Framework for Cooperative Perception of Intelligent Vehicles: Using Improved Neighbor Discovery

Neighbor discovery, providing the neighbor information by broadcasting discovery messages, is a promising solution for cooperative perception of Intelligent Vehicles (IVs). However, the high vehicle mobility and severe channel randomness of IV environments call for a frequent discovery, which results in a superabundant overhead. In this paper, we propose a new framework for cooperative perception of IVs by novelly introducing an improved neighbor discovery method. We first establish an analytical framework to capture the quantitive relation between the hitting probability of neighbor discovery with the vehicle mobility and channel randomness using a closed-form expression. Based on the analysis, an adaptive neighbor discovery method is developed to adaptively make tradeoff between the discovery accuracy and overhead at varying driving status of IVs. Applying the improved neighbor discovery, the process of cooperative perception is discussed. Accordingly, simulations in three IV scenarios are conducted whose results are consistent with our analysis.