Impact of Communication Loss on MPC based Cooperative Adaptive Cruise Control and Platooning

Razzaghpour, Mahdi; Shahram, Shahriar; Valiente, Rodolfo; Fallah, Yaser P.

doi:10.1109/vtc2021-fall52928.2021.9625177

Cited by 14 publications

(8 citation statements)

References 20 publications

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“…Therefore, controllers rely solely on local data to achieve platoon-wide performance. We used an All-Predecessor-Leader-Following (APLF) topology [22]. This paper considers V2V communication and local sensor measurements.…”

Section: Resultsmentioning

confidence: 99%

“…Communication issues can greatly affect the performance of CACC systems. If communication delays are too long or transmission rates are too low, string stability and other performance characteristics for a specific time gap may no longer be assured [22]. As a result, the transmission number must be large enough and packet delays must be short enough to achieve the desired platooning behavior [23].…”

Section: A Cooperative Adaptive Cruise Control (Cacc)mentioning

confidence: 99%

“…2) Control-aware Triggering Making explicit decisions based on current control system states results in a control-aware approach [35]. In desirable states, control systems perform modestly, whereas, in undesirable states, systems change their states and are given higher priority for data transmission.…”

Section: ) Absolute Triggeringmentioning

confidence: 99%

See 2 more Smart Citations

Predictive Model-Based and Control-Aware Communication Strategies for Cooperative Adaptive Cruise Control

Razzaghpour

Valiente

Zaman

et al. 2023

IEEE Open J. Intell. Transp. Syst.

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Utilizing Vehicle-to-everything (V2X) communication technologies, vehicle platooning systems are expected to realize a new paradigm of cooperative driving with higher levels of traffic safety and efficiency. Connected and Autonomous Vehicles (CAVs) need to have proper awareness of the traffic context. The cooperative platoon's performance will be influenced by the communication strategy. In particular, time-triggered or event-triggered are of interest here. The expenses related to communication will increase significantly as the number of connected entities increases. Periodic communication can be relaxed to more flexible aperiodic or event-triggered implementations while maintaining desired levels of performance. This paper proposes a predictive model-based and control-aware communication solution for vehicle platoons. The method uses a fully distributed Event-Triggered Communication (ETC) strategy combined with Model-Based Communication (MBC) and aims to minimize communication resource usage while preserving desired closed-loop performance characteristics. In our method, each vehicle runs a remote vehicle state estimator based on the most recently communicated model and the event-driven communication scheme only updates the model when the performance metric error exceeds a certain threshold. Our approach achieves a significant reduction in the average communication rate (82%) while only slightly reducing control performance (e.g., less than 1% speed deviation).

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Section: Resultsmentioning

confidence: 99%

Section: A Cooperative Adaptive Cruise Control (Cacc)mentioning

confidence: 99%

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Predictive Model-Based and Control-Aware Communication Strategies for Cooperative Adaptive Cruise Control

Razzaghpour

Valiente

Zaman

et al. 2023

IEEE Open J. Intell. Transp. Syst.

Self Cite

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“…In CVS systems, Remote Vehicles (RV) frequently broadcast their state information to the neighboring vehicles over a wireless channel in the form of an information message, for example, Basic Safety Messages (BSM) [4, 5] using Vehicle‐to‐Everything (V2X) communication. V2X communication allows the information from RVs to be available at the Host Vehicle (HV) over the wireless network extending the situational awareness of CAVs and alleviating the limitations of the sensor‐based systems that rely on line‐of‐sight sensing [6–8]. At the HV, the information messages are processed to monitor the neighboring road participants and create a real‐time map of all objects in its vicinity.…”

Section: Introductionmentioning

confidence: 99%

Context‐aware target classification with hybrid Gaussian process prediction for cooperative vehicle safety systems

Valiente

Raftari

Mahjoub

et al. 2023

IET Intelligent Trans Sys

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Vehicle-to-Everything (V2X) communication has been proposed as a potential solution to improve the robustness and safety of autonomous vehicles by improving coordination and removing the barrier of non-line-of-sight sensing. Cooperative Vehicle Safety (CVS) applications are tightly dependent on the reliability of the underneath data system, which can suffer from loss of information due to the inherent issues of their different components, such as sensors' failures or the poor performance of V2X technologies under dense communication channel load. Particularly, information loss affects the target classification module and, subsequently, the safety application performance. To enable reliable and robust CVS systems that mitigate the effect of information loss, a Context-Aware Target Classification (CA-TC) module coupled with a hybrid learning-based predictive modeling technique for CVS systems is proposed. The CA-TC consists of two modules: a Context-Aware Map (CAM), and a Hybrid Gaussian Process (HGP) prediction system. Consequently, the vehicle safety applications use the information from the CA-TC, making them more robust and reliable. The CAM leverages vehicles' path history, road geometry, tracking, and prediction; and the HGP is utilized to provide accurate vehicles' trajectory predictions to compensate for data loss (due to communication congestion) or sensor measurements' inaccuracies. Based on offline real-world data, a finite bank of driver models that represent the joint dynamics of the vehicle and the drivers' behavior is learned. Offline training and online model updates are combined with on-the-fly forecasting to account for new possible driver behaviors. Finally, the framework is validated using simulation and realistic driving scenarios to confirm its potential in enhancing the robustness and reliability of CVS systems.

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“…If all passenger cars form vehicle platoons, a 200% growth in the road capacity can be achieved [1], [2]. It is shown that platooning is more sensitive to communication losses compared to the CACC, mainly due to its very close coupling between vehicles [3]. Even though platooning is more sensitive to communication losses, its implementation is stable using Cellular Vehicle-To-Everything (C-V2X) [4].…”

Section: Introductionmentioning

confidence: 99%

Impact of Information Flow Topology on Safety of Tightly-coupled Connected and Automated Vehicle Platoons Utilizing Stochastic Control

Razzaghpour¹,

Mosharafian²,

Raftari³

et al. 2022

Preprint

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Impact of Communication Loss on MPC based Cooperative Adaptive Cruise Control and Platooning

Cited by 14 publications

References 20 publications

Predictive Model-Based and Control-Aware Communication Strategies for Cooperative Adaptive Cruise Control

Predictive Model-Based and Control-Aware Communication Strategies for Cooperative Adaptive Cruise Control

Context‐aware target classification with hybrid Gaussian process prediction for cooperative vehicle safety systems

Impact of Information Flow Topology on Safety of Tightly-coupled Connected and Automated Vehicle Platoons Utilizing Stochastic Control

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