Localization Error Modeling for Autonomous Driving in GPS Denied Environment

Zhang, Feihu; Wang, Zhiliang; Zhong, Yaohui; Chen, Liyuan

doi:10.3390/electronics11040647

Cited by 4 publications

(3 citation statements)

References 26 publications

(24 reference statements)

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“…Paper [10] reviews vision-based autonomous driving systems. Paper [11] proposes an effective empirical formula solution to assist autonomous driving in a GPS-denied environment. Paper [12] provide a survey on intelligent tires for tire-road interaction recognition.…”

Section: Sensorsmentioning

confidence: 99%

Security Issues and Solutions for Connected and Autonomous Vehicles in a Sustainable City: A Survey

et al. 2022

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Connected and Autonomous Vehicles (CAVs) combine technologies of autonomous vehicles (AVs) and connected vehicles (CVs) to develop quicker, more reliable, and safer traffic. Artificial Intelligence (AI)-based CAV solutions play significant roles in sustainable cities. The convergence imposes stringent security requirements for CAV safety and reliability. In practice, vehicles are developed with increased automation and connectivity. Increased automation increases the reliance on the sensor-based technologies and decreases the reliance on the driver; increased connectivity increases the exposures of vehicles’ vulnerability and increases the risk for an adversary to implement a cyber-attack. Much work has been dedicated to identifying the security vulnerabilities and recommending mitigation techniques associated with different sensors, controllers, and connection mechanisms, respectively. However, there is an absence of comprehensive and in-depth studies to identify how the cyber-attacks exploit the vehicles’ vulnerabilities to negatively impact the performance and operations of CAVs. In this survey, we set out to thoroughly review the security issues introduced by AV and CV technologies, analyze how the cyber-attacks impact the performance of CAVs, and summarize the solutions correspondingly. The impact of cyber-attacks on the performance of CAVs is elaborated from both viewpoints of intra-vehicle systems and inter-vehicle systems. We pointed out that securing the perception and operations of CAVs would be the top requirement to enable CAVs to be applied safely and reliably in practice. Additionally, we suggested to utilize cloud and new AI methods to defend against smart cyber-attacks on CAVs.

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Section: Sensorsmentioning

confidence: 99%

Security Issues and Solutions for Connected and Autonomous Vehicles in a Sustainable City: A Survey

et al. 2022

View full text Add to dashboard Cite

show abstract

“…[132] reviews vision based autonomous driving system. [133] proposes an effective empirical formula solution to help autonomous driving in GPS denied environment. [134] provide a survey on intelligent tires for tire-road interaction recognition.…”

Section: Sensorsmentioning

confidence: 99%

“…[14], [15], [133] TPMS Measuring the pressure of each tire and provide real-time information to vehicle system.…”

Section: Sensorsmentioning

confidence: 99%

Security Issues and Solutions for Connected and Autonomous Vehicle in Sustainable City: A Survey

Wang¹,

Wei²,

Wang³

et al. 2022

Preprint

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Connected and Autonomous Vehicle (CAV) combines technologies of autonomous vehicle (AV) and connected vehicles (CV) to develop quicker, more reliable and safer traffic. Artificial Intelligence (AI) based CAV solutions play significant roles in sustainable city. The convergence imposes stringent security requirements for CAV safety and reliability. In practice, vehicles are developed with increased automation and connectivity. Increased automation increases the reliance on the sensor-based technologies and decreases the reliance on driver; increased connectivity increases the exposures of vehicles vulnerability and increases the risk for an adversary to implement a cyber-attack. Much work has been dedicated to identifying the security vulnerabilities and recommending mitigation techniques associated with different sensors, controllers, and connection mechanisms, respectively. However, there is an absence of comprehensive and in-depth studies to identify how the cyber-attacks exploit the vehicles vulnerabilities to negatively impact the performance and operations of CAV. In this survey, we set out to thoroughly review the security issues introduced by AV and CV technologies, analyze how the cyber-attacks impact the performance of CAV, and summarize the solutions correspondingly. The impact of cyber-attacks on the performance of CAV is elaborated from both viewpoints of intra-vehicle system and inter-vehicle system. We pointed out that securing the perception and operations of CAV would be the top requirement to enable CAV to be applied safely and reliably in practice. Also, we suggested to utilize cloud and new AI methods to defend against smart cyber-attacks on CAV.

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A Comparative Simulation Study of Localization Error Models for Autonomous Navigation

Koliai,

Bazeille,

Basset

et al. 2023

Studies in Systems, Decision and Control

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Localization Error Modeling for Autonomous Driving in GPS Denied Environment

Cited by 4 publications

References 26 publications

Security Issues and Solutions for Connected and Autonomous Vehicles in a Sustainable City: A Survey

Security Issues and Solutions for Connected and Autonomous Vehicles in a Sustainable City: A Survey

Security Issues and Solutions for Connected and Autonomous Vehicle in Sustainable City: A Survey

A Comparative Simulation Study of Localization Error Models for Autonomous Navigation

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