Search Results for author: Diange Yang

Found 18 papers, 3 papers with code

DuMapNet: An End-to-End Vectorization System for City-Scale Lane-Level Map Generation

no code implementations20 Jun 2024 Deguo Xia, Weiming Zhang, Xiyan Liu, Wei zhang, Chenting Gong, Jizhou Huang, Mengmeng Yang, Diange Yang

This paper overcomes these limitations and presents an industrial-grade solution named DuMapNet that outputs standardized, vectorized map elements and their topology in an end-to-end paradigm.

EFFOcc: A Minimal Baseline for EFficient Fusion-based 3D Occupancy Network

1 code implementation11 Jun 2024 Yining Shi, Kun Jiang, Ke Wang, Kangan Qian, Yunlong Wang, Jiusi Li, Tuopu Wen, Mengmeng Yang, Yiliang Xu, Diange Yang

On Occ3D-nuScenes benchmark, EFFOcc has only 18. 4M parameters, and achieves 50. 46 in terms of mean IoU (mIoU), to our knowledge, it is the occnet with minimal parameters compared with related occnets.

3D Object Detection Active Learning +2

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.

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

Grid-Centric Traffic Scenario Perception for Autonomous Driving: A Comprehensive Review

no code implementations2 Mar 2023 Yining Shi, Kun Jiang, Jiusi Li, Zelin Qian, Junze Wen, Mengmeng Yang, Ke Wang, Diange Yang

Given the lack of current surveys for this rapidly expanding field, we present a hierarchically-structured review of grid-centric perception for autonomous vehicles.

Autonomous Driving Sensor Fusion

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

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

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

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

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.

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

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

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