Travel Behavior

Investigating Travel Survey Representativeness: Who’s Missing and What Can We Do?

The core source of data for transportation planning and forecasting comes from household travel surveys. Travel surveys are used to obtain insight into the behavioral decisions of travelers; for example: (1) trip purposes such as work or shopping; (2) means/mode of transport such as car, walk, bus, etc.; (3) travel time; and (4) time of […]

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Analysis and Implications of the Vehicle Inventory and Use Survey (VIUS)

To better understand the future of travel behavior and demand this research effort will explore the National Vehicle Inventory and Use Survey (VIUS).  There is a keen interest in this survey as a result of the fact that a growing share of all travel is non-household-based travel for freight commercial and service functions. These functions

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Michigan Mobility Metrics (M3): An Outcome-Focused, Multi-Year Survey Deployment and Data Collection Effort

Transportation modes, technologies, and the broader context within which people travel have evolved rapidly over the last decade. Examples of such changes include the introduction of: new/emerging modes like ridesharing and micromobility, electric and automated vehicle technologies, information and communication devices; and the increase in remote and hybrid work due to COVID-19. It is critical

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Exploring Top-Down Visual Attention for Transportation Behavior Analysis

This project stands at the intersection of cognitive psychology, AI and computer vision, and transportation safety and efficiency. By focusing on the nuanced ways in which humans allocate their visual attention, and how this can inform the development of artificial intelligence (AI) and machine learning (ML) to aid in self-driving cars, transportation safety automation, and

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Vehicle Edge Computing for Travel Behavior and Demand in Future Intelligent Transportation Systems (ITS)

Meeting the diverse needs of stakeholders such as passengers, drivers, and service providers is imperative. Modern travelers seek real-time updates and personalized journey experiences. Drivers need consolidated data for safety and punctuality (Chen et al., 2021), while service providers rely on data analytics to optimize resources and enhance reliability (Wang et al., 2020). Traditional centralized

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Emerging Travel Behavior Insights from 2023 National Surveys

The U.S. Census conducts three annual surveys that offer transportation analysts valuable insights into travel behaviors and trends: the American Community Survey (ACS), the American Time Use Survey (ATUS), and the Consumer Expenditure Survey (CE). With a multi-decade history, these surveys allow analysts to track changes over time and discern long-term trends. The newly available

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A Dynamic Analysis of the Built Environment-Travel Behavior Relationship Using Three Activity-Travel Surveys in the Austin, Texas Region

The relationship between the built environment (BE) and travel behavior (TB) has long interested scholars and practitioners in transportation, urban planning and design, health, and other fields. The proposed research aims to advance knowledge of the BE-TB relationship by taking a dynamic analysis approach. The study will pool three activity-travel surveys (1998, 2007, and 2017)

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Teleworking to Play or Playing to Telework? A Latent Segmentation Approach to Exploring the Relationship Between Telework and Nonwork Travel

Technology has evolved at a tremendous pace over the past decade, permeating into our everyday existence and affecting literally every aspect of our lives. Our activity-travel choices have been no exception in this regard, as we make continuous and joint decisions about which activities we can and want to undertake (either in-person or virtually). Add

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Trends in Time, Travel, Transit, Telework, and Treasure (T5)

The early 21st century to the present is a pivotal era in the study of travel behavior and time use. This two-decade period has witnessed not only incremental adjustments but also transformative shifts in how individuals allocate their time across various activities and make travel-related decisions within their time and monetary constraints. These shifts are

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