AdapTraj: A multi-source domain generalization framework for multi-agent trajectory prediction
Multi-agent trajectory prediction, as a critical task in modeling complex interactions of objects
in dynamic systems, has attracted significant research attention in recent years. Despite the …
in dynamic systems, has attracted significant research attention in recent years. Despite the …
PreCLN: Pretrained-based contrastive learning network for vehicle trajectory prediction
Trajectory prediction of vehicles is of great importance to various smart city applications
ranging from transportation scheduling, vehicle navigation, to location-based …
ranging from transportation scheduling, vehicle navigation, to location-based …
Graph Neural Processes for Spatio-Temporal Extrapolation
We study the task of spatio-temporal extrapolation that generates data at target locations
from surrounding contexts in a graph. This task is crucial as sensors that collect data are …
from surrounding contexts in a graph. This task is crucial as sensors that collect data are …
Multitype highway mobility analytics for efficient learning model design: A case of station traffic prediction
The provincial highway transportation system supports substantial cross-city transitions of
people and logistics, where the prediction tasks in terms of station/road traffic, urban …
people and logistics, where the prediction tasks in terms of station/road traffic, urban …
STTraj2Vec: A spatio-temporal trajectory representation learning approach
J Zhu, X Niu, F Li, Y Wang, P Fournier-Viger… - Knowledge-Based …, 2024 - Elsevier
Computing trajectory similarity plays a critical role in various spatio-temporal applications
that involve trajectory analysis. In recent years, trajectory representation learning has been …
that involve trajectory analysis. In recent years, trajectory representation learning has been …
F3VeTrac: Enabling Fine-grained, Fully-road-covered, and Fully-individual penetrative Vehicle Trajectory Recovery
Obtaining urban-scale vehicle trajectories is essential to understand urban mobility and
benefits various downstream applications. The mobility knowledge obtained from existing …
benefits various downstream applications. The mobility knowledge obtained from existing …
RouteKG: A knowledge graph-based framework for route prediction on road networks
Short-term route prediction on road networks allows us to anticipate the future trajectories of
road users, enabling a plethora of intelligent transportation applications such as dynamic …
road users, enabling a plethora of intelligent transportation applications such as dynamic …
궤적데이터마이닝연구동향: 응용분야와분석방법론을중심으로
김지연, 이도현, 이지윤, 조주연, 강영옥 - 한국지도학회지, 2022 - dbpia.co.kr
최근 GPS 에 기반한 위치 수집 기술의 발전과 스마트폰과 같은 GPS 를 탑재한 디바이스의
폭발적인 증가로 사람, 차량, 선박, 항공체와 같은 움직이는 물체의 지리적 위치에 대한 엄청난 …
폭발적인 증가로 사람, 차량, 선박, 항공체와 같은 움직이는 물체의 지리적 위치에 대한 엄청난 …
Efficient trajectory compression and range query processing
Nowadays, there are ubiquitousness of GPS sensors in various devices collecting,
transmitting and storing tremendous trajectory data. However, such an unprecedented scale …
transmitting and storing tremendous trajectory data. However, such an unprecedented scale …
Predicting Next Whereabouts Using Deep Learning
AP Galarreta, H Alatrista-Salas… - … Conference on Modeling …, 2023 - Springer
Trajectory prediction is a key task in the study of human mobility. This task can be done by
considering a sequence of GPS locations and using different mechanisms to predict the …
considering a sequence of GPS locations and using different mechanisms to predict the …