基于SocialGAN网络与自注意力机制的车辆轨迹预测方法

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主题词：智能车辆轨迹预测生成式对抗网络社交池化机制自注意力机制中图分类号：TP183；U461.91 文献标志码：A DOI： 10.19620/j.cnki.1000-3703.20240867

Vehicle Trajectory Prediction Method Based on Social GAN Network and Self-Attention Mechanism

ZhuLangqian’，Ma Shijun'，Liu Mingjian1²，LiMuyang'，Hao Changsheng1 （1.Collegeof Information Engineering，DalianOcean University，Dalian16023;2.KeyLaboratoryofEnvironment ControlledAquaculture，Ministryof Education，DalianOcean University，Dalian116023）

【Abstract】Toaddresstheissue thattemporalfeaturesand spatialfactors ofthe trafcenvironment affcttheaccuracyof vehicletrajectorypredictioninvehicledriving，thispaperproposesavehicletrajectorypredictionmethodintegratingtemporal multi-headself-attentionandsocial pooling basedonthe Social GenerativeAdversarial Network （SMA-GAN）.Firstly，the historicaltrajectoryfeaturesareextractedbythetemporalcorelationofthetargetvehicle'sowntrajectorydatausingthemultiheadself-atentionmechanism.Then，thespatialdimensionalfeaturesofthetargetvehicleareextractedbythesocialpoling mechanismbasedonthespatialpositionalrelationshipbetweenthetargetvehicleandthesuroundingvehicles.Finalythe predictedtrajectoryofthetargetvehicleisobtainedbytheencoder-decoder.Modeltrainingandcomparisontestsare conducted using the NGSIM dataset，and theresultsshow that theSMA-GAN model has higher predictionaccuracy and efficiency in the highway scene.

KeyWords：Intelligent vehicle，Trajectory prediction，Generative Adversarial Network（GAN）. Social pooling mechanism，Self-attention mechanism

【引用格式】祝朗千，马时俊，刘明剑，等.基于Social GAN网络与自注意力机制的车辆轨迹预测方法[J].汽车技术，2025（6）：8-14.ZHULQ，MASJ，LIUMJ，etal.VehicleTrajectoryPredictionMethodBasedonSocialGANNetworkandSelf-AtentionMechanism[J]. Automobile Technology，2025（6）： 8-14.

1前言

随着智能交通系统的迅速发展，车辆轨迹预测技术能够感知复杂交通环境中的潜在风险因素，结合驾驶辅助系统的应用，对于提升行车安全具有重要意义。（剩余11141字）