The development of new detection equipment and vehicle networking technology has enabled the acquisition of a significant quantity of accurate realtime vehicle trajectory data on urban roads, which is being utilized in the field of urban transportation research. However, due to the existence of ...
Stage I estimates the future destination point of the predicted vehicle using a destination point estimation module based on VAE. In stage II, it produces multiple trajectories using a multiple trajectories prediction module based on GAT wh...
Trajectory prediction in pipeline form for intercepting hypersonic gliding vehicles based on LSTM The interception problem of Hypersonic Gliding Vehicles(HGVs)has been an important aspect of missile defense systems.In order to provide interceptors with ... L Sun,B Yang,MA Jie - 中国航空学报:英文版...
Traditional approaches to prediction of future trajectory of road agents rely on knowing information about their past trajectory. This work rather relies only on having knowledge of the current state and intended direction to make predictions for multiple vehicles at intersections. Furthermore, message ...
Vehicle Trajectory Prediction based on Motion Model and Maneuver Recognition Predicting other traffic participants trajectories is a crucial task for an autonomous vehicle, in order to avoid collisions on its planned trajectory. It ... A Houenou,P Bonnifait,V Cherfaoui,... - IEEE/RSJ ...
Second, the basic LSTM models often suffer from vanishing gradient problem and are, thus, hard to train for long time series. These two problems sometimes lead to large prediction errors in vehicle trajectory predicting. In this paper, we proposed a spatio-temporal LSTM-based trajectory prediction...
LSTM-based graph attention network for vehicle trajectory prediction Vehicle Trajectory Prediction (VTP) is one of the key technologies for autonomous driving, which can improve the safety and collaboration of the autonomous... J Wang,K Liu,H Li - 《Computer Networks》 被引量: 0发表: 2024年 ...
Trajectory prediction of vehicles in city-scale road networks is of great importance to various location-based applications such as vehicle navigation, traffic management, and location-based recommendations. Existing methods typically represent a trajectory as a sequence of grid cells, road segments or ...
To solve several existing problems of maneuver-based trajectory prediction, we propose four targeted solutions and establish a trajectory prediction model that integrates semi-supervised And-or Graph (AOG) and Spatio-temporal LSTM (ST-LSTM). To reduce the dependence on the well-labeled dataset, we...
Autonomous?Vehicle Trajectory Combined Prediction Model Based on CC-LSTM) There will be a complex driving environment formed by manned and unmanned vehicles with highly uncertain and dynamic interaction when autonomous vehicles e... R Li,Z Zhong,J Chai,... - 《International Journal of Fuzzy System...