Vehicular Ad Hoc Networks Services Research Articles

Blockchain-based secret key extraction for efficient and secure authentication in VANETs

Intelligent transportation systems are an emerging technology that facilitates real-time vehicle-to-everything communication. Hence, securing and authenticating data packets for intra- and inter-vehicle communication are fundamental security services in vehicular ad-hoc networks (VANETs). However, public-key cryptography (PKC) is commonly used in signature-based authentication, which consumes significant computation resources and communication bandwidth for signatures generation and verification, and key distribution. Therefore, physical layer-based secret key extraction has emerged as an effective candidate for key agreement, exploiting the randomness and reciprocity features of wireless channels. However, the imperfect channel reciprocity generates discrepancies in the extracted key, and existing reconciliation algorithms suffer from significant communication costs and security issues. In this paper, PKC-based authentication is used for initial legitimacy detection and exchanging authenticated probing packets. Accordingly, we propose a blockchain-based reconciliation technique that allows the trusted third party (TTP) to publish the correction sequence of the mismatched bits through a transaction using a smart contract. The smart contract functions enable the TTP to map the transaction address to vehicle-related information and allow vehicles to obtain the transaction contents securely. The obtained shared key is then used for symmetric key cryptography (SKC)-based authentication for subsequent transmissions, saving significant computation and communication costs. The correctness and security robustness of the scheme are proved using Burrows–Abadi–Needham (BAN)-logic and Automated Validation of Internet Security Protocols and Applications (AVISPA) simulator. We also discussed the scheme’s resistance to typical attacks. The scheme’s performance in terms of packet delay and loss ratio is evaluated using the network simulator (OMNeT++). Finally, the computation analysis shows that the scheme saves ∼99% of the time required to verify 1000 messages compared to existing PKC-based schemes.

Bi-linear mapping integrated machine learning based authentication routing protocol for improving quality of service in vehicular Ad-Hoc network

Recently, most of the critical problems of real-time applications have been solved by one of the fast and most hastily growing technological tools, Machine Learning. The novel architectures of Vehicular Ad-hoc Networks reduce traffic congestion and accidents since the number of electric vehicles is increasing daily. There is a need for an efficient and secured routing protocol for better implementation of VANET. Machine learning algorithms help in achieving such efficiency and security. This paper develops a Novel Machine Learning based Authentication Routing protocol by integrating the Long-Short-Term-Memory model with the Bi-Lear Mapping algorithm to analyze the routing data and authenticate the network users. The bi-Linear Mapping model assigns and compares the node's private and public keys, whereas LSTM analyses the routing table information. The proposed model is simulated in NS3 software, and the performance is verified. The results show that the proposed model obtained better throughput, PDR, energy efficiency, authentication which is better than the earlier methods.

Using a Fuzzy-Bayesian Approach for Predicting the QoS in VANET

Abstract There are considerable obstacles in the transport sector of developing countries, including poor road conditions, poor road maintenance and congestion. The dire impacts of these challenges could be extremely damaging to both human lives and the economies of the countries involved. Intelligent Transportation Systems (ITSs) integrate modern technologies into existing transportation systems to monitor traffic. Adopting Vehicular Adhoc Network (VANET) into the road transport system is one of the most ITS developments demonstrating its benefits in reducing incidents, traffic congestion, fuel consumption, waiting times and pollution. However, this type of network is vulnerable to many problems that can affect the availability of services. This article uses a Fuzzy Bayesian approach that combines Bayesian Networks (BN) and Fuzzy Logic (FL) for predicting the risks affecting the quality of service in VANET. The implementation of this model can be used for different types of predictions in the networking field and other research areas.

Sybil Attack Detection in VANET Using Machine Learning Approach

VANET (Vehicular Ad-hoc Network) is a subclass of MANET in which many cars can connect with one another via node to node or equipment erected on the side of the road. However, due to the adaptability of centres and the unexpected trade in geography, there may be opportunities for attacks in VANET. One of the ostensible assaults is the Sybil attack, in which the attacker fabricates unequivocally unique equal personalities to undermine the value of VANET. Sybil creates fictitious identities inside the community as well in order to sabotage attempts to mediate conversations between community nodes. Sybil assaults have an impact on carrier transportation in relation to things like traffic congestion, road safety, and multimedia entertainment. VANETs therefore announce a security mechanism to protect you from Sybil attacks. In this regard, this work puts forth the SDTC method, which completely relies on machine learning techniques to prevent Sybil assaults in VANETs. In order to reduce identification time, increase detection accuracy, and enhance scalability, the SDTC (Sybil node detecting the use of Classification) mechanism uses a few vehicle-specific Extreme Learning Machine (ELM) features. The results suggest that SDTC is a suitable strategy to reduce Sybil assaults and sustain provider service in VANETs.

Autonomous Vehicles: Resource Allocation, Security, and Data Privacy

Vehicular Ad-hoc Network (VANET) is a technology of importance for the Intelligent Transportation System, which provides safe and comfortable driving, infotainment, traffic management, route optimization, accident prevention, etc. Imparting suitable Quality of Service (QoS), high reliability, and low latency in VANET is a task that is challenging due to the presence of various constraints such as dynamic topology, an imperfection in hardware, congestion in the channel, fluctuation in vehicle density, etc. It is essential to allocate and utilize the resources effectively to maximize the benefit and enhance network performance. It is vital to use the available bandwidth, power, computing, and storage resources efficiently. Along with resource allocation, security and privacy challenges are of equal importance for VANET. One of the major concerns is to make the communication channel secure and prevent the network from attacks by malicious agents. Also, preserving the privacy of vehicles by hiding real identities to circumvent tracking is a challenging task. The authorized agents are allowed to know the actual identity of vehicles. This paper exhibits an in-depth survey of resource allocation schemes in different aspects of VANET. It analyzes the security and privacy of messages, vehicles, and the overall network. Also, the paper presents and discusses the open issues and future research areas in resource allocation, security, and privacy of VANET.

Multi-objective flower pollination algorithm applied to 5G vehicular networks communication

The Cellular Vehicle-to-Everything (C-V2X) technology, as a widest version of Vehicular Ad-hoc Network (VANET), aims to interconnect vehicles and any other latest technological infrastructures. In this context, the fifth generation of mobile networks (5G) based on millimeter waves (mmWave) is an excellent alternative for the implementation of vehicular networks, mainly because it is capable of providing high data rates (Gbps) and ultra-low latency, requirements of C-V2X. On the other hand, mmWave signals are highly susceptible to blocking, causing low quality of service (QoS) in VANETs, compromising network functionality and the safety of drivers and pedestrians. Thus, in this work evolutionary computing techniques are applied in the simulation of a 5G vehicular network based on millimeter waves, exploring Media Access Control (MAC) sublayer parameters to optimize packet loss, latency and throughput, in order to optimize inter-vehicular communication. The Multi-objective Flower Pollination Algorithm (MOFPA) was used for this purpose. The results obtained show that the adopted approach can reach results close to the optimal pareto of non-dominated solutions, with a 75% reduction in exploration time in relation to the exhaustive search process. Finally, the performance of the metaheuristics adopted is compared with the non-dominated genetic classification algorithm (NSGA-II) and the multi-objective differential evolutionary algorithm (MODE).

Particle Swarm Optimization Video Streaming Service in Vehicular Ad-Hoc Networks

Owing to the increasing capabilities of mobile devices and the development of mobile communication techniques in vehicular ad hoc networks (VANETs), mobile multimedia services have focused on supporting high Quality of Service (QoS) and Quality of Experience (QoE) for the subscribers in video streaming services. In VANETs, high-quality video streaming services aim to provide safety, as well as various infotainment applications to the subscribers. Owing to the dynamic topology and frequent connectivity changes in moving vehicles, video streaming services require elastic and continuous updates of vehicle information to present interactive real-time views of nontrivial scenarios on roads. To achieve high QoS and QoE of video streaming services in VANETs, this paper proposes a novel protocol named PSOstreaming that is based on a particle swarm optimization (PSO) which is one one of the mainstream and nature-inspired algorithms for swarm intelligence (SI). PSOstreaming calculates the PSQ score, which is the scoring method of the node in the topology in terms of the data communication capability measurement to analyze and optimize topology information in real-road circumstances. In addition, PSOstreaming utilizes a 3D vector mobility prediction algorithm for the mobility prediction method for the vehicles to address the characteristics of VANETs. In the topology, PSOstreaming defines Global PSO members and Local PSO members to disseminate video packets for video-streaming services to the service requester by computational equations. Experimental results indicate that PSOstreaming achieves high-quality video streaming services with a flexible response to dynamic topology changes and a high frame delivery ratio in terms of QoS and QoE.

An optimized location service for the fifth generation VANETs inspired by traffic lights.

Vehicular ad-hoc networks (VANETs) address a steadily expanding demand, particularly for public emergency applications. Real-time localization of destination vehicles is important for determining the route to deliver messages. Existing location administration services in VANETs are classified as flooding-based, flat-based, and geographic-based location services. Existing localization techniques suffer from network disconnection and overloading because of 5G VANET topology changes. 5G VANETs have low delay and support time-sensitive applications. A traffic light-inspired location service (TLILS) is proposed to manage localization inspired by traffic lights. The proposed optimized localization service uses roadside units (RSUs) as location servers. RSUs with the maximum traffic weight metrics were chosen. Traffic weight metrics are based on speed of vehicles, connection time and density of neighboring vehicles. The proposed TLILS outperforms both Name-ID Hybrid Routing (NIHR) and Zoom-Out Geographic Location Service (ZGLS) for packet delivery ratio (PDR) and delay. TLILSs guarantee the highest PDR (0.96) and the shortest end-to-end delay (0.001 s) over NIHR and ZGLS.

Video Packet Distribution Scheme for Multimedia Streaming Services in VANETs.

By leveraging the development of mobile communication technologies and due to the increased capabilities of mobile devices, mobile multimedia services have gained prominence for supporting high-quality video streaming services. In vehicular ad-hoc networks (VANETs), high-quality video streaming services are focused on providing safety and infotainment applications to vehicles on the roads. Video streaming data require elastic and continuous video packet distributions to vehicles to present interactive real-time views of meaningful scenarios on the road. However, the high mobility of vehicles is one of the fundamental and important challenging issues for video streaming services in VANETs. Nevertheless, previous studies neither dealt with suitable data caching for supporting the mobility of vehicles nor provided appropriate seamless packet forwarding for ensuring the quality of service (QoS) and quality of experience (QoE) of real-time video streaming services. To address this problem, this paper proposes a video packet distribution scheme named Clone, which integrates vehicle-to-vehicle and vehicle-to-infrastructure communications to disseminate video packets for video streaming services in VANETs. First, an indicator called current network quality information (CNQI) is defined to measure the feature of data forwarding of each node to its neighbor nodes in terms of data delivery ratio and delay. Based on the CNQI value of each node and the trajectory of the destination vehicle, access points called clones are selected to cache video data packets from data sources. Subsequently, packet distribution optimization is conducted to determine the number of video packets to cache in each clone. Finally, data delivery synchronization is established to support seamless streaming data delivery from a clone to the destination vehicle. The experimental results show that the proposed scheme achieves high-quality video streaming services in terms of QoS and QoE compared with existing schemes.

State-of-Art and Open Issues of Cross-Layer Design and QOS Routing in Internet of Vehicles

VANET (Vehicular Ad Hoc Network) is a significant term in ITS (intelligent transportation systems). VANETs are also mentioned as ITN (intelligent transportation Networks), which are used to enhance road safety in growing technology. The connectivity of nodes is a challenging one because of its high mobility and the sparse network connectivity must be handled properly during its initial deployment of a VANET for avoiding accidents. Quality of service (QoS) in VANET becomes a significant term because of its increasing dare about unique features, like poor link quality, high mobility, and inadequate transporting distance. Routing is the foremost issue in the wireless ad hoc network, which is used to transmit data packets significantly. This paper provides a crucial review of the classification of existing QoS routing protocols, cross-layer design approach and classification, and various performance parameters used in QoS routing protocols. The corresponding cross-layer protocols are overviewed, followed by the major techniques in cross-layer protocol design. Moreover, VANET is presented with many exclusive networking research challenges in precise areas such as security, QoS, mobility, effective channel utilization, and scalability. Finally, the paper concluded by various comparison discussion, issues, and challenges of several routing protocols for VANET. No. of publications over the period from 2010 to 2019 in various scientific sources also showed in this review. This survey provided the technical direction for researchers on routing protocols for VANET using QoS.

BaaS: Broadcast as a service cross-layer learning-based approach in cloud assisted VANETs

Broadcasting plays a significant role for data dissemination in Vehicular Ad hoc Network (VANET). Many VANET services rely on broadcast communication mode to disseminate data packets over the network. However, due to high mobility of vehicles, it stills being a challenging task. In this paper, a BaaS (Broadcast as a Service ) broadcasting solution is proposed for VANET to disseminate the data efficiently to the vehicles in the network using cloud computing. Due to the limited storage and computing capacity of vehicles, all information about road traffic and the broadcasting protocol is both maintained and processed in the cloud. So, we introduce a new cloud assisted VANET (CAV) architecture organizing the different levels of communications between the VANET components and the cloud, as well as between the three cloud layers. The source vehicle broadcasts the message by requesting the best relay set from the nearby road side unit (RSU) which plays the role of intermediate to the cloud. To perform the message forwarding, the cloud provides cross layer services: infrastructure as a service for traffic data storage and relay set selection processing, and application layer service for communication with VANET entities. By integrating cloud services many broadcasting problems may be reduced such as the delay and link breakage.

An Advanced Fitness Based Routing Protocol for Improving QoS in VANET

The vehicular ad-hoc network (VANET) is the one Ad-hoc network in wireless which establishes sufficient communication between the vehicles. Improving the quality of service (QoS) in VANET is one of the demanding and crucial processes in recent days. For this reason, various routing protocols, such as proactive and reactive ones, are developed in the present works. Even though it still lacks because of limitations like reduced energy, packet delivery, throughput, and increased delay. Due to these shortcomings, an advanced protocol with reactive routing known as the fitness based ad-hoc on-demand distance vector (FBAODV) will be introduced in the proposed work with the novel computation of received signal strength indication along with the normal steps found in AODV like distance, velocity, mobility, direction. The functioning stages involved in this proposed work will be network formation, neighbour discovery, fitness function estimation, and routing process. After forming the network with a set of wireless nodes, the routes will be discovered between the source node and destination node by broadcasting the Hello message packets. Then, the nearest neighbouring nodes will be identified by calculating the Euclidean distance. Here, the fitness function considered is estimated by selecting the reliable nodes based on the parameters of QoS. Consequently, the routing process will be established by finding the cost for the routing paths that had been deployed earlier. By using this cost value, the reliable communicating nodes will then be selected for the packets export from the source to destination. During the network simulation, various performance measures will then be taken into account to evaluate our proposed FBAODV protocol. Also, we prove the efficiency by comparing it with other traditional protocols.

Analysing the Performance of SDN/OpenFlow Controllers in VANET

One of the key enablers of the evolving 5G technology are Vehicular Ad hoc Networks (VANETs) and Software Defined Networking (SDN). The development of next generation intelligent vehicular networks includes integration of SDN in Vehicular Ad hoc Networks (VANETs). Researchers have focused on the development of the integrated technology including architecture and benefits of SDN based VANET services. In this paper we have simulated the Vehicular Ad hoc Networks (VANETs) using Mininet-wifi. The VANET is incorporated with SDN controller. The performance is evaluated by varying the speed of vehicles. We have evaluated the performance in two ways: performance evaluation of V2V communication in same RSU and performance evaluation of V2V communication from different RSU. We have evaluated the proposed system for POX and RYU SDN OpenFlow controllers. As demonstrated in the results the RYU controller of SDN performs better as compared to POX controller in terms of average delay and throughput.

Towards a smarter directional data aggregation in VANETs

In the last decade, Vehicular Ad hoc NETworks (VANETs) have attracted researchers, automotive companies and public governments, as a new communication technology to improve the safety of transportation systems aiming at offering smooth driving and safer roads. In this respect, a new Traffic Information System (TIS) has benefited from VANET services. The ultimate goal of a TIS consists in properly informing vehicles about road traffic conditions in order to reduce traffic jams and consequently CO2 emission while increasing the user comfort. To fulfil these goals, traffic information data or Floating Car data (FCD) must be efficiently exchanged between mobile vehicles by avoiding as far as possible the broadcast storm problem. In this respect, data aggregation appears as an interesting approach allowing to integrate FCD messages to generate a summary (or aggregate), which undoubtedly leads to reduce network traffic. We introduce, in this paper, a new data aggregation protocol, called Smart Directional Data Aggregation (SDDA). The main idea behind our SDDA protocol is to select the most pertinent FCD messages that must be aggregated. To this end, we rely on three filters: The first one is based on the vehicle’s directions. Indeed, every vehicle aggregates only FCD messages corresponding to its direction. Furthermore, it stores, carries and forwards uninteresting data. The second one is carried out by using road speed limitation. The third one relies on a suppression technique to remove duplicated FCD messages. Interestingly enough, our protocol works properly in both highway and urban conditions. The performed experiments show that SDDA outperforms the pioneering approaches of the literature in terms of effectiveness and efficiency.

Security and design requirements for software-defined VANETs

The evolving of Fifth Generation (5G) networks is becoming more readily available as a significant driver of the growth of new applications and business models. Vehicular Ad hoc Networks (VANETs) and Software Defined Networking (SDN) represent the critical enablers of 5G technology with the development of next-generation intelligent vehicular networks and applications. In recent years, researchers have focused on the integration of SDN and VANET, and looked at different topics related to the architecture, the benefits of software-defined VANET services, and the new functionalities to adapt them. However, the security and robustness of the complete architecture is still questionable and have been largely neglected by the research community. Moreover, the deployment and integration of different entities and several architectural components drive new security threats and vulnerabilities.In this paper, first, we survey the state-of-the-art SDN based Vehicular ad-hoc Network (SDVN) architectures for their networking infrastructure design, functionalities, benefits, and challenges. Then we discuss these architectures against major security threats that violate the key security services such as availability, privacy, authentication, and data integrity. We also discuss different countermeasures for these threats. Finally, we present the lessons learned with the directions of future research work towards provisioning stringent security solutions in new SDVN architectures. To the best of our knowledge, this is the first work that presents a comprehensive survey and security analysis on SDVN architectures, and we believe that it will help researchers to address various challenges (e.g., flexible network management, control and high resource utilization, and scalability) in vehicular communication systems which are required to improve the future Intelligent Transportation Systems (ITS).

Spectrum Allocation Strategies Based on QoS in Cognitive Vehicle Networks

The vehicular ad hoc network (VANET) is an important part of modern intelligent transportation systems (ITS), and its emergence has provided support for improving traffic safety and driving experience. The problem of spectrum scarcity has become evident due to the increasing demand for various VANET services. Using cognitive radio (CR) technology in VANET to solve the problem of spectrum scarcity has become a research focus in recent years. The existing spectrum allocation mechanism cannot effectively solve problems, such as high delay, uncertain quality of service (QoS), and low throughput. In this study, we investigate the spectrum allocation strategies in CR for VANET(CR-VANET). For different network optimization indicators under different load networks, we divide CR-VANET into two scenarios: high-load CR-VANET (HCR-VANET) and low-load CR-VANET (LCR-VANET). In LCR-VANET, we establish a model for maximizing throughput with two constraints and propose a channel allocation scheme based on a greedy algorithm (CASGA) to maximize the network throughput. In HCR-VANET, application services are divided into safe application services(SAS) and unsafe application services. To improve the acceptance probability of SAS, we also propose an SMDP-based channel allocation scheme (SMDP-CAS) to maximize the acceptance probability of SAS. Simulation results prove that CASGA and SMDP-CAS greatly improve the throughput of the network and the acceptance probability of SAS.

Context-aware data-centric misbehaviour detection scheme for vehicular ad hoc networks using sequential analysis of the temporal and spatial correlation of the consistency between the cooperative awareness messages

Vehicular ad hoc Networks (VANETs) have emerged mainly to improve road safety, traffic efficiency, and passenger comfort. The performance of most VANET applications and services relies on the availability of accurate and up-to-date mobility-information, through so-called Cooperative Awareness Messages (CAMs), shared by neighbouring vehicles. However, sharing false mobility information can disrupt any potential VANET application. As cryptographic techniques used to protect CAMs in VANETs are expensive, complicated, and vulnerable to internal misbehaviour, security lapses are inevitable. Although several misbehaviour detection solutions have been proposed, those solutions assume that the VANET's context is stationary, which does not hold for VANETs in a real scenario, as the vehicle's context changes continuously. The use of static and predefined security thresholds in highly dynamic and harsh environments is the major drawback of those solutions. To address this issue, a context-aware data-centric misbehaviour detection scheme (CA-DC-MDS) is proposed, using sequential analysis of temporal and spatial correlation of the consistency between neighbouring vehicles' mobility information. The static thresholds have been replaced by a dynamic context reference model that is constructed online and updated in a timely fashion using statistical techniques. Firstly, the Kalman filter algorithm is used to track the mobility information received from neighbouring vehicles. Then, the innovation errors of the Kalman filter are utilized to construct a temporal consistency assessment model for each neighbouring vehicle, using a box-and-whisker plot. After that, the Hampel filter is used to construct a spatial consistency assessment model that represents the current context reference. Similarly, plausibility assessment reference models are built online and updated in a timely fashion using the Hampel filter and by utilizing the consistency assessment reference model of neighbouring information. Finally, a message is classified as suspicious if its consistency and plausibility scores deviate significantly from the context reference model. The proposed context-aware scheme achieved a 73% reduction in the false alarm rate while achieving a 37% improvement in the detection rate. This demonstrates the effectiveness of the proposed context-aware scheme compared with the existing static solutions.

LPPA: Lightweight Privacy-Preserving Authentication From Efficient Multi-Key Secure Outsourced Computation for Location-Based Services in VANETs

Location-based service (LBS) in vehicular ad hoc networks (VANETs) has significantly benefited information acquisition from geographically-based social networking. Authentication guarantees the unforgeability and the effectiveness of the LBS information. Unfortunately, owing to a large quantity of redundant or useless LBS messages disseminated in VANETs, the heavy authentication overhead of the existing work adopting a periodically released authentication key, filtering with message identifiers or exploiting public key (fully) homomorphic encryption (FHE), is either intolerable by resource-constrained on-board units (OBUs) or inappropriate to the realtime controlling requirement for VANETs. In this paper, an efficient multi-key secure outsourced computation scheme MSOC without exploiting public key FHE is first proposed, in the setting of two non-colluding servers, namely the cloud and the cryptographic service provider (CSP). Then, based on MSOC, an efficient and secure comparison protocol LSCP is devised, without the interaction between the server and the users. Furthermore, a lightweight privacy-preserving authentication protocol LPPA for LBS in VANETs is proposed, by eliminating duplicate and useless encrypted LBS messages before authentication is executed, through a newly devised efficient privacy-preserving information filtering system. Both user’s location privacy and interest privacy are well protected against even the collusion between the roadside units (RSUs) serving as the cloud (or CSP) and malicious users. Especially, the property of ciphertext re-encryption of our proposed MSOC also guarantees the interest pattern privacy whether two users accept the same LBS information. Finally, formal security proof and extensive simulation results verify the effectiveness and practicability of our proposed LPPA.

JARINGAN AD-HOC VEHICULAR (VANET) : TINJAUAN TENTANG ARSITEKTUR, KARAKTERISTIK, APLIKASI, DAN PROTOKOL MEDIUM ACCESS CONTROL (MAC)

VANET (Vehicular Ad-hoc Network) is an ad-hoc wireless network which nodes are composed by mostly moving vehicles and infrastructure communications or access points along the road. It integrates adhoc networking, cellular technology, wireless LAN and other technologies, which include GPS(Global Positioning System), digital mapping, sensing technologies and advanced information processing tools to support Intelligent Traffic Systems (ITS). VANET is developed mainly to improve road safety and to increase the traffic efficiency. It is designed to support the exchange of warning messages among the vehicles to increase the passenger safety and other information related to VANET applications and services . To achieve these goals, there are several issues that should be addressed. One of these challenges is designing reliable and efficient Medium Access Control (MAC) protocol for VANET. Due to VANET’s distinguishing characteristics, such as high mobility of the nodes, dynamic network topology, enough battery power, high processing power, etc, the MAC protocols designed for MANET (Mobile Ad-hoc Network) are not suitable for VANET. The research community has been working to develop MAC protocols appropriate for this ad-hoc network by proposing new design or modifying the existing one.In this paper, the VANET’s architecture, characteristics, applications and standard are discussed and then a comprehensive study of several MAC protocols available in the literature is presented.

A Game Theory Approach for Platoon-Based Driving for Multimedia Transmission in VANETs

Vehicular Ad Hoc Networks (VANETs) allow users, services, and vehicles to share information and will change our life experience with new autonomous driving applications. Multimedia will be one of the core services in VANETs and are becoming a reality in smart environments, ranging from safety and security traffic warnings to live entertainment and advertisement videos. However, VANETs have a dynamic network topology with short contact time, which leads to communication flaws and delays, increasing packet loss, and decreasing the Quality of Experience (QoE) of transmitted videos. To cope with this, neighbor vehicles moving on the same direction and wishing to cooperate should form a platoon, where platoon members act as a relay node to forward video packets in autonomous VANETs. In this article, we introduce a game theory approach for platoon-based driving (GT4P) for video dissemination services in urban and highway VANET scenarios. GT4P encourages the cooperation between neighbor vehicles by offering reward (e.g., money or coupon) for vehicles participating in the platoon. In this sense, GT4P establishes a platoon by taking into account vehicle direction, speed, distance, link quality, and travel path, which reduces the impact of vehicle mobility on the video transmission. Simulation results confirm the efficiency of GT4P for ensuring video transmissions with high QoE support compared to existing platoon-based driving protocols.