29 citations · 32 across the 7 of their papers we have counts for
5 papers · 1 filter
A Dynamic Fusion Large Language Model for Traffic Flow Prediction
Xue Qiu, Jianli Xiao
Traffic flow prediction is a core supporting technology for intelligent transportation systems. It uses historical data to infer future traffic dynamics in specific areas, thereby…
FPMT: Enhanced Semi-Supervised Model for Traffic Incident Detection
Xinying Lu, Jianli Xiao
For traffic incident detection, the acquisition of data and labels is notably resource-intensive, rendering semi-supervised traffic incident detection both a formidable and consequ…
ST-RetNet: A Long-term Spatial-Temporal Traffic Flow Prediction Method
Baichao Long, Wang Zhu, Jianli Xiao
Traffic flow forecasting is considered a critical task in the field of intelligent transportation systems. In this paper, to address the issue of low accuracy in long-term forecast…
A Hybrid Model for Traffic Incident Detection based on Generative Adversarial Networks and Transformer Model
Xinying Lu, Doudou Zhang, Jianli Xiao
In addition to enhancing traffic safety and facilitating prompt emergency response, traffic incident detection plays an indispensable role in intelligent transportation systems by…
Hybrid Transformer and Spatial-Temporal Self-Supervised Learning for Long-term Traffic Prediction
Wang Zhu, Doudou Zhang, Baichao Long +1
Long-term traffic prediction has always been a challenging task due to its dynamic temporal dependencies and complex spatial dependencies. In this paper, we propose a model that co…