Digital Twins for Autonomous Driving: A Comprehensive Implementation and Demonstration (2401.08653v1)
Abstract: The concept of a digital twin (DT) plays a pivotal role in the ongoing digital transformation and has achieved significant strides for various wireless applications in recent years. In particular, the field of autonomous vehicles is a domain that is ripe for exploiting the concept of DT. Nevertheless, there are many challenges that include holistic consideration and integration of hardware, software, communication methods, and collaboration of edge/cloud computing. In this paper, an end-to-end (E2E) real-world smart mobility DT is designed and implemented for the purpose of autonomous driving. The proposed system utilizes roadside units (RSUs) and edge computing to capture real-world traffic information, which is then processed in the cloud to create a DT model. This DT model is then exploited to enable route planning services for the autonomous vehicle to avoid heavy traffic. Real-world experimental results show that the system reliability can reach 99.53% while achieving a latency that is 3.36% below the 3GPP recommended value of 100 ms for autonomous driving. These results clearly validate the effectiveness of the system according to practical 3GPP standards for sensor and state map sharing (SSMS) and information sharing.
- S. Nižetić, P. Šolić, D. L.-d.-I. Gonzalez-De, and L. Patrono, “Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future,” Journal of Cleaner Production, vol. 274, p. 122877, 2020.
- Z. Wang, R. Gupta, K. Han, H. Wang, A. Ganlath, N. Ammar, and P. Tiwari, Prashant, “Mobility digital twin: Concept, architecture, case study, and future challenges,” IEEE Internet of Things Journal, vol. 9, no. 18, pp. 17 452–17 467, 2022.
- O. Hashash, C. Chaccour, W. Saad, T. Yu, K. Sakaguchi, and M. Debbah, “The seven worlds and experiences of the wireless metaverse: Challenges and opportunities,” arXiv preprint arXiv:2304.10282, 2023.
- H. X. Nguyen, R. Trestian, D. To, and M. Tatipamula, “Digital twin for 5G and beyond,” IEEE Communications Magazine, vol. 59, no. 2, pp. 10–15, 2021.
- S. Almeaibed, S. Al-Rubaye, A. Tsourdos, and N. P. Avdelidis, “Digital twin analysis to promote safety and security in autonomous vehicles,” IEEE Communications Standards Magazine, vol. 5, no. 1, pp. 40–46, 2021.
- O. Hashash, C. Chaccour, and W. Saad, “Edge continual learning for dynamic digital twins over wireless networks,” in Proc. of IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC), Oulu, Finland, Jul. 2022, pp. 1–5.
- O. Veledar, V. Damjanovic-Behrendt, and G. Macher, “Digital twins for dependability improvement of autonomous driving,” in Proc. of European Conference on software process improvement, Cham, Switzerlad: Springer, 2019, pp. 415–426.
- C. Schwarz and Z. Wang, “The role of digital twins in connected and automated vehicles,” IEEE Intelligent Transportation Systems Magazine, vol. 14, no. 6, pp. 41–51, 2022.
- Y. Hui, Q. Wang, N. Cheng, R. Chen, X. Xiao, and T. H. Luan, “Time or reward: Digital-twin enabled personalized vehicle path planning,” in Proc. of IEEE Global Communications Conference (GLOBECOM), Madrid, Spain, Feb. 2021, pp. 1–6.
- L. Kloeker, A. Kloeker, F. Thomsen, A. Erraji, and L. Eckstein, “How to build a highly accurate digital twin–intelligent infrastructure in the corridor for new mobility-accord,” in Proc. of 30th Aachen Colloquium Sustainable Mobility 2021, vol. 5, Oct. 2021, pp. 651–680.
- V. Tihanyi, A. and Rövid, V. Remeli, Z. Vincze, M. Csonthó, Z. Pethő, M. Szalai, B. Varga, A. Khalil, and Z. Szalay, “Towards cooperative perception services for ITS: Digital twin in the automotive edge cloud,” Energies, vol. 14, no. 18, p. 5930, 2021.
- R. Sell, E. Malayjerdi, M. Malayjerdi, and B. C. Baykara, “Safety toolkit for automated vehicle shuttle-practical implementation of digital twin,” in Proc. of International Conference on Connected Vehicle and Expo (ICCVE), Lakeland, FL, USA, Mar. 2022, pp. 1–6.
- H. Xu, A. Berres, S. B. Yoginath, H. Sorensen, P. J. Nugent, J. Severino, S.A. Tennille, A. Moore, W. Jones, and J. Sanyal, “Smart mobility in the cloud: Enabling real-time situational awareness and cyber-physical control through a digital twin for traffic,” IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 3, pp. 3145–3156, 2023.
- X. Liao, Z. Wang, X. Zhao, K. Han, P. Tiwari, M. J. Barth, and G. Wu, “Cooperative ramp merging design and field implementation: A digital twin approach based on vehicle-to-cloud communication,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 5, pp. 4490–4500, 2021.
- J. Dong, Q. Xu, J. Wang, C. Yang, M. Cai, C. Chen, Y. Liu, J. Wang, and K. Li, “Mixed cloud control testbed: Validating vehicle-road-cloud integration via mixed digital twin,” IEEE Transactions on Intelligent Vehicles, vol. 8, no. 4, pp. 2723–2736, 2023.
- K. Wang, T. Yu, Z. Li, and K. Sakaguchi, “Cloud and edge computing empowered mobility digital twin for automated driving: Design and proof-of-concept,” in Proc. of IEEE 97th Vehicular Technology Conference (VTC2023-Spring), Florence, Italy, Jun. 2023.
- T. Yu, Z. Li, K. Sakaguchi, O. Hashash, W. Saad, and M. Debbah, “Internet of federated digital twins (iofdt): Connecting twins beyond borders for society 5.0,” arXiv preprint arXiv:2312.06432, 2023.
- Z. Li, K. Wang, T. Yu, and K. Sakaguchi, “Het-SDVN: SDN-based radio resource management of heterogeneous V2X for cooperative perception,” IEEE Access, vol. 11, pp. 76 255–76 268, 2023.
- Autoware universe documentation. [Online]. Available: https://autowarefoundation.github.io/autoware.universe/main/.
- T. Yin, X. Zhou, and P. Krahenbuhl, “Center-based 3d object detection and tracking,” in Proc. of the IEEE/CVF conference on computer vision and pattern recognition, 2021, pp. 11 784–11 793.
- Autoware multi-object tracker. [Online]. Available: https://autowarefoundation.github.io/autoware.universe/main/perception/multi_object_tracker/.
- P. Greibe, “Braking distance, friction and behaviour,” Trafitec, Scion-DTU, 2007.
- Institute of Transportation Engineers. Technical Council Committee 4A-16, “Determining vehicle change intervals: A proposed recommended practice,” Institute of Transportation Engineers, 1985.
- 3GPP, “Study on enhancement of 3GPP support for 5G V2X services (Release 16),” Tech. Rep. 22.886 V16.2.0, 2018.
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