计算机工程与应用2026，Vol.62Issue(7)：21-35,15.DOI:10.3778/j.issn.1002-8331.2506-0091
卷积神经网络在公交车辆调度中的应用综述
Review of Convolutional Neural Network in Bus Vehicle Scheduling
摘要
Abstract
With the rapid advancement of deep learning,convolutional neural network(CNN)has gained widespread app-lication across various fields due to their superior performance in image processing.Leveraging its formidable capabilities in feature extraction and nonlinear modeling,CNN has gradually emerged as a pivotal technological approach for optimiz-ing urban public transportation systems.Based on existing research findings both domestically and internationally,this systematic review examines the advancements and practical applications of CNN in the field of bus vehicle scheduling.It delves into a comprehensive analysis centered around technological evolution,model architecture,and contextual applica-tions.Initially,the development history of CNN with bus vehicle scheduling is outlined,detailing their fundamental struc-ture and key operational workflows.Following this,the applications of CNN are conducted.Subsequently,a systematic review of the basic workflow of CNN is conducted,exploring pplications in urban bus scheduling,particularly in bus passenger flow prediction,arrival time prediction,and passenger crowding detection.Finally,the latest research achievements of CNN in bus vehicle scheduling are summarized and discussed,culminating in a projection of future development direc-tions to enhance the accuracy,reliability,and safety of bus scheduling.关键词
公交车辆调度/卷积神经网络/深度学习/智能交通Key words
bus vehicle scheduling/convolutional neural networks/deep learning/intelligent transportation分类
交通工程引用本文复制引用
洪荣荣,贾新朝,田苗苗..卷积神经网络在公交车辆调度中的应用综述[J].计算机工程与应用,2026,62(7):21-35,15.基金项目
新疆维吾尔自治区自然科学基金(2022D01C691) （2022D01C691）
天池英才引进计划-青年博士人才. （）
