Cloud-Assisted Safety Message Dissemination in VANET-Cellular Heterogeneous Wireless Network

In vehicular ad hoc networks (VANETs), efficient message dissemination is critical to road safety and traffic efficiency. Since many VANET-based schemes suffer from high transmission delay and data redundancy, the integrated VANET–cellular heterogeneous network has been proposed recently and attracted significant attention. However, most existing studies focus on selecting suitable gateways to deliver safety message from the source vehicle to a remote server, whereas rapid safety message dissemination from the remote server to a targeted area has not been well studied. In this paper, we propose a framework for rapid message dissemination that combines the advantages of diverse communication and cloud computing technologies. Specifically, we propose a novel Cloud-assisted Message Downlink dissemination Scheme (CMDS), with which the safety messages in the cloud server are first delivered to the suitable mobile gateways on relevant roads with the help of cloud computing (where gateways are buses with both cellular and VANET interfaces), and then being disseminated among neighboring vehicles via vehicle-to-vehicle (V2V) communication. To evaluate the proposed scheme, we mathematically analyze its performance and conduct extensive simulation experiments. Numerical results confirm the efficiency of CMDS in various urban scenarios

Information management and security protection for internet of vehicles

Considering the huge number of vehicles on the roads, the Internet of Vehicles is envisioned to foster a variety of new applications ranging from road safety enhancement to mobile entertainment. These new applications all face critical challenges which are how to handle a large volume of data streams of various kinds and how the secure architecture enhances the security of the Internet of Vehicles systems. This dissertation proposes a comprehensive message routing solution to provide the fundamental support of information management for the Internet of Vehicles. The proposed approach delivers messages via a self-organized moving-zone-based architecture formed using pure vehicle-to-vehicle communication and integrates moving object modeling and indexing techniques to vehicle management. It can significantly reduce the communication overhead while providing higher delivery rates. To ensure the identity and location privacy of the vehicles on the Internet of Vehicles environment, a highly efficient randomized authentication protocol, RAU+ is proposed to leverage homomorphic encryption and enable individual vehicles to easily generate a new randomized identity for each newly established communication while each authentication server would not know their real identities. In this way, not any single party can track the user. To minimize the infrastructure reliance, this dissertation further proposes a secure and lightweight identity management mechanism in which vehicles only need to contact a central authority once to obtain a global identity. Vehicles take turns serving as the captain authentication unit in self-organized groups. The local identities are computed from the vehicle's global identity and do not reveal true identities. Extensive experiments are conducted under a variety of Internet of Vehicles environments. The experimental results demonstrate the practicality, effectiveness, and efficiency of the proposed protocols.Includes bibliographical references

ASGR: An Artificial Spider-Web-Based Geographic Routing in Heterogeneous Vehicular Networks

Recently, vehicular ad hoc networks (VANETs) have been attracting significant attention for their potential for guaranteeing road safety and improving traffic comfort. Due to high mobility and frequent link disconnections, it becomes quite challenging to establish a reliable route for delivering packets in VANETs. To deal with these challenges, an artificial spider geographic routing in urban VAENTs (ASGR) is proposed in this paper. First, from the point of bionic view, we construct the spider web based on the network topology to initially select the feasible paths to the destination using artificial spiders. Next, the connection-quality model and transmission-latency model are established to generate the routing selection metric to choose the best route from all the feasible paths. At last, a selective forwarding scheme is presented to effectively forward the packets in the selected route, by taking into account the nodal movement and signal propagation characteristics. Finally, we implement our protocol on NS2 with different complexity maps and simulation parameters. Numerical results demonstrate that, compared with the existing schemes, when the packets generate speed, the number of vehicles and number of connections are varying, our proposed ASGR still performs best in terms of packet delivery ratio and average transmission delay with an up to 15% and 94% improvement, respectively

Internet of Vehicles: Motivation, Layered Architecture, Network Model, Challenges, and Future Aspects

© 2013 IEEE. Internet of Things is smartly changing various existing research areas into new themes, including smart health, smart home, smart industry, and smart transport. Relying on the basis of 'smart transport,' Internet of Vehicles (IoV) is evolving as a new theme of research and development from vehicular ad hoc networks (VANETs). This paper presents a comprehensive framework of IoV with emphasis on layered architecture, protocol stack, network model, challenges, and future aspects. Specifically, following the background on the evolution of VANETs and motivation on IoV an overview of IoV is presented as the heterogeneous vehicular networks. The IoV includes five types of vehicular communications, namely, vehicle-to-vehicle, vehicle-to-roadside, vehicle-to-infrastructure of cellular networks, vehicle-to-personal devices, and vehicle-to-sensors. A five layered architecture of IoV is proposed considering functionalities and representations of each layer. A protocol stack for the layered architecture is structured considering management, operational, and security planes. A network model of IoV is proposed based on the three network elements, including cloud, connection, and client. The benefits of the design and development of IoV are highlighted by performing a qualitative comparison between IoV and VANETs. Finally, the challenges ahead for realizing IoV are discussed and future aspects of IoV are envisioned

Using Ontologies and Intelligent Systems for Traffic Accident Assistance in Vehicular Environments

A pesar de que las medidas de seguridad en los sistemas de transporte cada vez son mayores, el aumento progresivo del número de vehículos que circulan por las ciudades y carreteras en todo el mundo aumenta, sin duda, la probabilidad de que ocurra un accidente. En este tipo de situaciones, el tiempo de respuesta de los servicios de emergencia es crucial, ya que está demostrado que cuanto menor sea el tiempo transcurrido entre el accidente y la atención hospitalaria de los heridos, mayores son sus probabilidades de supervivencia. Las redes vehiculares permiten la comunicación entre los vehículos, así como la comunicación entre los vehículos y la infraestructura [4], lo que da lugar a una plétora de nuevas aplicaciones y servicios en el entorno vehicular. Centrándonos en las aplicaciones relacionadas con la seguridad vial, mediante este tipo de comunicaciones, los vehículos podrían informar en caso de accidente al resto de vehículos (evitando así colisiones en cadena) y a los servicios de emergencia (dando información precisa y rápida, lo que sin duda facilitaría las tareas de rescate). Uno de los aspectos importantes a determinar sería saber qué información se debe enviar, quién será capaz de recibirla, y cómo actuar una vez recibida. Actualmente los vehículos disponen de una serie de sensores que les permiten obtener información sobre ellos mismos (velocidad, posición, estado de los sistemas de seguridad, número de ocupantes del vehículo, etc.), y sobre su entorno (información meteorológica, estado de la calzada, luminosidad, etc.). En caso de accidente, toda esa información puede ser estructurada y enviada a los servicios de emergencia para que éstos adecúen el rescate a las características específicas y la gravedad del accidente, actuando en consecuencia. Por otro lado, para que la información enviada por los vehículos accidentados pueda llegar correctamente a los servicios de emergencias, es necesario disponer de una infraestructura capaz de dar cobertura a todos los vehículos que circulan por una determinada área. Puesto que la instalación y el mantenimiento de dicha infraestructura conllevan un elevado coste, sería conveniente proponer, implementar y evaluar técnicas consistentes en dar cobertura a todos los vehículos, reduciendo el coste total de la infraestructura. Finalmente, una vez que la información ha sido recibida por las autoridades, es necesario elaborar un plan de actuación eficaz, que permita el rápido rescate de los heridos. Hay que tener en cuenta que, cuando ocurre un accidente de tráfico, el tiempo de personación de los servicios de emergencia en el lugar del accidente puede suponer la diferencia entre que los heridos sobrevivan o fallezcan. Además, es importante conocer si la calle o carretera por la que circulaban los vehículos accidentados ha dejado de ser transitable para el resto de vehículos, y en ese caso, activar los mecanismos necesarios que permitan evitar los atascos asociados. En esta Tesis, se pretende gestionar adecuadamente estas situaciones adversas, distribuyendo el tráfico de manera inteligente para reducir el tiempo de llegada de los servicios de emergencia al lugar del accidente, evitando además posibles atascos.Barrachina Villalba, J. (2014). Using Ontologies and Intelligent Systems for Traffic Accident Assistance in Vehicular Environments [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/39004TESI

Detection and Recognition of Traffic Signs Inside the Attentional Visual Field of Drivers

Traffic sign detection and recognition systems are essential components of Advanced Driver Assistance Systems and self-driving vehicles. In this contribution we present a vision-based framework which detects and recognizes traffic signs inside the attentional visual field of drivers. This technique takes advantage of the driver\u27s 3D absolute gaze point obtained through the combined use of a front-view stereo imaging system and a non-contact 3D gaze tracker. We used a linear Support Vector Machine as a classifier and a Histogram of Oriented Gradient as features for detection. Recognition is performed by using Scale Invariant Feature Transforms and color information. Our technique detects and recognizes signs which are in the field of view of the driver and also provides indication when one or more signs have been missed by the driver

Secure Harmonized Speed Under Byzantine Faults for Autonomous Vehicle Platoons Using Blockchain Technology

Autonomous Vehicle (AV) platooning holds the promise of safer and more efficient road transportation. By coordinating the movements of a group of vehicles, platooning offers benefits such as reduced energy consumption, lower emissions, and improved traffic flow. However, the realization of these advantages hinges on the ability of platooning vehicles to reach a consensus and maintain secure, cooperative behavior. Byzantine behavior [1,2], characterized by vehicles transmitting incorrect or conflicting information, threatens the integrity of platoon coordination. Vehicles within the platoon share vital data such as position, speed, and other relevant information to optimize their operation, ensuring safe and efficient driving. However, Byzantine behavior in AV platoons presents a critical challenge by disrupting coordinated operations. Consequently, the malicious transmission of conflicting information can lead to safety compromises, traffic disruptions, energy inefficiency, loss of trust, chain reactions of faults, and legal complexities [3,4]. In this light, this thesis delves into the challenges posed by Byzantine behavior within platoons and presents a robust solution using ConsenCar; a blockchain-based protocol for AV platoons which aims to address Byzantine faults in order to maintain reliable and secure platoon operations. Recognizing the complex obstacles presented by Byzantine faults in these critical real-time systems, this research exploits the potential of blockchain technology to establish Byzantine Fault Tolerance (BFT) through Vehicle-to-Vehicle (V2V) communications over a Vehicular Ad hoc NETwork (VANET). The operational procedure of ConsenCar involves several stages, including proposal validation, decision-making, and eliminating faulty vehicles. In instances such as speed harmonization, the decentralized network framework enables vehicles to exchange messages to ultimately agree on a harmonized speed that maximizes safety and efficiency. Notably, ConsenCar is designed to detect and isolate vehicles displaying Byzantine behavior, ensuring that their actions do not compromise the integrity of decision-making. Consequently, ConsenCar results in a robust assurance that all non-faulty vehicles converge on unanimous decisions. By testing ConsenCar on the speed harmonization operation, simulation results indicate that under the presence of Byzantine behavior, the protocol successfully detects and eliminates faulty vehicles, provided that more than two-thirds of the vehicles are non-faulty. This allows non-faulty vehicles to achieve secure harmonized speed and maintain safe platoon operations. As such, the protocol generalizes to secure other platooning operations, including splitting and merging, intersection negotiation, lane-changing, and others. The implications of this research are significant for the future of AV platooning, as it establishes BFT to enhance the safety, efficiency, and reliability of AV transportation, therefore paving the way for improved security and cooperative road ecosystems