Context-Aware Navigation Protocol for Safe Driving in Vehicular Cyber-Physical Systems

Mugabarigira, Bien Aime; Shen, Yiwen; Jeong, Jaehoon; Oh, Tae; Jeong, Han-You

doi:10.1109/tits.2022.3210753

Cited by 3 publications

(3 citation statements)

References 24 publications

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“…Context Awareness: Real-world road traffic presents a wide range of scenarios, necessitating robust situational awareness and analytic methods. The overall context, from the road conditions to the driving situations inside or outside the vehicle, is part of this situational awareness [45], [46]. In order to enhance the situational awareness of ADAS, the acquired context information is transmitted back to the vehicle.…”

Section: A System Architecture Of Autonomous Vehiclesmentioning

confidence: 99%

“…A CAW navigation protocol was developed by Mugabarigira et al [45] to improve the security of urban roadways for vehicles. The protocol's collision avoidance functionality enables AVs to navigate around barriers and roadside accidents in a safe mode.…”

Section: Active Inference Context Awareness and Other Full Observable...mentioning

confidence: 99%

“…-Validated based on two AVs, while TSs have lexical concepts. Mugabarigira et al [45] -Developed a CAW navigation service to enhance roadway security.…”

Section: Authorsmentioning

confidence: 99%

See 2 more Smart Citations

A Survey on Cyber-Physical Security of Autonomous Vehicles Using a Context Awareness Method

Zaboli,

Hong,

Kwon

et al. 2023

IEEE Access

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Autonomous vehicles face challenges in ensuring cyber-physical security due to their reliance on image data from cameras processed by machine learning. These algorithms, however, are vulnerable to anomalies in the imagery, leading to decreased recognition accuracy and presenting security concerns. Current machine learning models struggle to predict unexpected vehicular situations, particularly with unpredictable objects and unexpected anomalies. To combat this, scholars are focusing on active inference, a method that can adapt models based on human cognition. This paper aims to incorporate active inference into autonomous vehicle systems. Multiple studies have delved into this approach, showing its potential to address security gaps in this field. Specifically, these frameworks have proven effective in handling unforeseen vehicular anomalies.

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Section: A System Architecture Of Autonomous Vehiclesmentioning

confidence: 99%

Section: Active Inference Context Awareness and Other Full Observable...mentioning

confidence: 99%

See 1 more Smart Citation

A Survey on Cyber-Physical Security of Autonomous Vehicles Using a Context Awareness Method

Zaboli,

Hong,

Kwon

et al. 2023

IEEE Access

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Client selection and resource scheduling in reliable federated learning for UAV-assisted vehicular networks

ZHAO,

GENG,

FENG

et al. 2024

Chinese Journal of Aeronautics

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Perception System Architecture for Self-Driving Vehicles: A Cyber- Physical Systems Framework

Babaei,

Riahinia,

Ebadati

et al. 2023

Preprint

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This research is seeking for design the autonomous vehicle's perception system from the perspective of cyber-physical system. The perception system is considered a cyber and physical component. This research takes a systemic approach. Unified Modeling Language (UML) has been applied to design perception systems. The perceptual system was created using the 3 common UML diagrams. The findings show that UML can be used as a powerful tool for modeling every type of complex system. The sensors utilized in the tasks of the perception layer are shown in use case diagrams. To recognize surrounding things and avoid obstacles, a variety of technologies including cameras, LiDAR, RADAR, ultrasonic sensors, GPS, and GNSS are utilized in 2/3-d object detection, speed and distance detection, localization, and mapping. The class diagram displays the perception system's structural elements. The perception system's task execution was shown in the sequence diagram. The engineers can improve the functionality and security of autonomous vehicles by using UML to create a precise and organized description of the perception system. The model in which designed in this paper can improve autonomous vehicles' perception system performance, driving safety, and self-confidence of vehicles. this model is an innovative model based on the cyber-physical systems approach and with the UML modeling method. other models in the literature are pipeline modular and/or see the perception layer tasks in isolation.

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Context-Aware Navigation Protocol for Safe Driving in Vehicular Cyber-Physical Systems

Cited by 3 publications

References 24 publications

A Survey on Cyber-Physical Security of Autonomous Vehicles Using a Context Awareness Method

A Survey on Cyber-Physical Security of Autonomous Vehicles Using a Context Awareness Method

Client selection and resource scheduling in reliable federated learning for UAV-assisted vehicular networks

Perception System Architecture for Self-Driving Vehicles: A Cyber- Physical Systems Framework

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