Quantifying the effects of built environment on travel behavior in three Chinese cities during COVID-19

Cities, Journal Year: 2025, Volume and Issue: 158, P. 105722 - 105722

Published: Jan. 18, 2025

Language: Английский

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Active mobility in the green space: A spatial and temporal analysis of Indro Montanelli Park

Journal of Transport & Health, Journal Year: 2025, Volume and Issue: 42, P. 102018 - 102018

Published: March 8, 2025

Language: Английский

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Mobility Behavior and Patterns Using Cell Phone Trace Data: A Case Study of Fresno, California

International Conference on Transportation and Development 2022, Journal Year: 2025, Volume and Issue: unknown, P. 750 - 761

Published: June 5, 2025

Language: Английский

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Travel behaviour changes among post-secondary students after COVID-19 pandemic – A case of Greater Toronto and Hamilton Area, Canada

Case Studies on Transport Policy, Journal Year: 2024, Volume and Issue: 17, P. 101245 - 101245

Published: June 12, 2024

Recent research has reported travel behaviour changes during the COVID-19 pandemic. Speculatively, these short-term disruptions in may lead to new habit formation and longer-term among young adults belonging generations Y Z. Focusing on post-secondary students within Greater Toronto Hamilton Area, Canada using longitudinal data collected fall 2019 spring 2022, our exploratory study examined post-COVID-19 analyzed whether are associated with their socio-demographic characteristics life events experienced over course of Results show that many public transit users active travellers (pedestrians cyclists) switched cars for commuting post-pandemic. The post-pandemic retention use was lower compared cars, while transportation modes had lowest rate. Some such as age, living situation, work hours access were significantly changes. In terms events, who joined workforce after completion education between 2022 more likely shift commute mode from implying some influence this event changes, addition pandemic-induced Our findings suggest observed GTHA not be a result only pandemic also partly important they Future planning policy implications, directions future have been discussed.

Language: Английский

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Characterizing last-mile freight transportation using mobile phone data: The case of Santiago, Chile

Transportation Research Part A Policy and Practice, Journal Year: 2024, Volume and Issue: 186, P. 104149 - 104149

Published: July 2, 2024

Language: Английский

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Optimizing county-level infectious respiratory disease forecasts: a pandemic case study integrating social media-based physical and social connectivity networks

International Journal of Digital Earth, Journal Year: 2024, Volume and Issue: 17(1)

Published: Dec. 4, 2024

Forecasting infectious respiratory diseases is crucial for effective prevention and intervention strategies. However, existing time series forecasting models that incorporate human mobility data have faced challenges in making localized predictions on a large scale across the country due to costs constraints. Using COVID-19 pandemic as case study, this research explores whether integrating social media-based place connectivity networks can improve of disease transmission at county level various regions. Place networks, derived from Twitter users tweets, based Facebook interactions, were used map spatial linkages between locations. These integrated into weekly incidence 2,927 U.S. counties using Long Short-Term Memory (LSTM) models. The combined connectivity-weighted model significantly enhanced prediction accuracy, reducing Mean Absolute Percentage Error (MAPE) by 49.38% 96.62% counties, with greatest improvements observed urban Northeastern counties. results demonstrate combining enhances offering scalable sustainable solution diverse geographic areas publicly accessible media data.

Language: Английский

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Commuting Behavior Changes at Different Stages of Localized COVID-19 Outbreak: Evidence from Nanjing, China

Systems, Journal Year: 2024, Volume and Issue: 12(8), P. 271 - 271

Published: July 28, 2024

Commuting behaviors have been changed by the COVID-19 pandemic. To investigate impacts at different stages of sudden and localized outbreak, this paper carries out an online survey to obtain data, targeting residents in Nanjing China, where there had outbreaks proposes a sequential analysis method calculate complexity commuting behavior changes. The Tobit model is used explore factors that influence Results show commuters using public transportation drop significantly when occur, with 43.5% them switching private cars or working from home. number home increases 14 times. While outbreak gradually subsides, modes tend recover, but does not immediately return state before outbreak. Regression results indicate aged 40–60 maintain their habits, while younger workers are more flexible on options. Middle-income commuters, those living low-risk areas near subway within 800 m prefer change modes, opting for what they perceive be safer ways commute. For medium- high-risk who people non-green health codes, adjust real time based color codes risk level live. research findings contribute our understanding targeted management needs during local outbreaks, can help government formulate comprehensive effective pandemic prevention policy.

Language: Английский

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Understanding the Charging Behavior of Private Electric Vehicles: A Structural Equation Model Approach

Lecture notes in civil engineering, Journal Year: 2024, Volume and Issue: unknown, P. 408 - 415

Published: Nov. 13, 2024

Language: Английский

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