Research on Highway Node Management Method Based on ChatGLM Large Model
This paper comprehensively expounds a highway toll station management method based on ChatGLM large model, which integrates advanced traffic flow prediction technology, speech recognition and instruction execution system, intelligent service management system and innovative interaction technology. Through the deep learning and analysis capabilities of the ChatGLM large model, we have achieved accurate prediction of traffic flow and provided strong support for economic management. At the same time, the combination of speech recognition technology and large models has significantly improved work efficiency and intelligent management level. The construction of the intelligent service management system makes the management of highway toll stations more efficient and intelligent. Innovative interactive technologies, such as text-to-speech and digital avatars, further enhance user experience and satisfaction. The method proposed in this paper not only puts forward new ideas for the tradition.
Authors
- Bin Liao
- Tao Huang (ORCID: https://orcid.org/0000-0002-3545-1122)
- Hongmei Cui
Institutions
- Chongqing University of Posts and Telecommunications (CN)
- Chongqing Jiaotong University (CN)
Publication Details
- Published
- 2024-12-27
- DOI
- https://doi.org/10.1109/eiecc64539.2024.10929511
- Primary Topic
- Traffic Prediction and Management Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- China Railway
- National Natural Science Foundation of China
- Chongqing Municipal Education Commission