Poster: Multi-Camera Interoperable Emulation Framework Using Embedded Edge-Cloud AI Computing for Autonomous Vehicle Driving

초록

The growth of autonomous driving technology is accelerating. However, complete autonomous driving has not been implemented yet. This paper proposes a multi-camera interoperable emulation framework for developing autonomous vehicle driving. We implement two components of the Advanced Driver Assistance System (ADAS). The vehicle adjusts its speed based on the distance from the object and stays in its lane. Smart Cruise Control (SCC) and Lane Keeping Assist (LKA) are. These two systems are remotely controlled in our framework. As a result, developing, applying, and simulating algorithms will be more convenient, and this can protect drivers from accidents caused by incomplete algorithms during simulations. Moreover, these systems can relieve the drivers' burden and fatigue during real driving and prevent dangerous situations that can occur due to other vehicles or pedestrians. © 2024 IEEE.

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