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Special Issue "Enhances in V2X Communications for Connected Autonomous Vehicles"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (18 January 2019)

Special Issue Editors

Guest Editor
Dr. Toktam Mahmoodi

Centre for Telecommunications Research, Department of Informatics, King's College London, London, UK
Website | E-Mail
Interests: ultra-low latency communications and networking; network virtualization; V2X communications
Guest Editor
Dr. Massimo Condoluci

Ericsson Research, Stockholm, Sweden
Website | E-Mail
Interests: V2X; 5G system architecture; QoS adaptation; V2X service adaptation
Guest Editor
Dr. Taimoor Abbas

Volvo Car Corporation, Sweden
Website | E-Mail
Interests: V2X communications; MIMO systems; channel modeling; 5G for automotive
Guest Editor
Dr. Apostolos Kousaridas

Huawei Technologies, Munich, Germany
Website | E-Mail
Interests: V2X communications; wireless networks; network management; cognitive adaptive systems
Guest Editor
Dr. Jesus Alonso-Zarate

CTTC, Barcelona, Spain
Website | E-Mail
Interests: machine-type communications; IoT; business analysis and modeling

Special Issue Information

Dear Colleagues,

This Special Issue will be dedicated to advances in 5G V2X communications and the vision of deploying such advances in connected and autonomous cars. With the development of ultra-low latency, extremely high reliability and massive device access in 5G, the ambitions for smart driving applications will soon become a reality. To this end, topics of interests include, but are not limited to:

  • Use case analysis focusing on the interaction between vehicles and other on-board units (OBU), e.g., cameras, sensors, etc.
  • Novel business models for automotive connected to mobile networks.
  • V2X channel measurements and modeling.
  • V2X spectrum and radio design aspects.
  • NewRadio (NR) and sidelink communications for V2X traffic, enabling low-latency and ultra-high reliability.
  • Accurate positioning in V2X.
  • Exploitation and management of multiple radio access technologies (RATs) to improve reliability and coverage.
  • Network slice design for V2X communications.
  • Orchestration of end-to-end V2X traffic delivery and optimization.
  • Network architectures, functions and protocols for V2X communications.
  • Analysis and exploitation of learning approaches, such as mobility prediction, and predictive QoS.
  • Network- and data-assisted positioning techniques for accurate localization.

Dr. Toktam Mahmoodi
Dr. Massimo Condoluci
Dr. Taimoor Abbas
Dr. Apostolos Kousaridas
Dr. Jesus Alonso-Zarate
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • 5G
  • V2X
  • Automotive
  • Connected vehicles
  • QoS

Published Papers (11 papers)

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Research

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Open AccessArticle Deep Learning for Joint Adaptations of Transmission Rate and Payload Length in Vehicular Networks
Sensors 2019, 19(5), 1113; https://doi.org/10.3390/s19051113
Received: 21 January 2019 / Revised: 16 February 2019 / Accepted: 26 February 2019 / Published: 5 March 2019
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Abstract
Recently, vehicular networks have emerged to facilitate intelligent transportation systems (ITS). They enable vehicles to communicate with each other in order to provide various services such as traffic safety, autonomous driving, and entertainments. The vehicle-to-vehicle (V2V) communication channel is doubly selective, where the [...] Read more.
Recently, vehicular networks have emerged to facilitate intelligent transportation systems (ITS). They enable vehicles to communicate with each other in order to provide various services such as traffic safety, autonomous driving, and entertainments. The vehicle-to-vehicle (V2V) communication channel is doubly selective, where the channel changes within the transmission bandwidth and the frame duration. This necessitates robust algorithms to provide reliable V2V communications. In this paper, we propose a scheme that provides joint adaptive modulation, coding and payload length selection (AMCPLS) for V2V communications. Our AMCPLS scheme selects both the modulation and coding scheme (MCS) and the payload length of transmission frames for V2V communication links, according to the V2V channel condition. Our aim is to achieve both reliability and spectrum efficiency. Our proposed AMCPLS scheme improves the V2V effective throughput performance while satisfying a predefined frame error rate (FER). Furthermore, we present a deep learning approach that exploits deep convolutional neural networks (DCNN) for implementing the proposed AMCPLS. Simulation results reveal that the proposed DCNN-based AMCPLS approach outperforms other competing machine learning algorithms such as k-nearest neighbors (k-NN) and support vector machines (SVM) in terms of FER, effective throughput, and prediction time. Full article
(This article belongs to the Special Issue Enhances in V2X Communications for Connected Autonomous Vehicles)
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Open AccessArticle Time-Sensitive Network (TSN) Experiment in Sensor-Based Integrated Environment for Autonomous Driving
Sensors 2019, 19(5), 1111; https://doi.org/10.3390/s19051111
Received: 2 January 2019 / Revised: 21 February 2019 / Accepted: 27 February 2019 / Published: 5 March 2019
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Abstract
Recently, large amounts of data traffic from various sensors and image and navigation systems within vehicles are generated for autonomous driving. Broadband communication networks within vehicles have become necessary. New autonomous Ethernet networks are being considered as alternatives. The Ethernet-based in-vehicle network has [...] Read more.
Recently, large amounts of data traffic from various sensors and image and navigation systems within vehicles are generated for autonomous driving. Broadband communication networks within vehicles have become necessary. New autonomous Ethernet networks are being considered as alternatives. The Ethernet-based in-vehicle network has been standardized in the IEEE 802.1 time-sensitive network (TSN) group since 2006. The Ethernet TSN will be revised and integrated into a subsequent version of IEEE 802.1Q-2018 published in 2018 when various new TSN-related standards are being newly revised and published. A TSN integrated environment simulator is developed in this paper to implement the main functions of the TSN standards that are being developed. This effort would minimize the performance gaps that can occur when the functions of these standards operate in an integrated environment. As part of this purpose, we analyzed the simulator to verify that the traffic for autonomous driving satisfies the TSN transmission requirements in the in-vehicle network (IVN) and the preemption (which is one of the main TSN functions) and reduces the overall End-to-End delay. An optimal guard band size for the preemption was also found for autonomous vehicles in our work. Finally, an IVN model for autonomous vehicles was designed and the performance test was conducted by configuring the traffic to be used for various sensors and electronic control units (ECUs). Full article
(This article belongs to the Special Issue Enhances in V2X Communications for Connected Autonomous Vehicles)
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Open AccessArticle Minimum-Cost Offloading for Collaborative Task Execution of MEC-Assisted Platooning
Sensors 2019, 19(4), 847; https://doi.org/10.3390/s19040847
Received: 31 December 2018 / Revised: 31 January 2019 / Accepted: 14 February 2019 / Published: 18 February 2019
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Abstract
In this paper, we study the offloading decision of collaborative task execution between platoon and Mobile Edge Computing (MEC) server. The mobile application is represented by a series of fine-grained tasks that form a linear topology, each of which is either executed on [...] Read more.
In this paper, we study the offloading decision of collaborative task execution between platoon and Mobile Edge Computing (MEC) server. The mobile application is represented by a series of fine-grained tasks that form a linear topology, each of which is either executed on a local vehicle, offloaded to other members of the platoon, or offloaded to a MEC server. The objective of the design is to minimize the cost of tasks offloading and meets the deadline of tasks execution. The cost minimized task decision problem is transformed into the shortest path problem, which is limited by the deadline of the tasks on a directed acyclic graph. The classical Lagrangian Relaxation-based Aggregated Cost (LARAC) algorithm is adopted to solve the problem approximately. Numerical analysis shows that the scheduling method of the tasks decision can be well applied to the platoon scenario and execute the tasks in cooperation with the MEC server. In addition, compared with task local execution, platoon execution and MEC server execution, the optimal offloading decision for collaborative task execution can significantly reduce the cost of task execution and meet deadlines. Full article
(This article belongs to the Special Issue Enhances in V2X Communications for Connected Autonomous Vehicles)
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Open AccessFeature PaperArticle Trajectories and Resource Management of Flying Base Stations for C-V2X
Sensors 2019, 19(4), 811; https://doi.org/10.3390/s19040811
Received: 18 January 2019 / Revised: 8 February 2019 / Accepted: 13 February 2019 / Published: 16 February 2019
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Abstract
In a vehicular scenario where the penetration of cars equipped with wireless communication devices is far from 100% and application requirements tend to be challenging for a cellular network not specifically planned for it, the use of unmanned aerial vehicles (UAVs), carrying mobile [...] Read more.
In a vehicular scenario where the penetration of cars equipped with wireless communication devices is far from 100% and application requirements tend to be challenging for a cellular network not specifically planned for it, the use of unmanned aerial vehicles (UAVs), carrying mobile base stations, becomes an interesting option. In this article, we consider a cellular-vehicle-to-anything (C-V2X) application and we propose the integration of an aerial and a terrestrial component of the network, to fill the potential unavailability of short-range connections among vehicles and address unpredictable traffic distribution in space and time. In particular, we envision a UAV with C-V2X equipment providing service for the extended sensing application, and we propose a UAV trajectory design accounting for the radio resource (RR) assignment. The system is tested considering a realistic scenario by varying the RRs availability and the number of active vehicles. Simulations show the results in terms of gain in throughput and percentage of served users, with respect to the case in which the UAV is not present. Full article
(This article belongs to the Special Issue Enhances in V2X Communications for Connected Autonomous Vehicles)
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Open AccessArticle Slicing on the Road: Enabling the Automotive Vertical through 5G Network Softwarization
Sensors 2018, 18(12), 4435; https://doi.org/10.3390/s18124435
Received: 15 October 2018 / Revised: 7 December 2018 / Accepted: 11 December 2018 / Published: 14 December 2018
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Abstract
The demanding requirements of Vehicle-to-Everything (V2X) applications, such as ultra-low latency, high-bandwidth, highly-reliable communication, intensive computation and near-real time data processing, raise outstanding challenges and opportunities for fifth generation (5G) systems. By allowing an operator to flexibly provide dedicated logical networks with (virtualized) [...] Read more.
The demanding requirements of Vehicle-to-Everything (V2X) applications, such as ultra-low latency, high-bandwidth, highly-reliable communication, intensive computation and near-real time data processing, raise outstanding challenges and opportunities for fifth generation (5G) systems. By allowing an operator to flexibly provide dedicated logical networks with (virtualized) functionalities over a common physical infrastructure, network slicing candidates itself as a prominent solution to support V2X over upcoming programmable and softwarized 5G systems in a business-agile manner. In this paper, a network slicing framework is proposed along with relevant building blocks and mechanisms to support V2X applications by flexibly orchestrating multi-access and edge-dominated 5G network infrastructures, especially with reference to roaming scenarios. Proof of concept experiments using the Mininet emulator showcase the viability and potential benefits of the proposed framework for cooperative driving use cases. Full article
(This article belongs to the Special Issue Enhances in V2X Communications for Connected Autonomous Vehicles)
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Open AccessFeature PaperArticle A Path Loss and Shadowing Model for Multilink Vehicle-to-Vehicle Channels in Urban Intersections
Sensors 2018, 18(12), 4433; https://doi.org/10.3390/s18124433
Received: 1 October 2018 / Revised: 27 November 2018 / Accepted: 8 December 2018 / Published: 14 December 2018
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Abstract
The non line-of-sight (NLOS) scenario in urban intersections is critical in terms of traffic safety—a scenario where Vehicle-to-Vehicle (V2V) communication really can make a difference by enabling communication and detection of vehicles around building corners. A few NLOS V2V channel models exist in [...] Read more.
The non line-of-sight (NLOS) scenario in urban intersections is critical in terms of traffic safety—a scenario where Vehicle-to-Vehicle (V2V) communication really can make a difference by enabling communication and detection of vehicles around building corners. A few NLOS V2V channel models exist in the literature but they all have some form of limitation, and therefore further research is need. In this paper, we present an alternative NLOS path loss model based on analysis from measured V2V communication channels at 5.9 GHz between six vehicles in two urban intersections. We analyze the auto-correlation of the large scale fading process and the influence of the path loss model on this. In cases where a proper model for the path loss and the antenna pattern is included, the de-correlation distance for the auto-correlation is as low as 2–4 m, and the cross-correlation for the large scale fading between different links can be neglected. Otherwise, the de-correlation distance has to be much longer and the cross-correlation between the different communication links needs to be considered separately, causing the computational complexity to be unnecessarily large. With these findings, we stress that vehicular ad-hoc network (VANET) simulations should be based on the current geometry, i.e., a proper path loss model should be applied depending on whether the V2V communication is blocked or not by other vehicles or buildings. Full article
(This article belongs to the Special Issue Enhances in V2X Communications for Connected Autonomous Vehicles)
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Open AccessArticle A Novel Framework for Road Traffic Risk Assessment with HMM-Based Prediction Model
Sensors 2018, 18(12), 4313; https://doi.org/10.3390/s18124313
Received: 22 October 2018 / Revised: 13 November 2018 / Accepted: 5 December 2018 / Published: 7 December 2018
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Abstract
Over the past decades, there has been significant research effort dedicated to the development of intelligent vehicles and V2X systems. This paper proposes a road traffic risk assessment method for road traffic accident prevention of intelligent vehicles. This method is based on HMM [...] Read more.
Over the past decades, there has been significant research effort dedicated to the development of intelligent vehicles and V2X systems. This paper proposes a road traffic risk assessment method for road traffic accident prevention of intelligent vehicles. This method is based on HMM (Hidden Markov Model) and is applied to the prediction of steering angle status to (1) evaluate the probabilities of the steering angle in each independent interval and (2) calculate the road traffic risk in different analysis regions. According to the model, the road traffic risk is quantified and presented directly in a visual form by the time-varying risk map, to ensure the accuracy of assessment and prediction. Experiment results are presented, and the results show the effectiveness of the assessment strategies. Full article
(This article belongs to the Special Issue Enhances in V2X Communications for Connected Autonomous Vehicles)
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Open AccessArticle Millimeter Wave Vehicular Channel Emulation: A Framework for Balancing Complexity and Accuracy
Sensors 2018, 18(11), 3997; https://doi.org/10.3390/s18113997
Received: 11 October 2018 / Revised: 8 November 2018 / Accepted: 13 November 2018 / Published: 16 November 2018
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Abstract
We propose a general framework for the specification of a sparse representation of millimeter wave vehicular propagation channels and apply this to both synthetic data and real-world observations from channel sounding experiments. The proposed framework is based on the c-LASSO (complex Least Absolute [...] Read more.
We propose a general framework for the specification of a sparse representation of millimeter wave vehicular propagation channels and apply this to both synthetic data and real-world observations from channel sounding experiments. The proposed framework is based on the c-LASSO (complex Least Absolute Shrinkage and Selection Operator) which minimizes the mean squared error of the sparse representation for a given number of degrees of freedom. By choosing the number of degrees of freedom, we balance the numerical complexity of the representation in the channel emulation against its accuracy in terms of the mean squared error. A key ingredient is the choice of basis of the representation and we discuss two options: the Fourier basis and its projection onto a given subband. The results indicate that the subband-projected Fourier basis is a low-complexity choice with high fidelity for representing clustered channel impulse responses. Finally, a sequential estimator is formulated which enforces a consistent temporal evolution of the geometry of the interacting objects in the propagation environment. We demonstrate the performance of our approach using both synthetic data and measured 60 GHz vehicular channel traces. Full article
(This article belongs to the Special Issue Enhances in V2X Communications for Connected Autonomous Vehicles)
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Open AccessArticle A Swarming Approach to Optimize the One-Hop Delay in Smart Driving Inter-Platoon Communications
Sensors 2018, 18(10), 3307; https://doi.org/10.3390/s18103307
Received: 8 August 2018 / Revised: 26 September 2018 / Accepted: 28 September 2018 / Published: 1 October 2018
Cited by 1 | PDF Full-text (537 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Multi-platooning is an important management strategy for autonomous driving technology. The backbone vehicles in a multi-platoon adopt the IEEE 802.11 distributed coordination function (DCF) mechanism to transmit vehicles’ kinematics information through inter-platoon communications, and then forward the information to the member vehicles through [...] Read more.
Multi-platooning is an important management strategy for autonomous driving technology. The backbone vehicles in a multi-platoon adopt the IEEE 802.11 distributed coordination function (DCF) mechanism to transmit vehicles’ kinematics information through inter-platoon communications, and then forward the information to the member vehicles through intra-platoon communications. In this case, each vehicle in a multi-platoon can acquire the kinematics information of other vehicles. The parameters of DCF, the hidden terminal problem and the number of neighbors may incur a long and unbalanced one-hop delay of inter-platoon communications, which would further prolong end-to-end delay of inter-platoon communications. In this case, some vehicles within a multi-platoon cannot acquire the emergency changes of other vehicles’ kinematics within a limited time duration and take prompt action accordingly to keep a multi-platoon formation. Unlike other related works, this paper proposes a swarming approach to optimize the one-hop delay of inter-platoon communications in a multi-platoon scenario. Specifically, the minimum contention window size of each backbone vehicle is adjusted to enable the one-hop delay of each backbone vehicle to get close to the minimum average one-hop delay. The simulation results indicate that, the one-hop delay of the proposed approach is reduced by 12% as compared to the DCF mechanism with the IEEE standard contention window size. Moreover, the end-to-end delay, one-hop throughput, end-to-end throughput and transmission probability have been significantly improved. Full article
(This article belongs to the Special Issue Enhances in V2X Communications for Connected Autonomous Vehicles)
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Open AccessArticle Robust Beamforming Design for Secure V2X Downlink System with Wireless Information and Power Transfer under a Nonlinear Energy Harvesting Model
Sensors 2018, 18(10), 3294; https://doi.org/10.3390/s18103294
Received: 1 September 2018 / Revised: 24 September 2018 / Accepted: 28 September 2018 / Published: 30 September 2018
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Abstract
Vehicle to everything (V2X) has been deemed a promising technology due to its potential to achieve traffic safety and efficiency. This paper considers a V2X downlink system with a simultaneous wireless information and power transfer (SWIPT) system where the base station not only [...] Read more.
Vehicle to everything (V2X) has been deemed a promising technology due to its potential to achieve traffic safety and efficiency. This paper considers a V2X downlink system with a simultaneous wireless information and power transfer (SWIPT) system where the base station not only conveys data and energy to two types of wireless vehicular receivers, such as one hybrid power-splitting vehicular receiver, and multiple energy vehicular receivers, but also prevents information from being intercepted by the potential eavesdroppers (idle energy vehicular receivers). Both the base station and the energy vehicular receivers are equipped with multiple antennas, whereas the information vehicular receiver is equipped with a single antenna. In particular, the imperfect channel state information (CSI) and the practical nonlinear energy harvesting (EH) model are taken into account. The non-convex optimization problem is formulated to maximize the minimum harvested energy power among the energy vehicular receivers satisfying the lowest harvested energy power threshold at the information vehicular receiver and secure vehicular communication requirements. In light of the intractability of the optimization problem, the semidefinite relaxation (SDR) technique and variable substitutions are applied, and the optimal solution is proven to be tight. A number of results demonstrate that the proposed robust secure beamforming scheme has better performance than other schemes. Full article
(This article belongs to the Special Issue Enhances in V2X Communications for Connected Autonomous Vehicles)
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Review

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Open AccessReview Vehicle-to-Pedestrian Communication for Vulnerable Road Users: Survey, Design Considerations, and Challenges
Sensors 2019, 19(2), 358; https://doi.org/10.3390/s19020358
Received: 11 December 2018 / Revised: 9 January 2019 / Accepted: 14 January 2019 / Published: 17 January 2019
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Abstract
In the last few years, increasing attention has been provided to research Vehicle-to-Pedestrian (V2P) communication systems. These V2P systems serve different purposes (safety or convenience) and cater to different Vulnerable Road User (VRU) groups. Also, these V2P systems employ different communication technologies, and [...] Read more.
In the last few years, increasing attention has been provided to research Vehicle-to-Pedestrian (V2P) communication systems. These V2P systems serve different purposes (safety or convenience) and cater to different Vulnerable Road User (VRU) groups. Also, these V2P systems employ different communication technologies, and use different mechanisms to interact with the users. An effective V2P system also needs to consider varying characteristics of different VRUs. These various elements may be considered as design parameters of the V2P system. In this paper, we discuss such elements and propose a design framework for the V2P system based on them. We also provide an extensive survey of existing V2P efforts for safety and convenience applications and their design considerations. We perform a case study that compares the different approaches of V2P safety system for different VRU groups under different pre-crash scenarios. Finally, we discuss a few technological challenges in integration of VRUs into V2X systems. Full article
(This article belongs to the Special Issue Enhances in V2X Communications for Connected Autonomous Vehicles)
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