Transport mode detection based on mobile phone network data: A systematic review

H Huang, Y Cheng, R Weibel - Transportation Research Part C: Emerging …, 2019 - Elsevier
The rapid development in telecommunication networks is producing a huge amount of
information regarding how people (with their mobile devices) move and behave over space …

[HTML][HTML] Emerging data for pedestrian and bicycle monitoring: Sources and applications

K Lee, IN Sener - Transportation research interdisciplinary perspectives, 2020 - Elsevier
Growing attention on the benefits of non-motorized travel has increased the demand for
accurate and timely pedestrian and bicycle travel data. Advancements in technologies and …

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 …

LSTM network for transportation mode detection

S Kumar, A Damaraju, A Kumar, S Kumari… - Journal of Internet …, 2021 - jit.ndhu.edu.tw
Abstract The study of Transportation Mode Detection (TMD) has become a popular research
field in recent years. It will be a crucial part of Smart mobility and Smart cities in upcoming …

[HTML][HTML] Review and evaluation of methods in transport mode detection based on GPS tracking data

P Sadeghian, J Håkansson, X Zhao - Journal of Traffic and Transportation …, 2021 - Elsevier
Mobility data, based on global positioning system (GPS) tracking, have been widely used in
many areas, such as analyzing travel patterns, investigating transport safety and efficiency …

[HTML][HTML] Reviewing trip purpose imputation in GPS-based travel surveys

MH Nguyen, J Armoogum, JL Madre… - Journal of Traffic and …, 2020 - Elsevier
The global positioning system (GPS) has motivated rapid advances in mobility data
collection. A massive amount of spatio-temporal information has made it possible to know …

Semi-supervised deep ensemble learning for travel mode identification

JQ James - Transportation Research Part C: Emerging …, 2020 - Elsevier
Travel mode identification is among the key problems in transportation research. With the
gradual and rapid adoption of GPS-enabled smart devices in modern society, this task …

[HTML][HTML] Trackintel: An open-source Python library for human mobility analysis

H Martin, Y Hong, N Wiedemann, D Bucher… - … Environment and Urban …, 2023 - Elsevier
Over the past decade, scientific studies have used the growing availability of large tracking
datasets to enhance our understanding of human mobility behavior. However, so far data …

A review of GPS trajectories classification based on transportation mode

X Yang, K Stewart, L Tang, Z **e, Q Li - Sensors, 2018 - mdpi.com
GPS trajectories generated by moving objects provide researchers with an excellent
resource for revealing patterns of human activities. Relevant research based on GPS …

Inferring fine-grained transport modes from mobile phone cellular signaling data

K Chin, H Huang, C Horn, I Kasanicky… - … , Environment and Urban …, 2019 - Elsevier
Due to the ubiquity of mobile phones, mobile phone network data (eg, Call Detail Records,
CDR; and cellular signaling data, CSD), which are collected by mobile telecommunication …