16.7.2.7.7 Transportation Mode, Travel Mode, Transport Mode Detection

Chapter Contents (Back)
Traffic Flow. Transportation Mode. Travel Mode.

Gan, H.C.[Hong-Cheng],
To switch travel mode or not? Impact of Smartphone delivered high-quality multimodal information,
IET-ITS(9), No. 4, 2015, pp. 382-390.
DOI Link 1506
mobile computing BibRef

Jahangiri, A., Rakha, H.A.,
Applying Machine Learning Techniques to Transportation Mode Recognition Using Mobile Phone Sensor Data,
ITS(16), No. 5, October 2015, pp. 2406-2417.
IEEE DOI 1511
decision trees BibRef

Assemi, B., Safi, H., Mesbah, M., Ferreira, L.,
Developing and Validating a Statistical Model for Travel Mode Identification on Smartphones,
ITS(17), No. 7, July 2016, pp. 1920-1931.
IEEE DOI 1608
data privacy BibRef

Su, X., Caceres, H., Tong, H., He, Q.,
Online Travel Mode Identification Using Smartphones With Battery Saving Considerations,
ITS(17), No. 10, October 2016, pp. 2921-2934.
IEEE DOI 1610
Global Positioning System BibRef

Das, R.D.[Rahul Deb], Winter, S.[Stephan],
Detecting Urban Transport Modes Using a Hybrid Knowledge Driven Framework from GPS Trajectory,
IJGI(5), No. 11, 2016, pp. 207.
DOI Link 1612
BibRef

Xiao, Z.B.[Zhi-Bin], Wang, Y.[Yang], Fu, K.[Kun], Wu, F.[Fan],
Identifying Different Transportation Modes from Trajectory Data Using Tree-Based Ensemble Classifiers,
IJGI(6), No. 2, 2017, pp. xx-yy.
DOI Link 1703
BibRef

Wang, B., Gao, L., Juan, Z.,
Travel Mode Detection Using GPS Data and Socioeconomic Attributes Based on a Random Forest Classifier,
ITS(19), No. 5, May 2018, pp. 1547-1558.
IEEE DOI 1805
Automobiles, Feature extraction, Global Positioning System, Public transportation, Smart phones, GPS data, ROC curve, socioeconomic attributes BibRef

Ashqar, H.I., Almannaa, M.H., Elhenawy, M., Rakha, H.A., House, L.,
Smartphone Transportation Mode Recognition Using a Hierarchical Machine Learning Classifier and Pooled Features From Time and Frequency Domains,
ITS(20), No. 1, January 2019, pp. 244-252.
IEEE DOI 1901
Feature extraction, Frequency-domain analysis, Transportation, Sensors, Time-domain analysis, Global Positioning System, hierarchical modeling BibRef

Lee, K.J.[Kang-Jae], Kwan, M.P.[Mei-Po],
The Effects of GPS-Based Buffer Size on the Association between Travel Modes and Environmental Contexts,
IJGI(8), No. 11, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Revoredo, K.[Kate], Baião, F.[Fernanda], de M. S. Quintella, C.A.[Carlos A.], Campos, C.A.V.[Carlos Alberto V.], de S. Soares, E.F.[Elton F.],
A Combined Solution for Real-Time Travel Mode Detection and Trip Purpose Prediction,
ITS(20), No. 12, December 2019, pp. 4655-4664.
IEEE DOI 2001
Feature extraction, Global Positioning System, Sensors, Real-time systems, Data collection, Data models, Task analysis, automated machine learning BibRef

Liang, X., Zhang, Y., Wang, G., Xu, S.,
A Deep Learning Model for Transportation Mode Detection Based on Smartphone Sensing Data,
ITS(21), No. 12, December 2020, pp. 5223-5235.
IEEE DOI 2012
Transportation, Accelerometers, Sensors, Gravity, Acceleration, Deep learning, Data models, Transportation mode, deep learning, accelerometer BibRef

Lan, G., Xu, W., Ma, D., Khalifa, S., Hassan, M., Hu, W.,
EnTrans: Leveraging Kinetic Energy Harvesting Signal for Transportation Mode Detection,
ITS(21), No. 7, July 2020, pp. 2816-2827.
IEEE DOI 2007
Transportation, Kinetic energy, Global Positioning System, Accelerometers, Sensors, Biomedical monitoring, Monitoring, sparse representation BibRef

Nawaz, A.[Asif], Huang, Z.Q.[Zhi-Qiu], Wang, S.Z.[Sen-Zhang], Hussain, Y.[Yasir], Khan, I.[Izhar], Khan, Z.[Zaheer],
Convolutional LSTM based transportation mode learning from raw GPS trajectories,
IET-ITS(14), No. 6, June 2020, pp. 570-577.
DOI Link 2005
BibRef

Yu, J.J.Q.,
Travel Mode Identification With GPS Trajectories Using Wavelet Transform and Deep Learning,
ITS(22), No. 2, February 2021, pp. 1093-1103.
IEEE DOI 2102
Trajectory, Global Positioning System, Feature extraction, Data mining, Discrete wavelet transforms, Deep learning, feature selection BibRef

Namdarpour, F.[Farnoosh], Mesbah, M.[Mahmoud], Gandomi, A.H.[Amir H.], Assemi, B.[Behrang],
Using genetic programming on GPS trajectories for travel mode detection,
IET-ITS(16), No. 1, 2022, pp. 99-113.
DOI Link 2112
BibRef

Jiang, G.Y.[Gui-Yuan], Lam, S.K.[Siew-Kei], He, P.[Peilan], Ou, C.H.[Chang-Hai], Ai, D.[Dihao],
A Multi-Scale Attributes Attention Model for Transport Mode Identification,
ITS(23), No. 1, January 2022, pp. 152-164.
IEEE DOI 2201
Travel modes based on user trajectories. Trajectory, Global Positioning System, Feature extraction, Sensor phenomena and characterization, Smart phones, neural decision forest BibRef

Zhu, Y.S.[Yuan-Shao], Liu, Y.[Yi], Yu, J.J.Q.[James J. Q.], Yuan, X.L.[Xing-Liang],
Semi-Supervised Federated Learning for Travel Mode Identification From GPS Trajectories,
ITS(23), No. 3, March 2022, pp. 2380-2391.
IEEE DOI 2203
Global Positioning System, Trajectory, Data models, Collaborative work, Feature extraction, Servers, Data privacy, semi-supervised learning BibRef

Moreau, H.[Hugues], Vassilev, A.[Andrea], Chen, L.M.[Li-Ming],
The Devil is in the Details: An Efficient Convolutional Neural Network for Transport Mode Detection,
ITS(23), No. 8, August 2022, pp. 12202-12212.
IEEE DOI 2208
Machine learning, Trajectory, Global Positioning System, Deep learning, Convolutional neural networks, Training BibRef

Zhu, Y.[Yida], Luo, H.Y.[Hai-Yong], Chen, R.[Runze], Zhao, F.[Fang], Guo, S.[Song],
MSCPT: Toward Cross-Place Transportation Mode Recognition Based on Multi-Sensor Neural Network Model,
ITS(23), No. 8, August 2022, pp. 12588-12600.
IEEE DOI 2208
Transportation, Feature extraction, Data models, Navigation, Computational modeling, Bagging, Accelerometers, Cross-place, data augmentation BibRef

Liu, Z.Y.[Zhi-Yuan], Wang, Y.[Yunshan], Cheng, Q.X.[Qi-Xiu], Yang, H.[Hai],
Analysis of the Information Entropy on Traffic Flows,
ITS(23), No. 10, October 2022, pp. 18012-18023.
IEEE DOI 2210
Entropy, Uncertainty, Standards, Information entropy, Indexes, Data models, Analytical models, Information entropy, uncertainty, speed entropy BibRef

Zeng, J.Q.[Jia-Qi], Zhang, G.Z.[Guo-Zheng], Hu, Y.W.[You-Wei], Wang, D.H.[Dian-Hai],
Addressing robust travel mode identification with individual trip-chain trajectory noise reduction,
IET-ITS(17), No. 1, 2023, pp. 129-143.
DOI Link 2301
BibRef

Alam, M.G.R.[Md. Golam Rabiul], Haque, M.[Mahmudul], Hassan, M.R.[Md. Rafiul], Huda, S.[Shamsul], Hassan, M.M.[Mohammad Mehedi], Strickland, F.L.[Fred L.], Al Qahtani, S.A.[Salman A.],
Feature Cloning and Feature Fusion Based Transportation Mode Detection Using Convolutional Neural Network,
ITS(24), No. 4, April 2023, pp. 4671-4681.
IEEE DOI 2304
Feature extraction, Transportation, Sensors, Trajectory, Sensor systems, Global Positioning System, Smart phones, data augmentation BibRef

Lai, Z.L.[Zhi-Lin], Wang, J.[Jing], Zheng, J.J.[Jun-Jie], Ding, Y.X.[Yu-Xing], Wang, C.[Cheng], Zhang, H.Z.[Hui-Zhen],
Travel mode choice prediction based on personalized recommendation model,
IET-ITS(17), No. 4, 2023, pp. 667-677.
DOI Link 2304
BibRef

Jiang, Z.H.[Zhi-Huan], Huang, A.[Ailing], Qi, G.[Geqi], Guan, W.[Wei],
A Framework of Travel Mode Identification Fusing Deep Learning and Map-Matching Algorithm,
ITS(24), No. 6, June 2023, pp. 6401-6415.
IEEE DOI 2306
Hidden Markov models, Trajectory, Poles and towers, Data integrity, Urban areas, Global Positioning System, Cleaning, Deep learning, travel mode identification BibRef

Tang, L.[Li], Tang, C.[Chuanli], Fu, Q.[Qi], Ma, C.X.[Chang-Xi],
Predicting travel mode choice with a robust neural network and Shapley additive explanations analysis,
IET-ITS(18), No. 7, 2024, pp. 1339-1354.
DOI Link 2407
behavioural sciences computing, demand forecasting, feature selection, neural network interpretability BibRef

Zeng, J.Q.[Jia-Qi], Huang, Y.[Yulang], Zhang, G.Z.[Guo-Zheng], Cai, Z.Y.[Zheng-Yi], Wang, D.[Dianhai],
Travel Mode Identification for Non-Uniform Passive Mobile Phone Data,
ITS(25), No. 9, September 2024, pp. 11103-11116.
IEEE DOI 2409
Trajectory, Global Positioning System, Data models, Mobile handsets, Task analysis, Training, Motion segmentation, sequence-to-sequence model BibRef


Chapter on Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities continues in
Shared Ride Systems, Car Sharing, Taxi, Analysis .


Last update:Sep 28, 2024 at 17:47:54