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DeepTRANS: A Deep Learning System for Public Bus Travel Time Estimation using Traffic Forecasting

Summary: DeepTRANS extends a DL bus ETA model with predicted traffic forecasts to improve travel-time estimation. By fusing forecasted congestion as exogenous features, it yields about 21% accuracy gains over prior DL ETA baselines, highlighting forecast-informed data fusion for transport analytics. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12174
Venue
VLDB
Year
2020
Pagerank
7.0696727e-05
Overall Rank
3,464 | 75.91%
DOI
10.14778/3415478.3415518

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