Accurate flight trajectory prediction is a crucial and challenging task in air traffic control, especially for maneuver operations. Modern data-driven methods are typically formulated as a time series forecasting task and fail to retain high accuracy. Meantime, as the primary modeling method for time...
With the rapid advancement of autonomous driving technology, the accurate prediction of vehicle trajectories has become a research hotspot. In order to acc... Q Luo - 《Sustainability》 被引量: 0发表: 2024年 A Review of Trajectory Prediction Methods for the Vulnerable Road User Hence, this pape...
it can be seen that except for Adaboost, MLP, and SVR, most algorithms can perform predictions well. Among them, DecisionTree has obvious errors at about 150 and 230 prediction points. However, compared
Authors in [14] provided a comprehensive demonstration of the use of trajectory data to discover human behavior (Human mobility pattern, anomalous event detection..) travel pattern (Destination Prediction, Route Discovery..) and urban planning. A trajectory is considered as a series of points that...
and surveys the state-of-the-art in the context of future location and trajectory prediction. We provide an extensive review of over 50 works, also proposing a novel taxonomy of predictive algorithms over moving objects. We also list the properties of several real datasets used in the past ...
Trajectory prediction is imperative in the operation of autonomous vehicles because it aids in understanding the surrounding environment through perception fusion of multiple sensors and high-accuracy localisation. Furthermore, the output of algorithms used for trajectory prediction is used in decision making...
1.2 Literature review The majority of previous studies on AI prediction models have focused on improving prediction outputs. These outputs are evaluated based on either classification accuracy or regression error. Large-scale training, validation, and testing data are required to train and assess the ...
We model the interactions between different road agents using a novel LSTM-CNN hybrid network for trajectory prediction. In particular, we take into account heterogeneous interactions that implicitly account for the varying shapes, dynamics, and behaviors of different road agents. In addition, we ...
Human Motion Trajectory Prediction: A Survey, 2019. [paper] A literature review on the prediction of pedestrian behavior in urban scenarios, ITSC 2018. [paper] Survey on Vision-Based Path Prediction. [paper] Autonomous vehicles that interact with pedestrians: A survey of theory and practice. [pa...
1B). In addition, the trajectories of the TyG index in each participant over the exposure period (2006–2010) were characterized, to assess their utility for the prediction of the risk of HF in the general population during 2010–2020. The study was conducted in accordance with the ...