MetaScenario: A Framework for Driving Scenario Data Description, Storage and Indexing-Reference-Cited by-同舟云学术

MetaScenario: A Framework for Driving Scenario Data Description, Storage and Indexing

Published:2023-02 Issue:2 Volume:8 Page:1156-1175
ISSN:2379-8904
Container-title:IEEE Transactions on Intelligent Vehicles
language:
Short-container-title:IEEE Trans. Intell. Veh.

Author:

Chang Cheng¹^ORCID,Cao Dongpu²^ORCID,Chen Long³^ORCID,Su Kui⁴,Su Kuifeng⁵,Su Yuelong⁶,Wang Fei-Yue⁷^ORCID,Wang Jue⁸,Wang Ping⁸^ORCID,Wei Junqing⁹,Wu Gansha¹⁰^ORCID,Wu Xiangbin¹¹^ORCID,Xu Huile¹²,Zheng Nanning¹³^ORCID,Li Li¹⁴^ORCID

Affiliation:

1. Department of Automation, Tsinghua University, Beijing, China

2. Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON, Canada

3. Waytous Inc., Beijing, China

4. Alibaba DAMO Academy Autonomous Driving Lab, Hangzhou, China

5. Tencent Autonomous Driving, Beijing, China

6. Traffic Management Solution Division, AutoNavi Software Company, Beijing, China

7. State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China

8. Peking University, Beijing, China

9. DiDi Autonomous Driving Company, Beijing, China

10. Uisee Technology (Beijing) Company, Ltd., Beijing, China

11. Intel Labs China, Beijing, China

12. Momenta and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China

13. Institute of Artificial Intelligence and Robotics (IAIR), Xi'an Jiaotong University, Xi'an, China

14. Department of Automation, BNRist, Tsinghua University, Beijing, China

Funder

National Key Research and Development Program of China

Science and Technology Innovation Committee of Shenzhen

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/7274857/10076483/09925130.pdf?arnumber=9925130

Reference87 articles.

1. Scalability in Perception for Autonomous Driving: Waymo Open Dataset

2. CommonRoad: Composable benchmarks for motion planning on roads

3. One thousand and one hours: Self-driving motion prediction dataset;houston;Proc Conf Robot Learn,0

4. GeoScenario: An Open DSL for Autonomous Driving Scenario Representation

5. Recent advances in multisensor multitarget tracking using random finite set

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