Abstract
Cooperative systems are seen as catalysts for autonomous driving and driver assistance systems. They provide accurate and comprehensive information on the environment that enables the driver and vehicle to make better decisions. In this paper, different strategies for traffic optimization are developed and compared in two scenarios: highway merging and car following. The effectiveness was simulated under several traffic flow values and the impact of the algorithm parameter has been assessed. Results show the potential of cooperative systems to optimize common maneuvers. This optimization can be introduced into assistance systems and cooperative autonomous driving to improve traffic safety and efficiency. In addition, centralized information management would allow even greater benefits and the management of more complex environments.
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