Roadside Infrastructure Support for Urban Automated Driving
Author:
Affiliation:
1. Faculty of Electrical Engineering, Augsburg University of Applied Sciences, Augsburg, Germany
2. Siemens Mobility GmbH, Munich, Germany
3. Chair of Traffic Engineering and Control, Technical University of Munich, Munich, Germany
Funder
Siemens Mobility GmbH
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/10271405/10141533.pdf?arnumber=10141533
Reference37 articles.
1. An Open Approach to Autonomous Vehicles
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3. Cooperative RADAR Sensors for the Digital Test Field A9 (KoRA9) – Algorithmic Recap and Lessons Learned
4. On the human control of vehicles: an experimental study of acceleration
5. Networked Roadside Perception Units for Autonomous Driving
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1. Motion Planner for Automated Vehicle on Unstructured Roads;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02
2. Threshold Analysis of Static and Dynamic Occlusion in Urban Areas: A Connected Automated Vehicle Perspective;Transportation Research Record: Journal of the Transportation Research Board;2024-02-25
3. Transfer-Learning of a LiDAR Detection Algorithm Pre-Trained on Autonomous Driving Data for Roadside Infrastructure Application;2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC);2023-09-24
4. Intelligent Transportation Systems Using Roadside Infrastructure: A Literature Survey;IEEE Transactions on Intelligent Transportation Systems;2023
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