Spatio-temporal trajectory prediction is essential in traffic management and urban planning,but traditional models are constrained by data sparsity,noise pollution,and non-linear relationships.Swarm intelligence-driven spatio-temporal trajectory prediction technology can overcome the limitations of traditional models,achieving high-precision and real-time prediction.Firstly,the commonly-used swarm data sources in current swarm intelligence research are reviewed,and the core optimization algorithms,such as particle swarm optimization and ant colony optimization are summarized,and the representation of spatio-temporal trajectories is given.Secondly,the probability-based and machine learning-based spatio-temporal trajectory prediction methods are summarized,and the technical route of swarm intelligence-driven trajectory prediction is outlined.Lastly,the main application scenarios of swarm intelligence in current spatio-temporal trajectory prediction are discussed,including traffic path planning,natural environment monitoring,and operational risk warning,and the potential of swarm intelligence-driven spatio-temporal trajectory prediction technology in cognitive enhancement,autonomous systems,and decentralized learning is explored.
swarm intelligencetrajectory predictionspatio-temporal trajectoryswarm data mining
万方数据
维普
