Towards Smart Mobility: Journey Reconstruction for Frictionless Public Transit using GPS and GTFS Data

Author:

Alizadeh Maryam1,Haponenko Hanna1,Ghorbankhani Nafise1,Eilkhani Paniz1,Badr Mohamed1,Vidal Carlos1,Emadi Ali1

Affiliation:

1. McMaster University,McMaster Automotive Resource Centre (MARC),Hamilton,Ontario,Canada

Publisher

IEEE

Reference16 articles.

1. Forecasting dynamic public transport origin-destination matrices with long-short term memory recurrent neural networks;florian;2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC),2016

2. Learning transportation modes from smartphone sensors based on deep neural network;shih-hau;IEEE Sensors Journal,2017

3. Online travel mode identification using smartphones with battery saving considerations;xing;IEEE Transactions on Intelligent Transportation Systems,2016

4. Dy-namic origin-destination prediction in urban rail systems: A multi-resolution spatio-temporal deep learning approach;peyman;IEEE Transactions on Intelligent Transportation Systems,2021

5. Transportation mode detection using machine learning techniques on mobile phone sensor data;ifigenia;Proc of the ACM International Conference on Pervasive Technologies Related to Assistive Environments,2020

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