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arXiv · 2310.05290

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

Rusheng Zhang·Depu Meng·Shengyin Shen·Zhengxia Zou·Houqiang Li·Henry X. Liu
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Abstract

As vehicular communication and networking technologies continue to advance, infrastructure-based roadside perception emerges as a pivotal tool for connected automated vehicle (CAV) applications. Due to their elevated positioning, roadside sensors, including cameras and lidars, often enjoy unobstructed views with diminished object occlusion. This provides them a distinct advantage over onboard perception, enabling more robust and accurate detection of road objects. This paper presents MSight, a cutting-edge roadside perception system specifically designed for CAVs. MSight offers real-time vehicle detection, localization, tracking, and short-term trajectory prediction. Evaluations underscore the system's capability to uphold lane-level accuracy with minimal latency, revealing a range of potential applications to enhance CAV safety and efficiency. Presently, MSight operates 24/7 at a two-lane roundabout in the City of Ann Arbor, Michigan.

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Rusheng Zhang, Depu Meng, Shengyin Shen, Zhengxia Zou, Houqiang Li, Henry X. Liu. 2023-10-08. MSight: An Edge-Cloud Infrastructure-based Perception System for Connected Automated Vehicles. https://arxiv.org/abs/2310.05290

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