Using hierarchical tree-based regression model to examine university student travel frequency and mode choice patterns in China

Zhan, Guangjun; Yan, Xuedong; Zhu, Shanjiang; Wang, Yun

doi:10.1016/j.tranpol.2015.09.006

Cited by 86 publications

(67 citation statements)

References 38 publications

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“…Mode-specific costs, together with travel distance/time, access to bus and environmental awareness jointly influence mode choice [12]; transit access increases transit usage among university students [36]; perceived and actual travel times by bus or by bike have the greatest impacts on transit usage and biking behaviors among university members [9].…”

Section: Physical Environmentmentioning

confidence: 99%

“…Specifically, Collins and Chambers [12] find that mode-specific costs and access to bus, together with travel distance, travel time, and environmental awareness, may jointly influence the mode choice. Zhan, et al [36] argue that transit access increases transit usage among university students. Shannon, et al [9] find that perceived and actual travel time by bus or by bike has the greatest impact on transit usage and biking behaviors among university members.…”

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confidence: 99%

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Mode Choice of Commuter Students in a College Town: An Exploratory Study from the United States

Zhou

Yin

2018

Sustainability

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Research of travel behaviors of university students is of theoretical and empirical importance. The literature, however, has paid little attention to mode choice of students at college towns. This study aims to specifically explore influence factors of the mode choice of college town students. After conducting a survey of commuter students at Iowa State University, a college-town university in the United States, the study uses both simple statistics and advanced statistical models (e.g., multinomial logit and nested logit models) to analyze the data and produces findings to confirm and test existing knowledge and to gain new insights. Firstly, students at a college town are more likely to adopt greener (non-driving-alone) modes, especially walking, to commute compared to their counterparts at urban universities; this is as revealed in the literature. Secondly, students may use “bundled services” to fulfill their travel needs. The students who prioritized rent affordability in housing choice tend to live in proximity to bus stops and are more likely to ride buses. Lastly, commuter students who do not drive alone to school tend to prefer a residence with transit proximity. Moreover, students who reside in proximity to transit and who reported “peer effects” would use non-driving modes more if commute time was shortened.

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Section: Physical Environmentmentioning

confidence: 99%

mentioning

confidence: 99%

Mode Choice of Commuter Students in a College Town: An Exploratory Study from the United States

Zhou

Yin

2018

Sustainability

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“…In addition, the participants recruited by researchers to take part in a travel survey have not been divided into different types based on their social attributes, such as students, workers, and so on. Different types of people have different travel patterns; the travel time, travel frequency, and mode choice patterns might be not the same for university students and workers, for instance [48,49].…”

Section: Discussionmentioning

confidence: 99%

Travel Mode Detection Based on GPS Raw Data Collected by Smartphones: A Systematic Review of the Existing Methodologies

Yang

Jing

2016

Information

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Abstract:Over the past couple of decades, global positioning system (GPS) technology has been utilized to collect large-scale data from travel surveys. As the precise spatiotemporal characteristics of travel could be provided by GPS devices, the issues of traditional travel survey, such as misreporting and non-response, could be addressed. Considering the defects of dedicated GPS devices (e.g., the need for a large sum of money to buy devices, forgetfulness in the taking of devices to collect data, limiting of the sample size because of the number of devices, etc.), and the fact that the smartphone is becoming one of the necessities of life, there is an opportunity for smartphones to replace dedicated GPS devices. Although several general reviews of GPS travel survey and GPS data-processing methods have been written, a systematic review of smartphone-based GPS data collection and travel mode detection has not be made.. The studies were collected from six databases. The purpose of this review is to critically evaluate the current literature on the existing methodologies of travel mode detection based on GPS raw data collected by smartphones. Meanwhile, according to a systematic comparison of the different methods of data preprocessing for travel mode detection, this paper details the strengths and weaknesses of the existing methods. Furthermore, it is a very important step towards developing methodologies and applications for GPS raw data collected by smartphones.

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“…In addition, the participants recruited by researchers to take part in a travel survey have not been divided into different types based to their own social attributes, such as students, workers and so on, since different types of people have different travel features. For instance, the travel time, travel frequency and mode choice patterns of university students and workers might be not the same [48,49].…”

Section: Discussionmentioning

confidence: 99%

Travel mode detection based on GPS raw data collected by smartphones: a systematic review of the existing methodologies

Yang

Jing

2016

Preprint

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Over the past couple of decades, Global positioning system (GPS) technology has been utilized to collect large-scale data from travel surveys. As the precise spatiotemporal characteristics of travel could be provided by GPS devices, the issues of traditional travel survey, such as misreporting and non-response, could be addressed. Considering the defects of dedicated GPS devices (e.g., need much money to buy devices, forget to take devices to collect data, limit the simple size because of the number of devices, etc.), and the phenomenon that the smartphone is becoming one of necessities of life, there is a great chance for the smartphone to replace dedicated GPS devices. Although, several general reviews have been done about smartphone-based GPS travel survey in the literature review section in some articles, a systematic review from smartphone-based GPS data collection to travel mode detection has none. The included studies were searched from six databases. The purpose of this review is to critically assess the current literature on the existing methodologies of travel mode detection based on GPS raw data collected by smartphones. Meanwhile, according to the systematic comparison among different methods from data-preprocessing to travel mode detection, this paper could carefully provide the Strengths and Weaknesses of existing methods. Furthermore, it is the crucial step to develop the methodologies and applications of GPS raw data collected by smartphones.

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Using hierarchical tree-based regression model to examine university student travel frequency and mode choice patterns in China

Cited by 86 publications

References 38 publications

Mode Choice of Commuter Students in a College Town: An Exploratory Study from the United States

Mode Choice of Commuter Students in a College Town: An Exploratory Study from the United States

Travel Mode Detection Based on GPS Raw Data Collected by Smartphones: A Systematic Review of the Existing Methodologies

Travel mode detection based on GPS raw data collected by smartphones: a systematic review of the existing methodologies

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