The popularization of vehicles has created safety and environmental problems. Projects have been launched worldwide to improve road safety, reduce traffic congestion and bring more comfort to drivers. The vehicle network environment is dynamic and complex, sources are often heterogeneous, and therefore the exchanged information may be imperfect. The theory of belief functions offers flexibility in uncertainty modeling and provides rich tools for managing different types of imperfection. It is used to represent uncertainty, manage and fuse the various acquired information. We focus on the management of imperfect information exchanged between vehicles concerning events on the road. The carried work distinguishes local events and spatial events, which do not have the same characteristics. In an environment without infrastructure where each vehicle is a fusion center and creates its own vision, the goal is to provide to each driver the synthesis of the situation on the road as close as possible to the reality. Different models using belief functions are proposed. Different strategies are considered: discount or reinforce towards the absence of the event to take into account messages ageing, keep the original messages or just the fusion result in vehicle database, consider the world update, manage the spatiality of traffic jam events by taking into account neighborhood. Perspectives remain numerous; some are developed in the manuscript as the generalization of proposed methods to all spatial events such as fog blankets.