most citedReCoG: A Deep Learning Framework with Heterogeneous Graph for Interaction-Aware Trajectory Prediction

40 citations · 70 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO20214 cited

Multi-modal Motion Prediction with Transformer-based Neural Network for Autonomous Driving

Zhiyu Huang, Xiaoyu Mo, Chen Lv

Predicting the behaviors of other agents on the road is critical for autonomous driving to ensure safety and efficiency. However, the challenging part is how to represent the socia…

cs.RO20213 cited

Graph and Recurrent Neural Network-based Vehicle Trajectory Prediction For Highway Driving

Xiaoyu Mo, Yang Xing, Chen Lv

Integrating trajectory prediction to the decision-making and planning modules of modular autonomous driving systems is expected to improve the safety and efficiency of self-driving…

cs.RO202117 cited

Heterogeneous Edge-Enhanced Graph Attention Network For Multi-Agent Trajectory Prediction

Xiaoyu Mo, Yang Xing, Chen Lv

Simultaneous trajectory prediction for multiple heterogeneous traffic participants is essential for the safe and efficient operation of connected automated vehicles under complex d…

cs.RO202040 cited

ReCoG: A Deep Learning Framework with Heterogeneous Graph for Interaction-Aware Trajectory Prediction

Xiaoyu Mo, Yang Xing, Chen Lv

Predicting the future trajectory of surrounding vehicles is essential for the navigation of autonomous vehicles in complex real-world driving scenarios. It is challenging as a vehi…

cs.RO20206 cited

Interaction-Aware Trajectory Prediction of Connected Vehicles using CNN-LSTM Networks

Xiaoyu Mo, Yang Xing, Chen Lv

Predicting the future trajectory of a surrounding vehicle in congested traffic is one of the basic abilities of an autonomous vehicle. In congestion, a vehicle's future movement is…