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Joint Radar-Communications Strategies for Autonomous Vehicles
Self-driving cars constantly asses their environment in order to choose ...
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On Self Driving Cars: An LED Time of Flight (ToF) based Detection and Ranging using various Unipolar Optical CDMA Codes
The dramatic surge in the development of autonomous vehicles has generat...
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Validation Frameworks for Self-Driving Vehicles: A Survey
As a part of the digital transformation, we interact with more and more ...
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Sensing Hidden Vehicles by Exploiting Multi-Path V2V Transmission
This paper presents a technology of sensing hidden vehicles by exploitin...
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Sensing Hidden Vehicles Based on Asynchronous V2V Transmission: A Multi-Path-Geometry Approach
Accurate vehicular sensing is a basic and important operation in autonom...
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Team NCTU: Toward AI-Driving for Autonomous Surface Vehicles – From Duckietown to RobotX
Robotic software and hardware systems of autonomous surface vehicles hav...
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Road Quality Analysis Based on Cognitive Internet of Vehicles (CIoV)
This research proposal aims to use cognitive methods to analyze the qual...
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REITS: Reflective Surface for Intelligent Transportation Systems
Autonomous vehicles are predicted to dominate the transportation industry in the foreseeable future. Safety is one of the major challenges to the early deployment of self-driving systems. To ensure safety, self-driving vehicles must sense and detect humans, other vehicles, and road infrastructure accurately, robustly, and timely. However, existing sensing techniques used by self-driving vehicles may not be absolutely reliable. In this paper, we design REITS, a system to improve the reliability of RF-based sensing modules for autonomous vehicles. We conduct theoretical analysis on possible failures of existing RF-based sensing systems. Based on the analysis, REITS adopts a multi-antenna design, which enables constructive blind beamforming to return an enhanced radar signal in the incident direction. REITS further increases the signal-to-noise ratio (SNR) of the return signal by canceling out irrelevant reflections from the environment. Preliminary results show that REITS improves the detection distance of a self-driving car radar by a factor of 3.63.
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