Role of Income on Travel Behavior in Polluted Air

2021 ◽  
Author(s):  
Suji Kim ◽  
Yekang Ko ◽  
Kitae Jang
Keyword(s):  
Travel Behavior

Role of Urban Big Data in Travel Behavior Research

2020 ◽  
pp. 036119812097502
Author(s):  
Chihuangji Wang ◽  
Daniel Baldwin Hess
Keyword(s):  
Big Data ◽  
Survey Data ◽  
Travel Behavior ◽  
Data Science ◽  
Location Based Service ◽  
Labor Costs ◽  
Public And Private ◽  
Public And Private Sector ◽  
Data Analytic

Understanding urban travel behavior (TB) is critical for advancing urban transportation planning practice and scholarship; however, traditional survey data is expensive (because of labor costs) and error-prone. With advances in data collection techniques and data analytic approaches, urban big data (UBD) is currently generated at an unprecedented scale in relation to volume, variety, and speed, producing new possibilities for applying UBD for TB research. A review of more than 50 scholarly articles confirms the remarkable and expanding role of UBD in TB research and its advantages over traditional survey data. Using this body of published work, a typology is developed of four key types of UBD—social media, GPS log, mobile phone/location-based service, and smart card—focusing on the features and applications of each type in the context of TB research. This paper discusses in significant detail the opportunities and challenges in the use of UBD from three perspectives: conceptual, methodological, and political. The paper concludes with recommendations for researchers to develop data science knowledge and programming skills for analysis of UBD, for public and private sector agencies to cooperate on the collection and sharing of UBD, and for legislators to enforce data security and confidentiality. UBD offers both researchers and practitioners opportunities to capture urban phenomena and deepen knowledge about the TB of individuals.

scholarly journals The Role of Destination’s Built Environment on Nonmotorized Travel Behavior: A Case of Long Beach, California

2017 ◽  
Vol 38 (2) ◽  
pp. 152-166 ◽  
Author(s):  
Dohyung Kim ◽  
Jiyoung Park ◽  
Andy Hong
Keyword(s):  
Built Environment ◽  
Travel Behavior ◽  
Mode Choice ◽  
Long Beach ◽  
Environment Factors ◽  
Household Travel Survey ◽  
Future Policy ◽  
Household Travel ◽  
National Household Travel Survey

This study examines how built environment factors at trip destinations influence nonmotorized travel behavior in the City of Long Beach, California. Using 2008–2009 National Household Travel Survey with California Add-Ons, we found that nonmotorized users tend to choose more clustered destinations than motorized users, and that density, diversity, and design at destinations significantly affect mode choice decisions. Transportation networks and nonmotorized facilities at trip destinations are especially important factors for nonmotorized mode choice. Future policy and research need to consider built environment factors at trip destinations to effectively accommodate nonmotorized travel within a city.

scholarly journals Exploring the Influence of Built Environment on Car Ownership and Use with a Spatial Multilevel Model: A Case Study of Changchun, China

2018 ◽  
Vol 15 (9) ◽  
pp. 1868 ◽  
Author(s):  
Xiaoquan Wang ◽  
Chunfu Shao ◽  
Chaoying Yin ◽  
Chengxiang Zhuge
Keyword(s):  
Built Environment ◽  
Spatial Autocorrelation ◽  
Travel Behavior ◽  
Second Step ◽  
Car Ownership ◽  
Spatial Effects ◽  
Cascading Effects ◽  
Step Model

Although the impacts of built environment on car ownership and use have been extensively studied, limited evidence has been offered for the role of spatial effects in influencing the interaction between built environment and travel behavior. Ignoring the spatial effects may lead to misunderstanding the role of the built environment and providing inconsistent transportation policies. In response to this, we try to employ a two-step modeling approach to investigate the impacts of built environment on car ownership and use by combining multilevel Bayesian model and conditional autocorrelation (CAR) model to control for spatial autocorrelation. In the two-step model, the predicting car ownership status in the first-step model is used as a mediating variable in the second-step car use model. Taking Changchun as a case study, this paper identifies the presence of spatial effects in influencing the effects of built environment on car ownership and use. Meanwhile, the direct and cascading effects of built environment on car ownership and use are revealed. The results show that the spatial autocorrelation exists in influencing the interaction between built environment and car dependency. The results suggest that it is necessary for urban planners to pay attention to the spatial effects and make targeted policy according to local land use characteristics.

Travel Behavior in Troubled Times: The Role of Consumer Self‐Confidence

2008 ◽  
Vol 25 (1) ◽  
pp. 25-42 ◽  
Author(s):  
Juliana Valencia ◽  
Geoffrey I. Crouch
Keyword(s):  
Travel Behavior ◽  
Self Confidence

Results of the 2016 Hiawatha Service Passenger Survey

2017 ◽  
Author(s):  
Benjamin R. Sperry ◽  
Tyler Collins
Keyword(s):  
Travel Behavior ◽  
Department Of Transportation ◽  
Survey Analysis ◽  
Passenger Rail ◽  
Wisconsin Department ◽  
Work Commute ◽  
Profile Characteristics ◽  
Comparison Of The Results ◽  
Rail Service

The Hiawatha Service is an Amtrak intercity passenger rail service that operates the 90-mile route between Milwaukee, Wisconsin, and Chicago, Illinois. As part of its management and oversight role for the route, the Wisconsin Department of Transportation (WisDOT) routinely conducts surveys of passengers traveling on the Hiawatha Service. The most recent survey was conducted in May 2016. This paper reports a summary of the key findings from the 2016 Hiawatha Service passenger survey. Analysis of more than 2,400 surveys reveals significant details of the travel behavior and demographic profile characteristics of Hiawatha Service passengers. A majority of passengers on weekday trains are traveling for work commute or business-related purposes while a majority of weekend passenger trips are leisure or personal trips. Approximately 70 percent of passengers would drive if the Hiawatha Service were not available, indicating that the train has a meaningful impact on highway congestion. Additional details on passenger motivations for using rail and the importance of on-board Wi-Fi service are also provided. Comparison of the results from 2016 with previous surveys conducted in 2002/2003, 2005, and 2011 demonstrates the role of the Hiawatha Service in the Milwaukee-Chicago travel corridor.

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