Abstract
Crowd navigation path planning is important in public scenes. Existing strategies are mainly based on manual design, which is not flexible or effective enough. This article proposes an evolutionary framework for automatic crowd navigation path planning in public scenes. The proposed framework contains a new fitness evaluation mechanism that can quantitatively evaluate the quality of a path planning strategy by considering both crowd safety and flow speed. Based on the fitness evaluation mechanism, a framework based on multiobjective differential evolution (DE) is developed to efficiently evolve path planning strategies. Simulation results on two synthetic scenes and a real-world metro station scene show that the proposed framework can provide good path planning strategies.
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