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Ford Cars Communicate Through Crypto Tokens

Ford Cars Communicate Through Crypto Tokens

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Ford Cars Communicate Through Crypto Tokens

U.S. Car manufacturing giant ‘Ford’ has received a patent for an apparatus which will help cars on the road communicate with each other through exchange of crypto tokens and reduce traffic.

The patent “Vehicle-to-Vehicle cooperation to marshal traffic” was published and awarded to Ford Global Technologies LLC by U.S. Patent & Trademark Office (USPTO). The published document details a “Cooperatively Managed Merge & Pass (CMPP) system” according to which “driving behavior is monitored, recorded and evaluated in a collective manner by themselves and other participating vehicles.

The application explains how proposed communication model of cars and Cooperative Adaptive Cruise Control (CACC) can communicate with other cars through exchange of CMPP tokens, switching their priority from the individual to the “group flow rate through the traffic cataract.

The application further explains that the system would temporarily allow specific vehicles which are cooperating (referred as consumer vehicles) to drive at higher speeds in less-occupied lanes of traffic and merge & pass freely if needed.

Other participating vehicles (referred as merchant vehicles) voluntarily occupy slower lanes of traffic to allow the consumer vehicle to merge into their lanes & pass as needed.

The CMPP tokens are used to validate and authorize a transaction in which, at consumer vehicle’s request, the merchant vehicles either occupy slower lanes of traffic themselves or allow the consumer vehicle to merge into their own lane and pass as necessary. The CMPP tokens can also be used as on-the-road credit within the proposed system.

An example, if a driver is running late for his flight by 25 minutes, he can request via the system to pass any vehicle for the next 25 minutes in exchange for CMPP tokens.

The vehicles that sacrifice their time for the good of traffic will receive tokens from the other participating vehicles. The complete model runs on the psychology of human drivers who focus on their individual travel time preferences.

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