Search Results for author: Diange Yang

Found 14 papers, 2 papers with code

Extraction of V2V Encountering Scenarios from Naturalistic Driving Database

no code implementations27 Feb 2018 Zhaobin Mo, Sisi Li, Diange Yang, Ding Zhao

To overcome this problem, we extract naturalistic V2V encounters data from the database, and then separate the primary vehicle encounter category by clustering.

Clustering Dynamic Time Warping

Driving-Policy Adaptive Safeguard for Autonomous Vehicles Using Reinforcement Learning

no code implementations2 Dec 2020 Zhong Cao, Shaobing Xu, Songan Zhang, Huei Peng, Diange Yang

This paper proposes a driving-policy adaptive safeguard (DPAS) design, including a collision avoidance strategy and an activation function.

Autonomous Vehicles Collision Avoidance +2

Hybrid Car-Following Strategy based on Deep Deterministic Policy Gradient and Cooperative Adaptive Cruise Control

no code implementations24 Feb 2021 Ruidong Yan, Rui Jiang, Bin Jia, Jin Huang, Diange Yang

Deep deterministic policy gradient (DDPG)-based car-following strategy can break through the constraints of the differential equation model due to the ability of exploration on complex environments.

BE-STI: Spatial-Temporal Integrated Network for Class-Agnostic Motion Prediction With Bidirectional Enhancement

no code implementations CVPR 2022 Yunlong Wang, Hongyu Pan, Jun Zhu, Yu-Huan Wu, Xin Zhan, Kun Jiang, Diange Yang

In this paper, we propose a novel Spatial-Temporal Integrated network with Bidirectional Enhancement, BE-STI, to improve the temporal motion prediction performance by spatial semantic features, which points out an efficient way to combine semantic segmentation and motion prediction.

Autonomous Driving motion prediction +1

SRCN3D: Sparse R-CNN 3D for Compact Convolutional Multi-View 3D Object Detection and Tracking

2 code implementations29 Jun 2022 Yining Shi, Jingyan Shen, Yifan Sun, Yunlong Wang, Jiaxin Li, Shiqi Sun, Kun Jiang, Diange Yang

Our novel sparse feature sampling module only utilizes local 2D region of interest (RoI) features calculated by the projection of 3D query boxes for further box refinement, leading to a fully-convolutional and deployment-friendly pipeline.

3D Multi-Object Tracking 3D Object Detection +4

Long-Tail Prediction Uncertainty Aware Trajectory Planning for Self-driving Vehicles

no code implementations2 Jul 2022 Weitao Zhou, Zhong Cao, Yunkang Xu, Nanshan Deng, Xiaoyu Liu, Kun Jiang, Diange Yang

To this end, this work proposes a trajectory planner to consider the prediction model uncertainty arising from insufficient data for safer performance.

Autonomous Driving Trajectory Planning

Privacy of Autonomous Vehicles: Risks, Protection Methods, and Future Directions

no code implementations8 Sep 2022 Chulin Xie, Zhong Cao, Yunhui Long, Diange Yang, Ding Zhao, Bo Li

However, training AVs usually requires a large amount of training data collected from different driving environments (e. g., cities) as well as different types of personal information (e. g., working hours and routes).

Autonomous Vehicles

FusionMotion: Multi-Sensor Asynchronous Fusion for Continuous Occupancy Prediction via Neural-ODE

1 code implementation19 Feb 2023 Yining Shi, Kun Jiang, Ke Wang, Jiusi Li, Yunlong Wang, Diange Yang

This paper investigates multi-sensor spatio-temporal fusion strategies for continuous occupancy prediction in a systematic manner.

Motion Planning

Poses as Queries: Image-to-LiDAR Map Localization with Transformers

no code implementations7 May 2023 Jinyu Miao, Kun Jiang, Yunlong Wang, Tuopu Wen, Zhongyang Xiao, Zheng Fu, Mengmeng Yang, Maolin Liu, Diange Yang

High-precision vehicle localization with commercial setups is a crucial technique for high-level autonomous driving tasks.

Autonomous Driving

Dynamically Conservative Self-Driving Planner for Long-Tail Cases

no code implementations12 May 2023 Weitao Zhou, Zhong Cao, Nanshan Deng, Xiaoyu Liu, Kun Jiang, Diange Yang

In this way, the DCP is designed to automatically adjust to be more conservative in low-confidence "long-tail" cases while keeping efficient otherwise.

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