Khandker Nurul HabibUniversity of Toronto | U of T · Department of Civil & Mineral Engineering
Khandker Nurul Habib
PhD
About
365
Publications
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Introduction
Professor Khandker Nurul Habib works in the area of travel demand modelling, integrated land-use/transportation modelling, microsimulation, advanced econometric choice modelling and sustainable transportation planning. His current research is on transportation system and economic development in context of urban transformations and their impacts on peoples’ travel behaviour.
Research Website:
KhandkerNurulHabib.com
Additional affiliations
July 2020 - present
University of Toronto
Position
- Professor
May 2015 - June 2020
May 2010 - May 2015
Publications
Publications (365)
After two years of living with the threat of COVID-19 in Ontario, Canada, pre-pandemic circumstances returned. During the pandemic, we relied on ICT-based tools to carry out our daily tasks, and now we have reached a tipping point. Should we keep our new routines to benefit us in the future? Or should we return to our routines before the pandemic?...
This paper introduces an innovative travel survey methodology that utilizes Google Location History (GLH) data to generate travel diaries for transportation demand analysis. By leveraging the accuracy and omnipresence among smartphone users of GLH, the proposed methodology avoids the need for proprietary GPS tracking applications to collect smartph...
Travel diary is one of the fundamental methods for collecting data critical for transportation planning, demand modelling, and analyses. Self-reported household travel surveys are known for recall and proxy biases. Both biases lead to underreporting of travel demand in the dataset. On the other hand, travel diaries collected through GPS-based metho...
Modeling housing market dynamics is an important component of land use and transport interaction (LUTI) models, particularly for microsimulation models and how they handle the market clearance mechanism. However, most of these models include key assumptions not derived or validated through empirical testing, such as when and what action a seller wo...
Household travel surveys collect core datasets for modelling passenger travel demand. However, the decline in survey completion rate has become a concern in recent years. Among all components, the travel diaries are the most challenging part of CAWI travel surveys and suffer significant dropouts of participation. Therefore, an investigation is nece...
The introduction and subsequent growth of ride-sourcing services have been found to affect the use of existing modes of travel. Although prior studies have explored the impacts of these services as a whole, relatively little work has been done to explore the relationship between shared ride-sourcing and existing modes of travel. Given the potential...
To address the methodological limitation of cross-sectional studies and the data constraints of longitudinal/panel studies, this paper presents a model-based method to fuse repeated cross-sectional travel survey data based on the theory of rational inattention (RI) in discrete choice modeling. In the proposed framework, older cross-sectional data a...
This research investigates the immediate effects of the COVID-19 pandemic on residential preferences in the Greater Toronto Area (GTA), Canada, using a stated preference (SP) survey dataset. The study examines changes in relocation preferences and trends in the GTA after the Ontario government lifted the initial lockdown. The obtained choice data i...
Post-secondary students are a segment of the population whose activity-travel behaviour is not well understood. In particular, there is a relative dearth of studies that have examined the determinants of behaviours related to participation in out-of-home activities among post-secondary students. This study uses data from a web-based survey administ...
The land-use/transport interaction (LUTI) modeling framework has become the current state of best practice for analyzing the interdependency between the land-use and transportation systems. This paper presents a comprehensive review of the housing market-clearing mechanisms used in operational LUTI models. Market clearing is a critical component of...
Ride-sourcing has the potential to attract demand from more sustainable modes, alter activity patterns, and worsen congestion; however, it can also help increase the mobility and accessibility of those who cannot drive. Understanding how and why these services are used can help inform policies that address the negative externalities of these servic...
The rapid spread of the SARS-CoV-2 virus has resulted in changes in modal preferences, leading to an increased preference for individual modes (e.g., private vehicles and active modes) and a reduced preference for shared modes. However, ride-sourcing represents somewhat of a middle ground between individual and shared modes, given the relatively li...
The first stage in route choice modeling is the generation of the route choice sets, which directly affects the accuracy of model estimation. The random walk method proposed by Frejinger et al. for this purpose has the advantage of directly calculating the probabilities of paths chosen. However, its application has seldom been seen in a large-scale...
Amid the increased utilization of ride-sourcing, the relationship between these services and public transit received significant attention from policymakers and researchers. Prior studies have found that ride-sourcing has mixed impacts on transit ridership and that transit use tends to be positively associated with ride-sourcing use. However, these...
Post-secondary students are a segment of the population whose activity-travel behaviour is not well understood. In particular, there is a relative dearth of studies that have examined the determinants of behaviours related to the participation of out-of-home activities among post-secondary students. This study uses data from a web-based survey admi...
One objective of China’s High-speed rail (HSR) development is to promote regional cohesion, which can be reflected by the flow of people between city pairs. As a fast-speed intercity transport mode, same-day intercity mobility has been regarded as an essential measurement for regional cohesion and transport integration. The reduced time by HSR has...
The COVID-19 virus has unimaginably disrupted the transit system and its overall functions. Users' vigilant safety concerns posed by the pandemic and the consequent transit avoidance behaviour for a prolonged period could have lasting impacts on their transit preferences, leaving transit agencies to search for effective post-pandemic transit resili...
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...
This study investigates the roles of the socio-economic, land use, built environment, and weather factors in shaping up the demand for bicycle-sharing trips during the COVID-19 pandemic in Toronto. It uses “Bike Share Toronto” ridership data of 2019 and 2020 and a two-stage methodology. First, multilevel modelling is used to analyze how the factors...
The COVID-19 pandemic has significantly affected activity-travel behavior in cities across the world, and in particular, travel mode choices. Studies on the topic have attributed shifts in modal preferences to the changes in attitudes toward different modes of travel that resulted from the pandemic. A common theme is that attitudes toward so-called...
This paper examines individuals' choice of in-store and online grocery shopping channels using stated preference (SP) choice experiments. The study uses 1,391 records from a stated preference choice experiment in the Greater Toronto Area (GTA), Canada. It applies a Semi-Compensatory Independent Availability Logit (SCIAL) Model with latent variables...
Complete information in decision-making has been a common assumption in discrete choice modelling in practice. Such an assumption can be deemed valid for a limited information environment when the choice-maker can reasonably scrutinize all information. With the rise of the internet and social media, which provide a universal platform allowing anyon...
Household travel surveys collect core datasets for modelling passenger travel demand. However, decline in survey completion rate is becoming a concern in recent years. One major cause is the transition from computer-assisted telephone interviews (CATI) to computer-assisted web interviews (CAWI) surveys, where respondents need to self-complete the s...
The COVID-19 pandemic had a significant impact on travel mode choices in cities across the world. Driven by perceptions of risk and the fear of infection, the pandemic resulted in an increased preference for private vehicles and active modes and a reduced preference for public transit and ride-sourcing. As travel behavior and modal preferences evol...
An important aspect of post-secondary student travel behaviour is their commute mode usage frequencies. How frequently students use different transportation modes for their daily travel directly characterizes their habits, routines, and predispositions, which can ultimately affect long-term social welfare of the region, congestion of the transporta...
This paper presents a data fusion method to infer the origin and destination zones of transit trips from smart card data. The fusion framework has disaggregate mixed multinomial logit models at its core that predict the most probable origin and destination zones of individual transit trips using smart card transaction records, land use data, and tr...
The outbreak of coronavirus disease 2019 (COVID-19) spreads globally, disrupting every aspect of everyday activities. Countermeasures during the pandemic, such as remote working and learning, proliferated tele-activities worldwide during the COVID −19 pandemic. The prevalence of telecommuting could lead to new activity-travel patterns. It is in the...
Integrated urban models (IUM) typically rely on a measure of accessibility or travel time to form the link between the transportation and land use systems. Such integration does not fully capture the tradeoffs made by households in how they spend their limited temporal and monetary budgets. We propose a microeconomic foundation for transportation a...
The COVID-19 pandemic dramatically catalyzed the proliferation of e-shopping. The dramatic growth of e-shopping will undoubtedly cause significant impacts on travel demand. As a result, transportation modeller's ability to model e-shopping demand is becoming increasingly important. This study developed models to predict household' weekly home deliv...
The COVID-19 pandemic has altered travel patterns in cities across the world. Previous studies have found that travel choices during the pandemic are affected by attitudes and perceptions of risk in addition to transportation system level-of-service attributes. However, traditional travel demand models often rely on household travel survey data, wh...
COVID-19 had an unprecedented impact on transit demand and usage. Stiff and vigilant hygiene safety requirements changed travellers’ mode choice preferences during the COVID-19 pandemic. Specifically, transit modal share is radically impacted. Therefore, quantitative measurements on transit demand impact are urgently needed to facilitate evidence-b...
The COVID-19 lockdown provided many individuals an opportunity to explore changes in their daily routines, particularly when considered in combination with an ever-changing Information and Communication Technology (ICT) landscape. These new routines and alternative activities have the potential to be continued in the post-COVID era. Transportation...
Social distancing strategies and strict hygiene adherence during the pandemic have added an extra dimension to the safety requirements of transit usage. Thus, travelers’ altered safety perceptions, which can affect transit usage, need to be assessed for effective policy decisions for the post-pandemic period. This study examined the interaction bet...
Ride-hailing (RH) services have been growing rapidly and gaining popularity worldwide. However, many transit agencies are experiencing ridership stagnation or even decline. Understanding the correlation between RH trips and transit ridership has become an urgently important matter for transit agencies. This study aimed to explore the relationship b...
Automated fare collection (AFC) systems such as smart cards are becoming increasingly popular among transit agencies worldwide. Two main configurations of AFC systems can be found, characterized by whether users are required to scan their cards at the beginning of their trips (i.e., entry-only system) or both at the beginning and end of their trips...
This paper investigates the changes caused by the COVID-19 pandemic on households’ perceived utility of the accessibility of their residence in the Greater Toronto and Hamilton Area (GTHA). The paper considers several neighborhood and dwelling attributes and fuses those with property price data from mid-March 2019 to mid-March 2021 to analyze chang...
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...
Gentrification is being experienced by cities around the world. Its drivers and characteristic features are complex and diverse, ranging from the displacement of low-income households to the redevelopment of commercial districts. This paper combines multiple data sources to explore the coevolution of gentrification in the residential market and dev...
Data are important components of any research; however, it is often the case that the required data are not readily available. Researchers often fuse multiple datasets to obtain the data required to complete their work. In urban simulation, spatially referencing data is of paramount importance to capture local variations in travel and preferences....
The COVID-19 pandemic had an unprecedented impact on transit usage, primarily owing to the fear of infection. Social distancing measures, moreover, could alter habitual travel behavior, for example, using transit for commuting. This study explored the relationships among pandemic fear, the adoption of protective measures, changes in travel behavior...
This is the pre-print version. If you have any questions regarding the paper, please contact the corresponding author listed in the manuscript. Thank you.
The efficient adaptive choice experiment design is a real-time design method for tailoring choice experiments based on respondent's taste.
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As the widespread usage of autonomous vehicles is closer to becoming a reality, substantial consideration should be paid to the extent to which individuals choose vehicular mobility tools. The purpose of this study is to examine vehicle ownership models to better understand the adoption of vehicles by considering some factors such as liability issu...
The ongoing COVID-19 pandemic has fundamentally changed the nature of day-to-day life in cities worldwide. In the transportation sector, COVID-19 appears to have impacted modal preferences. In particular, people seem to be less willing to use modes where they may encounter strangers (such as public transit) and modes that involve coming into contac...
In this paper, we provide a comparison of implementations of Bayesian estimation of mixed multinomial logit (MMNL) models. Our objective is to provide a systematic comparison of the runtime, efficiency, and model implementation details associated with several alternative workflows. The analysis is based on three case studies. We argue that previous...
Home location choice is based on both the characteristics of the dwelling (e.g., size, style, number of bedrooms) and the location (e.g., proximity to work, quality of schools, accessibility). Recent years have seen a steep increase in the price of housing in many major cities. In this research, we examine how these price increases are affecting th...
Given the limitations of traditional methods of data collection and the increased use of smartphones, there is growing attention given to using smartphone apps for activity-travel surveys. Smartphones, through their location-logging capability, allow for the collection of high-quality data on the travel patterns of individuals over multiple days wh...
The paper employed a latent segmentation discrete choice model with endogenous social interaction effects to investigate the role of gender and age-cohort-specific peer influences on the choice of owning a bicycle by university students in Toronto. The empirical investigation used a dataset collected through a survey of students on seven campuses o...
Urban travel demand analysis efforts predominantly use household travel surveys for data supports, especially in North America. However, proxy-biases and under-representations are two dominant issues looming over the practice of using household travel surveys. Proxy biases arise from the fact that one household member reports travel diaries on beha...
The continued growth and utilization of ride-sourcing services have reshaped traditional perceptions of urban mobility. As the popularity of this relatively novel mode of travel has continued to grow, there has been a greater focus on the effect that the adoption and use of ride-sourcing have on the utilization of more traditional modes of transpor...
The spread of the novel coronavirus disease-2019 (COVID-19) since early in 2020 has affected every aspect of daily life, including urban passenger travel patterns. Lockdowns to control the spread of COVID-19 created unprecedented travel demand contexts that have never been seen in modern history. So, it is essential to benchmark trends of travel be...
Smartphones with embedded Global Positioning System (GPS) technology provide an opportunity to passively collect individuals’ travel trajectory data, which can be utilized to identify critical aspects of travel behavior such as transport modes. This paper presents a mode detection algorithm developed to infer modes from smartphone GPS data. The alg...
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 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...
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...