Publications
21.
Hegde, A.; Lobo, S.; Festag, A.
Cellular-V2X for Vulnerable Road User Protection in Cooperative ITS Proceedings Article
In: 2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), Thessaloniki, Greece, 2022.
Abstract | Links | BibTeX | Tags: Intelligent Transport Systems, safety, V2X communication, vulnerable road users
@inproceedings{Hegde:WiMob:2022,
title = {Cellular-V2X for Vulnerable Road User Protection in Cooperative ITS},
author = {A. Hegde and S. Lobo and A. Festag},
url = {http://www.wimob.org/wimob2022},
doi = {10.1109/WiMob55322.2022.9941707},
year = {2022},
date = {2022-12-31},
urldate = {2022-10-12},
booktitle = {2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)},
address = {Thessaloniki, Greece},
abstract = {Cooperative Intelligent Transport Systems (C-ITS) play a significant role in improving road traffic safety and efficiency. Primary use cases rely on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. In C-ITS, the safety of vulnerable road users (VRUs) such as pedestrians, motorists and other users with reduced mobility is being increasingly considered. A warning system, where VRUs actively send and receive messages instead of being passively monitored as road traffic objects, can play an important role in detecting risky situations and allowing the warning of vehicle drivers. However, in a dense urban traffic scenario with closely moving vehicles and pedestrians, the communication network can face severe resource constraints. Considering Cellular-V2X communication systems, the user equipments (UEs) may have to use the unmanaged mode of the sidelink interface. This paper analyzes the limitations of the existing radio resource allocation mechanisms and proposes adaptive strategies to ensure fairness in the distribution of radio resources between vehicles and VRUs. In addition, this work addresses the question about the situations in which VRU safety, being subject to a resource-constrained Cellular-V2X network, can be ensured.},
keywords = {Intelligent Transport Systems, safety, V2X communication, vulnerable road users},
pubstate = {published},
tppubtype = {inproceedings}
}
Cooperative Intelligent Transport Systems (C-ITS) play a significant role in improving road traffic safety and efficiency. Primary use cases rely on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. In C-ITS, the safety of vulnerable road users (VRUs) such as pedestrians, motorists and other users with reduced mobility is being increasingly considered. A warning system, where VRUs actively send and receive messages instead of being passively monitored as road traffic objects, can play an important role in detecting risky situations and allowing the warning of vehicle drivers. However, in a dense urban traffic scenario with closely moving vehicles and pedestrians, the communication network can face severe resource constraints. Considering Cellular-V2X communication systems, the user equipments (UEs) may have to use the unmanaged mode of the sidelink interface. This paper analyzes the limitations of the existing radio resource allocation mechanisms and proposes adaptive strategies to ensure fairness in the distribution of radio resources between vehicles and VRUs. In addition, this work addresses the question about the situations in which VRU safety, being subject to a resource-constrained Cellular-V2X network, can be ensured.
22.
Song, R.; Zhou, L.; Lyu, L.; Festag, A.; Knoll, A.
ResFed: Communication Efficient Federated Learning by Transmitting Deep Compressed Residuals Journal Article
In: arXiv, 2022, (arXiv:2212.05602 [cs.LG]).
Abstract | Links | BibTeX | Tags: federated learning, Intelligent Transport Systems
@article{Song:ARXIV:2022,
title = {ResFed: Communication Efficient Federated Learning by Transmitting Deep Compressed Residuals},
author = {R. Song and L. Zhou and L. Lyu and A. Festag and A. Knoll},
url = {https://arxiv.org/abs/2212.05602},
year = {2022},
date = {2022-12-22},
urldate = {2022-12-11},
journal = {arXiv},
abstract = {Federated learning enables cooperative training among massively distributed clients by sharing their learned local model parameters. However, with increasing model size, deploying federated learning requires a large communication bandwidth, which limits its deployment in wireless networks. To address this bottleneck, we introduce a residual-based federated learning framework (ResFed), where residuals rather than model parameters are transmitted in communication networks for training. In particular, we integrate two pairs of shared predictors for the model prediction in both server-to-client and client-to-server communication. By employing a common prediction rule, both locally and globally updated models are always fully recoverable in clients and the server. We highlight that the residuals only indicate the quasi-update of a model in a single inter-round, and hence contain more dense information and have a lower entropy than the model, comparing to model weights and gradients. Based on this property, we further conduct lossy compression of the residuals by sparsification and quantization and encode them for efficient communication. The experimental evaluation shows that our ResFed needs remarkably less communication costs and achieves better accuracy by leveraging less sensitive residuals, compared to standard federated learning. For instance, to train a 4.08 MB CNN model on CIFAR-10 with 10 clients under non-independent and identically distributed (Non-IID) setting, our approach achieves a compression ratio over 700X in each communication round with minimum impact on the accuracy. To reach an accuracy of 70%, it saves around 99% of the total communication volume from 587.61 Mb to 6.79 Mb in up-streaming and to 4.61 Mb in down-streaming on average for all clients.},
note = {arXiv:2212.05602 [cs.LG]},
keywords = {federated learning, Intelligent Transport Systems},
pubstate = {published},
tppubtype = {article}
}
Federated learning enables cooperative training among massively distributed clients by sharing their learned local model parameters. However, with increasing model size, deploying federated learning requires a large communication bandwidth, which limits its deployment in wireless networks. To address this bottleneck, we introduce a residual-based federated learning framework (ResFed), where residuals rather than model parameters are transmitted in communication networks for training. In particular, we integrate two pairs of shared predictors for the model prediction in both server-to-client and client-to-server communication. By employing a common prediction rule, both locally and globally updated models are always fully recoverable in clients and the server. We highlight that the residuals only indicate the quasi-update of a model in a single inter-round, and hence contain more dense information and have a lower entropy than the model, comparing to model weights and gradients. Based on this property, we further conduct lossy compression of the residuals by sparsification and quantization and encode them for efficient communication. The experimental evaluation shows that our ResFed needs remarkably less communication costs and achieves better accuracy by leveraging less sensitive residuals, compared to standard federated learning. For instance, to train a 4.08 MB CNN model on CIFAR-10 with 10 clients under non-independent and identically distributed (Non-IID) setting, our approach achieves a compression ratio over 700X in each communication round with minimum impact on the accuracy. To reach an accuracy of 70%, it saves around 99% of the total communication volume from 587.61 Mb to 6.79 Mb in up-streaming and to 4.61 Mb in down-streaming on average for all clients.
23.
Hegde, A.; Delooz, Q.; Mariyaklla, C. L.; Festag, A.; Klingler, F.
Radio Resource Allocation for Collective Perception in 5G-NR Vehicle-to-X Communication Systems Proceedings Article
In: IEEE Wireless Communications and Networking Conference (WCNC 2023), Glasgow, UK, 2022.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication
@inproceedings{Hegde:WCNC:2023,
title = {Radio Resource Allocation for Collective Perception in 5G-NR Vehicle-to-X Communication Systems},
author = {A. Hegde and Q. Delooz and C. L. Mariyaklla and A. Festag and F. Klingler},
url = {https://wcnc2023.ieee-wcnc.org},
doi = {10.1109/WCNC55385.2023.10118606},
year = {2022},
date = {2022-12-11},
urldate = {2022-12-11},
booktitle = {IEEE Wireless Communications and Networking Conference (WCNC 2023)},
address = {Glasgow, UK},
abstract = {Sensor data sharing has an immense potential to enhance the perception capabilities of vehicles and to provide better situational awareness. It is being standardized as collective perception by the European Telecommunication Standards Institute (ETSI) as part of Cooperative Intelligent Transport Systems (C-ITS). For the transmission of collective perception messages via sidelink in Cellular-V2X, sensing-based semi-persistent scheduling (SB-SPS) in the unmanaged mode of 5G-NR V2X provides low-latency communication among road traffic participants that are located outside the cellular network coverage. The unpredictability of the collective perception messages in periodicity and size poses certain challenges on the SB-SPS, thereby creating poor utilization of radio resources and high risk of resource collisions. Existing system level simulations study the performance of collective perception from the application perspective without addressing the radio resource allocation at the access layer. This work investigates the challenges of the sidelink resource allocation mechanisms in 5G-NR V2X and assesses the impact of the mechanism on the performance of collective perception by simulation in a realistic urban traffic environment. A practical approach is adopted to formulate mathematical models that can characterize the radio resource utilization and resource collisions arising in such environments and yield the appropriate 5G-NR V2X parameters.},
keywords = {Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication},
pubstate = {published},
tppubtype = {inproceedings}
}
Sensor data sharing has an immense potential to enhance the perception capabilities of vehicles and to provide better situational awareness. It is being standardized as collective perception by the European Telecommunication Standards Institute (ETSI) as part of Cooperative Intelligent Transport Systems (C-ITS). For the transmission of collective perception messages via sidelink in Cellular-V2X, sensing-based semi-persistent scheduling (SB-SPS) in the unmanaged mode of 5G-NR V2X provides low-latency communication among road traffic participants that are located outside the cellular network coverage. The unpredictability of the collective perception messages in periodicity and size poses certain challenges on the SB-SPS, thereby creating poor utilization of radio resources and high risk of resource collisions. Existing system level simulations study the performance of collective perception from the application perspective without addressing the radio resource allocation at the access layer. This work investigates the challenges of the sidelink resource allocation mechanisms in 5G-NR V2X and assesses the impact of the mechanism on the performance of collective perception by simulation in a realistic urban traffic environment. A practical approach is adopted to formulate mathematical models that can characterize the radio resource utilization and resource collisions arising in such environments and yield the appropriate 5G-NR V2X parameters.
24.
Maksimovski, D.; Facchi, C.; Festag, A.
Cooperative Driving: Research on Generic Decentralized Maneuver Coordination for Connected and Automated Vehicles Book Section
In: Klein, Cornel; Jarke, Matthias; Helfert, Markus; Berns, Karsten; Gusikhin, Oleg (Ed.): Smart Cities, Green Technologies, and Intelligent Transport Systems, pp. 348–370, Springer International Publishing, Cham, 2022.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, maneuver coordination, V2X communication, vehicle automation
@incollection{Maksimovski:Springer:2022,
title = {Cooperative Driving: Research on Generic Decentralized Maneuver Coordination for Connected and Automated Vehicles},
author = {D. Maksimovski and C. Facchi and A. Festag},
editor = {Cornel Klein and Matthias Jarke and Markus Helfert and Karsten Berns and Oleg Gusikhin},
url = {https://link.springer.com/chapter/10.1007/978-3-031-17098-0_18},
doi = {10.1007/978-3-031-17098-0_18},
year = {2022},
date = {2022-10-11},
urldate = {2022-10-11},
booktitle = {Smart Cities, Green Technologies, and Intelligent Transport Systems},
pages = {348–370},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {Maneuver coordination for Connected and Automated Vehicles (CAVs) can be enhanced by vehicle-to-everything (V2X) communication. In order to disseminate planned maneuver intentions or requests, Maneuver Coordination Messages (MCMs) are exchanged between the CAVs that enable them to negotiate and perform cooperative maneuvers. In this way, V2X communication can extend the perception range of the sensors, enhance the decision making and maneuver planning of the CAVs, as well as allow complex interactions between the vehicles. Various maneuver coordination schemes exist for specific traffic use cases. Recently, several maneuver coordination approaches have been proposed that target at generic decentralized solutions which can be applied for a wide range of use cases relying on direct vehicle-to-vehicle (V2V) communication. This paper presents such use cases and existing generic approaches for decentralized maneuver coordination. The approaches are systematically described, compared and classified considering explicit and implicit trajectory broadcast, space-time reservation, cost values, priority maneuvers and complex interactions among vehicles. Furthermore, this paper outlines open research gaps in the field and discusses future research directions.},
keywords = {Cooperative ITS, Intelligent Transport Systems, maneuver coordination, V2X communication, vehicle automation},
pubstate = {published},
tppubtype = {incollection}
}
Maneuver coordination for Connected and Automated Vehicles (CAVs) can be enhanced by vehicle-to-everything (V2X) communication. In order to disseminate planned maneuver intentions or requests, Maneuver Coordination Messages (MCMs) are exchanged between the CAVs that enable them to negotiate and perform cooperative maneuvers. In this way, V2X communication can extend the perception range of the sensors, enhance the decision making and maneuver planning of the CAVs, as well as allow complex interactions between the vehicles. Various maneuver coordination schemes exist for specific traffic use cases. Recently, several maneuver coordination approaches have been proposed that target at generic decentralized solutions which can be applied for a wide range of use cases relying on direct vehicle-to-vehicle (V2V) communication. This paper presents such use cases and existing generic approaches for decentralized maneuver coordination. The approaches are systematically described, compared and classified considering explicit and implicit trajectory broadcast, space-time reservation, cost values, priority maneuvers and complex interactions among vehicles. Furthermore, this paper outlines open research gaps in the field and discusses future research directions.
25.
Lobo, S.; Festag, A.; Facchi, C.
Enhancing the Safety of Vulnerable Road Users: Messaging Protocols for V2X Communication Proceedings Article
In: IEEE 96th Vehicular Technology Conference (VTC2022-Fall), London UK and Beijing, China, 2022.
Abstract | Links | BibTeX | Tags: Intelligent Transport Systems, safety, V2X communication, vulnerable road users
@inproceedings{Lobo:VTCFall:2022,
title = {Enhancing the Safety of Vulnerable Road Users: Messaging Protocols for V2X Communication},
author = {S. Lobo and A. Festag and C. Facchi},
url = {https://ieeexplore.ieee.org/document/10012775},
doi = {10.1109/VTC2022-Fall57202.2022.10012775},
year = {2022},
date = {2022-09-05},
urldate = {2022-09-05},
booktitle = {IEEE 96th Vehicular Technology Conference (VTC2022-Fall)},
address = {London UK and Beijing, China},
abstract = {The protection of vulnerable road users (VRUs) by means of V2X communication is increasingly considered for the next generation of cooperative safety systems. Two messaging protocols are being standardized: (i) With collective perception for sensor data sharing: VRUs can be passively perceived by the local sensors in vehicles and roadside units, which disseminate this information in dedicated messages carrying lists with VRU and other objects. (ii) VRUs can actively transmit messages in order to make other road users in their vicinity aware of their presence. This paper carries out a performance evaluation of a scenario with the two main messaging protocols and also their combined deployment, and compares them with two baseline approaches. Simulation results for a representative roundabout scenario with manifold interaction among vehicles and pedestrians indicate that the combination of sensor data sharing and active VRU transmissions performs best: It provides the highest VRU detection rate and the shortest VRU detection latency. This approach keeps the channel busy ratio below a critical threshold, which prevents the data congestion control of the V2X communication system from its activation.},
keywords = {Intelligent Transport Systems, safety, V2X communication, vulnerable road users},
pubstate = {published},
tppubtype = {inproceedings}
}
The protection of vulnerable road users (VRUs) by means of V2X communication is increasingly considered for the next generation of cooperative safety systems. Two messaging protocols are being standardized: (i) With collective perception for sensor data sharing: VRUs can be passively perceived by the local sensors in vehicles and roadside units, which disseminate this information in dedicated messages carrying lists with VRU and other objects. (ii) VRUs can actively transmit messages in order to make other road users in their vicinity aware of their presence. This paper carries out a performance evaluation of a scenario with the two main messaging protocols and also their combined deployment, and compares them with two baseline approaches. Simulation results for a representative roundabout scenario with manifold interaction among vehicles and pedestrians indicate that the combination of sensor data sharing and active VRU transmissions performs best: It provides the highest VRU detection rate and the shortest VRU detection latency. This approach keeps the channel busy ratio below a critical threshold, which prevents the data congestion control of the V2X communication system from its activation.
26.
Song, R.; Zhou, L.; Lakshminarasimhan, V.; Festag, A.; Knoll, A.
Federated Learning Framework Coping with Hierarchical Heterogeneity in Cooperative ITS Proceedings Article
In: IEEE International Intelligent Transportation Systems Conference (ITSC), pp. 3502-3508, Macau, China, 2022.
Abstract | Links | BibTeX | Tags: federated learning, Intelligent Transport Systems
@inproceedings{Song:ITSC:2022,
title = {Federated Learning Framework Coping with Hierarchical Heterogeneity in Cooperative ITS},
author = {R. Song and L. Zhou and V. Lakshminarasimhan and A. Festag and A. Knoll},
doi = {10.1109/ITSC55140.2022.9922064},
year = {2022},
date = {2022-06-22},
urldate = {2022-06-22},
booktitle = {IEEE International Intelligent Transportation Systems Conference (ITSC)},
pages = {3502-3508},
address = {Macau, China},
abstract = {In this paper, we introduce a federated learning framework coping with Hierarchical Heterogeneity (H2-Fed), which can notably enhance the conventional pre-trained deep learning model. The framework exploits data from connected public traffic agents in vehicular networks without affecting user data privacy. By coordinating existing traffic infrastructure, including roadside units and road traffic clouds, the model parameters are efficiently disseminated by vehicular communications and hierarchically aggregated. Considering the individual heterogeneity of data distribution, computational and communication capabilities across traffic agents and roadside units, we employ a novel method that addresses the heterogeneity of different aggregation layers of the framework architecture, i.e., aggregation in layers of roadside units and cloud. The experiment results indicate that our method can well balance the learning accuracy and stability according to the knowledge of heterogeneity in current communication networks. Compared to other baseline approaches, the evaluation on a Non-IID MNIST dataset shows that our framework is more general and capable especially in application scenarios with low communication quality. Even when 90% of the agents are timely disconnected, the pre-trained deep learning model can still be forced to converge stably, and its accuracy can be enhanced from 68% to over 90% after convergence.},
keywords = {federated learning, Intelligent Transport Systems},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we introduce a federated learning framework coping with Hierarchical Heterogeneity (H2-Fed), which can notably enhance the conventional pre-trained deep learning model. The framework exploits data from connected public traffic agents in vehicular networks without affecting user data privacy. By coordinating existing traffic infrastructure, including roadside units and road traffic clouds, the model parameters are efficiently disseminated by vehicular communications and hierarchically aggregated. Considering the individual heterogeneity of data distribution, computational and communication capabilities across traffic agents and roadside units, we employ a novel method that addresses the heterogeneity of different aggregation layers of the framework architecture, i.e., aggregation in layers of roadside units and cloud. The experiment results indicate that our method can well balance the learning accuracy and stability according to the knowledge of heterogeneity in current communication networks. Compared to other baseline approaches, the evaluation on a Non-IID MNIST dataset shows that our framework is more general and capable especially in application scenarios with low communication quality. Even when 90% of the agents are timely disconnected, the pre-trained deep learning model can still be forced to converge stably, and its accuracy can be enhanced from 68% to over 90% after convergence.
27.
Delooz, Q.; Willecke, A.; Garlichs, K.; Hagau, A. -C.; Wolf, L.; Vinel, A.; Festag, A.
Analysis and Evaluation of Information Redundancy Mitigation for V2X Collective Perception Journal Article
In: IEEE Access, vol. 10, pp. 47076-47093, 2022.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication
@article{Delooz:IEEEAccess:2022,
title = {Analysis and Evaluation of Information Redundancy Mitigation for V2X Collective Perception},
author = {Q. Delooz and A. Willecke and K. Garlichs and A. -C. Hagau and L. Wolf and A. Vinel and A. Festag},
url = {2022-04-27},
doi = {10.1109/ACCESS.2022.3170029},
year = {2022},
date = {2022-04-09},
urldate = {2022-04-09},
journal = {IEEE Access},
volume = {10},
pages = {47076-47093},
abstract = {Sensor data sharing enables vehicles to exchange locally perceived sensor data among each other and with the roadside infrastructure to increase their environmental awareness. It is commonly regarded as a next-generation vehicular communication service beyond the exchange of highly aggregated messages in the first generation. The approach is being considered in the European standardization process, where it relies on the exchange of locally detected objects representing anything safety-relevant, such as other vehicles or pedestrians, in periodically broadcasted messages to vehicles in direct communication range. Objects filtering methods for inclusion in a message are necessary to avoid overloading a channel and provoking unnecessary data processing. Initial studies provided in a pre-standardization report about sensor data sharing elaborated a first set of rules to filter objects based on their characteristics, such as their dynamics or type. However, these rules still lack the consideration of information received by other stations to operate. Specifically, to address the problem of information redundancy, several rules have been proposed, but their performance has not been evaluated yet comprehensively. In the present work, the rules are further analyzed, assessed, and compared. Functional and operational requirements are investigated. A performance evaluation is realized by discrete-event simulations in a scenario for a representative city with realistic vehicle densities and mobility patterns. A score and other redundancy-level metrics are elaborated to ease the evaluation and comparison of the filtering rules. Finally, improvements and future works to the filtering methods are proposed.},
keywords = {Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication},
pubstate = {published},
tppubtype = {article}
}
Sensor data sharing enables vehicles to exchange locally perceived sensor data among each other and with the roadside infrastructure to increase their environmental awareness. It is commonly regarded as a next-generation vehicular communication service beyond the exchange of highly aggregated messages in the first generation. The approach is being considered in the European standardization process, where it relies on the exchange of locally detected objects representing anything safety-relevant, such as other vehicles or pedestrians, in periodically broadcasted messages to vehicles in direct communication range. Objects filtering methods for inclusion in a message are necessary to avoid overloading a channel and provoking unnecessary data processing. Initial studies provided in a pre-standardization report about sensor data sharing elaborated a first set of rules to filter objects based on their characteristics, such as their dynamics or type. However, these rules still lack the consideration of information received by other stations to operate. Specifically, to address the problem of information redundancy, several rules have been proposed, but their performance has not been evaluated yet comprehensively. In the present work, the rules are further analyzed, assessed, and compared. Functional and operational requirements are investigated. A performance evaluation is realized by discrete-event simulations in a scenario for a representative city with realistic vehicle densities and mobility patterns. A score and other redundancy-level metrics are elaborated to ease the evaluation and comparison of the filtering rules. Finally, improvements and future works to the filtering methods are proposed.
28.
Song, R.; Hegde, A.; Senel, N.; Festag, A.
Edge-Aided Sensor Data Sharing in Vehicular Communication Networks Proceedings Article
In: IEEE Vehicular Technology Conference (VTC-Spring), pp. 8, Helsinki, Finland, 2022.
Abstract | Links | BibTeX | Tags: Cooperative ITS, cooperative perception, Intelligent Transport Systems, sensor data sharing, vehicular communication
@inproceedings{Song:VTC-Spring:2022,
title = {Edge-Aided Sensor Data Sharing in Vehicular Communication Networks},
author = {R. Song and A. Hegde and N. Senel and A. Festag},
url = {https://ieeexplore.ieee.org/document/9860849},
doi = {10.1109/VTC2022-Spring54318.2022.9860849},
year = {2022},
date = {2022-03-22},
urldate = {2022-03-22},
booktitle = {IEEE Vehicular Technology Conference (VTC-Spring)},
pages = {8},
address = {Helsinki, Finland},
abstract = {Sensor data sharing in vehicular networks can significantly improve the range and accuracy of environmental perception for connected automated vehicles. Different concepts and schemes for dissemination and fusion of sensor data have been developed. It is common to these schemes that measurement errors of the sensors impair the perception quality and can result in road traffic accidents. Specifically, when the measurement error from the sensors – also referred as measurement noise – is unknown and time varying, the performance of the data fusion process is restricted, which represents a major challenge in the calibration of sensors. In this paper, we consider sensor data sharing and fusion in a vehicular network with both, vehicle-to-infrastructure and vehicle-to-vehicle communication. We propose a method, named Bidirectional Feedback Noise Estimation (BiFNoE), in which an edge server collects and caches sensor measurement data from vehicles. The edge estimates the noise and the targets alternately in double dynamic sliding time windows and enhances the distributed cooperative environment sensing at each vehicle with low communication costs. We evaluate the proposed algorithm and data dissemination strategy in an application scenario by simulation and show that the perception accuracy is on average improved by around 80 percent with only 12 kbps uplink and 28 kbps downlink bandwidth.},
keywords = {Cooperative ITS, cooperative perception, Intelligent Transport Systems, sensor data sharing, vehicular communication},
pubstate = {published},
tppubtype = {inproceedings}
}
Sensor data sharing in vehicular networks can significantly improve the range and accuracy of environmental perception for connected automated vehicles. Different concepts and schemes for dissemination and fusion of sensor data have been developed. It is common to these schemes that measurement errors of the sensors impair the perception quality and can result in road traffic accidents. Specifically, when the measurement error from the sensors – also referred as measurement noise – is unknown and time varying, the performance of the data fusion process is restricted, which represents a major challenge in the calibration of sensors. In this paper, we consider sensor data sharing and fusion in a vehicular network with both, vehicle-to-infrastructure and vehicle-to-vehicle communication. We propose a method, named Bidirectional Feedback Noise Estimation (BiFNoE), in which an edge server collects and caches sensor measurement data from vehicles. The edge estimates the noise and the targets alternately in double dynamic sliding time windows and enhances the distributed cooperative environment sensing at each vehicle with low communication costs. We evaluate the proposed algorithm and data dissemination strategy in an application scenario by simulation and show that the perception accuracy is on average improved by around 80 percent with only 12 kbps uplink and 28 kbps downlink bandwidth.
29.
Festag, A.; Udupa, S.; Garcia, L.; Wellens, R.; Hecht, M.; Ulfig, P.
End-to-End Performance Measurements of Drone Communications in 5G Cellular Networks Proceedings Article
In: IEEE Vehicular Technology Conference (VTC-Fall), pp. 6, Virtual, 2021.
Abstract | Links | BibTeX | Tags: drones, measurements, mobile communication, wireless communication
@inproceedings{Festag:VTC-Fall:2021,
title = {End-to-End Performance Measurements of Drone Communications in 5G Cellular Networks},
author = {A. Festag and S. Udupa and L. Garcia and R. Wellens and M. Hecht and P. Ulfig},
url = {https://ieeexplore.ieee.org/document/9625429},
doi = {10.1109/VTC2021-Fall52928.2021.9625429},
year = {2021},
date = {2021-09-27},
urldate = {2021-12-10},
booktitle = {IEEE Vehicular Technology Conference (VTC-Fall)},
pages = {6},
address = {Virtual},
abstract = {Cellular communications with its ubiquitous cellular coverage enable various use cases for long-distance aerial inspection, surveillance and monitoring with drones. For these use cases, the exchange of command & control and sensor data, such as video, require a reliable and low-latency communication link. In this paper, we present results of a measurement campaign of drone communications in an experimental 5G network. The measurement scenarios cover (i) the capacity and quality of the link between the drone and the ground station, (ii) the robustness of drone communications with the isolation provided by network slicing, and (iii) the stability of the link between drone and ground station for long-distance flights. The results indicate that cellular communications in principle meet the reliability and latency of video and command & control data for long-distance flights even when the performance of cellular network is optimized for terrestrial devices. The application of network slicing in future 5G networks has a great potential to protect the drone critical command & control data from undesired wireless interferers.},
keywords = {drones, measurements, mobile communication, wireless communication},
pubstate = {published},
tppubtype = {inproceedings}
}
Cellular communications with its ubiquitous cellular coverage enable various use cases for long-distance aerial inspection, surveillance and monitoring with drones. For these use cases, the exchange of command & control and sensor data, such as video, require a reliable and low-latency communication link. In this paper, we present results of a measurement campaign of drone communications in an experimental 5G network. The measurement scenarios cover (i) the capacity and quality of the link between the drone and the ground station, (ii) the robustness of drone communications with the isolation provided by network slicing, and (iii) the stability of the link between drone and ground station for long-distance flights. The results indicate that cellular communications in principle meet the reliability and latency of video and command & control data for long-distance flights even when the performance of cellular network is optimized for terrestrial devices. The application of network slicing in future 5G networks has a great potential to protect the drone critical command & control data from undesired wireless interferers.
30.
Maksimovski, D.; Facchi, C.; Festag, A.
Priority Maneuver (PriMa) Coordination for Connected and Automated Vehicles Proceedings Article
In: IEEE International Intelligent Transportation Systems Conference (ITSC), Virtual, 2021.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, maneuver coordination, V2X communication, vehicle automation
@inproceedings{Maksimovski:ITSC:2021,
title = {Priority Maneuver (PriMa) Coordination for Connected and Automated Vehicles},
author = {D. Maksimovski and C. Facchi and A. Festag},
url = {https://ieeexplore.ieee.org/document/9564923},
doi = {10.1109/ITSC48978.2021.9564923},
year = {2021},
date = {2021-09-19},
urldate = {2021-10-25},
booktitle = {IEEE International Intelligent Transportation Systems Conference (ITSC)},
address = {Virtual},
abstract = {Connected and automated vehicles (CAVs) are expected to achieve safe and efficient driving by the broadcast of maneuver intentions using vehicle-to-vehicle (V2V) communications. The cooperative maneuver coordination has a high potential to help CAVs solving challenging traffic situations. We present a novel approach for decentralized and generic maneuver coordination. Relying on an explicit exchange of coordination messages, the proposed Priority Maneuver (PriMa) approach introduces three levels of maneuver requests. The priorities help vehicles that request and accept maneuvers to take decisions by differentiating among desired, necessary and critical maneuvers. Advantages of the prioritization lie in scenarios with many vehicles and with several subsequent maneuvers. Furthermore, the Maneuver Coordination Message (MCM) is extended defining several MCM subtypes. The paper presents the design of PriMa and analyzes three main scenarios by simulations: (i) maneuver coordination between two vehicles with and without prioritization, (ii) coordination with more than two vehicles, and (iii) cascading maneuver. PriMa utilizes different communication patterns for the presented scenarios to enable safe, fast and efficient coordination. The simulation results demonstrate the advantages of PriMa compared to existing coordination approaches in the decision-making process.},
keywords = {Cooperative ITS, Intelligent Transport Systems, maneuver coordination, V2X communication, vehicle automation},
pubstate = {published},
tppubtype = {inproceedings}
}
Connected and automated vehicles (CAVs) are expected to achieve safe and efficient driving by the broadcast of maneuver intentions using vehicle-to-vehicle (V2V) communications. The cooperative maneuver coordination has a high potential to help CAVs solving challenging traffic situations. We present a novel approach for decentralized and generic maneuver coordination. Relying on an explicit exchange of coordination messages, the proposed Priority Maneuver (PriMa) approach introduces three levels of maneuver requests. The priorities help vehicles that request and accept maneuvers to take decisions by differentiating among desired, necessary and critical maneuvers. Advantages of the prioritization lie in scenarios with many vehicles and with several subsequent maneuvers. Furthermore, the Maneuver Coordination Message (MCM) is extended defining several MCM subtypes. The paper presents the design of PriMa and analyzes three main scenarios by simulations: (i) maneuver coordination between two vehicles with and without prioritization, (ii) coordination with more than two vehicles, and (iii) cascading maneuver. PriMa utilizes different communication patterns for the presented scenarios to enable safe, fast and efficient coordination. The simulation results demonstrate the advantages of PriMa compared to existing coordination approaches in the decision-making process.
31.
Delooz, Q.; Festag, A.; Vinel, A.
Congestion Aware Objects Filtering for Collective Perception Proceedings Article
In: 16th International Workshop on Communication Technologies for Vehicles (Nets4Cars), colocated with International Conference on Networked Systems 2021(NetSys 2021), published in Electronic Communications of the EASST, Virtual, 2021, (Vol. 80).
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication
@inproceedings{Delooz:Nets4Cars:2021,
title = {Congestion Aware Objects Filtering for Collective Perception},
author = {Q. Delooz and A. Festag and A. Vinel},
url = {https://festag-net.de/wp-content/uploads/2021_Delooz_Nets4Cars.pdf},
doi = {10.14279/tuj.eceasst.80.1160},
year = {2021},
date = {2021-09-13},
urldate = {2021-12-15},
booktitle = {16th International Workshop on Communication Technologies for Vehicles (Nets4Cars), colocated with International Conference on Networked Systems 2021(NetSys 2021), published in Electronic Communications of the EASST},
address = {Virtual},
abstract = {This paper addresses collective perception for connected and automated driving. It proposes the adaptation of filtering rules based on the currently available channel resources, referred to as Enhanced DCC-Aware Filtering (EDAF).},
note = {Vol. 80},
keywords = {Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper addresses collective perception for connected and automated driving. It proposes the adaptation of filtering rules based on the currently available channel resources, referred to as Enhanced DCC-Aware Filtering (EDAF).
32.
Song, R.; Festag, A.
Analysis of Existing Approaches for Information Sharing in Cooperative Intelligent Transport Systems – V2X Messaging and SENSORIS Proceedings Article
In: FISITA World Congress, Virtual, 2021.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication
@inproceedings{Song:FISITA:2021,
title = {Analysis of Existing Approaches for Information Sharing in Cooperative Intelligent Transport Systems – V2X Messaging and SENSORIS},
author = {R. Song and A. Festag},
url = {https://www.fisita.com/diary/fisita-world-mobility-summit-2021},
doi = {10.46720/F2020-ACM-012},
year = {2021},
date = {2021-09-01},
urldate = {2021-09-01},
booktitle = {FISITA World Congress},
address = {Virtual},
abstract = {Information sharing is essential for connected and automated driving and smart traffic driven by big data. It enables the acquisition of knowledge in cooperative intelligent transport systems (C-ITS), which ultimately increases the integrity and accuracy of road environmental data and thereby improves the efficiency and safety of the traffic system. Moreover, many cloud services and applications, such as self-healing High-Definition Map (HD Maps), demand massive information sharing by means of vehicle-to-X (V2X) communications. In this paper, we review two existing frameworks for information sharing in C-ITS, which are open, standardized and commonly accepted: V2X Messaging focuses on road safety and traffic efficiency based on ad hoc communications among vehicles, the roadside infrastructure and backends. SENSORIS primarily targets at data sharing with and among clouds, specifically for HD Maps. We analyze both frameworks considering technical criteria and selected use cases. Finally, we propose a hybrid network software architecture that combines both information sharing approaches and facilitates interworking between SENSORIS and V2X Messaging in order to enhance C-ITS applications.},
keywords = {Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication},
pubstate = {published},
tppubtype = {inproceedings}
}
Information sharing is essential for connected and automated driving and smart traffic driven by big data. It enables the acquisition of knowledge in cooperative intelligent transport systems (C-ITS), which ultimately increases the integrity and accuracy of road environmental data and thereby improves the efficiency and safety of the traffic system. Moreover, many cloud services and applications, such as self-healing High-Definition Map (HD Maps), demand massive information sharing by means of vehicle-to-X (V2X) communications. In this paper, we review two existing frameworks for information sharing in C-ITS, which are open, standardized and commonly accepted: V2X Messaging focuses on road safety and traffic efficiency based on ad hoc communications among vehicles, the roadside infrastructure and backends. SENSORIS primarily targets at data sharing with and among clouds, specifically for HD Maps. We analyze both frameworks considering technical criteria and selected use cases. Finally, we propose a hybrid network software architecture that combines both information sharing approaches and facilitates interworking between SENSORIS and V2X Messaging in order to enhance C-ITS applications.
33.
Hegde, A.; Stahl, R.; Lobo, S.; Festag, A.
Modeling Cellular Network Infrastructure in SUMO Proceedings Article
In: SUMO User Conference, Virtual, 2021.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, modeling, simulation, V2X communication
@inproceedings{Hegde:SUMO:2021,
title = {Modeling Cellular Network Infrastructure in SUMO},
author = {A. Hegde and R. Stahl and S. Lobo and A. Festag},
url = {https://www.eclipse.org/sumo/2021/},
doi = {10.52825/scp.v2i.97},
year = {2021},
date = {2021-09-01},
urldate = {2021-09-01},
booktitle = {SUMO User Conference},
address = {Virtual},
abstract = {Communication networks are becoming an increasingly important part of the mobility system. They allow traffic participants to be connected and to exchange information related to traffic and roads. The information exchange impacts the behavior of traffic participants, such as the selection of travel routes or their mobility dynamics. Considering infrastructure-based networks, the information exchange depends on the availability of the network infrastructure and the quality of the communication links. Specifically in urban areas, today's 4G and 5G networks deploy small cells of high capacity, which do not provide ubiquitous cellular coverage due to their small range, signal blocking, etc. Therefore, the accurate modeling of the network infrastructure and its integration in simulation scenarios in microscopic traffic simulation software is gaining relevance. Unlike traffic infrastructure, such as traffic lights, the simulation of a cellular network infrastructure is not natively supported in SUMO. Instead, the protocols, functions and entities of the communication system with the physical wireless transmission are modeled in a dedicated and specialized network simulator that is coupled with SUMO. The disadvantage of this approach is that the simulated SUMO entities, typically vehicles, are not aware which portions of the roads are covered by wireless cells and what quality the wireless communication links have.},
keywords = {Cooperative ITS, Intelligent Transport Systems, modeling, simulation, V2X communication},
pubstate = {published},
tppubtype = {inproceedings}
}
Communication networks are becoming an increasingly important part of the mobility system. They allow traffic participants to be connected and to exchange information related to traffic and roads. The information exchange impacts the behavior of traffic participants, such as the selection of travel routes or their mobility dynamics. Considering infrastructure-based networks, the information exchange depends on the availability of the network infrastructure and the quality of the communication links. Specifically in urban areas, today's 4G and 5G networks deploy small cells of high capacity, which do not provide ubiquitous cellular coverage due to their small range, signal blocking, etc. Therefore, the accurate modeling of the network infrastructure and its integration in simulation scenarios in microscopic traffic simulation software is gaining relevance. Unlike traffic infrastructure, such as traffic lights, the simulation of a cellular network infrastructure is not natively supported in SUMO. Instead, the protocols, functions and entities of the communication system with the physical wireless transmission are modeled in a dedicated and specialized network simulator that is coupled with SUMO. The disadvantage of this approach is that the simulated SUMO entities, typically vehicles, are not aware which portions of the roads are covered by wireless cells and what quality the wireless communication links have.
34.
Volk, G.; Delooz, Q.; Schiegg, F. A.; vonBernuth, A.; Festag, A.; Bringmann, O.
Towards Realistic Evaluation of Collective Perception for Connected and Automated Driving Proceedings Article
In: IEEE International Intelligent Transportation Systems Conference (ITSC), pp. 1049-1056, Virtual, 2021.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication
@inproceedings{Volk:ITSC:2021,
title = {Towards Realistic Evaluation of Collective Perception for Connected and Automated Driving},
author = {G. Volk and Q. Delooz and F. A. Schiegg and A. vonBernuth and A. Festag and O. Bringmann},
url = {https://ieeexplore.ieee.org/document/9564783},
doi = {10.1109/ITSC48978.2021.9564783},
year = {2021},
date = {2021-09-01},
urldate = {2021-09-01},
booktitle = {IEEE International Intelligent Transportation Systems Conference (ITSC)},
pages = {1049-1056},
address = {Virtual},
abstract = {Collective perception in Vehicle-to-Everything (V2X) communications allows vehicles to exchange preprocessed sensor data with other traffic participants. It is currently standardized by ETSI as a second generation V2X communication service. The use of collective perception as a communication service for future fully autonomous driving requires a thorough evaluation and validation. Most of the previous work on collective perception has considered large scale-simulations with a focus on communications. However, the perception pipeline used for collective perception is equally important and must not be neglected or over-simplified. Also, to study collective perception in detail, large-scale field testing is practically infeasible. In this paper we extend an existing simulation framework with a realistic model for V2X communications and sensor-data based processing delays. The result is a simulation framework that incorporates the entire collective perception pipeline, which enables to comprehensively study sensor-based perception. We demonstrate the capabilities of this enhanced framework by analyzing the delay of each component involved in the perception pipeline. This allows a detailed insight in end-to-end delays and the age of information within the environmental model of autonomous vehicles.},
keywords = {Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication},
pubstate = {published},
tppubtype = {inproceedings}
}
Collective perception in Vehicle-to-Everything (V2X) communications allows vehicles to exchange preprocessed sensor data with other traffic participants. It is currently standardized by ETSI as a second generation V2X communication service. The use of collective perception as a communication service for future fully autonomous driving requires a thorough evaluation and validation. Most of the previous work on collective perception has considered large scale-simulations with a focus on communications. However, the perception pipeline used for collective perception is equally important and must not be neglected or over-simplified. Also, to study collective perception in detail, large-scale field testing is practically infeasible. In this paper we extend an existing simulation framework with a realistic model for V2X communications and sensor-data based processing delays. The result is a simulation framework that incorporates the entire collective perception pipeline, which enables to comprehensively study sensor-based perception. We demonstrate the capabilities of this enhanced framework by analyzing the delay of each component involved in the perception pipeline. This allows a detailed insight in end-to-end delays and the age of information within the environmental model of autonomous vehicles.
35.
Maksimovski, D.; Festag, A.; Facchi, C.
A Survey on Decentralized Cooperative Maneuver Coordination for Connected and Automated Vehicles Proceedings Article
In: Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS), Virtual, 2021.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, maneuver coordination, V2X communication, vehicle automation
@inproceedings{Maksimovski:VEHITS:2021,
title = {A Survey on Decentralized Cooperative Maneuver Coordination for Connected and Automated Vehicles},
author = {D. Maksimovski and A. Festag and C. Facchi},
url = {https://www.scitepress.org/Papers/2021/104425/104425.pdf},
doi = {10.5220/0010442501000111},
year = {2021},
date = {2021-09-01},
urldate = {2021-09-01},
booktitle = {Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS)},
address = {Virtual},
abstract = {V2X communications can be applied for maneuver coordination of automated vehicles, where the vehicles exchange messages to inform each other of their driving intentions and to negotiate for joint maneuvers. For motion and maneuver planning of automated vehicles, the cooperative maneuver coordination extends the perception range of the sensors, enhances the planning horizon and allows complex interactions among the vehicles. For specific scenarios, various schemes for maneuver coordination of connected automated vehicles exist. Recently, several proposals for maneuver coordination have been made that address generic instead of specific scenarios and apply different schemes for the message exchange of driving intentions and maneuver negotiation. This paper presents use cases for maneuver coordination and classifies existing generic approaches for decentralized maneuver coordination considering implicit and explicit trajectory broadcast, cost values and space-time reservation. We systematically describe the approaches, compare them and derive future research topics.},
keywords = {Cooperative ITS, Intelligent Transport Systems, maneuver coordination, V2X communication, vehicle automation},
pubstate = {published},
tppubtype = {inproceedings}
}
V2X communications can be applied for maneuver coordination of automated vehicles, where the vehicles exchange messages to inform each other of their driving intentions and to negotiate for joint maneuvers. For motion and maneuver planning of automated vehicles, the cooperative maneuver coordination extends the perception range of the sensors, enhances the planning horizon and allows complex interactions among the vehicles. For specific scenarios, various schemes for maneuver coordination of connected automated vehicles exist. Recently, several proposals for maneuver coordination have been made that address generic instead of specific scenarios and apply different schemes for the message exchange of driving intentions and maneuver negotiation. This paper presents use cases for maneuver coordination and classifies existing generic approaches for decentralized maneuver coordination considering implicit and explicit trajectory broadcast, cost values and space-time reservation. We systematically describe the approaches, compare them and derive future research topics.
36.
Otto, T.; Festag, A.
Mehr Augen für sichereres Fahren - Car-to-X Kommunikation unterstützt Verkehrskoordination an Kreuzungen Miscellaneous
InnoVision, 2021.
Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, V2X communication
@misc{Otto:InnoVisions:2021,
title = {Mehr Augen für sichereres Fahren - Car-to-X Kommunikation unterstützt Verkehrskoordination an Kreuzungen},
author = {T. Otto and A. Festag},
url = {https://www.fraunhofer-innovisions.de/mobilitaet/mehr-augen-fuer-sichereres-fahren},
year = {2021},
date = {2021-03-21},
urldate = {2021-03-21},
howpublished = {InnoVision},
keywords = {Cooperative ITS, Intelligent Transport Systems, V2X communication},
pubstate = {published},
tppubtype = {misc}
}
37.
Hegde, A.; Festag, A.
Mode Switching Performance in Cellular-V2X Proceedings Article
In: IEEE Vehicular Networking Conference (VNC), virtual, 2020.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, performance, V2X communication
@inproceedings{Hegde:VNC:2020,
title = {Mode Switching Performance in Cellular-V2X},
author = {A. Hegde and A. Festag},
url = {https://ieeexplore.ieee.org/document/9318394},
doi = {10.1109/VNC51378.2020.9318394},
year = {2020},
date = {2020-12-16},
urldate = {2020-12-16},
booktitle = {IEEE Vehicular Networking Conference (VNC)},
address = {virtual},
abstract = {Cellular-V2X aims at supporting road safety and traffic management applications and introduces sidelink (PC5) as a new interface. These applications primarily rely on periodic broadcast of small-sized periodic messages and event-triggered notification messages. A key requirement of the applications is to facilitate uninterrupted exchange of messages among the vehicles irrespective of whether the vehicles are inside a base station coverage or not. In Cellular-V2X standardization, two resource allocation modes have been specified: when a vehicle is located inside the coverage of the cellular network, the corresponding base station manages the transmission resources for the direct message exchange. When a vehicle is outside of cellular coverage, it allocates its resources autonomously. The modes are also referred to as ``managed'' and ``unmanaged'' mode, or mode 3 and mode 4, respectively. In situations with imperfect cellular coverage by base stations, a vehicle needs to perform mode switching. The present work aims to understand the different phases of the mode switching procedure and to study the latency involved in each phase for both switching scenarios, mode 3 to 4 and vice versa. Considering a realistic road traffic scenario with a highway tunnel, we assess the impact of mode switch latency on the data transmission for a selected mode switch strategy.},
keywords = {Cooperative ITS, Intelligent Transport Systems, performance, V2X communication},
pubstate = {published},
tppubtype = {inproceedings}
}
Cellular-V2X aims at supporting road safety and traffic management applications and introduces sidelink (PC5) as a new interface. These applications primarily rely on periodic broadcast of small-sized periodic messages and event-triggered notification messages. A key requirement of the applications is to facilitate uninterrupted exchange of messages among the vehicles irrespective of whether the vehicles are inside a base station coverage or not. In Cellular-V2X standardization, two resource allocation modes have been specified: when a vehicle is located inside the coverage of the cellular network, the corresponding base station manages the transmission resources for the direct message exchange. When a vehicle is outside of cellular coverage, it allocates its resources autonomously. The modes are also referred to as ``managed'' and ``unmanaged'' mode, or mode 3 and mode 4, respectively. In situations with imperfect cellular coverage by base stations, a vehicle needs to perform mode switching. The present work aims to understand the different phases of the mode switching procedure and to study the latency involved in each phase for both switching scenarios, mode 3 to 4 and vice versa. Considering a realistic road traffic scenario with a highway tunnel, we assess the impact of mode switch latency on the data transmission for a selected mode switch strategy.
38.
Delooz, Q.; Riebl, R.; Festag, A.; Vinel, A.
Design and Performance of Congestion-Aware Collective Perception Proceedings Article
In: IEEE Vehicular Networking Conference (VNC), virtual, 2020.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication
@inproceedings{Delooz:VNC:2020,
title = {Design and Performance of Congestion-Aware Collective Perception},
author = {Q. Delooz and R. Riebl and A. Festag and A. Vinel},
url = {https://ieeexplore.ieee.org/document/9318335},
doi = {10.1109/VNC51378.2020.9318335},
year = {2020},
date = {2020-12-16},
urldate = {2021-09-01},
booktitle = {IEEE Vehicular Networking Conference (VNC)},
address = {virtual},
abstract = {In vehicular ad hoc networks, congestion control prevents the overloading of the wireless channel and ensures a fair distribution of the transmission resources. For ITS-G5-based vehicular networks, the European standardization by ETSI has specified a Decentralized Congestion Control (DCC) function at the access layer. This function controls the medium occupancy of a network node by enforcing maximum values of message transmission parameters. In the present paper, we study the impact of DCC on the performance of the collective perception service. This communication service enables vehicles and roadside stations to exchange messages with pre-processed sensor data. Since collective perception can considerably contribute to the network load, the transmission restrictions imposed by DCC affect the performance of the information exchange and the quality of the perception. The current design of collective perception in ETSI does not adapt the messages to the actual DCC constraints. We propose a novel approach for DCC-aware collective perception, which enhances the object filtering process of collective perception by dynamically adapting the message size to the DCC constraints and implicitly the message generation rate. Compared to the current ETSI design, the obtained results show a better quality of perception and channel usage, with a reduced message generation rate.},
keywords = {Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication},
pubstate = {published},
tppubtype = {inproceedings}
}
In vehicular ad hoc networks, congestion control prevents the overloading of the wireless channel and ensures a fair distribution of the transmission resources. For ITS-G5-based vehicular networks, the European standardization by ETSI has specified a Decentralized Congestion Control (DCC) function at the access layer. This function controls the medium occupancy of a network node by enforcing maximum values of message transmission parameters. In the present paper, we study the impact of DCC on the performance of the collective perception service. This communication service enables vehicles and roadside stations to exchange messages with pre-processed sensor data. Since collective perception can considerably contribute to the network load, the transmission restrictions imposed by DCC affect the performance of the information exchange and the quality of the perception. The current design of collective perception in ETSI does not adapt the messages to the actual DCC constraints. We propose a novel approach for DCC-aware collective perception, which enhances the object filtering process of collective perception by dynamically adapting the message size to the DCC constraints and implicitly the message generation rate. Compared to the current ETSI design, the obtained results show a better quality of perception and channel usage, with a reduced message generation rate.
39.
Senel, N.; Elger, G.; Festag, A.
Sensor Time Synchronization in Smart Road Infrastructure Proceedings Article
In: FISITA World Congress, Virtual, 2020.
Abstract | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication
@inproceedings{Senel:FISITA:2020,
title = {Sensor Time Synchronization in Smart Road Infrastructure},
author = {N. Senel and G. Elger and A. Festag},
year = {2020},
date = {2020-11-24},
urldate = {2020-11-24},
booktitle = {FISITA World Congress},
address = {Virtual},
abstract = {To enable efficient and secure traffic, the roadside infrastructure can be equipped with sensor nodes, which contain the physical sensors, a data link for vehicle-to-infrastructure (V2I) communication and computing capabilities for data processing. The sensor nodes in the infrastructure will support the future autonomous road traffic. A precise time synchronization between the sensors and the central fusion node is a requirement for accurate detection of the roadside users' trajectories. In this paper, two architecture options are considered: (i) distributed pre-processing with transmission of compressed data over wireless links, i.e., WLAN, for temporary setups and (ii) centralized processing with transmission of raw data over wired links for permanent installations, i.e., Ethernet. A prototype system is described, which is composed of cameras, computing hardware and network equipment running under Linux using the Robotic Operating System (ROS) as middle-ware. For both architectures, the Network Time Protocol (NTP/Chrony) for time synchronization and ROS specific functions for data synchronization are used. Measurement results for the two architectures are presented and compared.},
keywords = {Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication},
pubstate = {published},
tppubtype = {inproceedings}
}
To enable efficient and secure traffic, the roadside infrastructure can be equipped with sensor nodes, which contain the physical sensors, a data link for vehicle-to-infrastructure (V2I) communication and computing capabilities for data processing. The sensor nodes in the infrastructure will support the future autonomous road traffic. A precise time synchronization between the sensors and the central fusion node is a requirement for accurate detection of the roadside users' trajectories. In this paper, two architecture options are considered: (i) distributed pre-processing with transmission of compressed data over wireless links, i.e., WLAN, for temporary setups and (ii) centralized processing with transmission of raw data over wired links for permanent installations, i.e., Ethernet. A prototype system is described, which is composed of cameras, computing hardware and network equipment running under Linux using the Robotic Operating System (ROS) as middle-ware. For both architectures, the Network Time Protocol (NTP/Chrony) for time synchronization and ROS specific functions for data synchronization are used. Measurement results for the two architectures are presented and compared.
40.
Hegde, A.; Festag, A.
Artery-C: An OMNeT++ Based Discrete Event Simulation Framework for Cellular V2X (Short version) Proceedings Article
In: ACM 23rd Annual International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM), pp. 47–51, Alicante, Spain, 2020.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, simulation, V2X communication
@inproceedings{Hegde:MSWIM:2020,
title = {Artery-C: An OMNeT++ Based Discrete Event Simulation Framework for Cellular V2X (Short version)},
author = {A. Hegde and A. Festag},
url = {https://dl.acm.org/doi/10.1145/3416010.3423240},
doi = {10.1145/3416010.3423240},
year = {2020},
date = {2020-11-16},
urldate = {2020-11-16},
booktitle = {ACM 23rd Annual International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM)},
pages = {47–51},
address = {Alicante, Spain},
abstract = {Introduced with LTE Release 14, Cellular V2X enables device-to-device communication to support road safety and traffic efficiency applications. We present Artery-C, a simulation framework for the performance evaluation of Cellular V2X protocols and V2X applications. Our simulator relies on the simulation framework SimuLTE and substantially extends it by implementing control and user planes, a dedicated sidelink interface with specific focus on dynamic mode switching and some advanced features of 5G mobile networks, such as variable numerologies. Artery-C integrates seamlessly into the simulation framework Artery, which enables the simulation of standardized V2X messages at the facilities layer as well as the coupling to the mobility simulator SUMO. In order to demonstrate the capabilities of Artery-C, we evaluate V2X-based platooning as a representative use case and present results for mode 3, mode 4 and mode switching in a highway scenario.},
keywords = {Cooperative ITS, Intelligent Transport Systems, simulation, V2X communication},
pubstate = {published},
tppubtype = {inproceedings}
}
Introduced with LTE Release 14, Cellular V2X enables device-to-device communication to support road safety and traffic efficiency applications. We present Artery-C, a simulation framework for the performance evaluation of Cellular V2X protocols and V2X applications. Our simulator relies on the simulation framework SimuLTE and substantially extends it by implementing control and user planes, a dedicated sidelink interface with specific focus on dynamic mode switching and some advanced features of 5G mobile networks, such as variable numerologies. Artery-C integrates seamlessly into the simulation framework Artery, which enables the simulation of standardized V2X messages at the facilities layer as well as the coupling to the mobility simulator SUMO. In order to demonstrate the capabilities of Artery-C, we evaluate V2X-based platooning as a representative use case and present results for mode 3, mode 4 and mode switching in a highway scenario.