research-article

Enhancing the realism of autonomous driving simulation with real-time co-simulation

Authors:

Shaukat AliAuthors Info & Claims

MODELS '22: Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings

Pages 659 - 667

https://doi.org/10.1145/3550356.3561558

Published: 09 November 2022 Publication History

Abstract

Autonomous driving simulators are commonly used to develop autonomous driving systems (ADS) since they provide the flexibility to experiment with scenarios that could even be dangerous in a real setting. This flexibility, however, comes with the possibility of experimenting with unrealistic scenarios. To this end, we present an initial co-simulation framework integrating OpenModelica and CARLA to enable real-time communication between them. As a proof of concept, we experimented with two Modelica models (air resistance and energy consumption). We connected the two models with CARLA to enable real-time communication between them to ensure the realism of scenarios in addition to connecting CARLA with OpenWeather through its API to access real weather conditions. We conducted experiments with a specific virtual electric vehicle (Tesla Model 3) running on the Town06 map in CARLA. Results provide preliminary evidence that co-simulation with Modelica models improved the realism of the virtual vehicle in CARLA.

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Cited By

Zhao HMeng MLi XXu JLi LGalland S(2024)A survey of autonomous driving frameworks and simulatorsAdvanced Engineering Informatics10.1016/j.aei.2024.10285062(102850)Online publication date: Oct-2024
https://doi.org/10.1016/j.aei.2024.102850
Ali SArcaini PArrieta A(2024)Foundation Models for the Digital Twins Creation of Cyber-Physical SystemsLeveraging Applications of Formal Methods, Verification and Validation. Application Areas10.1007/978-3-031-75390-9_2(9-26)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1007/978-3-031-75390-9_2
Lu CYue TAli S(2023)DeepScenario: An Open Driving Scenario Dataset for Autonomous Driving System Testing2023 IEEE/ACM 20th International Conference on Mining Software Repositories (MSR)10.1109/MSR59073.2023.00020(52-56)Online publication date: May-2023
https://doi.org/10.1109/MSR59073.2023.00020
Show More Cited By

Index Terms

Enhancing the realism of autonomous driving simulation with real-time co-simulation
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Embedded systems
2. Computing methodologies
  1. Artificial intelligence
  2. Modeling and simulation
    1. Simulation support systems

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cover image ACM Conferences

MODELS '22: Proceedings of the 25th International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings

October 2022

1003 pages

ISBN:9781450394673

DOI:10.1145/3550356

Conference Chairs:
Thomas Kühn
Karlsruhe Institute of Technology, Germany
,
Vasco Sousa
University of Montréal, Canada

Copyright © 2022 ACM.

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SIGSOFT: ACM Special Interest Group on Software Engineering

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Univ. of Montreal: University of Montreal
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 November 2022

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Co-evolver project
National Natural Science Foundation of China
Co-tester project

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MODELS '22

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SIGSOFT

MODELS '22: ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems

October 23 - 28, 2022

Quebec, Montreal, Canada

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Overall Acceptance Rate 144 of 506 submissions, 28%

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Cited By

Zhao HMeng MLi XXu JLi LGalland S(2024)A survey of autonomous driving frameworks and simulatorsAdvanced Engineering Informatics10.1016/j.aei.2024.10285062(102850)Online publication date: Oct-2024
https://doi.org/10.1016/j.aei.2024.102850
Ali SArcaini PArrieta A(2024)Foundation Models for the Digital Twins Creation of Cyber-Physical SystemsLeveraging Applications of Formal Methods, Verification and Validation. Application Areas10.1007/978-3-031-75390-9_2(9-26)Online publication date: 27-Oct-2024
https://dl.acm.org/doi/10.1007/978-3-031-75390-9_2
Lu CYue TAli S(2023)DeepScenario: An Open Driving Scenario Dataset for Autonomous Driving System Testing2023 IEEE/ACM 20th International Conference on Mining Software Repositories (MSR)10.1109/MSR59073.2023.00020(52-56)Online publication date: May-2023
https://doi.org/10.1109/MSR59073.2023.00020
Wang TTan CHuang LShi YYue THuang Z(2023)Simplexity testbedComputers in Industry10.1016/j.compind.2022.103804145:COnline publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1016/j.compind.2022.103804

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