- The effect of new transportation technologies on travel behavior and urban form
- Travel behavior changes during the COVID-19 Pandemic
- Social networks and travel behavior
- Passive methods to detect joint activities in social networks
- Validation methods for discrete choice models
- Evacuation behavior during natural disasters
- Built environment and travel behavior
■ As a research unit we are working on more topics (see our laboratory’s output here)
① The effect of new transportation technologies on travel behavior and urban form
New transportation technologies such as automated vehicles promise to be as disruptive, if not more than the advent of the automobile. In this project we attempt to understand the effect such technologies will have on our travel behavior and our cities in order to minimize its negative impacts while harnessing its potential.
② Travel behavior changes during the COVID-19 Pandemic
In this project we attempt to clarify how has travel behavior changed during the pandemic and what factors explain the observed changes. In particular we focus on the effects of risk perception and social influence.
③ Social networks and travel behavior
Our travel patterns are interdependent with the patterns of the people in our social networks, and while joint activities account a large share of total travel, this is still an understudied issue in the field.
This projects seeks to shed some light on the factors that affect social interaction among social networks and the decision making process behind group activities with the aim of improving the predictive ability of travel demand models.
④ Passive methods to detect joint activities in social networks
One of the key barriers in the study of travel behavior in social networks is the extreme response burden of travel behavior and social network surveys. As such, findings passive ways to collect these types of data is one of the upmost importance.
This projects evaluates the effectiveness of different passive data collection methods such as Google Maps Location History Data and GPS data to detect joint activities in social networks.
⑤ Validation methods for discrete choice models
Despite a strong dependence on cross-sectional data and the difficulties associated with conducting experiments in the transportation field, only 18.1% of articles in the field report model validation (Parady, Ory & Walker, 2021).
In addition to understand the current state of affairs regarding model reporting and validation practices, this project seeks to evaluate different validation methods and performance indices in order identify the most adequate methods given the type of models and typical datasets in the field.
⑥ Evacuation behavior during natural disasters
Short-notice natural disasters such as tsunamis present immense challenges to planners in terms of disaster preparedness.
This study seeks to understand evacuation patterns during short-notice natural disasters (prompt departure, destination choice, etc.) Such knowledge is expected to contribute to drawing better evacuation planning strategies taking into consideration, among others, psychological factors that might infuse a false sense of security on residents.
⑦ Built environment and travel behavior
Recent years have seen a paradigm shift in the conceptualization of what constitutes good urban development. Be it New Urbanism Smart Growth, or Compact Cities, one of the main premises behind these new paradigms is that mixed-use, high density developments can reduce automobile dependency and promote alternative modes such as transit, bicycles or walking (Parady, Takami & Harata, 2017).
This project seeks to quantify the magnitude of the built environment effect on travel behavior, while controlling for possible confounding factors such as residential self-selection.