Tanmoy Bhowmik

• Doctor of Philosophy
• Upcoming Assistant Professor at Portland State University

The current research effort is focused on improving the effective use of the multiple disparate sources of data available by proposing a novel maximum likelihood based probabilistic data fusion approach for modeling residential energy consumption. To demonstrate our data fusion algorithm, we consider energy usage by fuel type variables (for electri...

Although several approaches exist for data imputation, these approaches are not commonly applied in transportation. The current paper is geared toward assisting transportation researchers and practitioners in developing models using datasets with missing data. The study begins with a data simulation exercise evaluating different solutions implement...

In recent years, joint count and fractional split model structure based approaches have emerged as a credible alternative for multivariate crash frequency dependent variables. However, current approaches in the fractional split theme have a limitation. The fractional split component of these frameworks allocates a proportion to all crash configurat...

The current study contributes to safety literature by incorporating the influence of temporal factors (observed and unobserved) within a multivariate model system for medical professional generated body region specific injury severity score. For this purpose, we adopt a hybrid econometric modeling approach that accommodates for the unobserved facto...

In this study, we examine the factors affecting Chicago, U.S., transportation network companies (TNCs) users’ trip fare and destination choice behavior. While trip fare has been examined from various perspectives, earlier fare models have not considered an exhaustive set of independent variables. Further, trip fare decisions are significantly influ...

To model road crash frequency, studies apply count data models with different functional forms including traditional, Hoerl, and flexible forms. To capture unobserved heterogeneity, simulation-assisted random parameter (RP) negative binomial (NB) models are used. There is growing emphasis on including random parameters (RPs) in developing crash fre...

The current study proposes a novel modeling approach for modeling airline demand. Specifically, we develop a joint panel generalized ordered probit model system with observed thresholds for modeling air passenger arrivals and departures while accommodating for the influence of observed and unobserved effects on airline demand across multiple time p...

The main goal of the current study is to identify the factors affecting flight-level airline delay by jointly modeling departure and arrival delays. Toward this end, we develop a novel copula-based group generalized ordered logit (GGOL) model system that accommodates for the influence of common observed and unobserved effects on flight departure an...

Network-wide traffic prediction at the level of an intersection can benefit transportation systems management and operations. However, traditional traffic modeling approaches relying on mathematical or simulation-based models are either less useful or require higher computational time in predicting high fidelity traffic volumes. In addition, these...

Safety literature has traditionally developed independent model systems for macroscopic and microscopic level analysis. The current research effort contributes to the literature on crash frequency by building a bridge between these two divergent streams of crash frequency research. The study proposes an integrated micro-macro level model for crash...

This study presents a framework to employ naturalistic driving study (NDS) data to understand and predict crash risk at a disaggregate trip level accommodating for the influence of trip characteristics (such as trip distance, trip proportion by speed limit, trip proportion on urban/rural facilities) in addition to the traditional crash factors. Rec...

In this study, we examine the influence of Coronavirus disease 2019 (COVID-19) on airline demand at the disaggregate resolution of airport. The primary focus of our proposed research effort is to develop a framework that provides a blueprint for airline demand recovery as COVID-19 cases evolve over time. Airline monthly demand data is sourced from...

The sustained COVID-19 case numbers and the associated hospitalizations have placed a substantial burden on health care ecosystem comprising of hospitals, clinics, doctors and nurses. However, as of today, only a small number of studies have examined detailed hospitalization data from a planning perspective. The current study develops a comprehensi...

There is limited adoption of research modeling crash severity frequency considering different crash types due to the challenge associated with analyzing large number of dependent variables. The proposed research contributes to burgeoning econometric and safety literature by developing a joint modeling approach that can accommodate for several depen...

The current research contributes to the burgeoning literature on multivariate models by proposing a hybrid model framework that (a) incorporates unobserved heterogeneity in a parsimonious framework and (b) allows for additional flexibility to accommodate for observed/systematic heterogeneity. Specifically, we estimate a Latent Segmentation Panel Mi...

The right-turn flashing yellow arrow (FYA) signal display is still considered a new signal practice in the United States. The Manual on Uniform Traffic Control Devices (MUTCD; 2009) allocates a signal phasing section for the right-turn FYA, which requires a four-section configuration. It supports multiple phase indications that guide the motorists...

Recent hurricane experiences have created concerns for transportation agencies and policymakers to find better evacuation strategies, especially after Hurricane Irma-which forced about 6.5 million Floridians to evacuate and caused a significant amount of delay due to heavy congestion. A major concern for issuing an evacuation order is that it may i...

In safety literature, there are two ways to incorporate the potential correlation between multiple crash frequency variables: (1) simulation-based approach and (2) analytical closed-form approach. The current research effort undertakes a comparison between simulation-based multivariate model and copula based closed-form approach to analyze zonal le...

Traditionally, in developing non-motorized crash prediction models, safety researchers have employed land use and urban form variables as surrogate for exposure information (such as pedestrian, bicyclist volumes and vehicular traffic). The quality of these crash prediction models is affected by the lack of "true" non-motorized exposure data. High-r...

Background Several research efforts have evaluated the impact of various factors including a) socio-demographics, (b) health indicators, (c) mobility trends, and (d) health care infrastructure attributes on COVID-19 transmission and mortality rate. However, earlier research focused only on a subset of variable groups (predominantly one or two) that...

Background: As of February 19, 2021, our review yielded a small number of studies that investigated high resolution hospitalization demand data from a public health planning perspective. The earlier studies compiled were conducted early in the pandemic and do not include any analysis of the hospitalization trends in the last 3 months when the US ex...

Earlier research has extensively examined freight mode and shipment weight dimensions. However, freight destination behavior at a high resolution has received scant attention. In our study, we attempt to address the limited research on destination decision processes and develop a latent segmentation-based approach that accommodates mode and destina...

With the advancement in traffic management systems and improving accessibility to traffic information through various sources such as mobile apps, radio, variable message sign; road users tend to choose their route based on a complex interaction of various attributes including travel time, delay, travel cost and information provision mechanisms. Wh...

Introduction: Predicting crash counts by severity plays a dominant role in identifying roadway sites that experience overrepresented crashes, or an increase in the potential for crashes with higher severity levels. Valid and reliable methodologies for predicting highway accidents by severity are necessary in assessing contributing factors to sever...

Background: Several research efforts have evaluated the impact of various factors including a) socio-demographics, (b) health indicators, (c) mobility trends, and (d) health care infrastructure attributes on COVID-19 transmission and mortality rate. However, earlier research focused only on a subset of variable groups (predominantly one or two) tha...

Land use and transportation scenarios can help evaluate the potential impacts of urban compact or transit-oriented development (TOD). Future scenarios have been based on hypothetical developments or strategic planning but both have rarely been compared. We developed scenarios for an entire metropolitan area (Montreal, Canada) based on current strat...

We compared numbers of trips and distances by transport mode, air pollution and health impacts of a Business As Usual (BAU) and an Ideal scenario with urban densification and reductions in car share (76% to 62% in suburbs; 55% to 34% in urban areas) for the Greater Montreal (Canada) for 2061. We estimated the population in 87 municipalities using a...

Road traffic crashes remain a major concern globally resulting in loss of life and worsening the quality of life and productivity of the crash survivors. The current study contributes to road safety literature by focusing on developing high resolution crash severity models based on driver injury severity reported using Abbreviated Injury Scale (AIS...

In 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 var...

This study employs a copula-based multivariate temporal ordered probit model to simultaneously estimate the four common intersection crash consequence metrics – driver error, crash type, vehicle damage and injury severity – by accounting for potential correlations due to common observed and unobserved factors, while also accommodating the temporal...

Vehicle 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...

In 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 f...