Autonomous Cars: Research Results, Issues, and Future Challenges

Hussain, Rasheed; Zeadally, Sherali

doi:10.1109/comst.2018.2869360

Cited by 449 publications

(228 citation statements)

References 166 publications

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“…So the customers are more interested in buying autonomous cars for their comfort. The autonomous car is a motor vehicle that guides itself without any human intervention . It is also called a driver‐less car, robotic car, and self‐driving vehicle.…”

Section: Case Studiesmentioning

confidence: 99%

Tactile internet and its applications in 5G era: A comprehensive review

Gupta

Tanwar

Tyagi

et al. 2019

Int J Communication

127

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Over the last few years, communication latency has been a major hurdle for most of the applications deployed in different network domains. During this era, a number of communication protocols and standards were developed and used by the community. However, still, the problem of latency persists keeping in view of the quality of service (QoS) and quality of experience (QoE) for different applications. To mitigate the aforementioned issues, in this paper, we present an in-depth survey of state-of-the art proposals having tactile internet as a backbone for delay mitigation using 5G networks for future ultra-reliable low-latency applications such as Healthcare 4.0, Industry 4.0, virtual reality and augmented reality, and smart education. From the existing proposals, it has been observed that tactile internet can provide interactions between virtual objects to give a feel of real environment with maximum latency of 1 millisecond. Also, this paper highlights the key differences between the tactile internet and Internet of Things in context with 5G revolution. Then open issues and challenges of tactile internet for smart applications are analyzed. Finally, a comparison of existing proposals with respect to various parameters is presented, which allows the end users to select one of the proposals in comparison with its merits over the others. KEYWORDSHealthcare 4.0, Industry 4.0, IoT, latency, reliability, tactile internet, 5G INTRODUCTIONMobile communication allows users to exchange data using smart devices ubiquitously using the mobile internet (MI). MI has millions of connected smart devices irrespective of their locations. It has revolutionized the different segments of industries such as health care, logistics, education, gaming, and transportation for maintaining quality of service (QoS) and quality of experience (QoE) for different applications. Moreover, it provides a device-to-device (D2D) communication, ie, ubiquitous communication for data sharing and communication between devices. This D2D communication coined the new term, the Internet of Things (IoT), 1 which provides the low power devices or equipments to perform specific tasks in the environment where they are deployed. IoT is being used in various smart city applications such as smart lightening, smart parking, waste management, traffic congestion, and forest fire detection. In D2D communication, the mobile devices can share prime or critical information in which a delay of even millisecond can harm the persons life (for example, the information sharing during robotic telesurgery). Existing cellular systems infrastructure is not suitable for such sensitive data sharing because of low data rates and long delay (greater than 20 ms). However, for D2D communications, Int J Commun Syst. 2019;32:e3981.wileyonlinelibrary.com/journal/dac

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Section: Case Studiesmentioning

confidence: 99%

Tactile internet and its applications in 5G era: A comprehensive review

Gupta

Tanwar

Tyagi

et al. 2019

Int J Communication

127

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“…• Cause electrical damage [44] • Install malicious software (e.g., by firmware updates on CDs or USB sticks) [11] 3.1. 3…”

Section: Example Attacksmentioning

confidence: 99%

“…In recent years, interest in deploying connected autonomous vehicles (CAVs) on real road networks has been increasing [1]. In order to enable the applications that depend on connectivity [2] and autonomy [3], vehicle computer systems are becoming more complex and the number of ways in which the vehicles can communicate with other devices, each other, nearby Edge infrastructure, and the Cloud, is increasing. Such changes in complexity [4], connectivity and levels of autonomy means that there are more ways in which a CAV can be attacked [5] and a successful breach carries greater impact.…”

Section: Introductionmentioning

confidence: 99%

A Connected and Autonomous Vehicle Reference Architecture for Attack Surface Analysis

Maple

Bradbury

et al. 2019

Applied Sciences

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Connected autonomous vehicles (CAVs) will be deployed over the next decade with autonomous functionalities supported by new sensing and communication capabilities. Such functionality exposes CAVs to new attacks that current vehicles will not face. To ensure the safety and security of CAVs, it is important to be able to identify the ways in which the system could be attacked and to build defences against these attacks. One possible approach is to use reference architectures to perform an attack surface analysis. Existing research has developed a variety of reference architectures but none for the specific purpose of attack surface analysis. Existing approaches are either too simple for sufficiently detailed modelling or require too many details to be specified to easily analyse a CAV’s attack surface. Therefore, we propose a reference architecture using a hybrid Functional-Communication viewpoint for attack surface analysis of CAVs, including the Devices, Edge and Cloud systems CAVs interact with. Using two case studies, we demonstrate how attack trees can be used to understand the attack surface of CAV systems.

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“…Among these unmanned driving technologies, self-driving cars have attracted more and more attention for their important economic effect [3]. However, there are lots of challenges in self-driving cars [4,5]. For example, the safety problem is the key technology that must be solved efficiently in self-driving cars, otherwise, it is impossible to allow self-driving cars on the road.…”

Section: Introductionmentioning

confidence: 99%

A Survey on Theories and Applications for Self-Driving Cars Based on Deep Learning Methods

Chen

et al. 2020

Applied Sciences

118

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Self-driving cars are a hot research topic in science and technology, which has a great influence on social and economic development. Deep learning is one of the current key areas in the field of artificial intelligence research. It has been widely applied in image processing, natural language understanding, and so on. In recent years, more and more deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. This paper presents a review of recent research on theories and applications of deep learning for self-driving cars. This survey provides a detailed explanation of the developments of self-driving cars and summarizes the applications of deep learning methods in the field of self-driving cars. Then the main problems in self-driving cars and their solutions based on deep learning methods are analyzed, such as obstacle detection, scene recognition, lane detection, navigation and path planning. In addition, the details of some representative approaches for self-driving cars using deep learning methods are summarized. Finally, the future challenges in the applications of deep learning for self-driving cars are given out.

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Autonomous Cars: Research Results, Issues, and Future Challenges

Cited by 449 publications

References 166 publications

Tactile internet and its applications in 5G era: A comprehensive review

Tactile internet and its applications in 5G era: A comprehensive review

A Connected and Autonomous Vehicle Reference Architecture for Attack Surface Analysis

A Survey on Theories and Applications for Self-Driving Cars Based on Deep Learning Methods

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