Prof. Naveen Eluru is primarily involved in the formulation and development of discrete choice models that allow us to better understand the behavioral patterns involved in various decision processes. He has worked extensively with discrete choice models accounting for self-selection, simultaneous equation modeling, generalized ordered logit models, stated preference studies, multiple discrete-continuous frameworks, copula based models, composite likelihood approaches and multi-dimensional choice processes as part of his research. He is also actively involved in the development of activity-based modeling software for urban metropolitan regions. He has been extensively involved in the deployment of these micro-simulation tools in the cities of Dallas Fort-Worth and Los Angeles. He has also worked on integration of activity based models with dynamic traffic assignment modules.
There is a rapid growth of bicycle-sharing systems (BSS) around the world. Cities are supporting ... more There is a rapid growth of bicycle-sharing systems (BSS) around the world. Cities are supporting these systems as a more sustainable transport mode for short trips. Given the relatively recent adoption of BSS, there is substantial interest in understanding how these systems impact urban transportation. In this paper, we examine the functioning of the hugely successful New York City CitiBike system. We focus on the interaction of BSS with land-use and built environment attributes and the influence of weather condition and temporal characteristics on BSS usage. Towards this end, CitiBike system is analyzed along two dimensions: (1) at the system level, we examine the hourly station level arrival and departure rates using a linear mixed model and (2) at the trip level, we investigate users' destination station choice preferences after they pick up a bicycle from a station employing a random utility maximization approach. The results highlight clear spatial and temporal differences ...
Transportation Research Record: Journal of the Transportation Research Board, 2018
With the introduction of automated vehicles, the performance of the trucking industry is expected... more With the introduction of automated vehicles, the performance of the trucking industry is expected to be improved. In fact, this may impact the entire freight transportation system as trucks possess the highest mode share in freight transportation. To investigate this impact, a hybrid utility–regret-based mode choice model accommodating for shipper level unobserved heterogeneity is proposed in this study. It recognizes that not all attributes influencing shipment mode are evaluated following a homogenous decision rule (solely random utility maximization/solely random regret minimization). The proposed model system is developed using 2012 Commodity Flow Survey data. To demonstrate the applicability of the proposed model system, a detailed policy analysis is conducted considering several futuristic scenarios such as implementation of automation and controlled access of truck traffic to an urban region. The results indicate that introduction of automation in the freight industry would b...
Since public transit infrastructure affects road traffic volumes and influences transportation mo... more Since public transit infrastructure affects road traffic volumes and influences transportation mode choice, which in turn impacts health, it is important to estimate the alteration of the health burden linked with transit policies. We quantified the variation in health benefits and burden between a business as usual (BAU) and a public transit (PT) scenarios in 2031 (with 8 and 19 new subway and train stations) for the greater Montreal region. Using mode choice and traffic assignment models, we predicted the transportation mode choice and traffic assignment on the road network. Subsequently, we estimated the distance travelled in each municipality by mode, the minutes spent in active transportation, as well as traffic emissions. Thereafter we estimated the health burden attributed to air pollution and road traumas and the gains associated with active transportation for both the BAU and PT scenarios. We predicted a slight decrease of overall trips and kilometers travelled by car as we...
Transportation Research Record: Journal of the Transportation Research Board, 2015
In the transportation safety field, in an effort to improve safety, statistical models are develo... more In the transportation safety field, in an effort to improve safety, statistical models are developed to identify factors that contribute to crashes as well as those that affect injury severity. This study contributes to the literature on severity analysis. Injury severity and vehicle damage are two important indicators of severity in crashes and are typically modeled independently. However, there are common observed and unobserved factors affecting the two crash indicators that lead to potential interrelationships. Failure to account for the interrelationships between the indicators may lead to biased coefficient estimates in crash severity prediction models. The focus of this study was to explore interrelationships between injury severity and vehicle damage and to also identify the nature of these correlations across different types of crashes. A copula-based methodology that could simultaneously model injury severity and vehicle damage while also accounting for the interrelationsh...
There is a rapid growth of bicycle-sharing systems (BSS) around the world. Cities are supporting ... more There is a rapid growth of bicycle-sharing systems (BSS) around the world. Cities are supporting these systems as a more sustainable transport mode for short trips. Given the relatively recent adoption of BSS, there is substantial interest in understanding how these systems impact urban transportation. In this paper, we examine the functioning of the hugely successful New York City CitiBike system. We focus on the interaction of BSS with land-use and built environment attributes and the influence of weather condition and temporal characteristics on BSS usage. Towards this end, CitiBike system is analyzed along two dimensions: (1) at the system level, we examine the hourly station level arrival and departure rates using a linear mixed model and (2) at the trip level, we investigate users' destination station choice preferences after they pick up a bicycle from a station employing a random utility maximization approach. The results highlight clear spatial and temporal differences ...
Transportation Research Record: Journal of the Transportation Research Board, 2018
With the introduction of automated vehicles, the performance of the trucking industry is expected... more With the introduction of automated vehicles, the performance of the trucking industry is expected to be improved. In fact, this may impact the entire freight transportation system as trucks possess the highest mode share in freight transportation. To investigate this impact, a hybrid utility–regret-based mode choice model accommodating for shipper level unobserved heterogeneity is proposed in this study. It recognizes that not all attributes influencing shipment mode are evaluated following a homogenous decision rule (solely random utility maximization/solely random regret minimization). The proposed model system is developed using 2012 Commodity Flow Survey data. To demonstrate the applicability of the proposed model system, a detailed policy analysis is conducted considering several futuristic scenarios such as implementation of automation and controlled access of truck traffic to an urban region. The results indicate that introduction of automation in the freight industry would b...
Since public transit infrastructure affects road traffic volumes and influences transportation mo... more Since public transit infrastructure affects road traffic volumes and influences transportation mode choice, which in turn impacts health, it is important to estimate the alteration of the health burden linked with transit policies. We quantified the variation in health benefits and burden between a business as usual (BAU) and a public transit (PT) scenarios in 2031 (with 8 and 19 new subway and train stations) for the greater Montreal region. Using mode choice and traffic assignment models, we predicted the transportation mode choice and traffic assignment on the road network. Subsequently, we estimated the distance travelled in each municipality by mode, the minutes spent in active transportation, as well as traffic emissions. Thereafter we estimated the health burden attributed to air pollution and road traumas and the gains associated with active transportation for both the BAU and PT scenarios. We predicted a slight decrease of overall trips and kilometers travelled by car as we...
Transportation Research Record: Journal of the Transportation Research Board, 2015
In the transportation safety field, in an effort to improve safety, statistical models are develo... more In the transportation safety field, in an effort to improve safety, statistical models are developed to identify factors that contribute to crashes as well as those that affect injury severity. This study contributes to the literature on severity analysis. Injury severity and vehicle damage are two important indicators of severity in crashes and are typically modeled independently. However, there are common observed and unobserved factors affecting the two crash indicators that lead to potential interrelationships. Failure to account for the interrelationships between the indicators may lead to biased coefficient estimates in crash severity prediction models. The focus of this study was to explore interrelationships between injury severity and vehicle damage and to also identify the nature of these correlations across different types of crashes. A copula-based methodology that could simultaneously model injury severity and vehicle damage while also accounting for the interrelationsh...
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