Vehicle trajectory clustering based on dynamic representation learning of internet of vehicles
With the widely used Internet of Things, 5G, and smart city technologies, we are able to
acquire a variety of vehicle trajectory data. These trajectory data are of great significance …
acquire a variety of vehicle trajectory data. These trajectory data are of great significance …
RMGen: A tri-layer vehicular trajectory data generation model exploring urban region division and mobility pattern
As an important branch of the Internet of Things (IoT), the Internet of Vehicles (IoV) has
attracted extensive attention in the research field. To deeply study the IoV and build a …
attracted extensive attention in the research field. To deeply study the IoV and build a …
Region representation learning via mobility flow
Increasing amount of urban data are being accumulated and released to public; this enables
us to study the urban dynamics and address urban issues such as crime, traffic, and quality …
us to study the urban dynamics and address urban issues such as crime, traffic, and quality …
Vehicle trajectory prediction based on intention-aware non-autoregressive transformer with multi-attention learning for Internet of Vehicles
X Chen, H Zhang, F Zhao, Y Cai… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As a core function of autonomous driving (AD) and the Internet of Vehicles (IoV), accurately
predicting the trajectory of vehicles can significantly improve traffic safety and reduce crash …
predicting the trajectory of vehicles can significantly improve traffic safety and reduce crash …
Group vehicle trajectory prediction with global spatio-temporal graph
D Xu, X Shang, Y Liu, H Peng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Vehicle trajectory prediction is a challenging problem in the field of autonomous driving,
which is of great significance to the safety of autonomous driving and traffic roads. In view of …
which is of great significance to the safety of autonomous driving and traffic roads. In view of …
Probabilistic vehicle trajectory prediction over occupancy grid map via recurrent neural network
In this paper, we propose an efficient vehicle trajectory prediction framework based on
recurrent neural network. Basically, the characteristic of the vehicle's trajectory is different …
recurrent neural network. Basically, the characteristic of the vehicle's trajectory is different …
Sequence-to-sequence prediction of vehicle trajectory via LSTM encoder-decoder architecture
In this paper, we propose a deep learning based vehicle trajectory prediction technique
which can generate the future trajectory sequence of surrounding vehicles in real time. We …
which can generate the future trajectory sequence of surrounding vehicles in real time. We …
Interaction-aware trajectory prediction of connected vehicles using CNN-LSTM networks
Predicting the future trajectory of a surrounding vehicle in congested traffic is one of the
necessary abilities of an autonomous vehicle. In congestion, a vehicle's future movement is …
necessary abilities of an autonomous vehicle. In congestion, a vehicle's future movement is …
Machine learning-based vehicle trajectory prediction using v2v communications and on-board sensors
Predicting the trajectories of surrounding vehicles is important to avoid or mitigate collision
with traffic participants. However, due to limited past information and the uncertainty in future …
with traffic participants. However, due to limited past information and the uncertainty in future …
Trafficpredict: Trajectory prediction for heterogeneous traffic-agents
To safely and efficiently navigate in complex urban traffic, autonomous vehicles must make
responsible predictions in relation to surrounding traffic-agents (vehicles, bicycles …
responsible predictions in relation to surrounding traffic-agents (vehicles, bicycles …