The Experts below are selected from a list of 67314 Experts worldwide ranked by ideXlab platform
Ahmad El Assaad - One of the best experts on this subject based on the ideXlab platform.
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VTC Spring - Predictive Quality of Service: Adaptation of Platoon Inter-Vehicle Distance to Packet Inter-Reception Time
2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring), 2020Co-Authors: Andreas Pfadler, Ahmad El Assaad, Guillaume Jomod, Peter JungAbstract:Vehicle-to-everything (V2X) communication is seen as an enabler of high-density platooning as part of more environmentally friendly future transportation systems. Indeed, in high-density platooning, trucks are able to reduce their overall fuel consumption. Compared to platooning systems exclusively based on sensors, V2X enabled platooning systems can drive smaller inter-vehicle distances. They are then able to achieve this fuel consumption reduction thanks to the decreased air drag. It has been shown that the performance of the application is dependent on the performance of the communications system. The application therefore needs to be aware of the maximal tolerable communication degradation that keeps the platoon safe considering its driving parameters. In this article, we derive the relationship between the maximal tolerable packet losses, measured as the packet inter-Reception Time, and the intervehicle distance. We first study the relationship between these parameters through the analysis of simulation data. We then derive a functional link by fitting different statistical models. Finally, we apply the resulting models to packet inter-Reception Time measurements obtained in simulation of platoons supported by IEEE 802. 11p driving through varying surrounding traffic densities.
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Packet Inter-Reception Time Conditional Density Estimation Based on Surrounding Traffic Distribution
IEEE Open Journal of Intelligent Transportation Systems, 2020Co-Authors: Guillaume Jornod, Ahmad El Assaad, Thomas KurnerAbstract:Cooperation is an enabler for autonomous vehicles. A promising application of cooperative driving is high-density platooning, where trucks drive with low inter-vehicle distances. It aims at increasing the road and fuel efficiency whilst guaranteeing safety. The safe and efficient coordination of the control requires the regular and reliable exchange of V2V messages. The performance of the vehicular application has been shown to be strongly affected by the variation of the performances of the communications system. To be able to adapt their functional settings to these variations, vehicles need the ability to predict it. We present a prediction model for the packet inter-Reception Time platoon messages in an IEEE 802.11p network. This performance indicator is the subject of extensive research as it captures the irregularity of input for the control loop. The prediction model uses conditional density estimation based on the exponential distribution. We fit this model using a multi-layer perceptron regressor based on features representing the surrounding communication environment. The presented results are based on data collected during a full scale platooning simulations using ns-3 and SUMO. We compare different environment abstraction models and show the potential of on-line learning.
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prediction of packet inter Reception Time for platooning using conditional exponential distribution
International Symposium on Wireless Communication Systems, 2019Co-Authors: Guillaume Jornod, Ahmad El Assaad, Andreas Kwoczek, Thomas KurnerAbstract:We present a conditional exponential distribution model for the prediction of the packet inter-Reception Time. This value is our objective in terms of quality of service prediction for a high-density platooning application. This application indeed requires the exchange of information with low latency and high reliability. The prediction of the packet inter-Reception Time is therefore of high interest for this scenario.We extend our discrete kernel density estimation model to a continuous model based on the parametrization of an exponential distribution. In this model, the rate of the distribution is a function of our predictors, the inter-antenna distance and the spatial distribution of the surrounding communicating vehicles. We approach this function using a multi-layer perceptron regressor for different granularity values of our spatial model.Based on simulation data obtained with a combination of ns-3 and SUMO, we show that our model performs better than our previous model. This performance, combined with the advantages of being continuous and being able to be trained on-line, is promising for a further deployment and test on other scenarios. We present further results on the influence of the interaction between inter-antenna distance and spatial distribution of the communicating vehicles. Finally, we show a successful example of on-line instantaneous prediction of the packet inter-Reception Time along with the observed values of the predictors and the experienced packet inter-Reception Time.
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packet inter Reception Time modeling for high density platooning in varying surrounding traffic density
European Conference on Networks and Communications, 2019Co-Authors: Guillaume Jornod, Ahmad El Assaad, Andreas Kwoczek, Thomas KurnerAbstract:A recent feature of communications systems is the agile quality of service adaptation, in which the application and the communications system exchange requirements and prediction of quality of service. The application first provides its quality of service requirement. The communications system tries to enforce it, and makes a prediction of the available quality of service. Finally, the application adapts its settings to the future quality of service and provides updated requirements. Though this concept is originally designed for cellular-based technologies, it is also applicable to ad-hoc communication systems.In this paper, we focus on the prediction of quality of service for ad-hoc communications in a high-density platooning system. The quality of service of interest is the packet inter-Reception Time in an IEEE 802.11p network. Our platooning system drives through different vehicular traffic conditions, in which we gather transmission and position data. We then analyze the distribution of the packet inter-Reception Time to select the model features and then fit multiple distribution models. This empirical prediction modeling will then be the baseline for future modeling.
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ISWCS - Prediction of Packet Inter-Reception Time for Platooning using Conditional Exponential Distribution
2019 16th International Symposium on Wireless Communication Systems (ISWCS), 2019Co-Authors: Guillaume Jornod, Ahmad El Assaad, Andreas Kwoczek, Thomas KurnerAbstract:We present a conditional exponential distribution model for the prediction of the packet inter-Reception Time. This value is our objective in terms of quality of service prediction for a high-density platooning application. This application indeed requires the exchange of information with low latency and high reliability. The prediction of the packet inter-Reception Time is therefore of high interest for this scenario.We extend our discrete kernel density estimation model to a continuous model based on the parametrization of an exponential distribution. In this model, the rate of the distribution is a function of our predictors, the inter-antenna distance and the spatial distribution of the surrounding communicating vehicles. We approach this function using a multi-layer perceptron regressor for different granularity values of our spatial model.Based on simulation data obtained with a combination of ns-3 and SUMO, we show that our model performs better than our previous model. This performance, combined with the advantages of being continuous and being able to be trained on-line, is promising for a further deployment and test on other scenarios. We present further results on the influence of the interaction between inter-antenna distance and spatial distribution of the communicating vehicles. Finally, we show a successful example of on-line instantaneous prediction of the packet inter-Reception Time along with the observed values of the predictors and the experienced packet inter-Reception Time.
Peter Jung - One of the best experts on this subject based on the ideXlab platform.
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VTC Spring - Predictive Quality of Service: Adaptation of Platoon Inter-Vehicle Distance to Packet Inter-Reception Time
2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring), 2020Co-Authors: Andreas Pfadler, Ahmad El Assaad, Guillaume Jomod, Peter JungAbstract:Vehicle-to-everything (V2X) communication is seen as an enabler of high-density platooning as part of more environmentally friendly future transportation systems. Indeed, in high-density platooning, trucks are able to reduce their overall fuel consumption. Compared to platooning systems exclusively based on sensors, V2X enabled platooning systems can drive smaller inter-vehicle distances. They are then able to achieve this fuel consumption reduction thanks to the decreased air drag. It has been shown that the performance of the application is dependent on the performance of the communications system. The application therefore needs to be aware of the maximal tolerable communication degradation that keeps the platoon safe considering its driving parameters. In this article, we derive the relationship between the maximal tolerable packet losses, measured as the packet inter-Reception Time, and the intervehicle distance. We first study the relationship between these parameters through the analysis of simulation data. We then derive a functional link by fitting different statistical models. Finally, we apply the resulting models to packet inter-Reception Time measurements obtained in simulation of platoons supported by IEEE 802. 11p driving through varying surrounding traffic densities.
Thomas Kurner - One of the best experts on this subject based on the ideXlab platform.
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Packet Inter-Reception Time Conditional Density Estimation Based on Surrounding Traffic Distribution
IEEE Open Journal of Intelligent Transportation Systems, 2020Co-Authors: Guillaume Jornod, Ahmad El Assaad, Thomas KurnerAbstract:Cooperation is an enabler for autonomous vehicles. A promising application of cooperative driving is high-density platooning, where trucks drive with low inter-vehicle distances. It aims at increasing the road and fuel efficiency whilst guaranteeing safety. The safe and efficient coordination of the control requires the regular and reliable exchange of V2V messages. The performance of the vehicular application has been shown to be strongly affected by the variation of the performances of the communications system. To be able to adapt their functional settings to these variations, vehicles need the ability to predict it. We present a prediction model for the packet inter-Reception Time platoon messages in an IEEE 802.11p network. This performance indicator is the subject of extensive research as it captures the irregularity of input for the control loop. The prediction model uses conditional density estimation based on the exponential distribution. We fit this model using a multi-layer perceptron regressor based on features representing the surrounding communication environment. The presented results are based on data collected during a full scale platooning simulations using ns-3 and SUMO. We compare different environment abstraction models and show the potential of on-line learning.
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prediction of packet inter Reception Time for platooning using conditional exponential distribution
International Symposium on Wireless Communication Systems, 2019Co-Authors: Guillaume Jornod, Ahmad El Assaad, Andreas Kwoczek, Thomas KurnerAbstract:We present a conditional exponential distribution model for the prediction of the packet inter-Reception Time. This value is our objective in terms of quality of service prediction for a high-density platooning application. This application indeed requires the exchange of information with low latency and high reliability. The prediction of the packet inter-Reception Time is therefore of high interest for this scenario.We extend our discrete kernel density estimation model to a continuous model based on the parametrization of an exponential distribution. In this model, the rate of the distribution is a function of our predictors, the inter-antenna distance and the spatial distribution of the surrounding communicating vehicles. We approach this function using a multi-layer perceptron regressor for different granularity values of our spatial model.Based on simulation data obtained with a combination of ns-3 and SUMO, we show that our model performs better than our previous model. This performance, combined with the advantages of being continuous and being able to be trained on-line, is promising for a further deployment and test on other scenarios. We present further results on the influence of the interaction between inter-antenna distance and spatial distribution of the communicating vehicles. Finally, we show a successful example of on-line instantaneous prediction of the packet inter-Reception Time along with the observed values of the predictors and the experienced packet inter-Reception Time.
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packet inter Reception Time modeling for high density platooning in varying surrounding traffic density
European Conference on Networks and Communications, 2019Co-Authors: Guillaume Jornod, Ahmad El Assaad, Andreas Kwoczek, Thomas KurnerAbstract:A recent feature of communications systems is the agile quality of service adaptation, in which the application and the communications system exchange requirements and prediction of quality of service. The application first provides its quality of service requirement. The communications system tries to enforce it, and makes a prediction of the available quality of service. Finally, the application adapts its settings to the future quality of service and provides updated requirements. Though this concept is originally designed for cellular-based technologies, it is also applicable to ad-hoc communication systems.In this paper, we focus on the prediction of quality of service for ad-hoc communications in a high-density platooning system. The quality of service of interest is the packet inter-Reception Time in an IEEE 802.11p network. Our platooning system drives through different vehicular traffic conditions, in which we gather transmission and position data. We then analyze the distribution of the packet inter-Reception Time to select the model features and then fit multiple distribution models. This empirical prediction modeling will then be the baseline for future modeling.
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ISWCS - Prediction of Packet Inter-Reception Time for Platooning using Conditional Exponential Distribution
2019 16th International Symposium on Wireless Communication Systems (ISWCS), 2019Co-Authors: Guillaume Jornod, Ahmad El Assaad, Andreas Kwoczek, Thomas KurnerAbstract:We present a conditional exponential distribution model for the prediction of the packet inter-Reception Time. This value is our objective in terms of quality of service prediction for a high-density platooning application. This application indeed requires the exchange of information with low latency and high reliability. The prediction of the packet inter-Reception Time is therefore of high interest for this scenario.We extend our discrete kernel density estimation model to a continuous model based on the parametrization of an exponential distribution. In this model, the rate of the distribution is a function of our predictors, the inter-antenna distance and the spatial distribution of the surrounding communicating vehicles. We approach this function using a multi-layer perceptron regressor for different granularity values of our spatial model.Based on simulation data obtained with a combination of ns-3 and SUMO, we show that our model performs better than our previous model. This performance, combined with the advantages of being continuous and being able to be trained on-line, is promising for a further deployment and test on other scenarios. We present further results on the influence of the interaction between inter-antenna distance and spatial distribution of the communicating vehicles. Finally, we show a successful example of on-line instantaneous prediction of the packet inter-Reception Time along with the observed values of the predictors and the experienced packet inter-Reception Time.
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EuCNC - Packet Inter-Reception Time Modeling for High-Density Platooning in Varying Surrounding Traffic Density
2019 European Conference on Networks and Communications (EuCNC), 2019Co-Authors: Guillaume Jornod, Ahmad El Assaad, Andreas Kwoczek, Thomas KurnerAbstract:A recent feature of communications systems is the agile quality of service adaptation, in which the application and the communications system exchange requirements and prediction of quality of service. The application first provides its quality of service requirement. The communications system tries to enforce it, and makes a prediction of the available quality of service. Finally, the application adapts its settings to the future quality of service and provides updated requirements. Though this concept is originally designed for cellular-based technologies, it is also applicable to ad-hoc communication systems.In this paper, we focus on the prediction of quality of service for ad-hoc communications in a high-density platooning system. The quality of service of interest is the packet inter-Reception Time in an IEEE 802.11p network. Our platooning system drives through different vehicular traffic conditions, in which we gather transmission and position data. We then analyze the distribution of the packet inter-Reception Time to select the model features and then fit multiple distribution models. This empirical prediction modeling will then be the baseline for future modeling.
Kyungjoon Park - One of the best experts on this subject based on the ideXlab platform.
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beat beacon inter Reception Time ensured adaptive transmission for vehicle to vehicle safety communication
Sensors, 2019Co-Authors: Sunghwa Son, Kyungjoon ParkAbstract:To improve vehicle safety, vehicular ad hoc networks (VANETs) periodically broadcast safety messages known as beacons. Consequently, it becomes safety critical to guarantee the Timely Reception of periodic beacons under the Time-varying environments of VANET. However, existing approaches typically measure the packet delivery ratio, which is a Time-average metric that does not consider the temporal behavior associated with beacon Reception. In this paper, to properly reflect the temporal aspect of beacon Reception, we propose a congestion control algorithm, Beacon inter-Reception Time Ensured Adaptive Transmission (BEAT). The proposed algorithm tightly regulates the beacon inter-Reception Time compared to conventional techniques, which can significantly improve vehicle safety. Our simulation results demonstrate the effectiveness of the proposed scheme.
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Analysis of Safety Beacon Inter Reception Time in ETSI DCC Algorithm
2015Co-Authors: Sunghwa Son, Kyungjoon ParkAbstract:운전자에게 안전과 편의를 제공하기 위해서 Vehicleto-Vehicle (V2V) 혹은 Vehicle-to-Infrastructure (V2I) 통신을 하는 Vehicular Ad-hoc Network (VANET)에 대한 연구가 활발히 진행되고 있다. 차량간 통신에서 운전자의 안전을 위해 주기적인 안전 메시지를 주고 받으며 차량의 속도, 위치, 브레이크 상태 등의 정보를 전파하여 이것을 통해 사고를 예방할 수 있다. 미국에서는 IEEE Wireless Access in Vehicular Environment (WAVE)[1], 유럽에서는 European Telecommunications Standards Institute (ETSI) Intelligent Transportation System (ITS)[2]라는 이름으로 표준을 확립하였다. ETSI 에서는 차량 통신의 혼잡제어를 위해 Decentralized Congestion Control (DCC) 알고리즘을 제안하였다. 하지만 DCC 알고리즘에 대한 연구에서 DCC 알고리즘을 적용했지만 혼잡제어의 성능이 기대에 미치지 못하는 연구결과가 존재한다 [3]-[5]. 이 밖에도 근접한 차량임에도 불구하고 DCC 알고리즘의 상태차이로 인해 네트워크 자원을 사용함에 있어 불균형을 초래하여 전송속도의 차이 및 공정성문제가 발생하기도 한다. 이러한 문제는 차량 통신에서 주변 차량에게 정보를 보내지 못하거나 주위 차량의 정보를 받지 못하는 정보의 부재를 일으켜 운전자의 안전을 보장하지 못해 사고의 위험으로 귀결됨에 따라 반드시 해결해야 하는 문제다. 본 논문에서는 차량 통신환경에서 혼잡제어를 위해 유럽 ETSI 에서 제안한 DCC 알고리즘에 대해 살펴보고 실험을 통해 Periodic Safety Beacon 수신의 평가지표로서의 중요성과 DCC 혼잡제어 알고리즘의 Periodic Safety Beacon 수신 성능을 알아본다. II. 본 론
Andreas Pfadler - One of the best experts on this subject based on the ideXlab platform.
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VTC Spring - Predictive Quality of Service: Adaptation of Platoon Inter-Vehicle Distance to Packet Inter-Reception Time
2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring), 2020Co-Authors: Andreas Pfadler, Ahmad El Assaad, Guillaume Jomod, Peter JungAbstract:Vehicle-to-everything (V2X) communication is seen as an enabler of high-density platooning as part of more environmentally friendly future transportation systems. Indeed, in high-density platooning, trucks are able to reduce their overall fuel consumption. Compared to platooning systems exclusively based on sensors, V2X enabled platooning systems can drive smaller inter-vehicle distances. They are then able to achieve this fuel consumption reduction thanks to the decreased air drag. It has been shown that the performance of the application is dependent on the performance of the communications system. The application therefore needs to be aware of the maximal tolerable communication degradation that keeps the platoon safe considering its driving parameters. In this article, we derive the relationship between the maximal tolerable packet losses, measured as the packet inter-Reception Time, and the intervehicle distance. We first study the relationship between these parameters through the analysis of simulation data. We then derive a functional link by fitting different statistical models. Finally, we apply the resulting models to packet inter-Reception Time measurements obtained in simulation of platoons supported by IEEE 802. 11p driving through varying surrounding traffic densities.
