|
|
|
|
|
Chang Guo, Jianfeng Zhu and Xiaoming Wang
In recent years, the rapid growth of vehicles has imposed a significant burden on urban road resources. To alleviate urban traffic congestion in intelligent transportation systems (ITS), real-time and accurate traffic flow prediction has emerged as an ef...
ver más
|
|
|
|
|
|
|
|
|
Jin Li, Tao Han, Wenyang Guan and Xiaoqin Lian
With the development and popularization of Intelligent Transportation Systems (ITS), Vehicle Ad-Hoc Networks (VANETs) have attracted extensive attention as a key technology. In order to achieve real-time monitoring, VANET technology enables vehicles to c...
ver más
|
|
|
|
|
|
|
|
|
Nan Lao Ywet, Aye Aye Maw, Tuan Anh Nguyen and Jae-Woo Lee
Urban Air Mobility (UAM) emerges as a transformative approach to address urban congestion and pollution, offering efficient and sustainable transportation for people and goods. Central to UAM is the Operational Digital Twin (ODT), which plays a crucial r...
ver más
|
|
|
|
|
|
|
|
|
Sorin Zoican, Roxana Zoican, Dan Galatchi and Marius Vochin
This paper illustrates a general framework in which a neural network application can be easily integrated and proposes a traffic forecasting approach that uses neural networks based on graphs. Neural networks based on graphs have the advantage of capturi...
ver más
|
|
|
|
|
|
|
|
|
Zhikai Jiang, Li Su and Yuxin Sun
Accurate ship object detection ensures navigation safety and effective maritime traffic management. Existing ship target detection models often have the problem of missed detection in complex marine environments, and it is hard to achieve high accuracy a...
ver más
|
|
|
|