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Special Issue "Advances on Vehicular Networks: From Sensing to Autonomous Driving"

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

Deadline for manuscript submissions: closed (10 November 2018)

Special Issue Editors

Guest Editor
Dr. Francisco J. Martinez

Department of Computer Science and System Engineering, University of Zaragoza, Zaragoza, Spain
Website | E-Mail
Interests: VANET simulation; Intelligent Transportation Systems; traffic safety; 802.11p; warning messages; traffic safety; Artificial Intelligence; vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications
Guest Editor
Dr. Celimuge Wu

Department of Computer and Network Engineering, Graduate School of Informatics and Engineering, The University of Electro-Communications, 1-5-1, Chofugaoka, Chofu-shi, Tokyo,182-8585 Japan
Website | E-Mail
Interests: Ad Hoc Networks, Sensor Networks, Intelligent Transport Systems, Communication Protocols, IoT, Big data
Guest Editor
Prof. Johann M. Marquez-Barja

Faculty of Applied Engineering, Universiteit Antwerpen, Antwerpen, Belgium
Website | E-Mail
Interests: 5G advanced heterogeneous dense cells architectures; elastic and flexible future wireless networks and its integration and impact on optical networks; IoT clustering; virtualization; provisioning and dynamic resource allocation towards dynamic converged networks; vehicular networks, mobility and handovering within smart cities
Guest Editor
Dr. Syed Hassan Ahmed

Department of Computer Science, Georgia Southern University, Statesboro, GA 30460, USA
Website | E-Mail
Interests: vehicular communications (routing, MAC); next generation networks (information/content-centric and named data networking); Internet of Things (IoT); connected and smart communities; sensors and ad-hoc networks; smart and mobile health

Special Issue Information

Dear Colleagues,

Improving planning, design, management, and control of future autonomous transportation systems requires conducting both basic and applied research to expand the knowledge base on transportation. This Special Issue focuses on the design, analysis, and control of information systems, specially addressing smart sensing, information delivery, and communication issues. The objective is to provide an overview of the state of the art in the technological aspects of sensing, information dissemination, communications, and artificial intelligence applied to transportation.

Over the years, we have witnessed the joint efforts of academia and industry that have led to, not only the introduction of novel applications, but also the improvement of communications, and the use of Artificial Intelligence-based approaches intended to make future transportation a reality. This excellent combination of two important fields will propel our transportation capabilities even further, making possible to propose revolutionary applications in the transportation field, improving our life quality.

However, many issues remain unsolved. Further research efforts are required in the fields of vehicular networking, sensing, and autonomous driving, including defining the best structure for the information shared and delivered, providing common understanding platforms, information sharing, smart sensing, and also new communication paradigms for the advance of intelligent transportation systems.

This Special Issue is seeking for high quality original contributions, soliciting high level technical papers addressing the main research challenges in the vehicular networking, sensing, and information systems areas. The possible contributions should consist in original theoretical or practical analyses, never published elsewhere, and validated by simulations or real test beds. 

Topics

Potential topics include, but are not limited to:

  • Information management services
  • Vehicular ad hoc networks
  • Vehicular sensor networks
  • 5G in vehicular networking
  • Multimedia communications in vehicular scenarios
  • Ontologies for Intelligent Transportation Systems
  • Content distribution in vehicular environments
  • Vehicular cloud computing and networking
  • Knowledge data systems for Vehicular Communications
  • Advanced services through Vehicular Communications
  • Social Networks in vehicular environments
  • Security, trust and privacy in Vehicular Communications
  • Autonomous driving
  • Electric vehicles
  • Models, simulators and tools for Intelligent Transportation Systems

Prof. Francisco J. Martinez
Prof. Celimuge Wu
Prof. Johann M. Marquez-Barja
Dr. Syed Hassan Ahmed
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

  • Vehicular networks
  • Vehicle sensing
  • Artificial Intelligence
  • Intelligent Transportation Systems
  • Autonomous driving
  • 5G

Published Papers (28 papers)

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Research

Open AccessArticle A Secure and Efficient Group Key Agreement Scheme for VANET
Sensors 2019, 19(3), 482; https://doi.org/10.3390/s19030482
Received: 8 November 2018 / Revised: 20 January 2019 / Accepted: 21 January 2019 / Published: 24 January 2019
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Abstract
A vehicular ad hoc network (VANET) is a special mobile ad hoc network that provides vehicle collaborative security applications using intervehicle communication technology. The method enables vehicles to exchange information (e.g., emergency brake). In VANET, there are many vehicle platoon driving scenes, where [...] Read more.
A vehicular ad hoc network (VANET) is a special mobile ad hoc network that provides vehicle collaborative security applications using intervehicle communication technology. The method enables vehicles to exchange information (e.g., emergency brake). In VANET, there are many vehicle platoon driving scenes, where vehicles with identical attributes (location, organization, etc.) are organized as a group. However, this organization causes the issue of security threats (message confidentiality, identity privacy, etc.) because of an unsafe wireless communication channel. To protect the security and privacy of group communication, it is necessary to design an effective group key agreement scheme. By negotiating a dynamic session secret key using a fixed roadside unit (RSU), which has stronger computational ability than the on-board unit (OBU) equipped on the vehicle, the designed scheme can help to provide more stable communication performance and speed up the encryption and decryption processes. To effectively implement the anonymous authentication mechanism and authentication efficiency, we use a batch authentication scheme and a shared secret key mechanism among the vehicles, RSUs and trusted authority (TA). We design an efficient group secret key agreement scheme, which satisfies the above communication and security requirements, protects the privacy of vehicles, and traces the real identity of the vehicle at a time when it is necessary. Computational analysis shows that the proposed scheme is secure and more efficient than existing schemes. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle City-Wide Eco-Routing Navigation Considering Vehicular Communication Impacts
Sensors 2019, 19(2), 290; https://doi.org/10.3390/s19020290
Received: 29 November 2018 / Revised: 28 December 2018 / Accepted: 4 January 2019 / Published: 12 January 2019
PDF Full-text (1311 KB) | HTML Full-text | XML Full-text
Abstract
Intelligent Transportation Systems (ITSs) utilize Vehicular Ad-hoc Networks (VANETs) to collect, disseminate, and share data with the Traffic Management Center (TMC) and different actuators. Consequently, packet drop and delay in VANETs can significantly impact ITS performance. Feedback-based eco-routing (FB-ECO) is a promising ITS [...] Read more.
Intelligent Transportation Systems (ITSs) utilize Vehicular Ad-hoc Networks (VANETs) to collect, disseminate, and share data with the Traffic Management Center (TMC) and different actuators. Consequently, packet drop and delay in VANETs can significantly impact ITS performance. Feedback-based eco-routing (FB-ECO) is a promising ITS technology, which is expected to reduce vehicle fuel/energy consumption and pollutant emissions by routing drivers through the most environmentally friendly routes. To compute these routes, the FB-ECO utilizes VANET communication to update link costs in real-time, based on the experiences of other vehicles in the system. In this paper, we study the impact of vehicular communication on FB-ECO navigation performance in a large-scale real network with realistic calibrated traffic demand data. We conduct this study at different market penetration rates and different congestion levels. We start by conducting a sensitivity analysis of the market penetration rate on the FB-ECO system performance, and its network-wide impacts considering ideal communication. Subsequently, we study the impact of the communication network on system performance for different market penetration levels, considering the communication system. The results demonstrate that, for market penetration levels less than 30%, the eco-routing system performs adequately in both the ideal and realistic communication scenarios. It also shows that, for realistic communication, increasing the market penetration rate results in a network-wide degradation of the system performance. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Fuzzy Ontology and LSTM-Based Text Mining: A Transportation Network Monitoring System for Assisting Travel
Sensors 2019, 19(2), 234; https://doi.org/10.3390/s19020234
Received: 8 November 2018 / Revised: 31 December 2018 / Accepted: 7 January 2019 / Published: 9 January 2019
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Abstract
Intelligent Transportation Systems (ITSs) utilize a sensor network-based system to gather and interpret traffic information. In addition, mobility users utilize mobile applications to collect transport information for safe traveling. However, these types of information are not sufficient to examine all aspects of the [...] Read more.
Intelligent Transportation Systems (ITSs) utilize a sensor network-based system to gather and interpret traffic information. In addition, mobility users utilize mobile applications to collect transport information for safe traveling. However, these types of information are not sufficient to examine all aspects of the transportation networks. Therefore, both ITSs and mobility users need a smart approach and social media data, which can help ITSs examine transport services, support traffic and control management, and help mobility users travel safely. People utilize social networks to share their thoughts and opinions regarding transportation, which are useful for ITSs and travelers. However, user-generated text on social media is short in length, unstructured, and covers a broad range of dynamic topics. The application of recent Machine Learning (ML) approach is inefficient for extracting relevant features from unstructured data, detecting word polarity of features, and classifying the sentiment of features correctly. In addition, ML classifiers consistently miss the semantic feature of the word meaning. A novel fuzzy ontology-based semantic knowledge with Word2vec model is proposed to improve the task of transportation features extraction and text classification using the Bi-directional Long Short-Term Memory (Bi-LSTM) approach. The proposed fuzzy ontology describes semantic knowledge about entities and features and their relation in the transportation domain. Fuzzy ontology and smart methodology are developed in Web Ontology Language and Java, respectively. By utilizing word embedding with fuzzy ontology as a representation of text, Bi-LSTM shows satisfactory improvement in both the extraction of features and the classification of the unstructured text of social media. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Social-Aware Driver Assistance Systems for City Traffic in Shared Spaces
Sensors 2019, 19(2), 221; https://doi.org/10.3390/s19020221
Received: 5 November 2018 / Revised: 21 December 2018 / Accepted: 3 January 2019 / Published: 9 January 2019
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Abstract
Shared spaces are gaining presence in cities, where a variety of players and mobility types (pedestrians, bicycles, motorcycles, and cars) move without specifically delimited areas. This makes the traffic they comprise challenging for automated systems. The information traditionally considered (e.g., streets, and obstacle [...] Read more.
Shared spaces are gaining presence in cities, where a variety of players and mobility types (pedestrians, bicycles, motorcycles, and cars) move without specifically delimited areas. This makes the traffic they comprise challenging for automated systems. The information traditionally considered (e.g., streets, and obstacle positions and speeds) is not enough to build suitable models of the environment. The required explanatory and anticipation capabilities need additional information to improve them. Social aspects (e.g., goal of the displacement, companion, or available time) should be considered, as they have a strong influence on how people move and interact with the environment. This paper presents the Social-Aware Driver Assistance System (SADAS) approach to integrate this information into traffic systems. It relies on a domain-specific modelling language for social contexts and their changes. Specifications compliant with it describe social and system information, their links, and how to process them. Traffic social properties are the formalization within the language of relevant knowledge extracted from literature to interpret information. A multi-agent system architecture manages these specifications and additional processing resources. A SADAS can be connected to other parts of traffic systems by means of subscription-notification mechanisms. The case study to illustrate the approach applies social knowledge to predict people’s movements. It considers a distributed system for obstacle detection and tracking, and the intelligent management of traffic signals. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Practical Guidelines for Approaching the Implementation of Neural Networks on FPGA for PAPR Reduction in Vehicular Networks
Sensors 2019, 19(1), 116; https://doi.org/10.3390/s19010116
Received: 16 November 2018 / Revised: 12 December 2018 / Accepted: 25 December 2018 / Published: 31 December 2018
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Abstract
Nowadays, the sensor community has become wireless, increasing their potential and applications. In particular, these emerging technologies are promising for vehicles’ communications (V2V) to dramatically reduce the number of fatal roadway accidents by providing early warnings. The ECMA-368 wireless communication standard has been [...] Read more.
Nowadays, the sensor community has become wireless, increasing their potential and applications. In particular, these emerging technologies are promising for vehicles’ communications (V2V) to dramatically reduce the number of fatal roadway accidents by providing early warnings. The ECMA-368 wireless communication standard has been developed and used in wireless sensor networks and it is also proposed to be used in vehicular networks. It adopts Multiband Orthogonal Frequency Division Multiplexing (MB-OFDM) technology to transmit data. However, the large power envelope fluctuation of OFDM signals limits the power efficiency of the High Power Amplifier (HPA) due to nonlinear distortion. This is especially important for mobile broadband wireless and sensors in vehicular networks. Many algorithms have been proposed for solving this drawback. However, complexity and implementations are usually an issue in real developments. In this paper, the implementation of a novel architecture based on multilayer perceptron artificial neural networks on a Field Programmable Gate Array (FPGA) chip is evaluated and some guidelines are drawn suitable for vehicular communications. The proposed implementation improves performance in terms of Peak to Average Power Ratio (PAPR) reduction, distortion and Bit Error Rate (BER) with much lower complexity. Two different chips have been used, namely, Xilinx and Altera and a comparison is also provided. As a conclusion, the proposed implementation allows a minimal consumption of the resources jointly with a higher maximum frequency, higher performance and lower complexity. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle An Improved Channel Estimation Technique for IEEE 802.11p Standard in Vehicular Communications
Sensors 2019, 19(1), 98; https://doi.org/10.3390/s19010098
Received: 4 November 2018 / Revised: 18 December 2018 / Accepted: 21 December 2018 / Published: 28 December 2018
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Abstract
IEEE 802.11p based Dedicated Short-Range Communication (DSRC) is considered a potential wireless technology to enable transportation safety and traffic efficiency. A major challenge in the development of IEEE 802.11p technology is ensuring communication reliability in highly dynamic Vehicle-to-Vehicle (V2V) environments. The design of [...] Read more.
IEEE 802.11p based Dedicated Short-Range Communication (DSRC) is considered a potential wireless technology to enable transportation safety and traffic efficiency. A major challenge in the development of IEEE 802.11p technology is ensuring communication reliability in highly dynamic Vehicle-to-Vehicle (V2V) environments. The design of IEEE 802.11p does not have a sufficient number of training symbols in the time domain and pilot carriers in the frequency domain to enable accurate estimation of rapidly varying V2V channels. The channel estimation of IEEE 802.11p is preamble based, which cannot guarantee a suitable equalization in urban and highway scenarios, especially for longer length data packets. This limitation has been investigated by some research works, which suggest that one major challenge is determining an accurate means of updating channel estimate over the course of packet length while adhering to the standard. The motivation behind this article is to overcome this challenge. We have proposed an improved Constructed Data Pilot (iCDP) scheme which adheres to the standard and constructs data pilots by considering the correlation characteristics between adjacent data symbols in time domain and adjacent subcarriers in frequency domain. It is in contrast to previous schemes which considered the correlation in the time domain. The results have shown that the proposed scheme performs better than previous schemes in terms of bit error rate (BER) and root-mean-square error (RMSE). Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle A Real-Time Path Planning Algorithm for AUV in Unknown Underwater Environment Based on Combining PSO and Waypoint Guidance
Sensors 2019, 19(1), 20; https://doi.org/10.3390/s19010020
Received: 27 October 2018 / Revised: 17 December 2018 / Accepted: 18 December 2018 / Published: 21 December 2018
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Abstract
It is a challengeable task to plan multi-objective optimization paths for autonomous underwater vehicles (AUVs) in an unknown environments, which involves reducing travel time, shortening path length, keeping navigation safety, and smoothing trajectory. To address the above challenges, a real-time path planning approach [...] Read more.
It is a challengeable task to plan multi-objective optimization paths for autonomous underwater vehicles (AUVs) in an unknown environments, which involves reducing travel time, shortening path length, keeping navigation safety, and smoothing trajectory. To address the above challenges, a real-time path planning approach combining particle swarm optimization and waypoint guidance is proposed for AUV in unknown oceanic environments in this paper. In this algorithm, a multi-beam forward looking sonar (FLS) is utilized to detect obstacles and the output data of FLS are used to produce those obstacles’ outlines (polygons). Particle swarm optimization is used to search for appropriate temporary waypoints, in which the optimization parameters of path planning are taken into account. Subsequently, an optimal path is automatically generated under the guidance of the destination and these temporary waypoints. Finally, three algorithms, including artificial potential field and genic algorithm, are adopted in the simulation experiments. The simulation results show that the proposed algorithm can generate the optimal paths compared with the other two algorithms. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Vehicle-Type Detection Based on Compressed Sensing and Deep Learning in Vehicular Networks
Sensors 2018, 18(12), 4500; https://doi.org/10.3390/s18124500
Received: 10 November 2018 / Revised: 14 December 2018 / Accepted: 17 December 2018 / Published: 19 December 2018
Cited by 5 | PDF Full-text (1069 KB) | HTML Full-text | XML Full-text
Abstract
Throughout the past decade, vehicular networks have attracted a great deal of interest in various fields. The increasing number of vehicles has led to challenges in traffic regulation. Vehicle-type detection is an important research topic that has found various applications in numerous fields. [...] Read more.
Throughout the past decade, vehicular networks have attracted a great deal of interest in various fields. The increasing number of vehicles has led to challenges in traffic regulation. Vehicle-type detection is an important research topic that has found various applications in numerous fields. Its main purpose is to extract the different features of vehicles from videos or pictures captured by traffic surveillance so as to identify the types of vehicles, and then provide reference information for traffic monitoring and control. In this paper, we propose a step-forward vehicle-detection and -classification method using a saliency map and the convolutional neural-network (CNN) technique. Specifically, compressed-sensing (CS) theory is applied to generate the saliency map to label the vehicles in an image, and the CNN scheme is then used to classify them. We applied the concept of the saliency map to search the image for target vehicles: this step is based on the use of the saliency map to minimize redundant areas. CS was used to measure the image of interest and obtain its saliency in the measurement domain. Because the data in the measurement domain are much smaller than those in the pixel domain, saliency maps can be generated at a low computation cost and faster speed. Then, based on the saliency map, we identified the target vehicles and classified them into different types using the CNN. The experimental results show that our method is able to speed up the window-calibrating stages of CNN-based image classification. Moreover, our proposed method has better overall performance in vehicle-type detection compared with other methods. It has very broad prospects for practical applications in vehicular networks. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Reducing Message Collisions in Sensing-Based Semi-Persistent Scheduling (SPS) by Using Reselection Lookaheads in Cellular V2X
Sensors 2018, 18(12), 4388; https://doi.org/10.3390/s18124388
Received: 9 November 2018 / Revised: 5 December 2018 / Accepted: 7 December 2018 / Published: 11 December 2018
Cited by 1 | PDF Full-text (710 KB) | HTML Full-text | XML Full-text
Abstract
In the C-V2X sidelink Mode 4 communication, the sensing-based semi-persistent scheduling (SPS) implements a message collision avoidance algorithm to cope with the undesirable effects of wireless channel congestion. Still, the current standard mechanism produces a high number of packet collisions, which may hinder [...] Read more.
In the C-V2X sidelink Mode 4 communication, the sensing-based semi-persistent scheduling (SPS) implements a message collision avoidance algorithm to cope with the undesirable effects of wireless channel congestion. Still, the current standard mechanism produces a high number of packet collisions, which may hinder the high-reliability communications required in future C-V2X applications such as autonomous driving. In this paper, we show that by drastically reducing the uncertainties in the choice of the resource to use for SPS, we can significantly reduce the message collisions in the C-V2X sidelink Mode 4. Specifically, we propose the use of the “lookahead”, which contains the next starting resource location in the time-frequency plane. By exchanging the lookahead information piggybacked on the periodic safety message, vehicular user equipment (UEs) can eliminate most message collisions arising from the ignorance of other UEs’ internal decisions. Although the proposed scheme would require the inclusion of the lookahead in the control part of the packet, the benefit may outweigh the bandwidth cost, considering the stringent reliability requirement in future C-V2X applications. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Research on Path Planning Model Based on Short-Term Traffic Flow Prediction in Intelligent Transportation System
Sensors 2018, 18(12), 4275; https://doi.org/10.3390/s18124275
Received: 10 November 2018 / Revised: 28 November 2018 / Accepted: 30 November 2018 / Published: 5 December 2018
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Abstract
Vehicle driving path planning is an important information service in intelligent transportation systems. As an important basis for path planning optimization, the travel time prediction method has attracted much attention. However, traffic flow has features of high nonlinearity, time-varying, and uncertainty, which makes [...] Read more.
Vehicle driving path planning is an important information service in intelligent transportation systems. As an important basis for path planning optimization, the travel time prediction method has attracted much attention. However, traffic flow has features of high nonlinearity, time-varying, and uncertainty, which makes it hard for prediction method with single feature to meet the accuracy demand of intelligent transportation system in big data environment. In this paper, the historical vehicle Global Positioning System (GPS) information data is used to establish the traffic prediction model. Firstly, the Clustering in QUEst (CLIQUE)-based clustering algorithm V-CLIQUE is proposed to analyze the historical vehicle GPS data. Secondly, an artificial neural network (ANN)-based prediction model is proposed. Finally, the ANN-based weighted shortest path algorithm, A-Dijkstra, is proposed. We used mean absolute percentage error (MAPE) to evaluate the predictive model and compare it with the predicted results of Average and support regression vector (SRV). Experiments show that the improved ANN path planning model we proposed can accurately predict real-time traffic status at the given location. It has less relative error and saves time for users’ travel while saving social resources. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Velocity-Adaptive V2I Fair-Access Scheme Based on IEEE 802.11 DCF for Platooning Vehicles
Sensors 2018, 18(12), 4198; https://doi.org/10.3390/s18124198
Received: 25 October 2018 / Revised: 24 November 2018 / Accepted: 27 November 2018 / Published: 30 November 2018
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Abstract
Platooning strategy is an important component of autonomous driving technology. Autonomous vehicles in platoons are often equipped with a variety of on-board sensors to detect the surrounding environment. The abundant data collected by autonomous vehicles in platoons can be transmitted to the infrastructure [...] Read more.
Platooning strategy is an important component of autonomous driving technology. Autonomous vehicles in platoons are often equipped with a variety of on-board sensors to detect the surrounding environment. The abundant data collected by autonomous vehicles in platoons can be transmitted to the infrastructure through vehicle-to-infrastructure (V2I) communications using the IEEE 802.11 distributed coordination function (DCF) mechanism and then uploaded to the cloud platform through the Internet. The cloud platform extracts useful information and then sends it back to the autonomous vehicles respectively. In this way, autonomous vehicles in platoons can detect emergency conditions and make a decision in time. The characteristics of platoons would cause a fair-access problem in the V2I communications, i.e., vehicles in the platoons moving on different lanes with different velocities would have different resident time within the infrastructure’s coverage and thus successfully send different amounts of data to the infrastructure. In this case, the vehicles with different velocities will receive different amounts of useful information from the cloud. As a result, vehicles with a higher velocity are more likely to suffer from a traffic accident as compared to the vehicles with a lower velocity. Hence, this paper considers the fair-access problem and proposes a fair-access scheme to ensure that vehicles with different velocities successfully transmit the same amount of data by adaptively adjusting the minimum contention window of each vehicle according to its velocity. Moreover, the normalized throughput of the proposed scheme is derived. The validity of the fair-access scheme is demonstrated by simulation. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Wireless Communication Technologies for Safe Cooperative Cyber Physical Systems
Sensors 2018, 18(11), 4075; https://doi.org/10.3390/s18114075
Received: 9 September 2018 / Revised: 1 November 2018 / Accepted: 12 November 2018 / Published: 21 November 2018
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Abstract
Cooperative Cyber-Physical Systems (Co-CPSs) can be enabled using wireless communication technologies, which in principle should address reliability and safety challenges. Safety for Co-CPS enabled by wireless communication technologies is a crucial aspect and requires new dedicated design approaches. In this paper, we provide [...] Read more.
Cooperative Cyber-Physical Systems (Co-CPSs) can be enabled using wireless communication technologies, which in principle should address reliability and safety challenges. Safety for Co-CPS enabled by wireless communication technologies is a crucial aspect and requires new dedicated design approaches. In this paper, we provide an overview of five Co-CPS use cases, as introduced in our SafeCOP EU project, and analyze their safety design requirements. Next, we provide a comprehensive analysis of the main existing wireless communication technologies giving details about the protocols developed within particular standardization bodies. We also investigate to what extent they address the non-functional requirements in terms of safety, security and real time, in the different application domains of each use case. Finally, we discuss general recommendations about the use of different wireless communication technologies showing their potentials in the selected real-world use cases. The discussion is provided under consideration in the 5G standardization process within 3GPP, whose current efforts are inline to current gaps in wireless communications protocols for Co-CPSs including many future use cases. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Intersection Intelligence: Supporting Urban Platooning with Virtual Traffic Lights over Virtualized Intersection-Based Routing
Sensors 2018, 18(11), 4054; https://doi.org/10.3390/s18114054
Received: 31 October 2018 / Revised: 16 November 2018 / Accepted: 16 November 2018 / Published: 20 November 2018
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Abstract
The advent of the autonomous car is paving the road to the realization of ideas that will help optimize traffic flows, increase safety and reduce fuel consumption, among other advantages. We present one proposal to bring together Virtual Traffics Lights (VTLs) and platooning [...] Read more.
The advent of the autonomous car is paving the road to the realization of ideas that will help optimize traffic flows, increase safety and reduce fuel consumption, among other advantages. We present one proposal to bring together Virtual Traffics Lights (VTLs) and platooning in urban scenarios, leaning on vehicle-to-vehicle (V2V) communication protocols that turn intersections into virtual containers of data. Newly-introduced protocols for the combined management of VTLs and platoons are validated by simulation, comparing a range of routing protocols for the vehicular networks with the baseline given by common deployments of traditional traffic lights ruled by state-of-the-art policies. The simulation results show that the combination of VTLs and platoons can achieve significant reductions in travel times and fuel consumption, provided that proper algorithms are used to handle the V2V communications. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Design of a Cooperative Lane Change Protocol for a Connected and Automated Vehicle Based on an Estimation of the Communication Delay
Sensors 2018, 18(10), 3499; https://doi.org/10.3390/s18103499
Received: 3 September 2018 / Revised: 6 October 2018 / Accepted: 15 October 2018 / Published: 17 October 2018
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Abstract
Connected and automated vehicles (CAVs) have recently attracted a great deal of attention. Various studies have been conducted to improve vehicle and traffic safety through vehicle to vehicle (V2V) communication. In the field of CAVs, lane change research is considered a very challenging [...] Read more.
Connected and automated vehicles (CAVs) have recently attracted a great deal of attention. Various studies have been conducted to improve vehicle and traffic safety through vehicle to vehicle (V2V) communication. In the field of CAVs, lane change research is considered a very challenging subject. This paper presents a cooperative lane change protocol, considering the impact of V2V communication delay. When creating a path for a lane change in the local path planning module, V2V communication delay occurs. Each vehicle was represented, in our study, by an oriented bounding box (OBB) to determine the risk of collision. We set up a highway driving simulation environment and verified the improved protocol by implementing a longitudinal and lateral controller. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Error Resilient Coding Techniques for Video Delivery over Vehicular Networks
Sensors 2018, 18(10), 3495; https://doi.org/10.3390/s18103495
Received: 24 August 2018 / Revised: 3 October 2018 / Accepted: 15 October 2018 / Published: 17 October 2018
PDF Full-text (4029 KB) | HTML Full-text | XML Full-text
Abstract
Nowadays, more and more vehicles are equipped with communication capabilities, not only providing connectivity with onboard devices, but also with off-board communication infrastructures. From road safety (i.e., multimedia e-call) to infotainment (i.e., video on demand services), there are a lot of applications and [...] Read more.
Nowadays, more and more vehicles are equipped with communication capabilities, not only providing connectivity with onboard devices, but also with off-board communication infrastructures. From road safety (i.e., multimedia e-call) to infotainment (i.e., video on demand services), there are a lot of applications and services that may be deployed in vehicular networks, where video streaming is the key factor. As it is well known, these networks suffer from high interference levels and low available network resources, and it is a great challenge to deploy video delivery applications which provide good quality video services. We focus our work on supplying error resilience capabilities to video streams in order to fight against the high packet loss rates found in vehicular networks. So, we propose the combination of source coding and channel coding techniques. The former ones are applied in the video encoding process by means of intra-refresh coding modes and tile-based frame partitioning techniques. The latter one is based on the use of forward error correction mechanisms in order to recover as many lost packets as possible. We have carried out an extensive evaluation process to measure the error resilience capabilities of both approaches in both (a) a simple packet error probabilistic model, and (b) a realistic vehicular network simulation framework. Results show that forward error correction mechanisms are mandatory to guarantee video delivery with an acceptable quality level , and we highly recommend the use of the proposed mechanisms to increase even more the final video quality. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Secure Authentication Protocol for Wireless Sensor Networks in Vehicular Communications
Sensors 2018, 18(10), 3191; https://doi.org/10.3390/s18103191
Received: 27 July 2018 / Revised: 18 September 2018 / Accepted: 18 September 2018 / Published: 21 September 2018
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Abstract
With wireless sensor networks (WSNs), a driver can access various useful information for convenient driving, such as traffic congestion, emergence, vehicle accidents, and speed. However, a driver and traffic manager can be vulnerable to various attacks because such information is transmitted through a [...] Read more.
With wireless sensor networks (WSNs), a driver can access various useful information for convenient driving, such as traffic congestion, emergence, vehicle accidents, and speed. However, a driver and traffic manager can be vulnerable to various attacks because such information is transmitted through a public channel. Therefore, secure mutual authentication has become an important security issue, and many authentication schemes have been proposed. In 2017, Mohit et al. proposed an authentication protocol for WSNs in vehicular communications to ensure secure mutual authentication. However, their scheme cannot resist various attacks such as impersonation and trace attacks, and their scheme cannot provide secure mutual authentication, session key security, and anonymity. In this paper, we propose a secure authentication protocol for WSNs in vehicular communications to resolve the security weaknesses of Mohit et al.’s scheme. Our authentication protocol prevents various attacks and achieves secure mutual authentication and anonymity by using dynamic parameters that are changed every session. We prove that our protocol provides secure mutual authentication by using the Burrows–Abadi–Needham logic, which is a widely accepted formal security analysis. We perform a formal security verification by using the well-known Automated Validation of Internet Security Protocols and Applications tool, which shows that the proposed protocol is safe against replay and man-in-the-middle attacks. We compare the performance and security properties of our protocol with other related schemes. Overall, the proposed protocol provides better security features and a comparable computation cost. Therefore, the proposed protocol can be applied to practical WSNs-based vehicular communications. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Source Coding Options to Improve HEVC Video Streaming in Vehicular Networks
Sensors 2018, 18(9), 3107; https://doi.org/10.3390/s18093107
Received: 21 August 2018 / Revised: 11 September 2018 / Accepted: 12 September 2018 / Published: 14 September 2018
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Abstract
Video delivery in Vehicular Ad-hoc NETworks has a great number of applications. However, multimedia streaming over this kind of networks is a very challenging issue because (a) it is one of the most resource-demanding applications; (b) it requires high bandwidth communication channels; (c) [...] Read more.
Video delivery in Vehicular Ad-hoc NETworks has a great number of applications. However, multimedia streaming over this kind of networks is a very challenging issue because (a) it is one of the most resource-demanding applications; (b) it requires high bandwidth communication channels; (c) it shows moderate to high node mobility patterns and (d) it is common to find high communication interference levels that derive in moderate to high loss rates. In this work, we present a simulation framework based on OMNeT++ network simulator, Veins framework, and the SUMO mobility traffic simulator that aims to study, evaluate, and also design new techniques to improve video delivery over Vehicular Ad-hoc NETworks. Using the proposed simulation framework we will study different coding options, available at the HEVC video encoder, that will help to improve the perceived video quality in this kind of networks. The experimental results show that packet losses significantly reduce video quality when low interference levels are found in an urban scenario. By using different INTRA refresh options combined with appropriate tile coding, we will improve the resilience of HEVC video delivery services in VANET urban scenarios. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Integrated Longitudinal and Lateral Networked Control System Design for Vehicle Platooning
Sensors 2018, 18(9), 3085; https://doi.org/10.3390/s18093085
Received: 24 July 2018 / Revised: 9 September 2018 / Accepted: 11 September 2018 / Published: 13 September 2018
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Abstract
This paper investigates platoon control of vehicles via the wireless communication network. An integrated longitudinal and lateral control approaches for vehicle platooning within a designated lane is proposed. Firstly, the longitudinal control aims to regulate the speed of the follower vehicle on the [...] Read more.
This paper investigates platoon control of vehicles via the wireless communication network. An integrated longitudinal and lateral control approaches for vehicle platooning within a designated lane is proposed. Firstly, the longitudinal control aims to regulate the speed of the follower vehicle on the leading vehicle while maintaining the inter-distance to the desired value which may be chosen proportional to the vehicle speed. Thus, based on Lyapunov candidate function, sufficient stability conditions formulated in BMIs terms are proposed. For the general objective of string stability and robust platoon control to be achieved simultaneously, the obtained controller is complemented by additional conditions established for guaranteeing string stability. Furthermore, constraints such as actuator saturation, and controller constrained information are also considered in control design. Secondly, a multi-model fuzzy controller is developed to handle the vehicle lateral control. Its objective is to maintain the vehicle within the road through steering. The design conditions are strictly expressed in terms of LMIs which can be efficiently solved with available numerical solvers. The effectiveness of the proposed control method is validated under the CarSim software package. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Energy-Effective Power Control Algorithm with Mobility Prediction for 5G Heterogeneous Cloud Radio Access Network
Sensors 2018, 18(9), 2904; https://doi.org/10.3390/s18092904
Received: 26 July 2018 / Revised: 29 August 2018 / Accepted: 29 August 2018 / Published: 1 September 2018
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Abstract
In 5G networks, heterogeneous cloud radio access network (H-CRAN) is considered a promising future architecture to minimize energy consumption and efficiently allocate resources. However, with the increase in the number of users, studies are performed to overcome the energy consumption problems. In this [...] Read more.
In 5G networks, heterogeneous cloud radio access network (H-CRAN) is considered a promising future architecture to minimize energy consumption and efficiently allocate resources. However, with the increase in the number of users, studies are performed to overcome the energy consumption problems. In this study, we propose a power control algorithm with mobility prediction to provide a high-energy efficiency for 5G H-CRAN. In particular, the proposed algorithm predicts UE mobility in vehicular mobility scenarios and performs remote radio head (RRH) switching operations based on % prediction results. We formulate an optimization problem to maximize the energy efficiency while satisfying the outage probability requirement. We then propose an RRH switching operation based on Markov mobility prediction and optimize the transmission power based on a gradient method. Simulation results demonstrate the improved energy efficiency compared with those of existing RRH switching-operation algorithms. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle A Forward Collision Warning System for Smartphones Using Image Processing and V2V Communication
Sensors 2018, 18(8), 2672; https://doi.org/10.3390/s18082672
Received: 9 July 2018 / Revised: 3 August 2018 / Accepted: 3 August 2018 / Published: 14 August 2018
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Abstract
In this paper, we present a forward collision warning application for smartphones that uses license plate recognition and vehicular communication to generate warnings for notifying the drivers of the vehicle behind and the one ahead, of a probable collision when the vehicle behind [...] Read more.
In this paper, we present a forward collision warning application for smartphones that uses license plate recognition and vehicular communication to generate warnings for notifying the drivers of the vehicle behind and the one ahead, of a probable collision when the vehicle behind does not maintain an established safe distance between itself and the vehicle ahead. The application was tested in both static and mobile scenarios, from which we confirmed the working of our application, even though its performance is affected by the hardware limitations of the smartphones. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle DIFTOS: A Distributed Infrastructure-Free Traffic Optimization System Based on Vehicular Ad Hoc Networks for Urban Environments
Sensors 2018, 18(8), 2567; https://doi.org/10.3390/s18082567
Received: 9 June 2018 / Revised: 2 August 2018 / Accepted: 3 August 2018 / Published: 6 August 2018
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Abstract
Aiming to alleviate traffic congestion, many congestion avoidance and traffic optimization systems have been proposed recently. However, most of them suffer from three main problems. Firstly scalability: they rely on a centralized server, which has to perform intensive communication and computational tasks. Secondly [...] Read more.
Aiming to alleviate traffic congestion, many congestion avoidance and traffic optimization systems have been proposed recently. However, most of them suffer from three main problems. Firstly scalability: they rely on a centralized server, which has to perform intensive communication and computational tasks. Secondly unpredictability: they use smartphones and other sensors to detect the congested roads and warn upcoming vehicles accordingly. In other words, they are used to solve the problem rather than avoiding it. Lastly, infrastructure dependency: they assume the presence of pre-installed infrastructures such as roadside unit (RSU) or cellular 3G/4G networks. Motivated by the above-mentioned reasons, in this paper, we proposed a fully distributed and infrastructure-less congestion avoidance and traffic optimization system for VANET (Vehicular Ad-hoc Networks) in urban environments named DIFTOS (Distributed Infrastructure-Free Traffic Optimization System), in which the city map is divided into a hierarchy of servers. The vehicles that are located in the busy road intersections play the role of servers, thus DIFTOS does not rely on any centralized server and does not need internet connectivity or RSU or any kind of infrastructure. As far as we know, in the literature of congestion avoidance using VANET, DIFTOS is the first completely infrastructure-free congestion avoidance system. The effectiveness and scalability of DIFTOS have been proved by simulation under different traffic conditions. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Toward a More Complete, Flexible, and Safer Speed Planning for Autonomous Driving via Convex Optimization
Sensors 2018, 18(7), 2185; https://doi.org/10.3390/s18072185
Received: 9 May 2018 / Revised: 26 June 2018 / Accepted: 4 July 2018 / Published: 6 July 2018
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Abstract
In this paper, we present a complete, flexible and safe convex-optimization-based method to solve speed planning problems over a fixed path for autonomous driving in both static and dynamic environments. Our contributions are five fold. First, we summarize the most common constraints raised [...] Read more.
In this paper, we present a complete, flexible and safe convex-optimization-based method to solve speed planning problems over a fixed path for autonomous driving in both static and dynamic environments. Our contributions are five fold. First, we summarize the most common constraints raised in various autonomous driving scenarios as the requirements for speed planner developments and metrics to measure the capacity of existing speed planners roughly for autonomous driving. Second, we introduce a more general, flexible and complete speed planning mathematical model including all the summarized constraints compared to the state-of-the-art speed planners, which addresses limitations of existing methods and is able to provide smooth, safety-guaranteed, dynamic-feasible, and time-efficient speed profiles. Third, we emphasize comfort while guaranteeing fundamental motion safety without sacrificing the mobility of cars by treating the comfort box constraint as a semi-hard constraint in optimization via slack variables and penalty functions, which distinguishes our method from existing ones. Fourth, we demonstrate that our problem preserves convexity with the added constraints, thus global optimality of solutions is guaranteed. Fifth, we showcase how our formulation can be used in various autonomous driving scenarios by providing several challenging case studies in both static and dynamic environments. A range of numerical experiments and challenging realistic speed planning case studies have depicted that the proposed method outperforms existing speed planners for autonomous driving in terms of constraint type covered, optimality, safety, mobility and flexibility. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle A Context-Aware Edge-Based VANET Communication Scheme for ITS
Sensors 2018, 18(7), 2022; https://doi.org/10.3390/s18072022
Received: 22 May 2018 / Revised: 20 June 2018 / Accepted: 21 June 2018 / Published: 24 June 2018
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Abstract
We propose a context-aware edge-based packet forwarding scheme for vehicular networks. The proposed scheme employs a fuzzy logic-based edge node selection protocol to find the best edge nodes in a decentralized manner, which can achieve an efficient use of wireless resources by conducting [...] Read more.
We propose a context-aware edge-based packet forwarding scheme for vehicular networks. The proposed scheme employs a fuzzy logic-based edge node selection protocol to find the best edge nodes in a decentralized manner, which can achieve an efficient use of wireless resources by conducting packet forwarding through edges. A reinforcement learning algorithm is used to optimize the last two-hop communications in order to improve the adaptiveness of the communication routes. The proposed scheme selects different edge nodes for different types of communications with different context information such as connection-dependency (connection-dependent or connection-independent), communication type (unicast or broadcast), and packet payload size. We launch extensive simulations to evaluate the proposed scheme by comparing with existing broadcast protocols and unicast protocols for various network conditions and traffic patterns. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Modeling and Characterization of Traffic Flows in Urban Environments
Sensors 2018, 18(7), 2020; https://doi.org/10.3390/s18072020
Received: 11 May 2018 / Revised: 8 June 2018 / Accepted: 20 June 2018 / Published: 23 June 2018
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Abstract
Currently, one of the main challenges faced in large metropolitan areas is traffic congestion. To address this problem, adequate traffic control could produce many benefits, including reduced pollutant emissions and reduced travel times. If it were possible to characterize the state of traffic [...] Read more.
Currently, one of the main challenges faced in large metropolitan areas is traffic congestion. To address this problem, adequate traffic control could produce many benefits, including reduced pollutant emissions and reduced travel times. If it were possible to characterize the state of traffic by predicting future traffic conditions for optimizing the route of automated vehicles, and if these measures could be taken to preventively mitigate the effects of congestion with its related problems, the overall traffic flow could be improved. This paper performs an experimental study of the traffic distribution in the city of Valencia, Spain, characterizing the different streets of the city in terms of vehicle load with respect to the travel time during rush hour traffic conditions. Experimental results based on realistic vehicular traffic traces from the city of Valencia show that only some street segments fall under the general theory of vehicular flow, offering a good fit using quadratic regression, while a great number of street segments fall under other categories. Although in some cases such discrepancies are related to lack of traffic, injecting additional vehicles shows that significant mismatches still persist. Thus, in this paper we propose an equation to characterize travel times over a segment belonging to the sigmoid family; specifically, we apply logistic regression, being able to significantly improve the curve fitting results for most of the street segments under analysis. Based on our regression results, we performed a clustering analysis of the different street segments, showing that they can be classified into three well-defined categories, which evidences a predictable traffic distribution using the logistic regression throughout the city during rush hours, and allows optimizing the traffic for automated vehicles. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Smart Road Traffic Accidents Reduction Strategy Based on Intelligent Transportation Systems (TARS)
Sensors 2018, 18(7), 1983; https://doi.org/10.3390/s18071983
Received: 4 May 2018 / Revised: 6 June 2018 / Accepted: 12 June 2018 / Published: 21 June 2018
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Abstract
Traffic accidents have become an important problem for governments, researchers and vehicle manufacturers over the last few decades. However, accidents are unfortunate and frequently occur on the road and cause death, damage to infrastructure, and health injuries. Therefore, there is a need to [...] Read more.
Traffic accidents have become an important problem for governments, researchers and vehicle manufacturers over the last few decades. However, accidents are unfortunate and frequently occur on the road and cause death, damage to infrastructure, and health injuries. Therefore, there is a need to develop a protocol to avoid or prevent traffic accidents at the extreme level in order to reduce human loss. The aim of this research is to develop a new protocol, named as the Traffic Accidents Reduction Strategy (TARS), for Vehicular Ad-hoc NETworks (VANETs) to minimize the number of road accidents, decrease the death rate caused by road accidents, and for the successful deployment of the Intelligent Transportation System (ITS). We have run multiple simulations and the results showed that our proposed scheme has outperformed DBSR and POVRP routing protocols in terms of the Message Delivery Ratio (MDR), Message Loss Ratio (MLR), Average Delay, and Basic Safety Message. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Use of Energy Efficient Sensor Networks to Enhance Dynamic Data Gathering Systems: A Comparative Study between Bluetooth and ZigBee
Sensors 2018, 18(6), 1801; https://doi.org/10.3390/s18061801
Received: 29 April 2018 / Revised: 31 May 2018 / Accepted: 1 June 2018 / Published: 3 June 2018
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Abstract
As road traffic conditions worsen due to the constantly increasing number of cars, traffic management systems are struggling to provide a suitable environment, by gathering all the relevant information from the road network. However, in most cases these are obtained via traffic detectors [...] Read more.
As road traffic conditions worsen due to the constantly increasing number of cars, traffic management systems are struggling to provide a suitable environment, by gathering all the relevant information from the road network. However, in most cases these are obtained via traffic detectors placed near road junctions, thus providing no information on the conditions in between. A large-scale sensor network using detectors on the majority of vehicles would certainly be capable of providing useful data, but has two major impediments: the equipment installed on the vehicles should be cheap enough (assuming the willingness of private car owners to be a part of the network) and be capable of transferring the required amount of data in due time, as the vehicle passes by the road side unit that acts as interface with the traffic management system. These restrictions reduce the number of technologies that can be used. In this article a series of comprehensive tests have been performed to evaluate the Bluetooth and ZigBee protocols for this purpose from many points of view: handshake time, static and dynamic data transfer (in laboratory conditions and in real traffic conditions). An assessment of the environmental conditions (during tests and probable to be encountered in real conditions) was also provided. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks
Sensors 2018, 18(5), 1413; https://doi.org/10.3390/s18051413
Received: 19 March 2018 / Revised: 19 April 2018 / Accepted: 27 April 2018 / Published: 3 May 2018
Cited by 3 | PDF Full-text (2956 KB) | HTML Full-text | XML Full-text
Abstract
Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. [...] Read more.
Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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Open AccessArticle Estimation of Longitudinal Force and Sideslip Angle for Intelligent Four-Wheel Independent Drive Electric Vehicles by Observer Iteration and Information Fusion
Sensors 2018, 18(4), 1268; https://doi.org/10.3390/s18041268
Received: 13 March 2018 / Revised: 16 April 2018 / Accepted: 18 April 2018 / Published: 20 April 2018
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Abstract
Exact estimation of longitudinal force and sideslip angle is important for lateral stability and path-following control of four-wheel independent driven electric vehicle. This paper presents an effective method for longitudinal force and sideslip angle estimation by observer iteration and information fusion for four-wheel [...] Read more.
Exact estimation of longitudinal force and sideslip angle is important for lateral stability and path-following control of four-wheel independent driven electric vehicle. This paper presents an effective method for longitudinal force and sideslip angle estimation by observer iteration and information fusion for four-wheel independent drive electric vehicles. The electric driving wheel model is introduced into the vehicle modeling process and used for longitudinal force estimation, the longitudinal force reconstruction equation is obtained via model decoupling, the a Luenberger observer and high-order sliding mode observer are united for longitudinal force observer design, and the Kalman filter is applied to restrain the influence of noise. Via the estimated longitudinal force, an estimation strategy is then proposed based on observer iteration and information fusion, in which the Luenberger observer is applied to achieve the transcendental estimation utilizing less sensor measurements, the extended Kalman filter is used for a posteriori estimation with higher accuracy, and a fuzzy weight controller is used to enhance the adaptive ability of observer system. Simulations and experiments are carried out, and the effectiveness of proposed estimation method is verified. Full article
(This article belongs to the Special Issue Advances on Vehicular Networks: From Sensing to Autonomous Driving)
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