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This paper presents the computer vision-based V2X collaborative perception. Our system uses a forward-looking camera in the host vehicle. The camera detects road users such as pedestrians, vehicles, and motorcycles. Such information includes object type, relative location, direction, and speed. This information is used to compose proxy Basic Safety Messages on behalf of the detected objects. Early adopters of the V2X technology can experience the benefits of enhanced V2X market penetration. The outcome of adopting this concept will result in an inflated V2X market penetration rate leading to earlier safety, mobility, and situational awareness improvements. The ultimate goal is for all road participants to be fully aware of each other. The novelty of our work is the integration of computer vision-based detection and LTE-V V2X communications, in addition to implementing the concept for pedestrians and bicyclists.

Vehicle to Everything (V2X) technology has been studied extensively in the past years. Limited pilot and production deployments, and research work have demonstrated V2X benefits. These include improvement to safety, mobility conditions and environmental benefits. Several safety and mobility applications have been investigated in literature. Nonetheless, V2X holds a potential for broader innovation in connected and automated vehicle applications. Feasibility assessment and algorithm validation of such applications may prove to be challenging. This results from costs associated with test track rental and equipping vehicles with V2X technology. Besides, limited V2X penetration rate leads to unavailability of naturalistic testing environment. In this paper, we investigate the use of the autonomous vehicle simulation, named Carla, for V2X application validation. Carla is an open source project that we altered to enable V2X applications assessment.