Latency-aware C-ITS application for improving the road safety with CAM messages on the Smart Highway testbed

Charpentier, Vincent; Slamnik-Kriještorac, Nina; Marquez-Barja, Johann M.

doi:10.1109/infocomwkshps54753.2022.9798350

Cited by 9 publications

(3 citation statements)

References 8 publications

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“…As being shown in Figure 2, primarily ITS-G5 is a good fit to compare its performances against the cellular approach. Charpentier et al concluded similar results for the performance of CAM messages for his experimental evaluation between the technologies ITS-G5 and LTE-V2X PC5 [13]. With the average latency performance results of a single RSU and single OBU standing still next to each other in hand, we will move to a more realistic experimental setup using a moving vehicle over the Smart Highway.…”

Section: A Single Rsu Non-moving Resultsmentioning

confidence: 61%

The testing framework for Vehicular Edge Computing and Communications on the Smart Highway

Verschoor

Charpentier²,

Slamnik-Kriještorac

et al. 2023

2023 IEEE 20th Consumer Communications &Amp; Networking Conference (CCNC)

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Vehicular Edge Computing (VEC) brings cloud infrastructure to the vehicular edge, resulting in better performances and avoiding network congestions. In this workin-progress paper, the benefits of edge computing over cloud computing are discussed in a vehicular environment context, and they are leveraged by creating a Cooperative, Connected and Automated Mobility (CCAM) performance measurement framework. This measurement tool can follow vehicles by moving across different devices, enabling measurements on Key Performance Indicators (KPIs) using edge computing. We already used this tool to evaluate latencies of both a stationary and driving vehicle, moving over the Smart Highway testbed in Antwerp, Belgium. When driving, smart-edge-following algorithms can be deployed to choose the nearest Road Side Unit (RSU) using broadcasted Cooperative Awareness Messages (CAMs) of the vehicle. While driving on the Smart Highway, the application monitors important performance metrics such as throughput, latency, packet loss, packet delivery rate and more. We compare short-range vehicular communications technologies on the Smart Highway (ITS-G5 and LTE-V2X PC5) against the cellular. Our preliminary results demonstrate the benefits in terms of latency by using short-range communications technologies in VEC applications. These results validate that moving applications to the edge is truly beneficial, since our results confirmed up to 90% lower latency using ITS-G5, up to 50% using LTE-V2X PC5. Future deployments of 5G in the Smart Highway are planned, which would further improve the performance edge computing technologies.

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Section: A Single Rsu Non-moving Resultsmentioning

confidence: 61%

The testing framework for Vehicular Edge Computing and Communications on the Smart Highway

Verschoor

Charpentier²,

Slamnik-Kriještorac

et al. 2023

2023 IEEE 20th Consumer Communications &Amp; Networking Conference (CCNC)

Self Cite

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“…This forms already a first challenge to the vision where all different (vendor crossing) UAVs can speak and understand the same language. Moreover, recent research performed by Charpentier et al, proofed that ITS-G5 (IEEE 802.11p) and LTE-V2X (3GPP) do not meet the requirements for UAVs [3]. Which reconfirms that ITS-G5 and LTE-V2X are designed for basic safety and traffic management use cases i.e., to support basic cooperative active traffic safety, traffic management, and telematics applications and thus not for advanced UAV communication [11,16].…”

Section: Current Major Communication Technologiesmentioning

confidence: 99%

A proposal on a Connected Automated Mobility (CAM) communication system for (U)AVs

Charpentier

Slamnik-Kriještorac

Márquez-Barja

et al. 2022

Proceedings of the 2022 ACM Conference on Information Technology for Social Good

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The next generation of vehicular communications has the potential to interconnect Unmanned Automated Vehicles (UAVs), which are the level 5 autonomous vehicles, with its nearby surroundings including Vulnerable Road Users (VRUs), other UAVs, and roadside infrastructure. Given the increased interest in the demand of autonomous driving and Cooperative Connected and Automated Mobility (CCAM), the future UAVs will be safer through enabling communication between UAVs themselves and with their surroundings e.g., VRUs. Communication between UAVs and VRUs will be needed since VRUs will not be able to make a physical eye-contact with the UAVs since their is no physical driver anymore behind the steering wheel. In this way the VRUs can make themselves digitally aware in the UAV traffic and vice versa. Such that UAVs will not be isolated black boxes, i.e., operating and relying fully on their embedded sensors, to its surrounding UAVs and VRUs. This paper shows the current and future needs for autonomous vehicular communication between UAVs and VRUs. Therefore, we present the current trends in the vehicular communication domain and its research challenges. We propose a solution to enable communication between semi-autonomous vehicles, UAVs and their surrounding e.g., VRUs. In our paper, we provide also an early initial proposal to fuse the Vehicle-to-everything (V2X) communication with the embedded autonomous software in the autonomous vehicle.

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“…There has been a tremendous amount of work focusing on VANETs utilizing IEEE 802.11p, the default standard for distributed V2V communications. The IEEE 802.11p standard is a contention-based MAC protocol method using carrier-sense multiple access with collision avoidance (CSMA/CA) to avoid interference and collisions between different nodes [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Vehicles Communication and Connectivity Using Persistent Carrier Sensing Multiple Access Protocol

2023

IJIES

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This paper investigates the effectiveness of using P-persistent carrier sensing multiple access (P-Persistent CSMA) on vehicular connectivity as vehicles dynamically form temporary communication networks using simulation and mathematical modelling. In the connected and autonomous environment, effective and efficient connectivity between vehicles (V2V) and between vehicles and infrastructure (V2I) is critical. The simulation was performed in MATLAB and included the investigation of the effect of vehicular density, probability value change, and increase in Backoff time, and change in data frame size. The results showed that as vehicular density, probability, and data frame size increased, throughput decreased as data traffic increased, whereas as Backoff time and probability increased, throughput increased. Furthermore, as data size increases with decreasing probability level, channel utilization improves. Based on these findings and the derived mathematical expressions, a proposed dynamic and adaptive model is presented, allowing for maximum throughput while minimizing collisions. This is accomplished by equating four mathematical expressions and substituting them using iteration to achieve a balanced and optimal level of communication channel utilization by dynamically adjusting the three main parameters under consideration as a function of increasing vehicular density (P-Persistent probability level, Backoff time, and data frame length). To achieve such dynamical and adaptive optimization, four mathematical expressions are used. The resulting model is promising and will improve the efficiency of non-adaptive conventional P-Persistent CSMA. The presented work proved to increase the effectiveness of the conventional p-persistent technique using a multi-dimensional parameter correlation, which is more effective than weighted, slotted, or adaptive P-Persistent approaches.

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Latency-aware C-ITS application for improving the road safety with CAM messages on the Smart Highway testbed

Cited by 9 publications

References 8 publications

The testing framework for Vehicular Edge Computing and Communications on the Smart Highway

The testing framework for Vehicular Edge Computing and Communications on the Smart Highway

A proposal on a Connected Automated Mobility (CAM) communication system for (U)AVs

Vehicles Communication and Connectivity Using Persistent Carrier Sensing Multiple Access Protocol

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