Individual Commute Time Recognition Based on the Hierarchical Semantic Model

IEEE Access

Zhong Ziming¹  Jianqin Yin¹  Tao Wenxuan¹  Wei Liu¹ 

[1] Automation School, Beijing University of Posts and Telecommunications, Beijing, China;

关键词: Commute time recognition;    hierarchical semantic model;    traffic demand management;   

DOI  :  10.1109/ACCESS.2020.3019253

来源: DOAJ

【 摘 要 】

Individual commute time recognition is essential for traffic demand management. However, this problem has yet to be studied. In this study, we propose a hierarchical semantic model (HSM) to recognize individual commute time. To the best of our knowledge, this work is the first to integrates large scale travellers commute time prediction at an individual level. HSM consists of a low and a high semantic layer. The low semantic layer models spatial, temporal and environmental information, whereas the high semantic layer recognises commute time using the hidden Markov model on the basis of the low semantic layer outputs. Experimental results demonstrate the effectiveness of our proposed model for individual commute time recognition.

【 授权许可】

Unknown