scholarly journals A Utility Method for the Matching Optimization of Ride-Sharing Based on the E-CARGO Model in Internet of Vehicles

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiaohui Li ◽  
Hongbin Dong ◽  
Shuang Han ◽  
Xiaowei Wang ◽  
Xiaodong Yu
Keyword(s):  
Formal Method ◽  
Transportation Systems ◽  
The Internet ◽  
Time Cost ◽  
Matching Problem ◽  
Matching Rule ◽  
Internet Of Vehicles ◽  
Ride Sharing ◽  
One To One ◽  
On The Road

The Internet of Vehicles (IoV) is the extension of the Internet of Things (IoT) technology in the field of transportation systems. Ride-sharing is one of intelligent travel applications in IoV. Ride-sharing is aimed at taking passengers with similar itineraries and time arrangements to travel in the same car according to a certain matching rule. To effectively integrate transport capacity resources and reduce the number of cars on the road, ride-sharing has become a popular and economical way of travel. The matching and optimizing of drivers and passengers are the core contents of a ride-sharing application system. This paper mainly studies the dynamic real-time matching of passengers and drivers in IoV, considering the main factors such as travel cost, car capacity, and utility. The matching problem is formulated in a ride-sharing system as a Role-Based Collaboration (RBC). A new utility method for the matching optimization of ride-sharing is present. In this paper, we establish a model for simulating the assignment of ride-sharing with the help of the Environments-Classes, Agents, Roles, Groups, and Objects (E-CARGO) model. The objective function and formal definitions are proposed. The utility and time of optimal matching are obtained by using the Kuhn-Munkres algorithm on the revenue matrix. The experimental results show that the proposed formal method based on the E-CARGO model and utility theory can be applied in the ride-sharing problem. Numerical experiments show that the matching time cost increases with the increase of the number of drivers and passengers participating in the ride-sharing system. When the number of drivers and passengers is different, one-to-many matching takes the least time, and one-to-one matching takes more time. When the number of drivers and passengers is the same, the time cost of one-to-one matching increases sharply with a certain value (bigger than 800). Compared with other matching methods, the time spent by the one-to-many method is reduced by 30%. The results show that the proposed solution can be applied to the matching and pricing in a ride-sharing system.

scholarly journals Formal Verification on the Safety of Internet of Vehicles Based on TPN and Z

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yang Liu ◽  
Liyuan Huang ◽  
Jingwei Chen
Keyword(s):  
Formal Verification ◽  
Petri Net ◽  
Formal Method ◽  
Transportation Systems ◽  
Frame Structure ◽  
The Internet ◽  
Internet Of Vehicles ◽  
Accurate Localization ◽  
Verification Methods

Nowadays, the Internet of Vehicles has become the focus of global technological innovation and transformation in the automotive industry. Its flow modelling appears to play a very important role for designing and controlling the transportation systems, since it is not only necessary for improving safety and transportation efficiency but also can yield a series of society, economy, and ecosystem environment problems. Considering the characteristics of the frame structure includes states and actions and discrete and continuous aspects of traffic flow dynamics, both petri net and Z have proved to be useful tools for modelling the Internet of Vehicles. It can formally describe the vehicle behavior accurately with petri net and more details with Z frame structure. A new integration formal method of time petri net and Z is presented in this paper for modelling the vehicle behaviors and traffic rules through taking into account state dependencies on external rules. Moreover, a case study in the Internet of Vehicles is proposed to deal with the accurate localization of events. It shows that this formal verification methods significantly improves the safety and intelligence of the Internet of Vehicles.

scholarly journals Empowering the Internet of Vehicles with Multi-RAT 5G Network Slicing

Sensors ◽  
2019 ◽  
Vol 19 (14) ◽  
pp. 3107 ◽  
Author(s):  
Ramon Sanchez-Iborra ◽  
José Santa ◽  
Jorge Gallego-Madrid ◽  
Stefan Covaci ◽  
Antonio Skarmeta
Keyword(s):  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
The Internet ◽  
Critical Systems ◽  
Core Network ◽  
Resource Assignment ◽  
Network Slicing ◽  
Internet Of Vehicles ◽  
5G Network ◽  
Multi Access

Internet of Vehicles (IoV) is a hot research niche exploiting the synergy between Cooperative Intelligent Transportation Systems (C-ITS) and the Internet of Things (IoT), which can greatly benefit of the upcoming development of 5G technologies. The variety of end-devices, applications, and Radio Access Technologies (RATs) in IoV calls for new networking schemes that assure the Quality of Service (QoS) demanded by the users. To this end, network slicing techniques enable traffic differentiation with the aim of ensuring flow isolation, resource assignment, and network scalability. This work fills the gap of 5G network slicing for IoV and validates it in a realistic vehicular scenario. It offers an accurate bandwidth control with a full flow-isolation, which is essential for vehicular critical systems. The development is based on a distributed Multi-Access Edge Computing (MEC) architecture, which provides flexibility for the dynamic placement of the Virtualized Network Functions (VNFs) in charge of managing network traffic. The solution is able to integrate heterogeneous radio technologies such as cellular networks and specific IoT communications with potential in the vehicular sector, creating isolated network slices without risking the Core Network (CN) scalability. The validation results demonstrate the framework capabilities of short and predictable slice-creation time, performance/QoS assurance and service scalability of up to one million connected devices.

scholarly journals Blockchain for the Internet of Vehicles: A Decentralized IoT Solution for Vehicles Communication Using Ethereum

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3928 ◽  
Author(s):  
Rateb Jabbar ◽  
Mohamed Kharbeche ◽  
Khalifa Al-Khalifa ◽  
Moez Krichen ◽  
Kamel Barkaoui
Keyword(s):  
Intelligent Transportation Systems ◽  
Secure Communication ◽  
Data Exchange ◽  
Smart Cities ◽  
Transportation Systems ◽  
Smart Devices ◽  
The Internet ◽  
Internet Of Vehicles ◽  
Computing Platform ◽  
Blockchain Technology

The concept of smart cities has become prominent in modern metropolises due to the emergence of embedded and connected smart devices, systems, and technologies. They have enabled the connection of every “thing” to the Internet. Therefore, in the upcoming era of the Internet of Things, the Internet of Vehicles (IoV) will play a crucial role in newly developed smart cities. The IoV has the potential to solve various traffic and road safety problems effectively in order to prevent fatal crashes. However, a particular challenge in the IoV, especially in Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications, is to ensure fast, secure transmission and accurate recording of the data. In order to overcome these challenges, this work is adapting Blockchain technology for real time application (RTA) to solve Vehicle-to-Everything (V2X) communications problems. Therefore, the main novelty of this paper is to develop a Blockchain-based IoT system in order to establish secure communication and create an entirely decentralized cloud computing platform. Moreover, the authors qualitatively tested the performance and resilience of the proposed system against common security attacks. Computational tests showed that the proposed solution solved the main challenges of Vehicle-to-X (V2X) communications such as security, centralization, and lack of privacy. In addition, it guaranteed an easy data exchange between different actors of intelligent transportation systems.

scholarly journals A Survey of Trust Management in the Internet of Vehicles

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2223 ◽  
Author(s):  
Sarah Ali Siddiqui ◽  
Adnan Mahmood ◽  
Quan Z. Sheng ◽  
Hajime Suzuki ◽  
Wei Ni
Keyword(s):  
Intelligent Transportation Systems ◽  
Trust Management ◽  
Weighting Factor ◽  
Transportation Systems ◽  
The Internet ◽  
Internet Of Vehicles ◽  
The Past ◽  
Management Models ◽  
Open Research ◽  
The Subject

Over the past decade, the groundbreaking technological advancements in the Internet of Vehicles (IoV) coupled with the notion of trust have attracted increasing attention from researchers and experts in intelligent transportation systems (ITS), wherein vehicles establish a belief towards their peers in the pursuit of ensuring safe and efficacious traffic flows. Diverse domains have been taking advantage of trust management models in the quest of alleviating diverse insider attacks, wherein messages generated by legitimate users are altered or counterfeited by malicious entities, subsequently, endangering the lives of drivers, passengers, and vulnerable pedestrians. In the course of vehicles forming perceptions towards other participating vehicles, a range of contributing parameters regarding the interactions among these vehicles are accumulated to establish a final opinion towards a target vehicle. The significance of these contributing parameters is typically represented by associating a weighting factor to each contributing attribute. The values assigned to these weighting factors are often set manually, i.e., these values are predefined and do not take into consideration any affecting parameters. Furthermore, a threshold is specified manually that classifies the vehicles into honest and dishonest vehicles relying on the computed trust. Moreover, adversary models as an extension to trust management models in order to tackle the variants of insider attacks are being extensively emphasized in the literature. This paper, therefore, reviews the state of the art in the vehicular trust management focusing on the aforementioned factors such as quantification of weights, quantification of threshold, misbehavior detection, etc. Moreover, an overarching IoV architecture, constituents within the notion of trust, and attacks relating to the IoV have also been presented in addition to open research challenges in the subject domain.

Social Internet of Vehicles

2019 ◽  
pp. 172-188
Author(s):  
Talal A. Butt ◽  
Razi Iqbal ◽  
Mounir Kehal
Keyword(s):  
Intelligent Transportation Systems ◽  
Transportation Systems ◽  
Vital Role ◽  
The Internet ◽  
Internet Of Vehicles ◽  
Smart Systems ◽  
Gcc Countries ◽  
The World ◽  
Use Of Internet ◽  
Insight Into

Advent of internet of things (IoT) has significantly enriched the opportunities of crafting state-of-the-art applications of smart connected objects. Intelligent transportation systems (ITS) are playing a vital role in the development of smart systems for transportation throughout the world. Based on IoT, the internet of vehicles (IoV) paradigm is emerging to revolutionize the field of ITS. In this paradigm, vehicles leverage the use of internet for socializing with other vehicles, infrastructures, passengers, and drivers. This concept of vehicle socialization is referred to as social internet of vehicles (SIoV). This chapter presents the GCC (Gulf Cooperation Council) perspective of SIoVs by highlighting the latest trends being followed by GCC countries in the broader field ITS. It also provides an insight into opportunities enabled by SIoV applications that can be availed by GCC countries along with the challenges and limitations.

scholarly journals Cooperation and radio silence strategy in Mix Zone to Protect Location Privacy of Vehicle in VANET

2021 ◽  
Vol 28 (1) ◽  
pp. 31-39
Author(s):  
Izdihar Shaleesh ◽  
Akram Almohammedi ◽  
Naji Mohammad ◽  
Ali Ahmad ◽  
Vladimir Shepelev
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Accidents ◽  
Location Privacy ◽  
Smart Cities ◽  
Transportation Systems ◽  
High Rate ◽  
The Internet ◽  
Vehicular Communication ◽  
Internet Of Vehicles ◽  
The Internet Of Things

With increase in the population, the number of registered vehicles has dramatically increased over all the world, and this leads to a high rate of traffic accidents on the roads. Therefore, in order to prevent such accidents, an Intelligent Transportation Systems (ITSs) is needed to be installed to notify drivers of obstacles in advance. Recently, the Internet of things (IoT) evolves the vehicular communications and covers this technology under the Internet of vehicles (IoV) application. IoV is a new field for the automotive industry and a significant part of the smart cities. However, protecting the privacy of vehicle's location is the most challenging subject in the vehicular communication, as because it threatens the personal life of drivers. This paper provides cooperation and radio silence strategy in mix zone (CRSMZ) to protect location privacy of vehicle in IoV. The strategy implements either cooperation or radio silence depending on the speed of the vehicle while it is in mix _zone. The simulation results show that CRSMZ is an efficient strategy to protect location information of vehicle drivers. CRSMZ outperforms the existing strategies in terms of mean of the number tracker confusion, continuous tracking period and max of the entropy.

scholarly journals Convolutional neural networkscheme–based optical camera communication system for intelligent Internet of vehicles

2018 ◽  
Vol 14 (4) ◽  
pp. 155014771877015 ◽  
Author(s):  
Amirul Islam ◽  
Md Tanvir Hossan ◽  
Yeong Min Jang
Keyword(s):  
Light Emitting Diodes ◽  
Light Emitting Diode ◽  
Transportation Systems ◽  
Transport Systems ◽  
The Internet ◽  
Promising Alternative ◽  
Internet Of Vehicles ◽  
Light Emitting ◽  
Traffic Lights ◽  
Optical Camera Communication

The evolution of the Internet of vehicles and growing use of mobile devices has created a demand for new wireless communication technologies. Optical camera communication, which uses light-emitting diodes as transmitters and cameras as receivers, has emerged as a promising alternative. Since light-emitting diodes and cameras are already exploring in traffic lights, vehicles, and public lightings, optical camera communication has the potential to intelligently handle transport systems. Although other technologies have been proposed or developed in both academia and industry, they are not yet mature enough to uphold the huge requirements of the Internet of vehicles. This study introduces a new intelligent Internet of vehicles system based on optical camera communication combined with convolutional neural networks. Optical camera communication is a promising candidate for maintaining interference-free and more robust communication, for supporting the Internet of vehicles. Convolutional neural network is introduced for precise detection and recognition of light-emitting diode patterns at long distances and in bad weather conditions. We propose an algorithm to detect the interested light-emitting diode signals (i.e. regions-of-interest), measure the distance using a stereo-vision technique to find out the desired targets, and simulate our proposed scheme using a MATLAB Toolbox. Thus, our system will provide great advantages for next-generation transportation systems.

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