Short-Term Transit Decision Support System Using Multi-task Deep Neural Networks | |
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Abstract |
Unpredictability is one of the top reasons that prevent people from using public transportation. To improve the on-time performance of transit systems, prior work focuses on updating schedule periodically in the long-term and providing arrival delay prediction in real-time. But when no real-time transit and traffic feed is available (e.g., one day ahead), there is a lack of effective contextual prediction mechanism that can give alerts of possible delay to commuters. |
Year of Publication |
2018
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Conference Name |
2018 IEEE International Conference on Smart Computing (SMARTCOMP)
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Date Published |
07/2018
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Publisher |
IEEE
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Conference Location |
Taormina, Italy
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ISBN Number |
978-1-5386-4705-9
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Accession Number |
17972176
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Attachments |
Document
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Google Scholar | BibTeX | XML |