Low cost approach to real-time vehicle to vehicle communication using parallel CPU and GPU processing

This paper proposes a novel Vehicle to Vehicle (V2V) communication system for collision avoidance which merges four different wireless devices (GPS, Wi-Fi, ZigBee (R) and 3G) with a low power embedded Single Board Computer (SBC) in order to increase processing speed while maintaining a low cost. The three major technical challenges with such combinations are the limited system bandwidth, high memory requirement and slow response time during data processing when accessing various collision avoidance situations. Collision avoidance data processing includes processing data for vehicles on express ways, roads, tunnels, traffic jams and indoor V2V communication such as required in car parks. Effective methods are proposed to address these technical challenges through parallel Central Processing Unit (CPU) and Graphic Processing Unit (GPU) processing. With this, parallel V2V trilateration and parallel bandwidth optimization, multi-dimensional real time complex V2V data streaming can be attained in less than a second. The test results have shown that there is at least a 4 to 10 times improvement on processing speed with parallel CPU and GPU processing used in V2V communication depending on different road safety conditions.