Beyond Mode Detection: Reconstructing Detailed Transit Itineraries from Crowdsourced GPS Trajectories
Published in ACM SIGSPATIAL Workshop on Spatial Intelligence for Smart and Connected Communities, 2025
Abstract
This paper presents a novel approach to reconstructing detailed transit itineraries from crowdsourced GPS trajectories that goes beyond traditional mode detection. The method enables more granular understanding of transit usage patterns and rider experiences.
Key Contributions
- Development of methods to reconstruct complete transit itineraries from GPS data
- Goes beyond simple mode detection to provide leg-level transit information
- Enables analysis of detailed transit usage patterns from crowdsourced data
- Applications for transit planning and service improvement
Context
This work builds on the BALTO project’s infrastructure for ethical and sustainable mobility data collection, demonstrating practical applications of crowdsourced transit data for transportation planning.
Venue
1st ACM SIGSPATIAL International Workshop on Spatial Intelligence for Smart and Connected Communities, 2025
Recommended Citation
Jagtap, O., Awasthi, N., Jain, M., Abrar, S. M., & Frías-Martínez, V. (2025). Beyond Mode Detection: Reconstructing Detailed Transit Itineraries from Crowdsourced GPS Trajectories. In Proceedings of the 1st ACM SIGSPATIAL International Workshop on Spatial Intelligence for Smart and Connected Communities (pp. 35-38).
Recommended citation: Jagtap, O., Awasthi, N., Jain, M., Abrar, S. M., & Frías-Martínez, V. (2025). Beyond Mode Detection: Reconstructing Detailed Transit Itineraries from Crowdsourced GPS Trajectories. In Proceedings of the 1st ACM SIGSPATIAL International Workshop on Spatial Intelligence for Smart and Connected Communities (pp. 35-38).
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