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Omniverse-OpenDS: Enabling Agile Developments for Complex Driving Scenarios via Reconfigurable Abstractions

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HCI in Mobility, Transport, and Automotive Systems (HCII 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13335))

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Abstract

We present Omniverse, a set of configurable abstractions for efficient developments of complex driving events during simulated driving scenarios. The goal of Omniverse is to identify the inefficiency of existing scenario implementations and provide an alternative design for ease-of-implementations for simulated driving events. We first investigate the standard code base of driving scenarios and abstract their overlapped building blocks through mathematical models. Then, we design and implement a set of flexible and configurable abstractions as an external library, to allow further developments and adaptions for more generalized cases. Finally, we validate the correctness and examine the effectiveness of Omniverse through standard driving scenarios’ implementations, and the results show that Omniverse can (1) save 42.7% development time, averaged across all participants; and (2) greatly improve the overall user experience via significantly improved readability and extend-ability of codes. The whole library of Omniverse is online at https://github.com/unnc-ucc/Omniverse-OpenDS.

Z. Song and Y. Duan—Equal contributions.

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Acknowledgements

We thank anonymous reviewers in HCI’22 for their valuable feedback. We thank for all members of User-Centric Computing Group at the University of Nottingham Ningbo China for the stimulating environment. This work was started as Zilin Song’s internship and undergraduate thesis at the University of Nottingham Ningbo China.

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Authors and Affiliations

  1. User-Centric Computing Group, University of Nottingham, Ningbo, China

    Zilin Song, Yicun Duan, Wangkai Jin, Shuchang Huang, Shuolei Wang & Xiangjun Peng

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  1. Zilin Song
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  2. Yicun Duan
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  3. Wangkai Jin
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  4. Shuchang Huang
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  5. Shuolei Wang
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  6. Xiangjun Peng
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Correspondence to Xiangjun Peng .

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  1. Technische Universität Ilmenau, Ilmenau, Germany

    Heidi Krömker

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Song, Z., Duan, Y., Jin, W., Huang, S., Wang, S., Peng, X. (2022). Omniverse-OpenDS: Enabling Agile Developments for Complex Driving Scenarios via Reconfigurable Abstractions. In: Krömker, H. (eds) HCI in Mobility, Transport, and Automotive Systems. HCII 2022. Lecture Notes in Computer Science, vol 13335. Springer, Cham. https://doi.org/10.1007/978-3-031-04987-3_5

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  • DOI: https://doi.org/10.1007/978-3-031-04987-3_5

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