On the Impact of Communication and Computing Delays on MEC-Enabled Cooperative Maneuvers

Cooperative driving maneuvers can improve the efficiency of road transportation by actively coordinating vehicles to maximize traffic flow and minimize fuel consumption. Different from platooning, where direct vehicle-to-vehicle (V2V) communication might represent the best option, maneuvers are usually local and time-bound. In such situations, an approach exploiting multi-access edge computing (MEC) can yield the benefits of a centralized solution with reduced delay, as control and coordination traffic does not need to flow through the network core. Moreover, deploying maneuvers as MEC applications effectively realizes a new paradigm that we call cooperative driving-as-a-service (CDaaS), where the resources to manage and control maneuvers are flexibly hosted and managed by the same network that connects the vehicles. As the MEC is a shared computing infrastructure not dedicated to traffic optimization, its use raises concerns related to delays: excessive delays (e.g., due to server overload) could compromise the safety and the efficiency of the maneuvers. Moreover, to keep delay contained, applications may need to be migrated to different servers. In this work, we present the CDaaS concept and implement two maneuvers as MEC applications: a cooperative overtake and an intersection merge. Via an open-source simulator, we then study the impact of communication delays on their performance. Our results show that the impact of the delay is actually maneuver-dependent, hence migration decisions should depend on the maneuvers themselves, besides other factors such as the network delay and server load.

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Publication Details

Published
2025-06-02
DOI
https://doi.org/10.1109/vnc64509.2025.11054264
Citations
1
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
1.49
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article

On the Impact of Communication and Computing Delays on MEC-Enabled Cooperative Maneuvers

Andrea Piccin, Paolo Casari, Anish Shastri, Michele Segata et al.
1 citations
Distributed Control Multi-Agent Systems
1.49
article

On the Impact of Communication and Computing Delays on MEC-Enabled Cooperative Maneuvers

Andrea Piccin, Paolo Casari, Anish Shastri, Michele Segata, Ioan Gabriel Duta
article en
1 citations

Abstract

Cooperative driving maneuvers can improve the efficiency of road transportation by actively coordinating vehicles to maximize traffic flow and minimize fuel consumption. Different from platooning, where direct vehicle-to-vehicle (V2V) communication might represent the best option, maneuvers are usually local and time-bound. In such situations, an approach exploiting multi-access edge computing (MEC) can yield the benefits of a centralized solution with reduced delay, as control and coordination traffic does not need to flow through the network core. Moreover, deploying maneuvers as MEC applications effectively realizes a new paradigm that we call cooperative driving-as-a-service (CDaaS), where the resources to manage and control maneuvers are flexibly hosted and managed by the same network that connects the vehicles. As the MEC is a shared computing infrastructure not dedicated to traffic optimization, its use raises concerns related to delays: excessive delays (e.g., due to server overload) could compromise the safety and the efficiency of the maneuvers. Moreover, to keep delay contained, applications may need to be migrated to different servers. In this work, we present the CDaaS concept and implement two maneuvers as MEC applications: a cooperative overtake and an intersection merge. Via an open-source simulator, we then study the impact of communication delays on their performance. Our results show that the impact of the delay is actually maneuver-dependent, hence migration decisions should depend on the maneuvers themselves, besides other factors such as the network delay and server load.

University of Trento (IT)
Openalex Percentile: Top 15%
Distributed Control Multi-Agent Systems
1.49
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On the Impact of Communication and Computing Delays on MEC-Enabled Cooperative Maneuvers — Andrea Piccin, Paolo Casari, et al. · (2025) | TGRS Research Map | TGRS