Md Sami Hasnine

Howard University | HU · Civil and Environmental Engineering

The paper presents an evaluation of welfare gains and losses of individual commuters in response to various transportation demand management (TDM) strategies. A computationally tractable mode choice model for commuters is estimated using data collected in the Region of Peel, Ontario in 2014 through a joint revealed and stated preference survey. The...

The paper presents a critical review of the methodological approaches used in tour-based mode choice models within the activity-based modelling frameworks. Various components of the activity-based models, such as activity type choice, activity location choice, and activity duration have already matured significantly. However, the mode choice compon...

This paper investigates the effects of the built environment and weather on the demands for transportation network companies (TNC) in Toronto. The research is based on a historical dataset of Uber trips from September 2016 to September 2018 in Toronto. A wide range of built environments, sociodemographic, and weather data are generated at the disse...

The paper presents a heteroskedastic dynamic discrete choice (HDDC) model for tour-based mode choices modelling with an empirical investigation of university students' daily mode choices in Toronto. The reality of connected trips and resulting constrained mode choices are captured through the HDDC framework that is suitable for fitting in an activi...

The paper presents a dynamic discrete–continuous modelling approach to capture individuals’ tour-based mode choices and continuous time expenditure choices tradeoffs in a 24-h time frame. The analysis of traditional activity-based models are typically limited to activity-type, location and time expenditure choices. Besides, mode choice is often sim...

The objective of this study is to investigate the impact of the COVID-19 vaccine on bike sharing demand in New York City (NYC). The vaccination’s impact was also compared with other known influences (COVID-19 cases counts, COVID-19 deaths, weather data, trip purpose, and more) to help improve bike share demand modeling in a pandemic setting. Autore...

In recent years, bikesharing systems have become increasingly popular as affordable and sustainable micromobility solutions. Advanced mathematical models such as machine learning are required to generate good forecasts for bikeshare demand. To this end, this study proposes a machine learning modeling framework to estimate hourly demand in a large-s...

This paper presents a study of various factors that influenced online and in-store shopping behaviors in New York City during the COVID-19 pandemic. It uses panel data collected by the New York City Department of Transportation for May, July, and October 2020. In the survey, 696 respondents consistently responded in all three months and, therefore,...

This paper investigates the use of an elicited consideration set in a mathematical model of choice and consideration set formation. It proposes an econometric formulation by allowing unrestricted correlations among alternatives in the consideration set formation and a flexible substitution pattern in the choice model. Data from a stated preference...

Introduction This study investigates the influence of vaccination along with other pandemic-related factors on driving, transit, and walking in New York City (NYC). The results of this study help inform policymakers of the weight of their decisions in a pandemic setting as well as factors to consider when modeling transportation during a pandemic....

The e-commerce market has grown rapidly in the past two decades. The need for predicting e-commerce demand and evaluating relevant policies and solutions is increasing. However, the existing simulation models for e-commerce demand are still limited and do not consider the impacts of delivery options and their attributes that shoppers face on multip...

This study investigates the factors influencing university student’s living arrangement choice, the distance between home and the university, and mode choice. A closed-form probabilistic choice modelling formulation is developed to model three choices jointly: student’s living arrangement choice, the distance between home and the university, and st...

The paper presents an application of the choice-based sample to explain the choice of non-chosen alternatives. It uses a passenger survey of GO rail transit of the Greater Toronto and Hamilton Area (GTHA) to investigate the factors that may affect the potential mode switching of the current GO rail users. It used a hybrid Generalized Extreme Value...

This paper presents a large-scale integrated modelling framework that can capture the relationships between travel mode choice, departure time choice and route choices simultaneously. Conventional transportation models have typically been applied to small scale networks to avoid the complexity of the large-scale simulation. While there are differen...

This paper presents a closed-form Latent Class Model (LCM) of joint mode and departure time choices. The proposed LCM offers compound substitution patterns between the two choices. The class-specific choice models are of two opposing nesting structures, each of which provides expected maximum utility feedback to the corresponding class membership m...

This paper investigates the factors influencing the physical health condition and the trip distance of e-bike users’ in Toronto, Canada. The research is based on a survey of e-bike and bicycle users' health condition and travel behaviour in Toronto. A Bivariate Ordered Probit model is used to draw links between different factors that affect the hea...

The e-commerce delivery demand has grown rapidly in the past two decades and such trend has accelerated tremendously due to the ongoing coronavirus pandemic. Given the situation, the need for predicting e-commerce delivery demand and evaluating relevant logistics solutions is increasing. However, the existing simulation models for e-commerce delive...

The paper investigates the impacts and barriers posed by connected autonomous vehicles (CAVs) for pedestrians with visual impairment. This study uses a customized web-based survey of visually impaired people from Canada and abroad. Collected data are used to estimate econometric models to identify the critical factors that affect the level of trust...

The paper investigates the impacts and barriers posed by connected autonomous vehicles (CAVs) for pedestrians with visual impairment. This study uses a customized web-based survey of visually impaired people from Canada and abroad. Collected data are used to estimate econometric models to identify the critical factors that affect the level of trust...

The paper presents an evaluation of welfare changes of commuters due to implementations of various transportation demand management (TDM) strategies. A mode choice model of commuting mode choice in the Region of Peel is estimated using data collected through a joint revealed and stated preference survey. The survey obtained information on the impac...

This paper presents a case study on commuter’s departure time, route and mode choice responses to optimized tolling in the Toronto, Ontario, Canada. The study integrates a toll optimization component into an integrated framework of econometric departure time choice, dynamic traffic assignment model, and random utility maximization (RUM) based mode...

This paper investigates the effects of built environment and weather on transportation network companies (TNC) demand in Toronto, Canada. The research is based on an historical dataset of Uber trips from January 2017 to September 2018. A wide range of built environment, sociodemographic, and weather attributes are generated at the dissemination are...

Using stated preference data collected in the Greater Toronto Area (GTA), this study presents a combined choice model that considers alternatives consisting of bundles of home relocation and mobility tool choices. The model is estimated for changes in housing and mobility tool ownership choices in response to increasing commuting costs. The major f...

The paper presents the results of an empirical investigation of the influence of transit pass ownership on daily transit service usage behavior under a flat fare system. The transit system of the City of Toronto (TTC) is investigated to evaluate the factors that influence the choice of owning a transit pass and at the same time whether or not a pas...

This thesis presents a tour-based mode choice modelling structure for activity-based travel demand models by exploiting the classical dynamic discrete choice modelling approach. Many activity-based modelling systems rely on either trip-based or ‘simplified’ tour-based mode choice models that in many cases completely overlook the dynamics of mode ch...

The objective of this thesis is to develop an employer-based Transportation Demand Management (TDM) evaluation tool that can be used for evaluating various employer-based TDM policies. The conventional method of evaluating TDM policies has typically been conducting expensive before and after TDM policy implementation surveys. On the contrary, this...

The paper proposes a joint econometric model to investigate the effects of inertia; elicited confidence rating on SP choices and socio-economic variables on the choice model parameter estimates. The proposed model is estimated empirically by using a dataset collected in the Region of Peel, Ontario, which was designed to collect data for evaluating...

The topic of transit loyalty has been marginalized in transportation literature. Nevertheless, in recent years, an interest in understanding the factors that affect transit loyalty has developed. This paper uses data from a passenger survey conducted by GO rail-the Greater Toronto and Hamilton Area regional rail service-to investigate the factors t...

This paper presents a closed-form Latent Class Model (LCM) of joint mode and departure time 2 choices. The proposed LCM offers compound substitution patterns between the two choices. The 3 class-specific choice models are of two opposing nesting structures, each of which provides 4 expected maximum utility feedback to the corresponding class member...

The paper presents a dynamic modelling framework for modelling tour-based mode choices. It intends to overcome the limitations stemmed from the simplifications made in mode choice modelling of operational activity-based models (ABM). A computationally tractable dynamic discrete choice modelling (DDCM) framework is used. Dynamics in daily travel mod...

Peak period crowding in transit networks mirrors peak hour congestion in road networks, particularly in large cities such as Toronto. One of the effective strategies to tackle this problem is time-based transit fares. One potential unintended consequence of implementing such a strategy, however, can be modal shifts from transit to other modes. In o...

This paper presents a comparison of methods for capturing spatial correlation between location 3 alternatives. Three different methods are compared and analyzed based on their statistical 4 performances. To test their performances, the choice of school location for high school students 5 is examined. This analysis shows that the Spatially Weighted...

This paper presents a case study on commuter's mode, departure time, and route choice responses to optimized tolling in the Toronto, Ontario, Canada. The study integrates a toll optimization module into a testbed of hybrid departure time choice, dynamic traffic assignment simulation model, and random utility maximization (RUM) based mode choice mod...

The paper presents a dynamic discrete-continuous modelling approach to capture individuals' tour-based mode choices and continuous time expenditure choices tradeoffs in a 24-hour time frame. The analysis of traditional activity-based models (ABM) are typically limited to activity-type, location and time expenditure choices. Besides, mode choice is...

The paper presents a random utility-based measure of accessibility to explain the first-mile issue in urban transit. A discrete access stop/station location choice model is used to calculate the expected maximum utility of transit access choices as the measure of the proposed access to transit measurement approach. It captures the effects of change...

1 The study explores the causal relationships between latent factors and various observed external variables 2 along with their ability to explain multimodal behaviors of post-secondary students in Toronto. 3 Multimodality is measured by the number of unique modes used by any individual for their daily travels. 4 As opposed to using a single type o...

The paper presents an investigation of the choices of mobility tool ownership of post-secondary (young adults) students in Toronto. Data came from a 2015 survey of post-secondary students across four universities in Toronto. The choices of owning a basic mobility tool (driver's license, car, transit pass, and bicycle) or combinations of basic tools...

The paper presents an investigation on the mode choice behaviour of post-secondary students commuting to school in the city of Toronto. It uses a large-scale dataset collected through a web-based travel diary survey among all students of four universities (seven campuses) in Toronto. Multinomial logit (MNL), nested logit (NL) and cross-nested logit...

The paper presents a heteroskedastic dynamic discrete choice (HDDC) model for tour-based mode choices modelling with an empirical investigation of university students’ daily mode choices in Toronto. The reality of connected trips and resulting constrained mode choices are captured through the HDDC framework that is suitable for fitting in an activi...

The paper presents a random utility-based measure of accessibility to explain the first-mile issue in urban transit. A discrete access stop/station location choice model is used to calculate the expected maximum utility of transit access choices as the measure of the proposed access to transit measurement approach. It captures the effects of change...

Research Background Sidewalk asset management is one of the key means of promoting active recreational and utilitarian travel. Encouraging active travel reduces congestion and promotes physical fitness and healthy lifestyles. To promote active travel, municipalities should make educated design and maintenance decisions regarding their investment in...

This paper presents a jointly estimated Revealed Preference – Stated Preference (RP-SP) choice model to explore mode choice behavior of commuters in a multimodal regional transportation system in the Greater Toronto and Hamilton Area (GTHA). The paper focuses on the commuting trips that are long enough to be served by more than one transit services...

The paper presents a study on commuter’s responses to various employer-based transportation demand management (TDM) for the study are of the Region of Peel, Ontario, Canada. The study involves design and implementation of a web-based survey of daily commuting mode choices and an efficient design-based stated preference (SP) experiments on the mode...

The paper presents an investigation on the effectiveness of Smart Commute program, a well-established Travel Demand Management (TDM) program in the Greater Toronto and Hamilton Area (GTHA). It exploits data fusion technique to combine data collected through cross-sectional ex-ante and ex-post surveys at each Smart Commute member workplace. Two type...

This paper uses household travel survey data (of the National Capital Region of Canada) and a comprehensive random utility maximizing travel options modelling approach to investigate non-workers’ activity-travel scheduling behaviour. The empirical model reveals that the presence of children shapes the daily activity-travel patterns of non-workers b...

The paper proposes a two-staged modelling approach to identify the association between one vehicle's attributes, as well as roadway engineering, environmental and crash characteristics, and the injury severity of occupants in the partnering vehicle in two-vehicle crashes. The modelling approach uses a bivariate binary probit model, and crash data f...

This paper presents a tool for the evaluation of employer-based transportation demand management (TDM) strategies. The conventional method of evaluating TDM strategies has typically been to conduct expensive before-and-after strategy implementation surveys. As an alternative approach, this research uses a joint revealed preference (RP) and stated p...

This paper presents a robust method of joint RP-SP choice model that exploits the endogeneity between stated choice and its corresponding certainty indices. The proposed model also accounts for inertia effect, effects of socio-economic variables and heteroskedasticity in the joint RP-SP context. SP scale parameter was parameterized as a function of...

The paper proposes a two-staged modelling approach to identify the association between one vehicle’s attributes and the injury severity of victims in the partnering vehicle in two-vehicle crashes. The two-staged modelling approach involves using a bivariate binary probit model to first determine the probability of injury and the corresponding proba...

The paper investigates the use of an elicited consideration set in a joint model of choice and consideration set formation. It proposes a joint econometric formulation by allowing unrestricted correlations among alternatives in the consideration set formation and flexible substitution pattern in the choice model. Data from a stated preference (SP)...

The paper presents a Transportation Demand Management (TDM) evaluation tool for employer-based TDM strategies. The conventional method of evaluating TDM strategies has typically been conducting expensive before and after strategy implementation surveys. As an alternative approach, this research uses a pre-strategy deployment joint Revealed and Stat...