Publications
1.
Song, R.; Liang, C.; Cao, H.; Yan, Z.; Zimmer, W.; Gross, M.; Festag, A.; Knoll, A.
Collaborative Semantic Occupancy Prediction with Hybrid Feature Fusion in Connected Automated Vehicles Proceedings Article
In: 2024 Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, 2024.
Abstract | Links | BibTeX | Tags: Intelligent Transport Systems, perception, sensor data sharing
@inproceedings{Song:CVPR:2024,
title = {Collaborative Semantic Occupancy Prediction with Hybrid Feature Fusion in Connected Automated Vehicles},
author = {R. Song and C. Liang and H. Cao and Z. Yan and W. Zimmer and M. Gross and A. Festag and A. Knoll},
url = {https://cvpr.thecvf.com/Conferences/2024},
year = {2024},
date = {2024-02-27},
urldate = {2024-02-27},
booktitle = {2024 Conference on Computer Vision and Pattern Recognition (CVPR)},
address = {Seattle, WA, USA},
abstract = {Collaborative perception in automated vehicles leverages the exchange of information between agents, aiming to elevate perception results. Previous camera-based collaborative 3D perception methods typically employ 3D bounding boxes or bird’s eye views as representations of the environment. However, these approaches fall short in offering a comprehensive 3D environmental prediction. To bridge this gap, we introduce the first method for collaborative 3D semantic occupancy prediction. Particularly, it improves local 3D semantic occupancy predictions by hybrid fusion of (i) semantic and occupancy task features, and (ii) compressed orthogonal attention features shared between vehicles. Additionally, due to the lack of a collaborative perception dataset designed for semantic occupancy prediction, we augment a current collaborative perception dataset to include 3D collaborative semantic occupancy labels for amore robust evaluation. The experimental findings highlight that: (i) our collaborative semantic occupancy predictions excel above the results from single vehicles by over 30%, and (ii) models anchored on semantic occupancy outpace state-of-the-art collaborative 3D detection techniques in subsequent perception applications, showcasing enhanced accuracy and enriched semantic-awareness in road environments.},
keywords = {Intelligent Transport Systems, perception, sensor data sharing},
pubstate = {accepted},
tppubtype = {inproceedings}
}
Collaborative perception in automated vehicles leverages the exchange of information between agents, aiming to elevate perception results. Previous camera-based collaborative 3D perception methods typically employ 3D bounding boxes or bird’s eye views as representations of the environment. However, these approaches fall short in offering a comprehensive 3D environmental prediction. To bridge this gap, we introduce the first method for collaborative 3D semantic occupancy prediction. Particularly, it improves local 3D semantic occupancy predictions by hybrid fusion of (i) semantic and occupancy task features, and (ii) compressed orthogonal attention features shared between vehicles. Additionally, due to the lack of a collaborative perception dataset designed for semantic occupancy prediction, we augment a current collaborative perception dataset to include 3D collaborative semantic occupancy labels for amore robust evaluation. The experimental findings highlight that: (i) our collaborative semantic occupancy predictions excel above the results from single vehicles by over 30%, and (ii) models anchored on semantic occupancy outpace state-of-the-art collaborative 3D detection techniques in subsequent perception applications, showcasing enhanced accuracy and enriched semantic-awareness in road environments.
2.
Delooz, Q.; Festag, A.; Vinel, A.; Lobo, S.
Simulation-Based Performance Optimization of V2X Collective Perception by Adaptive Object Filtering Proceedings Article
In: IEEE Intelligent Vehicles Symposium (IV), Anchorage, Alaska, US, 2023.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication
@inproceedings{Delooz:IV:2023,
title = {Simulation-Based Performance Optimization of V2X Collective Perception by Adaptive Object Filtering},
author = {Q. Delooz and A. Festag and A. Vinel and S. Lobo},
url = {https://ieeexplore.ieee.org/document/10186788},
doi = {10.1109/IV55152.2023.10186788},
year = {2023},
date = {2023-04-04},
urldate = {2023-04-04},
booktitle = {IEEE Intelligent Vehicles Symposium (IV)},
address = {Anchorage, Alaska, US},
abstract = {V2X Collective Perception is the principle of exchanging sensor data among V2X-capable stations, such as vehicles or roadside units, by exchanging lists of perceived objects in the 5.9 GHz frequency band for road safety and traffic efficiency. An object can be anything relevant to traffic safety, e.g., vehicles or pedestrians. The current standardization of Collective Perception in Europe considers filtering objects for transmission based on their locally perceived dynamics and freshness to preserve channel resources. However, two remaining problems of object filtering are: information redundancy and adapting object filtering to the available channel resources. In this paper, we combine redundancy mitigation and congestion control-aware filtering. We evaluate the performance of the resulting object filtering techniques by realizing realistic, large-scale simulations of a mid-size city in Germany. We assess the performance using a scoring metric. The results show better information redundancy control and adjustable channel usage for object filtering.},
keywords = {Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication},
pubstate = {published},
tppubtype = {inproceedings}
}
V2X Collective Perception is the principle of exchanging sensor data among V2X-capable stations, such as vehicles or roadside units, by exchanging lists of perceived objects in the 5.9 GHz frequency band for road safety and traffic efficiency. An object can be anything relevant to traffic safety, e.g., vehicles or pedestrians. The current standardization of Collective Perception in Europe considers filtering objects for transmission based on their locally perceived dynamics and freshness to preserve channel resources. However, two remaining problems of object filtering are: information redundancy and adapting object filtering to the available channel resources. In this paper, we combine redundancy mitigation and congestion control-aware filtering. We evaluate the performance of the resulting object filtering techniques by realizing realistic, large-scale simulations of a mid-size city in Germany. We assess the performance using a scoring metric. The results show better information redundancy control and adjustable channel usage for object filtering.
3.
Delooz, Q.; Vinel, A.; Festag, A.
Optimizing the Channel Resource Usage for Sensor Data Sharing with V2X Communications Journal Article
In: at – Automatisierungstechnik, vol. 71, no. 4, pp. 311-317, 2023.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication
@article{Delooz:ATJournal:2023,
title = {Optimizing the Channel Resource Usage for Sensor Data Sharing with V2X Communications},
author = {Q. Delooz and A. Vinel and A. Festag},
url = {2023-02-21},
doi = {10.1515/auto-2022-0162},
year = {2023},
date = {2023-04-01},
urldate = {2023-02-21},
journal = {at – Automatisierungstechnik},
volume = {71},
number = {4},
pages = {311-317},
abstract = {Sensor data sharing in V2X communication enables vehicles to exchange locally perceived sensor data with each other to increase their environmental awareness. It relies on the periodic exchange of selected, safety-relevant objects. Object selection is used to reduce channel resource usage. Additionally, vehicles use congestion control mechanisms to avoid overloading the channel. Currently, both object selection and congestion control mechanisms operate independently. We study a congestion-aware object filtering approach combining both and improving the performance of sensor data sharing. Die Übertragung von Sensordaten mit V2X-Kommunikation ermöglicht Fahrzeugen, lokale Umgebungsinformationen auszutauschen, um die Wahrnehmungsreichweite zu erhöhen. Der Sensordatenaustausch basiert auf der periodischen Übertragung sicherheitsrelevanter Objekte. Dabei wird die Anzahl der Objekte reduziert, um die Datenlast zu verringern. Zusätzlich steuern Mechanismen die Datenlast um eine Überlast zu vermeiden. Bisher arbeiten die Objektauswahl und die Datenüberlaststeuerung unabhängig voneinander. Wir untersuchen einen kombinierten Ansatz zur Objektfilterung, der die Performanz des Sensordatenaustauschs verbessert.},
keywords = {Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication},
pubstate = {published},
tppubtype = {article}
}
Sensor data sharing in V2X communication enables vehicles to exchange locally perceived sensor data with each other to increase their environmental awareness. It relies on the periodic exchange of selected, safety-relevant objects. Object selection is used to reduce channel resource usage. Additionally, vehicles use congestion control mechanisms to avoid overloading the channel. Currently, both object selection and congestion control mechanisms operate independently. We study a congestion-aware object filtering approach combining both and improving the performance of sensor data sharing. Die Übertragung von Sensordaten mit V2X-Kommunikation ermöglicht Fahrzeugen, lokale Umgebungsinformationen auszutauschen, um die Wahrnehmungsreichweite zu erhöhen. Der Sensordatenaustausch basiert auf der periodischen Übertragung sicherheitsrelevanter Objekte. Dabei wird die Anzahl der Objekte reduziert, um die Datenlast zu verringern. Zusätzlich steuern Mechanismen die Datenlast um eine Überlast zu vermeiden. Bisher arbeiten die Objektauswahl und die Datenüberlaststeuerung unabhängig voneinander. Wir untersuchen einen kombinierten Ansatz zur Objektfilterung, der die Performanz des Sensordatenaustauschs verbessert.
4.
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.
5.
Hegde, A.; Lobos, S.; Festag, A.
Cellular-V2X for Vulnerable Road User Protection in Cooperative ITS Proceedings Article
In: WiMob, Thessaloniki, Greece, 2022.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication
@inproceedings{Hegde::2021,
title = {Cellular-V2X for Vulnerable Road User Protection in Cooperative ITS},
author = {A. Hegde and S. Lobos and A. Festag},
url = {http://www.wimob.org/wimob2022/programme.html},
year = {2022},
date = {2022-10-11},
urldate = {2022-10-11},
booktitle = {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 = {Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication},
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.
6.
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.
7.
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.
8.
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).
9.
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.
10.
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.
11.
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.
12.
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.
13.
Delooz, Q.; Festag, A.; Vinel, A.
Revisiting Message Generation Strategies for Collective Perception in Connected and Automated Driving Proceedings Article
In: 9th International Conference on Advances in Vehicular Systems, Technologies and Applications (VEHICULAR), Porto, Portugal, 2020, ISBN: 978-1-61208-795-5.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication
@inproceedings{Delooz:VEHICULAR:2020,
title = {Revisiting Message Generation Strategies for Collective Perception in Connected and Automated Driving},
author = {Q. Delooz and A. Festag and A. Vinel},
url = {https://www.thinkmind.org/articles/vehicular_2020_1_80_30039.pdf},
isbn = {978-1-61208-795-5},
year = {2020},
date = {2020-10-18},
urldate = {2020-10-18},
booktitle = {9th International Conference on Advances in Vehicular Systems, Technologies and Applications (VEHICULAR)},
address = {Porto, Portugal},
abstract = {Collective perception enables vehicles to exchange preprocessed sensor data and is being standardized as a 2nd generation V2X communication service. The European standardization in ETSI foresees the exchange of detected objects and defined a dedicated message type (Collective Perception Message, CPM) with rules to decide when and with which objects the message should be generated, referred to as generation rules. The choice of these rules is not straightforward and influences both channel load and perception quality. For the object inclusion, ETSI currently follows a similar policy as for the generation of Cooperative Awareness Messages (CAM): The objects are filtered based on their dynamics. We regard this approach as conservative. The present paper revisits the generation rules for the CPM and applies two approaches for object inclusion to the CPM – the conservative strategy of ETSI and a more 'greedy' strategy. We assess the performance by discrete-event simulations in a scenario representing a city with realistic vehicle densities and mobility patterns. The simulations take into account the effects imposed by decentralized congestion control. Considering that ETSI currently follows the conservative strategy, we conclude that the application of a greedy strategy improves the perception quality in low-density scenarios.},
keywords = {Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication},
pubstate = {published},
tppubtype = {inproceedings}
}
Collective perception enables vehicles to exchange preprocessed sensor data and is being standardized as a 2nd generation V2X communication service. The European standardization in ETSI foresees the exchange of detected objects and defined a dedicated message type (Collective Perception Message, CPM) with rules to decide when and with which objects the message should be generated, referred to as generation rules. The choice of these rules is not straightforward and influences both channel load and perception quality. For the object inclusion, ETSI currently follows a similar policy as for the generation of Cooperative Awareness Messages (CAM): The objects are filtered based on their dynamics. We regard this approach as conservative. The present paper revisits the generation rules for the CPM and applies two approaches for object inclusion to the CPM – the conservative strategy of ETSI and a more 'greedy' strategy. We assess the performance by discrete-event simulations in a scenario representing a city with realistic vehicle densities and mobility patterns. The simulations take into account the effects imposed by decentralized congestion control. Considering that ETSI currently follows the conservative strategy, we conclude that the application of a greedy strategy improves the perception quality in low-density scenarios.
14.
Delooz, Q.; Festag, A.
Network Load Adaptation for Collective Perception in V2X Communication Proceedings Article
In: IEEE International Conference on Connected Vehicles and Expo (ICCVE), Graz, Austria, 2019.
Abstract | Links | BibTeX | Tags: Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication
@inproceedings{Delooz:ICCVE:2019,
title = {Network Load Adaptation for Collective Perception in V2X Communication},
author = {Q. Delooz and A. Festag},
url = {https://ieeexplore.ieee.org/document/8964988},
doi = {10.1109/ICCVE45908.2019.8964988},
year = {2019},
date = {2019-11-04},
urldate = {2019-11-04},
booktitle = {IEEE International Conference on Connected Vehicles and Expo (ICCVE)},
address = {Graz, Austria},
abstract = {Collective perception uses V2X communications to increase the perception capabilities of vehicles. Relying on the perceived data from their local sensors, nodes exchange information about the objects they detect in their surroundings. An object can be anything significant for the nodes' safety, e.g., obstacles on the road, other vehicles or pedestrians. The amount of data generated by each node is determined by the number of perceived objects and the generation frequency of the messages carrying the detected objects. Considering the limited bandwidth of the wireless channel, the data load generated by collective perception can easily exceed the channel capacity. In this paper, we investigate three schemes that filter the number of objects in the messages and thereby adjust the network load in order to optimize the transmission of perceived objects. Our simulation-based performance evaluation indicates that the use of filtering is an effective approach to improve network-related performance metrics, whereas the expected impairment of the perception quality is rather small. The comparison of the filtering algorithms provide insights into the tradeoff between network-related metrics and perception quality.},
keywords = {Cooperative ITS, Intelligent Transport Systems, sensor data sharing, V2X communication},
pubstate = {published},
tppubtype = {inproceedings}
}
Collective perception uses V2X communications to increase the perception capabilities of vehicles. Relying on the perceived data from their local sensors, nodes exchange information about the objects they detect in their surroundings. An object can be anything significant for the nodes' safety, e.g., obstacles on the road, other vehicles or pedestrians. The amount of data generated by each node is determined by the number of perceived objects and the generation frequency of the messages carrying the detected objects. Considering the limited bandwidth of the wireless channel, the data load generated by collective perception can easily exceed the channel capacity. In this paper, we investigate three schemes that filter the number of objects in the messages and thereby adjust the network load in order to optimize the transmission of perceived objects. Our simulation-based performance evaluation indicates that the use of filtering is an effective approach to improve network-related performance metrics, whereas the expected impairment of the perception quality is rather small. The comparison of the filtering algorithms provide insights into the tradeoff between network-related metrics and perception quality.