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Shengyin Shen on Muck Rack

Shengyin Shen

As seen in: Nature, arXiv, Roads & Bridges
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Articles

Breaking through safety performance stagnation in autonomous vehicles with dense learning - Nature Communications

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By Shuo Feng, Haojie Zhu, Haowei Sun, Xintao Yan, Linxuan He, Jingxuan Yang, Boqi Li, Shu Q. Li, Ling Wang, Shengyin Shen, Henry X. Liu, Guangzhen Su
| Nature Verified
Abstract Autonomous vehicles remain commercially limited largely due to safety performance stagnation. Existing deep learning, heavily reliant on failure data from rare safety-critical events, suffers from the seesaw effect—improvement in some scenarios causes regression in others. We introduce an innovative dense learning approach that prioritizes both informative failures and successes, informed by theoretical findings.
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Traffic light optimization with low penetration rate vehicle trajectory data - Nature Communications

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By Xingmin Wang, Zihao Wang, Shengyin Shen, Zachary Jerome
| Nature Verified
Abstract Traffic light optimization is known to be a cost-effective method for reducing congestion and energy consumption in urban areas without changing physical road infrastructure. However, due to the high installation and maintenance costs of vehicle detectors, most intersections are controlled by fixed-time traffic signals that are not regularly optimized.
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Robust Roadside Perception: an Automated Data Synthesis Pipeline Minimizing Human Annotation

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By Depu Meng, Lance Bassett, Shengyin Shen, Zhengxia Zou
| arXiv
[Submitted on 29 Jun 2023 ( v1 ), last revised 8 Feb 2024 (this version, v2)] Title:Robust Roadside Perception: an Automated Data Synthesis Pipeline Minimizing Human Annotation Download a PDF of the paper titled Robust Roadside Perception: an Automated Data Synthesis Pipeline Minimizing Human Annotation, by Rusheng Zhang and 5 other authors Download PDF HTML (experimental) Abstract:Recently, advancements in vehicle-to-infrastructure communication technologies have elevated the significance of...
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