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B-AWARE: Blockage Aware RSU Scheduling for 5G Enabled Autonomous Vehicles

Publication ,  Journal Article
Szeto, M; Andert, E; Shrivastava, A; Reisslein, M; Lin, CW; Richmond, C
Published in: ACM Transactions on Embedded Computing Systems
September 9, 2023

5G Millimeter Wave (mmWave) technology holds great promise for Connected Autonomous Vehicles (CAVs) due to its ability to achieve data rates in the Gbps range. However, mmWave suffers from a high beamforming overhead and requirement of line of sight (LOS) to maintain a strong connection. For Vehicle-to-Infrastructure (V2I) scenarios, where CAVs connect to roadside units (RSUs), these drawbacks become apparent. Because vehicles are dynamic, there is a large potential for link blockages. These blockages are detrimental to the connected applications running on the vehicle, such as cooperative perception and remote driver takeover. Existing RSU selection schemes base their decisions on signal strength and vehicle trajectory alone, which is not enough to prevent the blockage of links. Many modern CAVs motion planning algorithms routinely use other vehicle's near-future path plans, either by explicit communication among vehicles, or by prediction. In this paper, we make use of the knowledge of other vehicle's near future path plans to further improve the RSU association mechanism for CAVs. We solve the RSU association algorithm by converting it to a shortest path problem with the objective to maximize the total communication bandwidth. We evaluate our approach, titled B-AWARE, in simulation using Simulation of Urban Mobility (SUMO) and Digital twin for self-dRiving Intelligent VEhicles (DRIVE) on 12 highway and city street scenarios with varying traffic density and RSU placements. Simulations show B-AWARE results in a 1.05× improvement of the potential datarate in the average case and 1.28× in the best case vs. the state-of-the-art. But more impressively, B-AWARE reduces the time spent with no connection by 42% in the average case and 60% in the best case as compared to the state-of-the-art methods. This is a result of B-AWARE reducing nearly 100% of blockage occurrences.

Duke Scholars

Published In

ACM Transactions on Embedded Computing Systems

DOI

EISSN

1558-3465

ISSN

1539-9087

Publication Date

September 9, 2023

Volume

22

Issue

5 s

Related Subject Headings

  • Computer Hardware & Architecture
  • 4606 Distributed computing and systems software
  • 4006 Communications engineering
  • 1006 Computer Hardware
  • 0805 Distributed Computing
  • 0803 Computer Software
 

Citation

APA
Chicago
ICMJE
MLA
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Szeto, M., Andert, E., Shrivastava, A., Reisslein, M., Lin, C. W., & Richmond, C. (2023). B-AWARE: Blockage Aware RSU Scheduling for 5G Enabled Autonomous Vehicles. ACM Transactions on Embedded Computing Systems, 22(5 s). https://doi.org/10.1145/3609133
Szeto, M., E. Andert, A. Shrivastava, M. Reisslein, C. W. Lin, and C. Richmond. “B-AWARE: Blockage Aware RSU Scheduling for 5G Enabled Autonomous Vehicles.” ACM Transactions on Embedded Computing Systems 22, no. 5 s (September 9, 2023). https://doi.org/10.1145/3609133.
Szeto M, Andert E, Shrivastava A, Reisslein M, Lin CW, Richmond C. B-AWARE: Blockage Aware RSU Scheduling for 5G Enabled Autonomous Vehicles. ACM Transactions on Embedded Computing Systems. 2023 Sep 9;22(5 s).
Szeto, M., et al. “B-AWARE: Blockage Aware RSU Scheduling for 5G Enabled Autonomous Vehicles.” ACM Transactions on Embedded Computing Systems, vol. 22, no. 5 s, Sept. 2023. Scopus, doi:10.1145/3609133.
Szeto M, Andert E, Shrivastava A, Reisslein M, Lin CW, Richmond C. B-AWARE: Blockage Aware RSU Scheduling for 5G Enabled Autonomous Vehicles. ACM Transactions on Embedded Computing Systems. 2023 Sep 9;22(5 s).

Published In

ACM Transactions on Embedded Computing Systems

DOI

EISSN

1558-3465

ISSN

1539-9087

Publication Date

September 9, 2023

Volume

22

Issue

5 s

Related Subject Headings

  • Computer Hardware & Architecture
  • 4606 Distributed computing and systems software
  • 4006 Communications engineering
  • 1006 Computer Hardware
  • 0805 Distributed Computing
  • 0803 Computer Software