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20242026
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eess.SY2024

EDRF: Enhanced Driving Risk Field Based on Multimodal Trajectory Prediction and Its Applications

Junkai Jiang, Zeyu Han, Yuning Wang +4

Driving risk assessment is crucial for both autonomous vehicles and human-driven vehicles. The driving risk can be quantified as the product of the probability that an event (such…

cs.RO2024

DenserRadar: A 4D millimeter-wave radar point cloud detector based on dense LiDAR point clouds

Zeyu Han, Junkai Jiang, Xiaokang Ding +4

The 4D millimeter-wave (mmWave) radar, with its robustness in extreme environments, extensive detection range, and capabilities for measuring velocity and elevation, has demonstrat…

cs.RO2024

CSDO: Enhancing Efficiency and Success in Large-Scale Multi-Vehicle Trajectory Planning

Yibin Yang, Shaobing Xu, Xintao Yan +3

This paper presents an efficient algorithm, naming Centralized Searching and Decentralized Optimization (CSDO), to find feasible solution for large-scale Multi-Vehicle Trajectory P…

cs.CV2024

PreGSU-A Generalized Traffic Scene Understanding Model for Autonomous Driving based on Pre-trained Graph Attention Network

Yuning Wang, Zhiyuan Liu, Haotian Lin +3

Scene understanding, defined as learning, extraction, and representation of interactions among traffic elements, is one of the critical challenges toward high-level autonomous driv…

cs.RO2024

A Risk-aware Planning Framework of UGVs in Off-Road Environment

Junkai Jiang, Zhenhua Hu, Zihan Xie +7

Planning module is an essential component of intelligent vehicle study. In this paper, we address the risk-aware planning problem of UGVs through a global-local planning framework…