ADBench: benchmarking autonomous driving systems

Abstract

Driven by the improvements in a variety of domains, autonomous driving is becoming a reality and today, industry aims at moving toward fully autonomous vehicles. High-tech chip manufacturers are designing high-performance and energy-efficient platforms in accordance with safety standard requirements. However, the software used to implement advanced functionalities in autonomous vehicles challenges real-time constraints on those platforms. Hence, there is a clear need for industry-level autonomous driving benchmarks to evaluate platforms and systems. In this paper, we propose ADBench, a benchmarking approach and benchmark suite for state-of-the-art autonomous driving platforms, in accordance with the key modules, structural design and functions of AD systems, building on several industry-level autonomous driving systems. The use of standard benchmarks facilitates the design, verification and validation process of autonomous systems.

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    A bag is a file format in ROS for storing ROS message data. They are typically created by a tool like rosbag, which subscribes to one or more ROS topics, and stores the serialized message data in a file as it is received. These bag files can also be played back in ROS to the same topics they were recorded from, or even remapped to new topics.

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Acknowledgements

This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under Grant TIN2015-65316-P, the SuPerCom European Research Council (ERC) project under the European Union’s Horizon 2020 research and innovation programme (Grant Agreement No. 772773), and the HiPEAC Network of Excellence.

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Correspondence to Hamid Tabani.

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Tabani, H., Pujol, R., Alcon, M. et al. ADBench: benchmarking autonomous driving systems. Computing (2021). https://doi.org/10.1007/s00607-021-00975-1

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Keywords

  • Benchmarking
  • Autonomous driving systems
  • Safety-critical systems

Mathematics Subject Classification

  • 68M20
  • 68M15