Toward The Design of An Efficient Transparent Traffic Environment Based on Vehicular Edge Computing

In recent years, with the continuously increasing number of vehicles, how to solve the frequent traffic accidents, the increasing traffic congestion, and the corresponding exhaust pollution in the transportation system is the problem that must be solved to ensure people's safe, efficient, and green travel needs. As one of the core components of future intelligent transportation systems (ITS), autonomous vehicles have become a common area of interest for academia and industry because they can strictly follow traffic laws and regulations while avoiding traffic accidents caused by improper driving behavior of human drivers. However, the current autonomous driving technology often relies on a single vehicle to independently detect its surrounding traffic environment. Under the impression of the detection range of the corresponding detector and the occlusion of different types of objects in the traffic system, a single vehicle often has a large detection blind spot. As a result, it may not be possible to develop an effective driving strategy in complex environments. For addressing this issue, in this article, we will introduce a collaborative object detection and warning method based on vehicular edge computing (VEC) to achieve a transparent traffic environment. In other words, by exploiting the computing power provided by the VEC, we will eliminate the detection blind spots of traffic system participants as much as possible. The efficiency of the proposed method will be evaluated through physical experiments.