Decision-making is a crucial task for autonomous driving. Taking the wrong decision might cause a cartographical accident. Decision-making implies planning the appropriate behavior based on the current state of the vehicle and its environment. The paper aims to review the current state of the art of behavior Planning for autonomous driving. A basic categorization for behavior planning algorithms is introduced. Besides, a review of different algorithms is discussed with a comparison between different algorithms from the point of view of the suitable scenario. Finally, promising research topics are discussed.
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