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Simultaneous estimation of discrete outcome and continuous dependent variable equations: A bivariate random effects modeling approach with unrestricted instruments
Publication date: December 2017 Source:Analytic Methods in Accident Research, Volume 16 Author(s): Md Tawfiq Sarwar, Grigorios Fountas, Panagiotis Ch. Anastasopoulos This paper proposes a novel methodology to simultaneously model discrete outcome (binary) and continuous dependent variables. The proposed modeling framework addresses unobserved heterogeneity by accounting for both panel effects, and for contemporaneous (cross-equation) error correlation between the two dependent variables; while, variable endogeneity is addressed through the use of unrestricted – equation specific – instruments. To illustrate the ap...
Source: Analytic Methods in Accident Research - June 15, 2017 Category: Accident Prevention Source Type: research

A new spatial and flexible multivariate random-coefficients model for the analysis of pedestrian injury counts by severity level
Publication date: December 2017 Source:Analytic Methods in Accident Research, Volume 16 Author(s): Chandra R. Bhat, Sebastian Astroza, Patrícia S. Lavieri We propose in this paper a spatial random coefficients flexible multivariate count model to examine, at the spatial level of a census tract, the number of pedestrian injuries by injury severity level. Our model, unlike many other macro-level pedestrian injury studies in the literature, explicitly acknowledges that risk factors for different types of pedestrian injuries can be very different, as well as accounts for unobserved heterogeneity in the risk factor effect...
Source: Analytic Methods in Accident Research - June 7, 2017 Category: Accident Prevention Source Type: research

The effect of passengers on driver-injury severities in single-vehicle crashes: A random parameters heterogeneity-in-means approach
Publication date: June 2017 Source:Analytic Methods in Accident Research, Volume 14 Author(s): Ali Behnood, Fred Mannering This paper seeks to investigate the effects of passengers on driver-injury severities. Using single-vehicle crashes, a random parameters logit model with heterogeneity in parameter means is estimated to explore the differences in driver-injury severities in three distinct subgroups; vehicles with one occupant (driver-only), vehicles with two occupants (driver and a passenger), and vehicles with three occupants (driver and two passengers). In addition to considering age, gender and the presence of t...
Source: Analytic Methods in Accident Research - May 17, 2017 Category: Accident Prevention Source Type: research

Roadway classifications and the accident injury severities of heavy-vehicle drivers
Publication date: September 2017 Source:Analytic Methods in Accident Research, Volume 15 Author(s): Jason Anderson, Salvador Hernandez Previous heavy-vehicle (a truck with a gross vehicle weight rating greater than 10,000 pounds) injury severity studies have disaggregated data by factors such as urban/rural and time-of-day, yet a focus on contributing factors by roadway classification is lacking. Taking this into consideration, the current study aims to extend traditional heavy-vehicle driver injury severity analyses, through the application of a mixed logit modeling framework, by determining statistically significant ...
Source: Analytic Methods in Accident Research - May 7, 2017 Category: Accident Prevention Source Type: research

A random thresholds random parameters hierarchical ordered probit analysis of highway accident injury-severities
This study uses highway accident data collected in the State of Washington, between 2011 and 2013, to study the factors that affect accident injury-severities. To account for the fixed thresholds limitation of the traditional ordered probability models – which typically leads to incorrect estimation of outcome probabilities for the intermediate categories – and for the possibility of unobserved factors systematically varying across the observations, a random thresholds hierarchical ordered probit model with random parameters is estimated. This approach simultaneously allows the explanatory parameters to vary across roa...
Source: Analytic Methods in Accident Research - April 27, 2017 Category: Accident Prevention Source Type: research

A Modified Rank Ordered Logit model to analyze injury severity of occupants in multivehicle crashes
Publication date: June 2017 Source:Analytic Methods in Accident Research, Volume 14 Author(s): Shelley Bogue, Rajesh Paleti, Lacramioara Balan The current study developed a simultaneous model of injury severity outcomes of all occupants in multi-vehicle crashes including all the drivers and the passengers of all vehicles involved in a crash. Specifically, a Modified Rank Ordered Logit (MROL) methodology that can predict the relative order of occupant injury severity as well as the actual injury severity was developed. The final model captures the effects of several key occupant, vehicle, and accident level variables o...
Source: Analytic Methods in Accident Research - March 9, 2017 Category: Accident Prevention Source Type: research

Grouped random parameters bivariate probit analysis of perceived and observed aggressive driving behavior: A driving simulation study
Publication date: March 2017 Source:Analytic Methods in Accident Research, Volume 13 Author(s): Md Tawfiq Sarwar, Panagiotis Ch. Anastasopoulos, Nima Golshani, Kevin F. Hulme This paper uses driving simulation data and surveys conducted in 2014 and 2015 in Buffalo, NY, to study the factors that affect perceived (self-reported, based on surveys) and observed (as measured, based on driving simulation experiments) aggressive driving behavior. Perceived and observed aggressive driving behavior are likely to share unobserved characteristics. To simultaneously account for this cross-equation error correlation, and for unob...
Source: Analytic Methods in Accident Research - January 20, 2017 Category: Accident Prevention Source Type: research

The effect of variations in spatial units on unobserved heterogeneity in macroscopic crash models
This study uses two advanced modeling techniques, the random parameter negative binomial (RPNB) and the semi-parametric geographically weighted Poisson regression (S-GWPR), to investigate whether explanatory variables found to be significant and random in one spatial aggregation will remain significant and random when another spatial aggregation is used. The key finding is that variations in spatial units do have an impact on unobserved heterogeneity. We also found that variations in spatial units have a greater impact on unobserved heterogeneity in the RPNB models compared to the S-GWPR models. We found that the S-GWPR mo...
Source: Analytic Methods in Accident Research - January 20, 2017 Category: Accident Prevention Source Type: research

A multivariate spatial model of crash frequency by transportation modes for urban intersections
This study proposes a multivariate spatial model to simultaneously analyze the occurrence of motor vehicle, bicycle and pedestrian crashes at urban intersections. The proposed model can account for both the correlation among different modes involved in crashes at individual intersections and spatial correlation between adjacent intersections. According to the results of the model comparison, multivariate spatial model outperforms the univariate spatial model and the multivariate model in the goodness-of-fit. The results confirm the highly correlated heterogeneous residuals in modeling crash risk among motor vehicles, bicyc...
Source: Analytic Methods in Accident Research - January 20, 2017 Category: Accident Prevention Source Type: research

A negative binomial crash sum model for time invariant heterogeneity in panel crash data: Some insights
Publication date: June 2017 Source:Analytic Methods in Accident Research, Volume 14 Author(s): Ghasak I.M.A. Mothafer, Toshiyuki Yamamoto, Venkataraman N. Shankar This paper presents a negative binomial crash sum model as an alternative for modeling time invariant heterogeneity in short panel crash data. Time invariant heterogeneity arising through multiple years of observation for each segment is viewed as a common unobserved effect at the segment level, and typically treated with panel models involving fixed or random effects. Random effects model unobserved heterogeneity through the error term, typically following ...
Source: Analytic Methods in Accident Research - January 19, 2017 Category: Accident Prevention Source Type: research

Using a flexible multivariate latent class approach to model correlated outcomes: A joint analysis of pedestrian and cyclist injuries
Publication date: March 2017 Source:Analytic Methods in Accident Research, Volume 13 Author(s): Shahram Heydari, Liping Fu, Luis F. Miranda-Moreno, Lawrence Joseph Several recent transportation safety studies have indicated the importance of accounting for correlated outcomes, for example, among different crash types, including differing injury-severity levels. In this paper, we discuss inference for such data by introducing a flexible Bayesian multivariate model. In particular, we use a Dirichlet process mixture to keep the dependence structure unconstrained, relaxing the usual homogeneity assumptions. The resulting...
Source: Analytic Methods in Accident Research - December 23, 2016 Category: Accident Prevention Source Type: research

The effect of long term non-invasive pavement deterioration on accident injury-severity rates: A seemingly unrelated and multivariate equations approach
Publication date: March 2017 Source:Analytic Methods in Accident Research, Volume 13 Author(s): Md Tawfiq Sarwar, Panagiotis Ch. Anastasopoulos This paper seeks to measure the effect of long term non-invasive pavement deterioration on accident injury-severity rates, and demonstrate the potential of considering safety as one of the criteria in the pavement management decision making process. Using data from Indiana, a system of seemingly unrelated regression equations (SURE) is estimated to predict pavement deterioration curves over a 30-year projection period based on three commonly used pavement performance indicators...
Source: Analytic Methods in Accident Research - November 18, 2016 Category: Accident Prevention Source Type: research

The Palm distribution of traffic conditions and its application to accident risk assessment
Publication date: December 2016 Source:Analytic Methods in Accident Research, Volume 12 Author(s): Ilkka Norros, Pirkko Kuusela, Satu Innamaa, Eetu Pilli-Sihvola, Riikka Rajamäki We introduce a method for assessing the influence of various road, weather and traffic conditions on traffic accidents. The idea is to contrast the distribution of conditions as seen by the driver involved in an accident with their distribution as seen by an arbitrary driver. The latter is considered as a variant of the notion of Palm probability of a point process, and it is easy to compute when road, weather and traffic measurement data ...
Source: Analytic Methods in Accident Research - October 29, 2016 Category: Accident Prevention Source Type: research

Safety-oriented pavement performance thresholds: Accounting for unobserved heterogeneity in a multi-objective optimization and goal programming approach
Publication date: December 2016 Source:Analytic Methods in Accident Research, Volume 12 Author(s): Panagiotis Ch. Anastasopoulos, Md Tawfiq Sarwar, Venky N. Shankar The cornerstone of transportation infrastructure asset management is managing the physical infrastructure, with pavement preservation being one of the most critical and costly assets. Preserving pavements in an appropriate manner extends their service life, and most importantly improves motorists’ safety and satisfaction while saving public tax dollars. To that end, this paper presents a methodology to estimate pavement performance thresholds that are co...
Source: Analytic Methods in Accident Research - October 29, 2016 Category: Accident Prevention Source Type: research

Bayesian nonparametric modeling in transportation safety studies: Applications in univariate and multivariate settings
Publication date: December 2016 Source:Analytic Methods in Accident Research, Volume 12 Author(s): Shahram Heydari, Liping Fu, Lawrence Jopseph, Luis F. Miranda-Moreno In transportation safety studies, it is often necessary to account for unobserved heterogeneity and multimodality in data. The commonly used standard or over-dispersed generalized linear models (e.g., negative binomial models) do not fully address unobserved heterogeneity, assuming that crash frequencies follow unimodal exponential families of distributions. This paper employs Bayesian nonparametric Dirichlet process mixture models demonstrating some o...
Source: Analytic Methods in Accident Research - October 9, 2016 Category: Accident Prevention Source Type: research