计算机工程与应用2024，Vol.60Issue(9)：65-78,14.DOI:10.3778/j.issn.1002-8331.2308-0127
基于深度学习的公交行驶轨迹预测研究综述
Review of Research on Bus Travel Trajectory Prediction Based on Deep Learning
摘要
Abstract
Bus travel trajectory prediction predicts when the bus arrives at important track points on its route,such as stops and road intersections.Accurate bus arrival time prediction at road intersections and stops can improve the efficiency and service quality of urban public transport system,which is crucial for urban public transport planning and bus dispatch.From the perspective of the development of bus travel trajectory prediction methods,this paper analyzes the factors that affect bus operation,explores the types of datasets,and summarizes the data preprocessing methods.According to their development venation,bus travel trajectory prediction methods are divided into three categories:historical methods,para-metric models represented by time series models,and non-parametric models including machine learning and deep learning methods.The advantages and limitations of different methods are summarized.Due to the superior performance of deep learning models in time series prediction tasks,more and more scholars begin to adopt deep learning based models to solve the problem of bus travel trajectory prediction,and consider combining the spatial and temporal features exhibited by urban roads to improve prediction accuracy further.Finally,the challenges faced in bus travel trajectory prediction field are analyzed,and future development and research directions in this field are prospected.关键词
公交行驶轨迹预测/深度学习/时空特征/时间序列预测/智能交通Key words
bus travel trajectory prediction/deep learning/spatial-temporal features/time series forecasting/intelligent transportation分类
信息技术与安全科学引用本文复制引用
杨晨曦,庄旭菲,陈俊楠,李衡..基于深度学习的公交行驶轨迹预测研究综述[J].计算机工程与应用,2024,60(9):65-78,14.基金项目
内蒙古自治区科技计划项目(2020GG0104) （2020GG0104）
内蒙古自然科学基金(2023MS06021) （2023MS06021）
内蒙古自治区直属高校基本科研业务费项目(JY20230065). （JY20230065）
