TY - GEN
T1 - Improving GPS-Based Mode of Transport Detection in Multi-Modal Trips using Stop Analysis
AU - Klinker, Jens
AU - Avezum-Mercer, Mariana
AU - Jonas, Stephan
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper presents an extension to existing GPS-based approaches for tracking modes of transportation in multimodal trips. The extension focuses on analyzing stops and mapping them to surrounding public transport stations in order to improve the accuracy of the mode of transport detection. The proposed method is evaluated using data from the city of Munich, resulting in a 17% improvement of the F1-Score, from 73% to 90%. It is applicable to any GPS-based mode of transport detection system to potentially improve their accuracy.
AB - This paper presents an extension to existing GPS-based approaches for tracking modes of transportation in multimodal trips. The extension focuses on analyzing stops and mapping them to surrounding public transport stations in order to improve the accuracy of the mode of transport detection. The proposed method is evaluated using data from the city of Munich, resulting in a 17% improvement of the F1-Score, from 73% to 90%. It is applicable to any GPS-based mode of transport detection system to potentially improve their accuracy.
KW - Data Processing
KW - GPS
KW - Labeling
UR - http://www.scopus.com/inward/record.url?scp=85169809966&partnerID=8YFLogxK
U2 - 10.1109/MOST57249.2023.00023
DO - 10.1109/MOST57249.2023.00023
M3 - Conference contribution
AN - SCOPUS:85169809966
T3 - Proceedings - 2023 IEEE International Conference on Mobility, Operations, Services and Technologies, MOST 2023
SP - 142
EP - 151
BT - Proceedings - 2023 IEEE International Conference on Mobility, Operations, Services and Technologies, MOST 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1st IEEE International Conference on Mobility, Operations, Services and Technologies, MOST 2023
Y2 - 17 May 2023 through 19 May 2023
ER -
