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Transportation Planning and Technology Volume 40, 2017 - Issue 2
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Articles

Identifying travel mode with GPS data

Fang ZongCollege of Transportation, Jilin University, Changchun, People’s Republic of ChinaCorrespondence[email protected]
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,
Yixin YuanCollege of Transportation, Jilin University, Changchun, People’s Republic of ChinaView further author information
,
Jianfeng LiuBeijing Urban Construction Design Development Group Co., Ltd., Beijing, People’s Republic of ChinaView further author information
,
Yu BaiCollege of Transportation, Jilin University, Changchun, People’s Republic of ChinaView further author information
&
Yanan HeCollege of Transportation, Jilin University, Changchun, People’s Republic of ChinaView further author information
Pages 242-255 | Received 11 Jun 2015, Accepted 15 Jul 2016, Published online: 16 Dec 2016

Citations (13)

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Yang Zhou, Chao Yang & Rongrong Zhu. (2019) Identifying trip ends from raw GPS data with a hybrid spatio-temporal clustering algorithm and random forest model: a case study in Shanghai. Transportation Planning and Technology 42:8, pages 739-756.
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Articles from other publishers (12)

Ye Hong, Emanuel Stüdeli & Martin Raubal. (2023) Evaluating geospatial context information for travel mode detection. Journal of Transport Geography 113, pages 103736.
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Jiaqi Zeng, Yi Yu, Yong Chen, Di Yang, Lei Zhang & Dianhai Wang. (2023) Trajectory-as-a-Sequence: A novel travel mode identification framework. Transportation Research Part C: Emerging Technologies 146, pages 103957.
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Jinyu Chen, Wenjing Li, Qing Yu, Ryosuke Shibasaki & Haoran Zhang. 2023. Handbook of Mobility Data Mining. Handbook of Mobility Data Mining 117 137 .
Yang Zhou, Yuantao Zhang, Quan Yuan, Chao Yang, Tangyi Guo & Yinhai Wang. (2022) The Smartphone-Based Person Travel Survey System: Data Collection, Trip Extraction, and Travel Mode Detection. IEEE Transactions on Intelligent Transportation Systems 23:12, pages 23399-23407.
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Jiaqi Zeng, Guozheng Zhang, Youwei Hu & Dianhai Wang. (2022) Addressing robust travel mode identification with individual trip‐chain trajectory noise reduction. IET Intelligent Transport Systems.
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Jinyu Chen, Haoran Zhang, Wenjing Li & Ryosuke Shibasaki. 2022. Big Data and Mobility as a Service. Big Data and Mobility as a Service 25 75 .
G. W. H. A. Chandrasiri, K. A. G. G. K. Kumarasinghe & H. K. Nandalal. 2020. ICSBE 2018. ICSBE 2018 11 21 .
Armel Kemajou, Rémi Jaligot, Martí Bosch & Jérôme Chenal. (2019) Assessing motorcycle taxi activity in Cameroon using GPS devices. Journal of Transport Geography 79, pages 102472.
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Joseph Broach, Jennifer Dill & Nathan Winslow McNeil. (2019) Travel mode imputation using GPS and accelerometer data from a multi-day travel survey. Journal of Transport Geography 78, pages 194-204.
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Zong Fang, Lv Jian‐yu, Tang Jin‐jun, Wang Xiao & Gao Fei. (2018) Identifying activities and trips with GPS data. IET Intelligent Transport Systems 12:8, pages 884-890.
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Young-Ji Byon, Jun Ha, Chung-Suk Cho, Tae-Yeon Kim & Chan Yeun. (2017) Real-Time Transportation Mode Identification Using Artificial Neural Networks Enhanced with Mode Availability Layers: A Case Study in Dubai. Applied Sciences 7:9, pages 923.
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Jiaqi Zeng, Yi Yu, Yong Chen, Di Yang, Lei Zhang & Dianhai Wang. (2022) Trajectory-as-A-Sequence: A Novel Travel Mode Identification Framework. SSRN Electronic Journal.
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