自动驾驶技术的前沿研究涵盖了多个方面,包括感知、决策与规划、传感器融合、仿真与测试、安全性与可靠性等。以下是一些近期关于自动驾驶技术的前沿论文和研究方向,可以通过查找相关的学术数据库和会议论文来进一步了解。
- **感知与视觉识别**:
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"PointPillars: Fast Encoders for Object Detection from Point Clouds" - Alex H. Lang et al., CVPR 2019.
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"CenterNet: Keypoint Triplets for Object Detection" - Xingyi Zhou et al., CVPR 2019.
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"PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud" - Shi et al., CVPR 2019.
- **决策与规划**:
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"Motion Planning for Automated Driving on Unstructured Road Scenarios using Deep Reinforcement Learning" - Yoo et al., IEEE IV 2020.
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"End-to-End Learning of Driving Models from Large-Scale Video Datasets" - Codevilla et al., CoRL 2018.
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"Safe Reinforcement Learning for Autonomous Driving" - Yang et al., NeurIPS 2018.
- **传感器融合与感知**:
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"Probabilistic Multisensor Fusion for Safe Urban Driving" - Engelhard et al., IEEE Transactions on Intelligent Transportation Systems, 2019.
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"Deep Multi-Sensor Fusion for Object Detection in Autonomous Vehicles" - Chen et al., IEEE Intelligent Vehicles Symposium, 2020.
- **仿真与测试**:
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"ScenarioNet: A Large-Scale Benchmark for Modular Autonomous Driving" - Devarakonda et al., arXiv:2105.09685, 2021.
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"Development and Validation of Autonomous Vehicle Testing Methodologies" - Barkan et al., IEEE Transactions on Intelligent Vehicles, 2020.
- **安全性与可靠性**:
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"Safety-Critical Control for Autonomous Vehicles Using Convex Optimization" - Li et al., IEEE Transactions on Control Systems Technology, 2020.
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"A Comprehensive Study on the Deployment of Self-Driving Cars: from Perception and Control to Safety-Critical Challenges" - Wu et al., IEEE Transactions on Intelligent Transportation Systems, 2020.
这些论文代表了自动驾驶技术在不同方面的最新研究进展和应用案例。你可以通过访问IEEE Xplore、ACM Digital Library、Google Scholar等学术数据库,或者关注顶级会议如CVPR、ICRA、IV等,深入了解