Implementation of Distributed AI in an Autonomous Driving Application

K. Rahimunnisa
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Abstract

Vehicle driving is an art to be performed with maximum attention. A small distraction or error in the driving practice may lead to severe problem to the people and the vehicle. The autonomous driving systems are implemented partially in few applications to rectify such human errors through an Artificial Intelligence (AI) algorithm. The AI algorithms require certain peripheral units like camera and sensors for their operation and are very effective and fast compared to the manual process. The computational complexity of autonomous driving systems are very high than the other applications where it requires continuous monitoring and instantaneous processing. Therefore it requires a huge amount of memory space and heavy processors. To address such limitations, the recent year applications are implemented with a cloud communication system for processing the collected data in a remote place. However, security and communication concerns present in such models have led this proposed work to implement a distributed AI architecture for an autonomous driving system.
分布式人工智能在自动驾驶应用中的实现
驾驶汽车是一门需要全神贯注的艺术。在驾驶过程中,一个小小的分心或失误都可能给人和车带来严重的问题。自动驾驶系统在少数应用中部分实现,以通过人工智能(AI)算法纠正此类人为错误。人工智能算法需要特定的外围设备,如摄像头和传感器才能运行,与人工过程相比,人工智能算法非常有效和快速。自动驾驶系统的计算复杂度比其他需要连续监控和即时处理的应用要高得多。因此,它需要大量的内存空间和重型处理器。为了解决这些限制,近年来的应用程序使用云通信系统来实现远程处理收集的数据。然而,这些模型中存在的安全和通信问题导致了这项提议的工作,即为自动驾驶系统实现分布式人工智能架构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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