Latent Semantic Sequence Coding Applied to Taxi Travel Time Estimation Article Swipe
Zilin Zhao
,
Yuanying Chi
,
Zhiming Ding
,
Mengmeng Chang
,
Zhi Cai
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/ijgi12020044
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/ijgi12020044
Taxi travel time estimation based on real-time traffic flow collection in IoT has been well explored; however, it becomes a challenge to use the limited taxi data to estimate the travel time. Most of the existing methods in this scenario rely on shallow feature engineering. Nevertheless, they have limited performance in learning complex moving patterns. Thus, a Latent Semantic Pulse Sequence-based Deep Neural Network (LSPS-DNN) is proposed in this paper to improve the taxi travel time estimation performance by constructing a latent semantic propagation graph representing the latent path sequence. It first extracts the shallow modal features of trips, such as the time period and spatial location at different granularities. The representation of the pulse propagation graph is then extracted from shallow spatial features using a Pulse Coupled Neural Network (PCNN). Further, the propagation graph is encoded with negative sampling to obtain the embedding of deep propagation features between ODs. Meanwhile, we conduct deep network learning based on the Chengdu and NYC taxi datasets; our experimental evaluation results show it has a better performance compared to traditional feature construction methods.
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- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/ijgi12020044
- https://www.mdpi.com/2220-9964/12/2/44/pdf?version=1675159695
- OA Status
- gold
- References
- 21
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4318823936
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https://openalex.org/W4318823936Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/ijgi12020044Digital Object Identifier
- Title
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Latent Semantic Sequence Coding Applied to Taxi Travel Time EstimationWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-01-31Full publication date if available
- Authors
-
Zilin Zhao, Yuanying Chi, Zhiming Ding, Mengmeng Chang, Zhi CaiList of authors in order
- Landing page
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https://doi.org/10.3390/ijgi12020044Publisher landing page
- PDF URL
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https://www.mdpi.com/2220-9964/12/2/44/pdf?version=1675159695Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2220-9964/12/2/44/pdf?version=1675159695Direct OA link when available
- Concepts
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Computer science, Graph, Artificial neural network, Coding (social sciences), Modal, Deep learning, Artificial intelligence, Feature (linguistics), Data mining, Pattern recognition (psychology), Theoretical computer science, Statistics, Mathematics, Chemistry, Polymer chemistry, Philosophy, LinguisticsTop concepts (fields/topics) attached by OpenAlex
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10Other works algorithmically related by OpenAlex
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