Inferring trip purposes and uncovering travel patterns from taxi trajectory data

L Gong, X Liu, L Wu, Y Liu - Cartography and Geographic …, 2016 - Taylor & Francis
Global positioning system-enabled vehicles provide an efficient way to obtain large
quantities of movement data for individuals. However, the raw data usually lack activity …

Identifying different transportation modes from trajectory data using tree-based ensemble classifiers

Z Xiao, Y Wang, K Fu, F Wu - ISPRS International Journal of Geo …, 2017 - mdpi.com
Recognition of transportation modes can be used in different applications including human
behavior research, transport management and traffic control. Previous work on …

Learning travel recommendations from user-generated GPS traces

Y Zheng, X Xie - ACM Transactions on Intelligent Systems and …, 2011 - dl.acm.org
The advance of GPS-enabled devices allows people to record their location histories with
GPS traces, which imply human behaviors and preferences related to travel. In this article …

Processing raw data from global positioning systems without additional information

N Schuessler, KW Axhausen - Transportation Research …, 2009 - journals.sagepub.com
Since the first Global Positioning System (GPS) studies in the mid-1990s, this method of
surveying individual travel behavior has gained attention in transport research. Compared …

An interactive-voting based map matching algorithm

J Yuan, Y Zheng, C Zhang, X Xie… - … conference on mobile …, 2010 - ieeexplore.ieee.org
Matching a raw GPS trajectory to roads on a digital map is often referred to as the Map
Matching problem. However, the occurrence of the low-sampling-rate trajectories (eg one …

Semi-supervised federated learning for travel mode identification from GPS trajectories

Y Zhu, Y Liu, JQ James, X Yuan - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
GPS trajectories serve as a significant data source for travel mode identification along with
the development of various GPS-enabled smart devices. However, such data directly …

Classifying transportation mode and speed from trajectory data via deep multi-scale learning

R Zhang, P Xie, C Wang, G Liu, S Wan - Computer Networks, 2019 - Elsevier
With the rapid development of mobile Internet, the Internet of Things and other new
technologies, mobile devices are generating massive amounts of spatio-temporal trajectory …

Location-based social networks: Users

Y Zheng - Computing with spatial trajectories, 2011 - Springer
In this chapter, we introduce and define the meaning of location-based social network
(LBSN) and discuss the research philosophy behind LBSNs from the perspective of users …

Semi-supervised deep learning approach for transportation mode identification using GPS trajectory data

S Dabiri, CT Lu, K Heaslip… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Identification of travelers' transportation modes is a fundamental step for various problems
that arise in the domain of transportation such as travel demand analysis, transport planning …

[HTML][HTML] Inferring hybrid transportation modes from sparse GPS data using a moving window SVM classification

A Bolbol, T Cheng, I Tsapakis, J Haworth - Computers, Environment and …, 2012 - Elsevier
Understanding travel behaviour and travel demand is of constant importance to
transportation communities and agencies in every country. Nowadays, attempts have been …