78 citations · 88 across the 39 of their papers we have counts for
12 papers · 1 filter
DEMO: A Dynamics-Enhanced Learning Model for Multi-Horizon Trajectory Prediction in Autonomous Vehicles
Chengyue Wang, Haicheng Liao, Kaiqun Zhu +2
Autonomous vehicles (AVs) rely on accurate trajectory prediction of surrounding vehicles to ensure the safety of both passengers and other road users. Trajectory prediction spans b…
NEST: A Neuromodulated Small-world Hypergraph Trajectory Prediction Model for Autonomous Driving
Chengyue Wang, Haicheng Liao, Bonan Wang +6
Accurate trajectory prediction is essential for the safety and efficiency of autonomous driving. Traditional models often struggle with real-time processing, capturing non-linearit…
DRIVE: Dependable Robust Interpretable Visionary Ensemble Framework in Autonomous Driving
Songning Lai, Tianlang Xue, Hongru Xiao +7
Recent advancements in autonomous driving have seen a paradigm shift towards end-to-end learning paradigms, which map sensory inputs directly to driving actions, thereby enhancing…
Real-time Accident Anticipation for Autonomous Driving Through Monocular Depth-Enhanced 3D Modeling
Haicheng Liao, Yongkang Li, Chengyue Wang +7
The primary goal of traffic accident anticipation is to foresee potential accidents in real time using dashcam videos, a task that is pivotal for enhancing the safety and reliabili…
When, Where, and What? A Novel Benchmark for Accident Anticipation and Localization with Large Language Models
Haicheng Liao, Yongkang Li, Chengyue Wang +6
As autonomous driving systems increasingly become part of daily transportation, the ability to accurately anticipate and mitigate potential traffic accidents is paramount. Traditio…
CRASH: Crash Recognition and Anticipation System Harnessing with Context-Aware and Temporal Focus Attentions
Haicheng Liao, Haoyu Sun, Huanming Shen +6
Accurately and promptly predicting accidents among surrounding traffic agents from camera footage is crucial for the safety of autonomous vehicles (AVs). This task presents substan…
Characterized Diffusion and Spatial-Temporal Interaction Network for Trajectory Prediction in Autonomous Driving
Haicheng Liao, Xuelin Li, Yongkang Li +7
Trajectory prediction is a cornerstone in autonomous driving (AD), playing a critical role in enabling vehicles to navigate safely and efficiently in dynamic environments. To addre…
MFTraj: Map-Free, Behavior-Driven Trajectory Prediction for Autonomous Driving
Haicheng Liao, Zhenning Li, Chengyue Wang +5
This paper introduces a trajectory prediction model tailored for autonomous driving, focusing on capturing complex interactions in dynamic traffic scenarios without reliance on hig…
A Cognitive-Driven Trajectory Prediction Model for Autonomous Driving in Mixed Autonomy Environment
Haicheng Liao, Zhenning Li, Chengyue Wang +6
As autonomous driving technology progresses, the need for precise trajectory prediction models becomes paramount. This paper introduces an innovative model that infuses cognitive i…
Human Observation-Inspired Trajectory Prediction for Autonomous Driving in Mixed-Autonomy Traffic Environments
Haicheng Liao, Shangqian Liu, Yongkang Li +5
In the burgeoning field of autonomous vehicles (AVs), trajectory prediction remains a formidable challenge, especially in mixed autonomy environments. Traditional approaches often…
World Models for Autonomous Driving: An Initial Survey
Yanchen Guan, Haicheng Liao, Zhenning Li +5
In the rapidly evolving landscape of autonomous driving, the capability to accurately predict future events and assess their implications is paramount for both safety and efficienc…
A Cognitive-Based Trajectory Prediction Approach for Autonomous Driving
Haicheng Liao, Yongkang Li, Zhenning Li +4
In autonomous vehicle (AV) technology, the ability to accurately predict the movements of surrounding vehicles is paramount for ensuring safety and operational efficiency. Incorpor…