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Deep spatial-temporal travel time prediction model based on trajectory feature

文献类型：期刊论文

作者Sheng, Zhaoyu1,3; Lv, Zhiqiang1,2,3; Li, Jianbo3; Xu, Zhihao1,3
刊名COMPUTERS & ELECTRICAL ENGINEERING
出版日期2023-09-01
卷号110页码:12
关键词Travel time prediction Trajectory feature Traffic condition Spatial correlation Temporal dependence
ISSN号0045-7906
DOI10.1016/j.compeleceng.2023.108868
英文摘要Research on travel time prediction shows its importance in the rational planning of travel arrangements and traffic congestion mitigation. The scale of taxi and online ride-hailing users is huge, and accurate travel time prediction is convenient for passengers to reasonably arrange travel planning. Unlike highways and buses, the trajectory of taxis is complex. At the same time, the travel time prediction of the taxi is affected by many factors. Existing models lack effective trajectory feature. They have low accuracy in predicting travel time in urban areas. This will affect the travel arrangement of passengers. In this paper, we propose a trajectory feature learning method based on the image processing method and time series prediction. Traffic congestion is quantified as the congestion value, and a variety of external factors are considered. The experimental results show that this model has advantages over some classical models in predicting travel time.
资助项目National Key Research and Development Plan Key Special Projects, China[2018YFB2100303] ; Shandong Province Colleges and Universities Youth Innovation Technology Plan Innovation Team project, China[2020KJN011] ; Shandong Provincial Natural Science Foundation, China[ZR2020MF060] ; Program for Innovative Postdoctoral Talents in Shandong Province, China[40618030001] ; National Natural Science Foundation of China[61802216] ; Postdoctoral Science Foundation of China[2018M642613]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:001046097400001
出版者PERGAMON-ELSEVIER SCIENCE LTD
源URL[http://119.78.100.204/handle/2XEOYT63/21353]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Li, Jianbo
作者单位1.Inst Ubiquitous Networks & Urban Comp, Ningxia Rd, Qingdao 266071, Shandong, Peoples R China
2.Chinese Acad Sci, Inst Comp Technol, Haidian Rd, Beijing 100086, Peoples R China
3.Qingdao Univ, Coll Comp Sci & Technol, Ningxia Rd, Qingdao 266071, Shandong, Peoples R China
推荐引用方式
GB/T 7714		 Sheng, Zhaoyu,Lv, Zhiqiang,Li, Jianbo,et al. Deep spatial-temporal travel time prediction model based on trajectory feature[J]. COMPUTERS & ELECTRICAL ENGINEERING,2023,110:12.
APA Sheng, Zhaoyu,Lv, Zhiqiang,Li, Jianbo,&Xu, Zhihao.(2023).Deep spatial-temporal travel time prediction model based on trajectory feature.COMPUTERS & ELECTRICAL ENGINEERING,110,12.
MLA Sheng, Zhaoyu,et al."Deep spatial-temporal travel time prediction model based on trajectory feature".COMPUTERS & ELECTRICAL ENGINEERING 110(2023):12.

入库方式： OAI收割

来源：计算技术研究所

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