Abstract

This technical paper proposes a new waveform combining the low-rate and high-rate data streams to detect the region-of-interest signal in a high-mobility environment using optical camera communication. The proposed technique augments the bit rate of the low-rate stream; consequently, the link setup time is reduced and the requirement of low frame rate camera is eliminated. Additionally, both the low-rate and high-rate data streams in the proposed bi-level pulse position modulation are decoded with a unique adaptive thresholding mechanism with a high frame rate camera. We also propose a vehicle localization scheme to assist the drivers in maintaining a safe following distance that can significantly reduce the frequency of accidents. Moreover, two neural networks are proposed to detect the light-emitting diodes (LEDs) for localization and communication, and to estimate the road curvature from different rear LED shapes of the forwarding vehicle, respectively. The system is implemented, and its performance is analyzed in Python 3.7. The implementation results show that the proposed system is able to achieve 75% localization accuracy, a 150 bps low-rate stream, and a 600 bps high-rate stream over a range of 25 m with a commercial 30 fps camera.

Highlights

  • Vehicle navigation systems first drew attention in the late 1960s in the United States.The related primary goals included reducing highway congestion, increasing fuel efficiency, guiding routes, avoiding vehicle collisions, and collecting tolls electronically [1]

  • As a rolling shutter camera scans the pixels row by row, significant distortion may occur owing to the high-mobility, whereas a global shutter camera reads all pixels at the same time to detect all light-emitting diodes (LEDs) states simultaneously, showing superior performance in high-mobility environments

  • LEDs that transmit visible light are primarily used as vehicle headlights or backlights, which are mainly utilized as the transmitter in Optical camera communication (OCC)

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Summary

Introduction

Vehicle navigation systems first drew attention in the late 1960s in the United States. A novel modulation technique is proposed for V2X communications wherein both low-rate and high-rate streams can be simultaneously decoded from the light intensities This technique successfully converts two camera-based vehicular OCC systems into one;. A vehicle localization scheme is proposed that can determine the inter-vehicular distance and angle from the rear LED shapes of the FWVs using a single camera. It can localize an FWV of any size and any taillight design via the assistance of the OCC system; To reduce accidents at road bends, a road curvature estimation technique from the rear LED shapes of the FWVs is implemented.

System Overview
Proposed OCC System for V2V Scenario
Transmitter
LED Detection
Vehicle Localization
Results
Conclusions

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