Search Results for author: Shengyin Shen

Found 5 papers, 1 papers with code

Evaluating Roadside Perception for Autonomous Vehicles: Insights from Field Testing

no code implementations22 Jan 2024 Rusheng Zhang, Depu Meng, Shengyin Shen, Tinghan Wang, Tai Karir, Michael Maile, Henry X. Liu

This paper introduces a comprehensive evaluation methodology specifically designed to assess the performance of roadside perception systems.

Autonomous Vehicles

MSight: An Edge-Cloud Infrastructure-based Perception System for Connected Automated Vehicles

no code implementations8 Oct 2023 Rusheng Zhang, Depu Meng, Shengyin Shen, Zhengxia Zou, Houqiang Li, Henry X. Liu

As vehicular communication and networking technologies continue to advance, infrastructure-based roadside perception emerges as a pivotal tool for connected automated vehicle (CAV) applications.

Trajectory Prediction

Robust Roadside Perception: an Automated Data Synthesis Pipeline Minimizing Human Annotation

no code implementations29 Jun 2023 Rusheng Zhang, Depu Meng, Lance Bassett, Shengyin Shen, Zhengxia Zou, Henry X. Liu

Our approach was rigorously tested at two key intersections in Michigan, USA: the Mcity intersection and the State St./Ellsworth Rd roundabout.

Autonomous Driving Generative Adversarial Network

ROCO: A Roundabout Traffic Conflict Dataset

1 code implementation1 Mar 2023 Depu Meng, Owen Sayer, Rusheng Zhang, Shengyin Shen, Houqiang Li, Henry X. Liu

With the traffic conflict data collected, we discover that failure to yield to circulating vehicles when entering the roundabout is the largest contributing reason for traffic conflicts.

Traffic Accident Detection

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