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An Indoor Smart Traffic Dataset and Data Collection System: Dataset

Published: 24 January 2023 Publication History

Abstract

Smart traffic is an emerging research area gaining more attention due to a class of emerging applications such as autonomous driving. Most smart traffic scenarios are outdoors, which are hard to collect traffic data and build demanding sensing systems. In this work, an indoor smart traffic testbed with an F1TENTH autonomous driving vehicle is built, allowing the collection of traffic datasets under different scenarios and performing various smart traffic tasks. This novel data collection system and collected dataset can help research teams build various smart traffic systems and evaluate indoor smart traffic datasets. The collected traffic light dataset is publicly available at the link1.

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Cited By

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  • (2024)Pantheon: Preemptible Multi-DNN Inference on Mobile Edge GPUsProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661878(465-478)Online publication date: 3-Jun-2024

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  1. An Indoor Smart Traffic Dataset and Data Collection System: Dataset

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    cover image ACM Conferences
    SenSys '22: Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems
    November 2022
    1280 pages
    ISBN:9781450398862
    DOI:10.1145/3560905
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    Publication History

    Published: 24 January 2023

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    Author Tags

    1. F1TENTH
    2. autonomous driving
    3. dataset
    4. smart traffic

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    SenSys '22 Paper Acceptance Rate 52 of 187 submissions, 28%;
    Overall Acceptance Rate 198 of 990 submissions, 20%

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    • (2024)Pantheon: Preemptible Multi-DNN Inference on Mobile Edge GPUsProceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services10.1145/3643832.3661878(465-478)Online publication date: 3-Jun-2024

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