Autonomous vehicles play an important part in intelligent transportation systems.In these vehicles,driving control decision is obtained based on the collection of massive traffic states and intensive information processing.However,the spatial-temporal characteristics of the traffic states and the constrained environmental perception range of an individual vehicle seriously undermine the effectiveness of the state collection.Multi-agent driven collaborative decision provides a potential approach to address the problem.A multi-dimensional information fusion mechanism was proposed,which improved the gain of vehicular information fusion for autonomous driving tasks.Moreover,an intelligent distributed decision algorithm was designed for autonomous driving applications,which maximized the road traffic flow while maximizing the gain of information fusion on the autonomous driving mission under vehicular cost and resource constraints.Numerical results demonstrate the convergence and practicability of the proposed algorithm.
Multi-agent driven collaborative decision mechanism of information fusion for autonomous driving vehicles
2020
Article (Journal)
Electronic Resource
Unknown
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