BCAS: A Blockchain Model for Collision Avoidance to Prevent Overtaking Accidents on Roads
Keywords:Road Accident, Overtaking, Blockchain, V2V routing , Machine Learning
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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