BCAS:防止道路超车事故的区块链避碰模型

Nadeem H. Malik, S. Altaf, Muhammad Azeem Abbas
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摘要

高速超车,特别是在无分隔道路上,是交通事故的主要原因。在超车操作中,由于无法预测的因素,人类更容易出错。对于自动驾驶汽车的超车操作,之前的研究主要集中在图像处理和驾驶环境的遥感上,没有考虑到周围交通的速度、驶近车辆的大小,也没有考虑到他们无法看到道路障碍物之外的事实。过去的研究没有关注周围交通的速度或接近车辆的大小。此外,大多数技术都是基于单代理系统,其中一个代理管理源车辆在其周围环境中的(自主)移动性。本研究对基于专用短程通信(Dedicated Short-Range communication, DSRC)的V2V远程通信框架进行可行性研究,以提高超车安全性。这项工作还试图通过引入基于区块链的安全模型BCAS(基于区块链的避碰系统)来提高安全性。提出的多智能体技术通过将处理责任的总计算量分配给每个智能体来增强实时、高速车辆的决策能力。实验结果表明,该方法优于现有技术,有效地弥补了现有研究的局限性。
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BCAS: A Blockchain Model for Collision Avoidance to Prevent Overtaking Accidents on Roads
Overtaking at high speeds, especially on non-divided roadways, is a leading cause of traffic accidents. During overtaking maneuvers, humans are more likely to make mistakes due to factors that cannot be predicted. For overtaking operations in autonomous vehicles, prior research focused on image processing and distant sensing of the driving environment, which didn't consider the speed of the surrounding traffic, the size of the approaching vehicles, or the fact that they could not see beyond impediments in the road. The past researches didn't focus on the speed of the surrounding traffic or the size of the approaching vehicles. Moreover, most of the techniques were based on single agent systems where one agent manages the source vehicle's (autonomous) mobility within its surroundings. This research conducts a feasibility study on a remote Vehicle-to-Vehicle (V2V) communication framework based on Dedicated Short-Range Communication (DSRC) to improve overtaking safety. This work also tries to improve safety by introducing a blockchain-based safety model called BCAS (Blockchain-based Collision Avoidance System). The proposed multi-agent technique strengthens the ability of real-time, high-speed vehicles to make decisions by allocating the total computation of processing responsibilities to each agent. From the experimental results, it is concluded that the proposed approach performs better than existing techniques and efficiently covers the limitations of existing studies.
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