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20242026
most citedA Cognitive-Driven Trajectory Prediction Model for Autonomous Driving in Mixed Autonomy Environment

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Planning-Oriented End-to-End Autonomous Driving: Architectures, Evaluation, and Emerging Paradigms

Yanchen Guan, Xingcheng Liu, Bin Rao +7

End-to-end autonomous driving has evolved from camera-to-control regression toward planning-oriented systems that use structured representations, trajectory-level outputs, and incr…

cs.CV2025

Map-World: Masked Action planning and Path-Integral World Model for Autonomous Driving

Bin Hu, Zijian Lu, Haicheng Liao +7

Motion planning for autonomous driving must handle multiple plausible futures while remaining computationally efficient. Recent end-to-end systems and world-model-based planners pr…

cs.RO2024

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…

cs.CV2024

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…

cs.RO2024★ 1 cited

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…

cs.AI2024★ 1 cited

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…

cs.LG2024

Inferring Heterogeneous Treatment Effects of Crashes on Highway Traffic: A Doubly Robust Causal Machine Learning Approach

Shuang Li, Ziyuan Pu, Zhiyong Cui +3

Highway traffic crashes exert a considerable impact on both transportation systems and the economy. In this context, accurate and dependable emergency responses are crucial for eff…