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Drone-Truck Cooperated Delivery Under Time Varying Dynamics

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Published:25 July 2022Publication History

ABSTRACT

Rapid technological developments in autonomous unmanned aerial vehicles (or drones) could soon lead to their large-scale implementation in the last-mile delivery of products. However, drones have a number of problems such as limited energy budget, limited carrying capacity, etc. On the other hand, trucks have a larger carrying capacity, but they cannot reach all the places easily. Intriguingly, last-mile delivery cooperation between drones and trucks can synergistically improve delivery efficiency.

In this paper, we present a drone-truck co-operated delivery framework under time-varying dynamics. Our framework minimizes the total delivery time while considering low energy consumption as the secondary objective. The empirical results support our claim and show that our algorithm can help to complete the deliveries time efficiently and saves energy.

References

  1. Francesco Betti Sorbelli, Cristina M. Pinotti, Simone Silvestri, and Sajal K. Das. 2020. Measurement Errors in Range-based Localization Algorithms for UAVs: Analysis and Experimentation. IEEE Trans. on Mobile Computing (2020), 1--1.Google ScholarGoogle Scholar
  2. Igor Bisio, Chiara Garibotto, Fabio Lavagetto, et al. 2018. Blind detection: Advanced techniques for WiFi-based drone surveillance. IEEE Trans. on Vehicular Technology, Vol. 68, 1 (2018), 938--946.Google ScholarGoogle ScholarCross RefCross Ref
  3. Nils Boysen, Dirk Briskorn, Stefan Fedtke, and Stefan Schwerdfeger. 2018. Drone delivery from trucks: Drone scheduling for given truck routes. Networks, Vol. 72, 4 (2018), 506--527.Google ScholarGoogle ScholarCross RefCross Ref
  4. Federico Busato and Nicola Bombieri. 2015. An efficient implementation of the Bellman-Ford algorithm for Kepler GPU architectures. IEEE Trans. Parallel and Distributed Systems, Vol. 27, 8 (2015), 2222--2233.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Tiziana Calamoneri, Federico Corò, and Simona Mancini. 2022. A Realistic Model to Support Rescue Operations After an Earthquake via UAVs. IEEE Access, Vol. 10 (2022), 6109--6125.Google ScholarGoogle ScholarCross RefCross Ref
  6. Gloria Cerasela Crics an and Elena Nechita. 2019. On a cooperative truck-and-drone delivery system. Procedia Computer Science, Vol. 159 (2019), 38--47.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Rami Daknama and Elisabeth Kraus. 2017. Vehicle Routing with Drones. CoRR, Vol. abs/1705.06431 (2017). showeprint[arXiv]1705.06431 http://arxiv.org/abs/1705.06431Google ScholarGoogle Scholar
  8. Anurag Ingole and Rupesh Nasre. 2015. Dynamic shortest paths using javascript on GPUs. In IEEE 22nd Int Conf on High-Performance Computing (HiPC). 1--5.Google ScholarGoogle Scholar
  9. Arindam Khanda, Federico Coro, Francesco Betti Sorbelli, Cristina M Pinotti, and Sajal K Das. 2021 a. Efficient route selection for drone-based delivery under time-varying dynamics. In 2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS). IEEE, 437--445.Google ScholarGoogle ScholarCross RefCross Ref
  10. Arindam Khanda, Sriram Srinivasan, Sanjukta Bhowmick, Boyana Norris, and Sajal K Das. 2021 b. A Parallel Algorithm Template for Updating Single-Source Shortest Paths in Large-Scale Dynamic Networks. IEEE Transactions on Parallel and Distributed Systems (2021).Google ScholarGoogle Scholar
  11. Aakash Khochare, Yogesh Simmhan, Francesco Betti Sorbelli, and Sajal K. Das. 2021. Heuristic Algorithms for Co-scheduling of Edge Analytics and Routes for UAV Fleet Missions. In 40th IEEE Conference on Computer Communications, INFOCOM 2021, Vancouver, BC, Canada, May 10--13, 2021. IEEE, 1--10.Google ScholarGoogle Scholar
  12. S. Knight, H.X. Nguyen, N. Falkner, R. Bowden, and M. Roughan. 2011. The Internet Topology Zoo. Selected Areas in Communications, IEEE Journal on, Vol. 29, 9 (october 2011), 1765 --1775. https://doi.org/10.1109/JSAC.2011.111002Google ScholarGoogle Scholar
  13. Chase C Murray and Amanda G Chu. 2015. The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery. Transportation Research Part C: Emerging Technologies, Vol. 54 (2015), 86--109.Google ScholarGoogle ScholarCross RefCross Ref
  14. Chase C Murray and Ritwik Raj. 2020. The multiple flying sidekicks traveling salesman problem: Parcel delivery with multiple drones. Transportation Research Part C: Emerging Technologies, Vol. 110 (2020), 368--398.Google ScholarGoogle ScholarCross RefCross Ref
  15. Deepak Murugan, Akanksha Garg, and Dharmendra Singh. 2017. Development of an adaptive approach for precision agriculture monitoring with drone and satellite data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 10, 12 (2017), 5322--5328.Google ScholarGoogle ScholarCross RefCross Ref
  16. Akif Rehman, Masab Ahmad, and Omer Khan. 2020. Exploring accelerator and parallel graph algorithmic choices for temporal graphs. In 11th Int. Workshop on Programming Models and Applications for Multicores and Manycores. 1--10.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Roberto Roberti and Mario Ruthmair. 2021. Exact methods for the traveling salesman problem with drone. Transportation Science, Vol. 55, 2 (2021), 315--335.Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Suttinee Sawadsitang, Dusit Niyato, Puay Siew Tan, Ping Wang, and Sarana Nutanong. 2019. Multi-Objective Optimization for Drone Delivery. In IEEE 90th Vehicular Technology Conference (VTC2019-Fall). 1--5.Google ScholarGoogle Scholar
  19. Weisen Shi, Haibo Zhou, Junling Li, Wenchao Xu, Ning Zhang, and Xuemin Shen. 2018. Drone assisted vehicular networks: Architecture, challenges and opportunities. IEEE Network, Vol. 32, 3 (2018), 130--137.Google ScholarGoogle ScholarCross RefCross Ref
  20. Francesco Betti Sorbelli, Federico Corò, Sajal K. Das, Lorenzo Palazzetti, and Cristina M. Pinotti. 2022. Greedy Algorithms for Scheduling Package Delivery with Multiple Drones. In 23rd International Conference on Distributed Computing and Networking (ICDCN). ACM, 31--39.Google ScholarGoogle Scholar
  21. Francesco Betti Sorbelli, Federico Corò, Sajal K. Das, and Cristina M. Pinotti. 2021 a. Energy-Constrained Delivery of Goods With Drones Under Varying Wind Conditions. IEEE Trans. Intell. Transp. Syst., Vol. 22, 9 (2021), 6048--6060.Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Francesco Betti Sorbelli, Federico Corò, Sajal K. Das, and Cristina M. Pinotti. 2021 b. Energy-Constrained Delivery of Goods With Drones Under Varying Wind Conditions. IEEE Trans. Intell. Transp. Syst., Vol. 22, 9 (2021), 6048--6060.Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Sriram Srinivasan, Sara Riazi, Boyana Norris, Sajal K Das, and Sanjukta Bhowmick. 2018. A Shared-Memory Parallel Algorithm for Updating Single-Source Shortest Paths in Large Dynamic Networks. In 25th IEEE Int. Conf. on High Performance Computing (HiPC). 245--254.Google ScholarGoogle ScholarCross RefCross Ref
  24. Amila Thibbotuwawa, Grzegorz Bocewicz, Peter Nielsen, and Banaszak Zbigniew. 2019. Planning deliveries with UAV routing under weather forecast and energy consumption constraints. IFAC-PapersOnLine, Vol. 52, 13 (2019), 820--825.Google ScholarGoogle ScholarCross RefCross Ref
  25. Desheng Wang, Peng Hu, Jingxuan Du, Pan Zhou, Tianping Deng, and Menglan Hu. 2019. Routing and scheduling for hybrid truck-drone collaborative parcel delivery with independent and truck-carried drones. IEEE Internet of Things Journal, Vol. 6, 6 (2019), 10483--10495.Google ScholarGoogle ScholarCross RefCross Ref
  26. Yangzihao Wang, Andrew Davidson, Yuechao Pan, Yuduo Wu, Andy Riffel, and John D Owens. 2016. Gunrock: A high-performance graph processing library on the GPU. In 21st Symp. on Principles and Practice of Parallel Programming. 1--12.Google ScholarGoogle ScholarDigital LibraryDigital Library

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      cover image ACM Conferences
      ApPLIED '22: Proceedings of the 2022 Workshop on Advanced tools, programming languages, and PLatforms for Implementing and Evaluating algorithms for Distributed systems
      July 2022
      75 pages
      ISBN:9781450392808
      DOI:10.1145/3524053

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      Publication History

      • Published: 25 July 2022

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