ABSTRACT

The deployment and implementation of self-driving cars (SDC) is becoming a reality. Various units and subsystems of the SDC ecosystem are needed to be impeccable in their executions. It is therefore relevant to have communication subsystem for transmitting information from Vehicle-to-Everything (V2X) which is useful in efficient implementation of the SDC technology. However, the heterogeneous and dynamic environments and overall ecosystems pose a reliability challenge on the information transmitted to be processed by the central processor for efficient communication decision of the SDC in the vehicular environments. This study demonstrates a proposed solution by examining and providing a SDC communication model and an algorithm that can enhance the operation of the SDC. The model considers the impact of vehicle speed, delay on information transmitted, radio frequency, and vehicular environments which are incorporated into the SDC decision making software. The proposed approach is compared with theoretical model and existing study. The results show that the proposed algorithm is about 95 % efficient at an average speed of 30 mph with a processing time less than 𝟏𝒎𝒔 and less than 𝟏𝝁𝒔 delay on information transmitted in a highly signal impacted SDC complex environment case. It also shows about 99 % efficient at an average speed of 70 mph in a less signal impacted SDC complex environment case. This proposed approach could be used to design the communication capability of on-board Vehicle-to-Everything devices and for efficient planning and future deployments of SDC.

Keywords: - Decision making, Energy per bit to noise, Propagation model, Self-driving cars, Vehicle-to-everything communications