ORCID Profile
0000-0002-0715-8121
Current Organisation
The University of Texas at Austin
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Springer Science and Business Media LLC
Date: 26-07-2017
Publisher: SAGE Publications
Date: 2014
DOI: 10.3141/2413-04
Publisher: SAGE Publications
Date: 05-05-2022
DOI: 10.1177/03611981221087233
Abstract: This paper analyzes the impact of the COVID-19 pandemic on activity time use and timing behavior in Switzerland. The evaluation is based on mobility tracking data collected in Switzerland during the COVID-19 pandemic. The pandemic has affected how people spend their time and schedule their activities throughout the day, subsequently creating new activity patterns. Because of the rare occurrences of pandemics in the recent past, little is known about their implications on the behavioral choices of affected people. This paper analyzes these implications by applying a multiple discrete-continuous choice model on mobility tracking data from Switzerland. The applied model is consistent with the results of the descriptive analysis and shows that the different stages of the pandemic drove changes in the activity patterns. During the lockdown, an increase in home activities comes along with decreases in the other activity types. With progressive relaxation of the measures in the following phases, the trends slowly return to the initial state before the pandemic. In addition, it can be seen that the impact of main drivers such as age, gender, household size, income and weather on time use and activity scheduling varies between phases, activity types, and time of day.
Publisher: Elsevier BV
Date: 12-2017
Publisher: SAGE Publications
Date: 2017
DOI: 10.3141/2664-10
Abstract: This study explored differences in activity travel behavior within the millennial generation to understand better how their choices might shape transportation systems of the future. Through the estimation of a generalized heterogeneous data model on a mobility attitude survey data set targeting millennials, this study investigates heterogeneity among millennials with respect to their driver’s license–holding status, vehicle ownership, and commute mode choice. After self-selection effects are accounted for, age, parenting status, and location of residence have a substantial and statistically significant influence on automobile-oriented mobility choices. Millennials seem to become more automobile-oriented as they age and gain economic resources. Parenthood is associated with an increase in driver’s license holding and personal vehicle ownership however, in general, it does not seem to have a direct effect on commute mode choice. For all types of millennials, mode choice seems to be strongly correlated with residence location. Thus, the development of a well-connected public transit system and dense, mixed land use are still the key ingredients for reducing the car commute. Planning professionals should explore ways to retain millennials in the city core so that their sustainable patterns of transportation mode use can be preserved.
Publisher: SAGE Publications
Date: 2017
DOI: 10.3141/2666-03
Abstract: Smartphone ownership and use are becoming increasingly prevalent around the world. However, little is known about the impacts of this technology on activity travel choices. The objective of this study was to determine the extent to which smartphone ownership and use influence activity travel demand, after controlling for other lifestyle and demographic attributes. The impacts of smartphone ownership and use on multiple travel dimensions were examined through the specification and estimation of a joint model system that explicitly accounts for self-selection effects arising from lifestyle preferences (such as green lifestyle propensity and technology savviness). Specifically, the impacts of smartphone ownership and use on the following choice dimensions were estimated: ( a) use of multiple modes of transportation, ( b) pursuit of complex trip chains with a large number of intermediate stops, ( c) engagement in tours that have a recreational activity, and ( d) participation in joint tours that involve an accompanying person. Travel survey data from the 2014–2015 Puget Sound (Washington) Regional Travel Study were used. The results show substantial and statistically significant effects of smartphone ownership and use on activity travel patterns, even after controlling for lifestyle preferences. Smartphone ownership and use were found to increase the likelihood of using multiple modes of transportation and participating in complex tours, joint tours, and recreational tours.
Publisher: Elsevier BV
Date: 12-2018
Publisher: SAGE Publications
Date: 2009
DOI: 10.3141/2132-08
Abstract: The occurrence of natural disasters in the coastal regions and numerous potential events in urban regions have drawn considerable attention among transportation stakeholders. Federal, state, and local officials need to be effectively prepared to address the challenges raised by an evacuation. The focus of this research effort is to develop a tool to study the repercussions of evacuation of an entire regional transportation network recognizing the human behavior element. Neglecting these seemingly chaotic traffic flow patterns would lead to inaccurate system assessment and predictions. The influences of evacuees’ locations in the urban region at the moment of emergency alert are studied. In addition, the locations of all members of the household are identified, and household member interactions are explicitly considered. Further, the accurate times the in iduals enter the network to evacuate the study region are studied times can vary according to where the other household members are located at that time and the travel time on the network to reach those locations. To accomplish the goals, the integration framework of activity-based modeling and dynamic traffic assignment is used to study the evacuation traffic flow patterns at the time of evacuation. Specifically, the paper describes the evacuation problem, discusses the utility of deploying the integrated module of activity-based modeling and dynamic traffic assignment for evacuation planning, and outlines the challenges in integrating these two tools.
Publisher: Springer Science and Business Media LLC
Date: 17-11-2017
Publisher: Elsevier BV
Date: 11-2016
Publisher: SAGE Publications
Date: 04-04-2018
Abstract: Ridesourcing has experienced exponential growth in recent years, yet its impact on in idual travel are unclear and have not been adequately examined. Recently, an Austin-based ridesourcing company released a large dataset containing disaggregate trip-level information. In this research, we use this new dataset in tandem with several publicly available data sources to estimate two models: a spatially lagged multivariate count model, which is used to describe how many trips are generated in a specific zone on both weekdays and weekend days and a fractional split model, which helps us identify the characteristics of zones that attract ridesourcing trips. Our results show spatial dependence in ridesourcing trips among proximally located zones, as well as correlation between weekday and weekend day trips originating in a zone. Another interesting finding is the identification of a possible substitution effect between ridesourcing and transit use for weekday trips. Moreover, our results suggest that different income segments in the population may use ridesourcing for different activity purposes. From a travel behavior researcher perspective, the results in this paper identify aggregate area-level variables impacting ridesourcing, which can guide future efforts to better understand the demand for ridesourcing as well as the demand for autonomous and connected vehicles.
Publisher: SAGE Publications
Date: 2008
DOI: 10.3141/2076-06
Abstract: The traditional trip-based approach to transportation modeling has been used for the past 30 years. Because of limitations of traditional planning for short-term policy analysis, researchers have explored alternative paradigms for incorporating more behavioral realism in planning methodologies. On the demand side, activity-based approaches have evolved as an alternative to traditional trip-based transportation demand forecasting. On the supply side, dynamic traffic assignment models have been developed as an alternative to static assignment procedures. Much of the research effort in activity-based approaches (the demand side) and dynamic traffic assignment techniques (the supply side) has been undertaken relatively independently. To maximize benefits from these advanced methodologies, it is essential to combine them through a unified framework. The objective of this paper is to develop a conceptual framework and explore practical integration issues for combining the two streams of research. Technical, computational, and practical issues involved in this demand–supply integration problem are discussed. The framework is general, but specific technical details related to the integration are explored by using CEMDAP for activity-based modeling and VISTA for dynamic traffic assignment modeling. Solution convergence properties of the integrated system, specifically examining different criteria for convergence, different methods of accommodating time of day, and the influence of step size on convergence are studied. The integrated system developed is empirically applied to two s le networks selected from the Dallas–Fort Worth system in Texas.
Publisher: SAGE Publications
Date: 2016
DOI: 10.3141/2601-13
Abstract: This paper presents a comprehensive model of injury severity that accounts for unmeasured driver behavior attributes. The results of the model have important implications for the design of safety interventions and advanced vehicular features and technologies. Engineering designs that accommodate the diminished capabilities of older drivers, that include rear-seat safety features, and that alert drivers to potential frontal collisions before they occur (collision warning systems and automated braking systems) would contribute to substantial reductions in injury severity for occupants of vehicles.
Publisher: Elsevier BV
Date: 2014
Publisher: Springer Science and Business Media LLC
Date: 12-2005
Location: United States of America
Location: United States of America
No related grants have been discovered for Chandra Bhat.