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Scalability in Perception for Autonomous Driving: Waymo Open Dataset [article]

Pei Sun, Henrik Kretzschmar, Xerxes Dotiwalla, Aurelien Chouard, Vijaysai Patnaik, Paul Tsui, James Guo, Yin Zhou, Yuning Chai, Benjamin Caine, Vijay Vasudevan, Wei Han (+13 others)
2020 arXiv   pre-print
Finally, we provide strong baselines for 2D as well as 3D detection and tracking tasks. We further study the effects of dataset size and generalization across geographies on 3D detection methods.  ...  In an effort to help align the research community's contributions with real-world self-driving problems, we introduce a new large scale, high quality, diverse dataset.  ...  Related Work High-quality, large-scale datasets are crucial for autonomous driving research. There have been an increasing number of efforts in releasing datasets to the community in recent years.  ... 
arXiv:1912.04838v7 fatcat:els2cnyc3vhrth2sryinkudidi

The NEOLIX Open Dataset for Autonomous Driving [article]

Lichao Wang, Lanxin Lei, Hongli Song, Weibao Wang
2021 arXiv   pre-print
In this paper,we present the NEOLIX dataset and its applica-tions in the autonomous driving area.  ...  It is expected thatour dataset and related algorithms can support andmotivate researchers for the further developmentof autonomous driving in the field of computer vi-sion.  ...  Waymo Open Dataset [9] is a high-quality multi-mode annotation dataset for autonomous driving.  ... 
arXiv:2011.13528v2 fatcat:ertihxfgxffpxbinqvzqauvxqm

TJ4DRadSet: A 4D Radar Dataset for Autonomous Driving [article]

Lianqing Zheng, Zhixiong Ma, Xichan Zhu, Bin Tan, Sen Li, Kai Long, Weiqi Sun, Sihan Chen, Lu Zhang, Mengyue Wan, Libo Huang, Jie Bai
2022 arXiv   pre-print
We provide a 4D radar-based 3D object detection baseline for our dataset to demonstrate the effectiveness of deep learning methods for 4D radar point clouds.  ...  In this paper, we introduce an autonomous driving dataset named TJ4DRadSet, including multi-modal sensors that are 4D radar, lidar, camera and GNSS, with about 40K frames in total. 7757 frames within 44  ...  RELATED WORK Deep learning technique is playing an increasing role in autonomous driving. It relies on a large amount of high-quality data.  ... 
arXiv:2204.13483v2 fatcat:lbgzfr5ozfgdxmoavrakntf5wa

Machine Learning and Embedded Computing in Advanced Driver Assistance Systems (ADAS)

John E. Ball, Bo Tang
2019 Electronics  
Advanced driver assistance systems (ADAS) are rapidly being developed for autonomous vehicles [...]  ...  We also thank the reviewers for their dedication and suggestions to improve each of the papers.  ...  We finally thank the Editorial Board of MDPI's Electronics for allowing us to be Guest Editors for this Special Issue, and to the Electronics Editorial Office for their guidance, dedication, and support  ... 
doi:10.3390/electronics8070748 fatcat:he6y4kj7z5eufeo3dxrxtdjzzu

Model-free Vehicle Tracking and State Estimation in Point Cloud Sequences [article]

Ziqi Pang, Zhichao Li, Naiyan Wang
2021 arXiv   pre-print
The main purpose for this new setting is to break the strong limitation of the popular "detection and tracking" scheme in multi-object tracking.  ...  Estimating the states of surrounding traffic participants stays at the core of autonomous driving.  ...  In our experiments, leveraging these shapes improves the performance of tracking. This utility of shape aggregation also benefits a series of other applications in autonomous driving.  ... 
arXiv:2103.06028v2 fatcat:6jalpy756nhlbftlste4wieha4

Accurate Mapping and Planning for Autonomous Racing [article]

Leiv Andresen, Adrian Brandemuehl, Alex Hönger, Benson Kuan, Niclas Vödisch, Hermann Blum, Victor Reijgwart, Lukas Bernreiter, Lukas Schaupp, Jen Jen Chung, Mathias Bürki, Martin R. Oswald (+2 others)
2020 arXiv   pre-print
The presented solution combines early fusion of camera and LiDAR data, a layered mapping approach, and a planning approach that uses Bayesian filtering to achieve high-speed driving on unknown race tracks  ...  Furthermore, the new pipeline makes it possible to reliably raise the maximum driving speed in unknown environments from 3~m/s to 12~m/s while still mapping with an acceptable RMSE of 0.29~m.  ...  We also wish to express our appreciation for everyone at the Autonomous Systems Lab of ETH Zürich for their supervision and support throughout this project.  ... 
arXiv:2003.05266v4 fatcat:c6fze2cp2jbgzctpd4e6nki5vi

Autonomous Vehicles Perception (AVP) Using Deep Learning: Modeling, Assessment, Challenges

Hrag-Harout Jebamikyous, Rasha Kashef
2022 IEEE Access  
The detection and tracking of dynamic objects (e.g., bikes, vehicles, and pedestrians) in autonomous driving scenarios are of utmost importance for reliable decision-making and smart navigation of autonomous  ...  Autonomous vehicles use LiDAR and Camera sensors for their perception, as described in the previous section, to accurately detect obstacles and take the appropriate actions for a given scenario to avoid  ... 
doi:10.1109/access.2022.3144407 fatcat:27zpuomnxzbs3gl3ab55a46wru

Sensors and Sensor's Fusion in Autonomous Vehicles

Andrzej Stateczny, Marta Wlodarczyk-Sielicka, Pawel Burdziakowski
2021 Sensors  
Autonomous vehicle navigation has been at the center of several major developments, both in civilian and defense applications [...]  ...  Acknowledgments: We would like to thank all the authors who contributed to the Special Issue and the staff in the editorial office.  ...  Intelligent autonomous vehicles while driving should detect the target very accurately. This is the basis of safe driving.  ... 
doi:10.3390/s21196586 pmid:34640906 fatcat:l46q6lgphbgw7clcd4d7vtksuu

MmWave Radar and Vision Fusion for Object Detection in Autonomous Driving: A Review [article]

Zhiqing Wei, Fengkai Zhang, Shuo Chang, Yangyang Liu, Huici Wu, Zhiyong Feng
2022 arXiv   pre-print
With autonomous driving developing in a booming stage, accurate object detection in complex scenarios attract wide attention to ensure the safety of autonomous driving.  ...  In addition, we introduce three-dimensional(3D) object detection, the fusion of lidar and vision in autonomous driving and multimodal information fusion, which are promising for the future.  ...  . 2) Lidar in Autonomous Driving: As the cost of lidar decreases, autonomous driving vehicles equipped with lidar have become a trend.  ... 
arXiv:2108.03004v3 fatcat:xr5vch2xwbgb3gfnqp2b5cvqee

Exploiting Playbacks in Unsupervised Domain Adaptation for 3D Object Detection [article]

Yurong You, Carlos Andres Diaz-Ruiz, Yan Wang, Wei-Lun Chao, Bharath Hariharan, Mark Campbell, Kilian Q Weinberger
2021 arXiv   pre-print
Self-driving cars must detect other vehicles and pedestrians in 3D to plan safe routes and avoid collisions.  ...  We show, on five autonomous driving datasets, that fine-tuning the object detector on these pseudo-labels substantially reduces the domain gap to new driving environments, yielding drastic improvements  ...  designed to improve detection, i.e., generating higher quality pseudo-labels for self-training.  ... 
arXiv:2103.14198v1 fatcat:bksapc7lcvchnbnfcnfyejptvu

V2X-Sim: A Virtual Collaborative Perception Dataset for Autonomous Driving [article]

Yiming Li, Ziyan An, Zixun Wang, Yiqi Zhong, Siheng Chen, Chen Feng
2022 arXiv   pre-print
Vehicle-to-everything (V2X), which denotes the collaboration between a vehicle and any entity in its surrounding, can fundamentally improve the perception in self-driving systems.  ...  In this work, we present the V2X-Sim dataset, the first public large-scale collaborative perception dataset in autonomous driving.  ...  To fill in the gap in current research, it is an imperative to develop a well-established dataset for collaborative autonomous driving settings.  ... 
arXiv:2202.08449v1 fatcat:zkhc4ibpiralhkxdj22pqpl6u4

Sensor-Based Environmental Perception Technology for Intelligent Vehicles

Biyao Wang, Yi Han, Di Tian, Tian Guan, Haibin Lv
2021 Journal of Sensors  
The functions of the intelligent vehicle assistance system which has been applied to the ground at present are described, and the lane detection, adaptive cruise control (ACC), and autonomous emergency  ...  Target detection, target recognition, and multisensor fusion are analyzed in the optimized part of sensor results.  ...  In summary, object detection and recognition for autonomous driving are of great significance. LiDAR.  ... 
doi:10.1155/2021/8199361 fatcat:hw4m3ikkhfcstl33nxmdcdcxzu

Efficient Online Transfer Learning for 3D Object Classification in Autonomous Driving [article]

Rui Yang, Zhi Yan, Tao Yang, Yassine Ruichek
2021 arXiv   pre-print
Autonomous driving has achieved rapid development over the last few decades, including the machine perception as an important issue of it.  ...  Through experiments, we show that our system is capable of learning a high-performance model for LiDAR-based 3D object classification on-the-fly, which is especially suitable for robotics in-situ deployment  ...  Tixiao Shan for his initial barebone tracker package. UTBM is a member of the Autoware Foundation.  ... 
arXiv:2104.10037v3 fatcat:lqhgp2kdujbdvnb6s3dulsd42y

Sequential Joint Shape and Pose Estimation of Vehicles with Application to Automatic Amodal Segmentation Labeling [article]

Josephine Monica, Wei-Lun Chao, Mark Campbell
2021 arXiv   pre-print
One fundamental challenge in solving this problem is the incomplete sensor signal (e.g., LiDAR scans), especially for faraway or occluded objects.  ...  Shape and pose estimation is a critical perception problem for a self-driving car to fully understand its surrounding environment.  ...  ACKNOWLEDGEMENT The authors would like to acknowledge the support from NSF grant S&AS: INT: Inference, Reasoning and Learning for Robust Autonomous Driving Grant, IIS-1724282.  ... 
arXiv:2109.09840v1 fatcat:3nt3v6q2tvdyhchcijy2n2hoya

PandaSet: Advanced Sensor Suite Dataset for Autonomous Driving [article]

Pengchuan Xiao, Zhenlei Shao, Steven Hao, Zishuo Zhang, Xiaolin Chai, Judy Jiao, Zesong Li, Jian Wu, Kai Sun, Kun Jiang, Yunlong Wang, Diange Yang
2021 arXiv   pre-print
The accelerating development of autonomous driving technology has placed greater demands on obtaining large amounts of high-quality data.  ...  We provide baselines for LiDAR-only 3D object detection, LiDAR-camera fusion 3D object detection and LiDAR point cloud segmentation.  ...  ACKNOWLEDGMENT The dataset analysis and baseline experiments presented in this paper were supported by the National Key Research and Development Program of China (2018YFB0105000).  ... 
arXiv:2112.12610v1 fatcat:ftdbvysktbfrdfrzhbwa5djn5e
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