Methods in Accident Research - October 9, 2018 Category: Accident Prevention Source Type: research

Analysis of accident injury-severity outcomes: The zero-inflated hierarchical ordered probit model with correlated disturbances
Publication date: December 2018Source: Analytic Methods in Accident Research, Volume 20Author(s): Grigorios Fountas, Panagiotis Ch. AnastasopoulosAbstractIn accident injury-severity analysis, an inherent limitation of the traditional ordered probit approach arises from the a priori consideration of a homogeneous source for the accidents that result in a no-injury (or zero-injury) outcome. Conceptually, no-injury accidents may be subject to the effect of two underlying injury-severity states, which are more likely to be observed in accident datasets with excessive amounts of no-injury accident observations. To account for t...
Source: Analytic Methods in Accident Research - October 5, 2018 Category: Accident Prevention Source Type: research

Evaluating temporal variability of exogenous variable impacts over 25 years: An application of scaled generalized ordered logit model for driver injury severity
Publication date: December 2018Source: Analytic Methods in Accident Research, Volume 20Author(s): Robert Marcoux, Shamsunnahar Yasmin, Naveen Eluru, Moshiur RahmanAbstractThe current study undertakes a unique research effort to quantify the impact of various exogenous factors on crash severity over time. Specifically, we examine if over time, the impact of exogenous variables has changed and if so what is the magnitude of the change. The research contributes to driver injury severity analysis both methodologically and empirically by proposing a framework that addresses the challenges associated with pooled (or pseudo-panel...
Source: Analytic Methods in Accident Research - October 5, 2018 Category: Accident Prevention Source Type: research

Exploring driver injury severity patterns and causes in low visibility related single-vehicle crashes using a finite mixture random parameters model
This study provides an insightful understanding of the impacts of these variables on driver injury severity outcomes in low visibility related crashes, and a beneficial reference for developing countermeasures and strategies to mitigate driver injury severities under these conditions. (Source: Analytic Methods in Accident Research)
Source: Analytic Methods in Accident Research - September 7, 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 predomi...
Source: Analytic Methods in Accident Research - July 10, 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 2018Source: Analytic Methods in Accident Research, Volume 18Author(s): Grigorios Fountas, Panagiotis Ch. Anastasopoulos, Fred L. ManneringAbstractUsing 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 grou...
Source: Analytic Methods in Accident Research - July 10, 2018 Category: Accident Prevention Source Type: research

Developing a Random Parameters Negative Binomial-Lindley Model to analyze highly over-dispersed crash count data
Publication date: June 2018Source: Analytic Methods in Accident Research, Volume 18Author(s): Mohammad Razaur Rahman Shaon, Xiao Qin, Mohammadali Shirazi, Dominique Lord, Srinivas Reddy GeedipallyAbstractThe 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-disperse...
Source: Analytic Methods in Accident Research - July 10, 2018 Category: Accident Prevention Source Type: research

A joint framework for static and real-time crash risk analysis
Publication date: June 2018Source: Analytic Methods in Accident Research, Volume 18Author(s): Shamsunnahar Yasmin, Naveen Eluru, Ling Wang, Mohamed A. Abdel-AtyAbstractThe current research effort bridges the gap between traditional crash risk and real-time crash risk models by developing a joint model that accommodates for both dimensions in developing crash risk analysis models. Specifically, we develop a joint reactive and proactive crash modeling framework by coupling the monthly crash risk and real-time crash risk in a unified econometric framework for a microscopic analysis unit. In the joint modeling approach, we pro...
Source: Analytic Methods in Accident Research - July 10, 2018 Category: Accident Prevention Source Type: research

Analysis of accident injury-severities using a correlated random parameters ordered probit approach with time variant covariates
Publication date: June 2018Source: Analytic Methods in Accident Research, Volume 18Author(s): Grigorios Fountas, Panagiotis Ch. Anastasopoulos, Mohamed Abdel-AtyAbstractThis paper employs a correlated random parameters ordered probit modeling framework to explore time-variant and time-invariant factors affecting injury-severity outcomes in single-vehicle accidents. The proposed approach extends traditional random parameters modeling, by accounting for possible correlations among the random parameters. On the basis of an unrestricted covariance matrix for the random parameters, the proposed framework can capture the combine...
Source: Analytic Methods in Accident Research - July 10, 2018 Category: Accident Prevention Source Type: research

Developing a grouped random parameters multivariate spatial model to explore zonal effects for segment and intersection crash modeling
Publication date: September 2018Source: Analytic Methods in Accident Research, Volume 19Author(s): Qing Cai, Mohamed Abdel-Aty, Jaeyoung Lee, Ling Wang, Xuesong WangAbstractIt is acknowledged that crash occurrence on segments and intersections could be affected by multilevel factors. Omission of important explanatory variables could result in biased and inconsistent parameter estimates. This paper contributes to the literature by examining the zonal effects which are always excluded or ignored in traffic safety research for segments and intersections. A grouped random parameters multivariate spatial model is proposed to id...
Source: Analytic Methods in Accident Research - July 10, 2018 Category: Accident Prevention Source Type: research

A joint econometric approach for modeling crash counts by collision type
Publication date: September 2018Source: Analytic Methods in Accident Research, Volume 19Author(s): Tanmoy Bhowmik, Shamsunnahar Yasmin, Naveen EluruAbstractIn recent years, there is growing recognition that common unobserved factors that influence crash frequency by one attribute level are also likely to influence crash frequency by other attribute levels. The most common approach employed to address the potential unobserved heterogeneity in safety literature is the development of multivariate crash frequency models. The current study proposes an alternative joint econometric framework to accommodate for the presence of un...
Source: Analytic Methods in Accident Research - July 10, 2018 Category: Accident Prevention Source Type: research

Benchmarking regions using a heteroskedastic grouped random parameters model with heterogeneity in mean and variance: Applications to grade crossing safety analysis
This study provides valuable guidelines to Canadian transportation authorities, revealing important underlying crash mechanisms at highway railway grade crossings in Canada. (Source: Analytic Methods in Accident Research)
Source: Analytic Methods in Accident Research - July 10, 2018 Category: Accident Prevention Source Type: research