Challenges and Opportunities for Multimedia Transmission in Vehicular Ad Hoc Networks: A Comprehensive Review

Abstract

This review paper delves into the challenges and opportunities associated with multimedia transmission in vehicular ad hoc networks (VANETs), with a particular focus on audio-visual transmission using IEEE 802.11p. The currently deployed message dictionaries for VANETs only allow for textual exchange. By examining current research in the field of multimedia transmission within transportation systems, we explore the technical issues, challenges, and opportunities involved in transmitting audio-visual-enhanced emergency notifications to transportation users. Additionally, we shed light on the challenges related to video transmission in VANETs and propose focused research areas where Artificial Intelligence can be applied to address the bandwidth constraints imposed by devices. This work makes three significant contributions. Firstly, it presents a detailed comparison between video and image transmission, highlighting their respective strengths and limitations. Secondly, it identifies and discusses the challenges associated with multimedia transmission, emphasizing the need for quality of service and resource availability. Lastly, it examines the opportunities for using intelligence at the edge for transmitting short clips of audio-visual emergency notifications within VANETs to support new services that can coexist with the currently deployed message dictionaries.

1. Introduction

Vehicular communication is pivotal in intelligent transportation systems, aiming to provide users with advanced safety, efficiency, and infotainment services [1,2]. Within this domain, prior to the deployment of the emerging New Radio (NR), two prominent technologies dominated the vehicular network landscape, namely Dedicated Short-Range Communications (DSRCs) and Long-Term Evolution Vehicle-to-Everything (LTE-V2X) [3]. These technologies have gained considerable recognition due to their potential to augment the safety and efficacy of connected vehicles.

With the rise in accidents, crime, and transportation incidents, the impact of connected vehicles on our lives has become increasingly significant [4,5]. Improving safety in intelligent transportation systems requires effective situational awareness adaptation within the vehicular network [6]. Although this paper is geared towards DSRCs that have been effectively deployed in most countries, as we delve into the world of vehicular communication, understanding the evolution from DSRC and LTE-V2X to the emerging NR technology opens new possibilities and advancements for the future of connected vehicles. According to the National Highway Traffic Safety Administration (NHTSA) in the USA, on-road crashes in 2021 increased by 21%, speeding-related crashes rose by 5%, and pedestrian fatalities increased by 13% [7]. Situational awareness adaptation in the vehicular network is critical to improving safety in intelligent transportation systems [8].

To ensure communication interface alignment among all manufacturers and enable seamless communication within the V2X arena, standards have been established to ensure uniformity within automotive and infrastructure organizations. The Institute of Electrical and Electronics Engineers (IEEE) provides DSRC standards [9]. Specifically, the IEEE 802.11p standardizes the physical and medium access control (MAC) layers for DSRC [10,11]. Similarly, the 3rd-Generation Partnership Project (3GPP) develops the standards for LTE-V2X (Long-Term Evolution Vehicle-to-Everything) [12]. The 3GPP is a collaboration between various telecommunications-standardization organizations that work together to develop specifications for mobile communication systems that include LTE-V2X technology.

In recent years, the 3rd-Generation Partnership Project (3GPP) has introduced significant updates to its system releases, including the New Radio (NR) release-16 and release-17 [13]. These updates have been designed to enhance vehicular communication capabilities, providing higher data rates, improved reliability, and lower latency compared to the previous release-14 [14]. The introduction of these advancements has highlighted the need for the deployment of technology for transportation and public safety [15,16,17,18] and has captured the interest of public organizations. These organizations acknowledge the potential benefits of utilizing these advancements to improve communication with first responders and law-enforcement agencies, particularly in critical situations. This exploration could also be extended to the realms of multimedia transmission and Artificial Intelligence (AI) integration into VANETs, particularly in the areas of image-compression techniques. These include Singular Value Decomposition (SVD), Discrete Wavelet Transform (DWT), and Information Aggregation (IA). These pivotal methods play a crucial role in enhancing the efficiency and efficacy of multimedia transmission within vehicular communication systems.

Several countries have actively embraced the deployment of LTE-V2X technology to advance their transportation systems. China, the United States [19], South Korea, Germany, and the United Kingdom are among the countries that have shown considerable interest in and have made progress in implementing LTE-V2X [20]. Through large-scale trials, pilot projects, and field tests, these countries aim to evaluate the performance and applicability of LTE-V2X in real-world scenarios. Other countries, including Japan, Australia, France, and Canada, have also shown interest in exploring the LTE-V2X deployment.

The performance of DSRC and LTE-V2X (Long-Term Evolution Vehicle-to-Everything) in high-vehicle-density scenarios has been the subject of investigation [20]. The authors conducted a comparative analysis by evaluating various performance metrics such as throughput, packet-delivery ratio, and latency in the context of network congestion. They examined the congestion control mechanisms specified by the SAE for both DSRC and LTE-V2X PC5 Mode 4 to understand their impact on network performance. The outcome shows that a semi-persistent scheduling mechanism imposes packet loss in LTE-Sidelink comparisons to DSRC. Also, it is imperative to point out that LTE-V2X operates in two modes: Uu-based LTE-V2X and PC5-based LTE-V2X. Uu-based LTE-V2X utilizes the downlink and uplink of LTE networks for communication between user equipment (UEs). On the other hand, PC5-based LTE-V2X uses sidelinks, which are direct links between UE devices, for communication among UEs, with or without the support of eNBs (eNodeBs). PC5-based LTE-V2X is further divided into two modes: mode 3 and mode 4.

In PC5 mode 3, the eNBs allocate sidelink resources to each UE, and the UEs broadcast packets using the allocated resources. In PC5 mode 4, each UE autonomously selects sidelink resources and broadcasts packets using the selected resources. Therefore, the operation scenario of PC5 mode 4 is similar to DSRC in the sense that both protocols do not rely on base stations for communication, and the channel access mechanisms are fully distributed.

The DSRC has undergone notable advancements in recent years, with the establishment of updated system releases [21]. Notably, the Institute of Electrical and Electronics Engineers (IEEE) has played a crucial role in standardizing DSRC technology. These advancements include improvements in the transmission capabilities, with the aim of supporting higher data rates, enhanced reliability, and reduced latency compared to previous releases [22]. These advancements have garnered attention from public safety organizations seeking to leverage the benefits of DSRC for improved communication with first responders and law enforcement agencies. In Europe, DSRC is known as ETSI ITS-G5 and has been deployed in many European countries [23]. Australia has also embraced DSRC, referred to as Cooperative Intelligent Transport Systems (C-ITSs) and deployed it significantly in the country, while Singapore has been deploying DSRC technology in major cities since 2010 [24].

The international deployments of DSRC serve as significant milestones in realizing its potential for revolutionizing the transportation system. These deployments reflect the global efforts made toward its integration and adoption. Despite the remarkable progress in the field of vehicular communication using DSRC, [22] acknowledges that there are still challenges to be addressed. However, [25] emphasizes the need for further work in optimizing bandwidth utilization, particularly in the context of multimedia transmission.

The existing literature on multimedia for vehicular ad hoc networks (VANETs) reveals limited applicability due to regulatory bandwidth constraints and device limitations. As a result, message dictionaries established by standards bodies lack multimedia support. While many studies have veered away from pursuing multimedia in VANETs, it is crucial to consider that a complete pull-back could exclude new multimedia services that can benefit transportation use cases and coexist with the deployed VANET infrastructure.

Instead of dismissing multimedia altogether, a more intelligent approach can be adopted to selectively transmit concise audio-visual content at the edge of the network. This opens up possibilities for innovative applications without compromising the core functionalities and safety-critical communication of the existing VANET ecosystem. By addressing the challenges highlighted by [25] in optimizing bandwidth utilization for multimedia transmission, a more effective and diverse vehicular communication system can be achieved.

Further research and development efforts are necessary to overcome these challenges and improve the efficiency of multimedia content dissemination within vehicular networks. While advancements have been made, ongoing research and development efforts, along with international collaborations, are crucial to further enhance the capabilities of vehicular communication systems, address the remaining challenges, and unlock the full potential of multimedia transmission with the DSRC VANETs.

This paper is focused on a comprehensive review of DSRC in the context of multimedia transmission. The subsequent sections of the paper are organized as follows: Section 2 provides background on VANET/DSRC, DSRC standards, DSRC channelization, and multimedia in VANET/DSRC. In Section 3, a literature review on multimedia in VANETs is presented. Section 4 introduces the challenges and metrics of the study. Section 5 identifies opportunities and open research areas, discusses technical challenges, and presents potential research approaches. Finally, Section 5 presents the conclusions of the paper.

2. Background of DSRC

Mobile ad hoc networks (MANETs) have been widely studied to enable communication among wireless devices without the need for fixed infrastructure. One important type of MANET is the vehicular ad hoc network (VANET), which consists of vehicles equipped with wireless communication devices that allow them to communicate with each other and with infrastructure; see Figure 1. In VANETs, DSRC is specifically designed to utilize the IEEE 802.11p standard for communication. Within DSRC, the 802.11p standard plays a vital role, as it is tailored to address the unique challenges posed by vehicular communications.

Derived from the widely used 802.11 Wi-Fi standard, 802.11p has undergone significant modifications to cater specifically to the demanding requirements of vehicular communication scenarios. Significantly, one notable advantage setting 802.11p apart is its enhanced bandwidth capacity, surpassing traditional 802.11 Wi-Fi networks. This high bandwidth capability is of paramount importance in vehicular communications, as it enables the seamless transmission of substantial volumes of data, encompassing various forms of multimedia content such as video and audio. Compared to the standard 802.11 Wi-Fi, which primarily caters to local area network (LAN) environments, 802.11p has been purposefully designed to deliver higher data rates, wider coverage, and improved reliability in vehicular settings. Consequently, this heightened bandwidth capability of 802.11p empowers the efficient and reliable delivery of multimedia information across vehicles and infrastructure, contributing to vehicular communication systems’ overall effectiveness and performance.

Dedicated Short-Range Communication (DSRC) technology, designed to facilitate information exchange within a range of up to 1000 m, is a promising tool for enhancing road safety and efficiency. Its application in Vehicle-to-Everything (V2X) communication allows vehicles to interact wirelessly with other vehicles, infrastructure, pedestrians, and the power grid. However, transmitting multimedia data in connected environments presents a significant challenge. Resource allocation is critical for effective communication and data transmission in vehicular ad hoc networks (VANETs) utilizing DSRC. This includes managing bandwidth, transmission power, and spectrum to optimize asset utilization while minimizing delays and congestion.

In vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) contexts, VANETs consist of On-Board Units (OBUs) in vehicles and roadside units (RSUs) along the infrastructure for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication as shown in Figure 1. The system’s communication range is approximately 1000 m, prioritizing seamless connectivity in close-proximity scenarios. Despite their potential, both DSRC and LTE-V2X technologies have limitations. These include a restricted communication range that may be problematic for long-range communication needs, securing an interference-free spectrum for V2X communication amid increasing wireless bandwidth demand, and potential interference and congestion in densely populated or high-vehicular-density areas that could impact V2X communication reliability.

Security and privacy of transmitted data are paramount in V2X communication due to the risk of cyber-attacks and unauthorized access. Achieving uniform standards and compatibility between different vehicle brands and infrastructure providers can also pose a challenge. The cost of deploying RSUs can be substantial, with potential logistical and financial obstacles to widespread implementation. Integrating V2X technologies with existing transportation systems may require significant effort and resources. Considering these limitations alongside the potential benefits provides a balanced perspective on the capabilities and challenges of DSRC and LTE-V2X technologies within VANETs.

2.1. Dsrc Spectrum and Channelization

The spectrum allocation for DSRC is not uniform across different countries. Each country has its own specific regulations and frequency bands for DSRC operation. This ensures efficient and reliable communication for vehicular applications while addressing regional requirements and considerations. DSRC spectrum allocations vary across different regions, and It is important to note that these allocations are subject to regulatory updates and changes.

In Europe, the primary frequency band for DSRC is typically within 5.855–5.925 GHz. However, there can be variations among European Union (EU) member states. Some countries allocate the entire band for Intelligent Transport Systems (ITS) use, while others assign a portion of the band specifically for DSRC. In Japan, DSRC operates in the 5.8 GHz frequency band, specifically from 5.780 to 5.825 GHz. This band is further divided into channels dedicated to various applications, including V2V and V2I communication. In China, DSRC is allocated to the 5.725–5.850 GHz frequency band. Within this band, different channels are designated for specific applications, such as V2V and V2I communication. Various other countries have also designated specific frequency bands for DSRC. For example, Canada, South Korea, and Australia have their own allocations. The exact frequency bands and channelization may vary among these countries.

2.2. Standardization and Collaboration

Standardization organizations play a crucial role in the development and establishment of standards for DSRC systems. Among these organizations, the Institute of Electrical and Electronics Engineers (IEEE) stands out with its significant contributions. The IEEE is actively involved in shaping the field of wireless communication in vehicular environments through its IEEE 802.11p standard. This standard specifically addresses the wireless communication protocols and requirements for DSRC, ensuring reliable and efficient communication between vehicles and infrastructure. Another prominent organization in the realm of automotive and mobility-related technologies is SAE International (Society of Automotive Engineers). SAE International has published standards related to DSRC, including SAE J2735, which defines message sets used for vehicle-to-vehicle and vehicle-to-infrastructure communication. Their contributions play a crucial role in ensuring interoperability and standardized communication within the DSRC ecosystem.

In Europe, the European Telecommunications Standards Institute (ETSI) takes the lead in developing standards for information and communication technologies. ETSI has published standards specific to DSRC, such as EN 302 571, which outlines the requirements for DSRC implementation within the European Union. Their efforts aim to harmonize and regulate DSRC deployments in Europe, promoting consistent and interoperable communication systems. The International Organization for Standardization (ISO) is a global standardization body that also contributes to the development of intelligent transportation systems. ISO has developed standards like ISO 15628, which provides guidelines for utilizing DSRC in road vehicle communications. Their work ensures a cohesive and standardized approach to DSRC implementation across various regions.

In the United States, the Intelligent Transportation Society of America (ITS America) plays a vital role in promoting the deployment and advancement of intelligent transportation systems. They actively support the implementation of DSRC and advocate for its benefits in enhancing road safety and mobility. Additionally, the CAR-2-CAR Communication Consortium operates as an esteemed international organization with a primary focus on the development and standardization of cooperative intelligent transportation systems (C-ITSs) that are based on the DSRC technology. Its establishment stemmed from the purpose of advancing and promoting the implementation of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication systems, which aim to enhance road safety, optimize traffic efficiency, and foster environmental sustainability.

2.3. DSRC Communication Stack

The DSRC stack is a layered architecture that forms the foundation for communication in DSRC networks. DSRC is a wireless communication technology specifically designed for vehicular ad hoc networks, enabling vehicles and infrastructure to exchange information for various applications such as road safety, traffic management, and other services. The DSRC stack, as seen in Figure 2, consists of multiple layers, each serving a specific purpose in the communication process.

The foundation of the DSRC structure lies in the Physical (PHY) and Media Access Control (MAC) layers, where the implementation of the IEEE 802.11p standard plays a crucial role. This layer serves as the gatekeeper, controlling access to the shared communication medium within DSRC networks. To ensure efficient management of access and to alleviate potential collisions among vehicles, it utilizes the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) mechanisms. This strategic deployment of protocols and mechanisms underscores the sophistication and robustness of DSRC’s design.

By capitalizing on the virtues of the IEEE 802.11p standard, the DSRC system optimizes communication efficiency, particularly in the demanding vehicular environments in which it operates. To this end, it judiciously allocates specific channels for control- and safety-related communications, while reserving separate channels for general applications. This strategic channel allocation is complemented by the inclusion of synchronization intervals and guard times, further bolstering communication effectiveness. Consequently, the DSRC architecture operates seamlessly within its designated frequency range.

3. Multimedia

Multimedia in Vehicle-to-Everything (V2X) communication is a rapidly evolving field with numerous promising applications. These include in-vehicle infotainment, offering passengers a range of entertainment and information services such as streaming video, gaming, and access to news and weather updates. Additionally, multimedia can enhance advanced driver assistance systems (ADASs), providing drivers with features like lane departure warnings, blind spot monitoring, and adaptive cruise control. Moreover, multimedia can be leveraged for telematics, enabling the collection and transmission of data on vehicle performance, and driving behavior to enhance vehicle safety, fuel efficiency, and maintenance.

Multimedia in DSRCs can be categorized into broadcasting and multicasting. In broadcasting, the approach involves a single vehicle or infrastructure unit transmitting multimedia content to all other vehicles or infrastructure units within range. Broadcasting is particularly suitable for applications such as real-time traffic information dissemination or emergency alerts. On the other hand, in multicasting, a single vehicle or infrastructure unit transmits multimedia content to a specific group of vehicles or infrastructure units. Multicasting is well-suited for applications such as sending personalized messages or providing updates to a group of vehicles.

The future of multimedia in V2X appears bright, with continued development and investment driving its potential to revolutionize the transportation system. DSRC technology shows promise in improving road safety, traffic management, and various aspects of the transportation system. The integration of multimedia in DSRCs presents further opportunities for enhancing these benefits through a range of innovative applications and services. With ongoing development and investment, DSRCs and multimedia in V2X have the potential to transform the transportation system. Multimedia encompasses the combination of video and audio, as well as image and audio components. This study specifically examines the transmission of video content with or without audio and images with or without audio. Regardless of audio inclusion, given the DSRC bandwidth limitation of 2300 bytes, the primary focus of this research is to evaluate the data sizes that can be transmitted across VANETs, including combinations of video and audio or text and audio.

3.1. Applications and Use-Cases

The integration of multimedia capabilities into vehicular ad hoc networks (VANETs) and DSRCs has presented a multitude of opportunities for enhancing different facets of vehicular communication systems. This convergence of multimedia and vehicular technologies has paved the way for the development of various applications and services that leverage multimedia content to improve safety, public safety, entertainment, telemedicine, and advertising within the driving environment as shown in Figure 3. These advancements signify a significant step forward in the realm of vehicular communication, offering promising opportunities for further exploration and innovation.

Safety of life is a critical aspect of multimedia integration in VANETs/DSRC, aiming to mitigate the risk of accidents and enhance overall road safety. One prominent application within this category is collision avoidance, where vehicles share sensor data and cooperate to prevent collisions. This involves real-time multimedia sharing between vehicles to enable effective sensor fusion and accurate situational awareness. Additionally, intersection assistance systems utilize multimedia to facilitate safe and efficient maneuvering at intersections, improving traffic flow and minimizing the risk of accidents.

Public safety applications leverage multimedia capabilities to enhance the effectiveness of law enforcement and emergency response operations. Police departments, for instance, can benefit from real-time dashcam video streaming from patrol cars, providing valuable visual information for situational analysis and incident response. Furthermore, multimedia content can be streamed from a central server to vehicles over DSRC, enabling the dissemination of critical information, such as traffic updates, emergency alerts, and public service announcements.

Entertainment is another domain that has been enriched by the integration of multimedia in VANETs/DSRC. Passengers and drivers can access a variety of entertainment services through streaming platforms, providing them with access to music, podcasts, audiobooks, and other multimedia content. This enhances the overall in-vehicle experience, making travel more enjoyable and engaging.

Advertising opportunities have also emerged within the context of VANETs/DSRC, enabling targeted multimedia advertising campaigns. Welcome Centers, for instance, can utilize audio streaming capabilities to greet approaching vehicles and provide relevant information about local attractions and services. Video streaming can also be employed to deliver engaging advertisements to passengers and drivers, leveraging the connectivity and multimedia capabilities of VANETs/DSRC to enhance marketing efforts.

The integration of multimedia capabilities into vehicular ad hoc networks (VANETs) and DSRC has brought forth a multitude of opportunities for enhancing various aspects of vehicular communication systems. This convergence has led to the development of applications and services that leverage multimedia content to improve safety, public safety, entertainment, and advertising within the driving environment. However, alongside these advancements, researchers face the challenge of addressing bandwidth issues that affect the seamless transmission of multimedia content.

In the realm of safety, applications such as collision avoidance and intersection assistance rely on real-time multimedia sharing between vehicles to enable effective sensor fusion and accurate situational awareness. Public safety applications benefit from real-time dashcam video streaming and the dissemination of multimedia content over DSRCs, providing valuable visual information for law enforcement operations and facilitating the delivery of critical information to vehicles. The integration of multimedia has also enriched the entertainment domain within VANETs/DSRC, allowing passengers and drivers to access various streaming services and enhancing the in-vehicle experience.

Researchers need to explore innovative approaches to improve bandwidth utilization, reduce latency, and ensure reliable multimedia transmission within VANETs/DSRC. By tackling these challenges, researchers can contribute to the continued advancement of multimedia applications in vehicular communication systems, ultimately enhancing safety, entertainment, and advertising capabilities for a seamless driving experience.

3.2. Challenges and Metrics of Study in Multimedia

In the realm of multimedia transmission in VANET, one of the challenges encountered relates to the sheer volume of data involved, which poses a significant demand for extensive bandwidth. This becomes particularly challenging in DSRC communication networks, where bandwidth resources are limited to 2300 bytes [2,26]. When considering the compression and transmission of various forms of multimedia content such as images, audio, videos, or audio-visual materials, a fundamental concept of compression, encoding, and bitstream comes into play [27].

A bitstream represents a continuous flow of meticulously organized binary information, serving as a representation of encoded data. Within this bitstream lies the encapsulated version of the compressed or encoded image, audio, or video content [28]. To ensure the successful transmission of this bitstream from its source to its intended destination, it is crucial to give careful consideration to various technical challenges. This involves establishing appropriate metrics, as demonstrated in Table 1, for effectively evaluating the transmission’s performance [1,29].

In VANET multimedia communication, the successful transmission of the bitstream, which represents the encoded multimedia content, is crucial for ensuring high-quality multimedia experiences. This transmission is influenced by the interplay between Quality of Service (QoS) and Quality of Experience (QoE). QoS parameters, such as bandwidth availability, latency, packet loss, and reliability, impact the performance of the communication network and the successful delivery of the bitstream. QoE, on the other hand, focuses on the user’s satisfaction with the received multimedia content, considering factors like visual and auditory quality, synchronization, and overall user experience. To optimize QoS and QoE in VANET, more studies should be geared towards techniques such as efficient compression algorithms, traffic prioritization, adaptive streaming, error resilience mechanisms, and QoS-aware routing protocols.

An extensive survey, as presented by [1], investigates the correlation between Quality of Experience (QoE) and Quality of Service (QoS) models, specifically within the context of video streaming over vehicular ad hoc networks (VANETs). This work offers a comprehensive examination of these interconnected factors. The authors scrutinize various existing models and techniques for evaluating QoE and QoS metrics in the context of video streaming. The survey addresses the challenges and opportunities tied to delivering a satisfactory streaming experience in VANETs, taking into account factors such as network connectivity, bandwidth limitations, and dynamic mobility. The findings enrich our understanding of the relationship between QoE and QoS in VANETs and provide valuable insights for the design of efficient video streaming systems.

In line with the views presented by [1,30] presents real-world measurements and analysis of video transmission over the IEEE 802.11p standard, which is specifically designed for vehicular communication. The authors conducted experiments to evaluate the performance of video streaming in terms of packet loss, delay, and video quality. The authors conducted a series of experiments aimed at evaluating the performance of video streaming, focusing on key aspects such as packet loss, delay, and video quality. The study explores the influence of various parameters, including vehicle speed and transmission power, on the overall video transmission performance. Through their investigation, the researchers shed light on the practical challenges and limitations associated with video streaming over the IEEE 802.11p standard. Additionally, Ref. [30] introduces a novel approach to video compression by leveraging the Three-Dimensional Discrete Wavelet Transform (3-D DWT) and a unique bit-plane entropy coding method for wavelet sub-band matrices. This innovative approach as presented by [30] holds promise for enhancing the quality of video transmission within vehicular networks. However, the researchers did not indicate the impact of video transmission on other safety messages, and the outcomes are only suitable for short-range video delivery.

A comparative analysis, as presented in [31], evaluates various video streaming techniques used in vehicular ad hoc networks (VANETs). The study also explores potential future strategies to enhance video streaming performance within these networks. The author systematically evaluates the performance of different video streaming approaches, including adaptive streaming and multicast techniques, by considering important metrics such as delay, throughput, and video quality. This comparative analysis provides valuable insights into the strengths and limitations of various video transmission approaches, shedding light on the challenges that must be addressed to achieve efficient video streaming in VANETs. Additionally, the article highlights a significant observation, also presented by [32], that the high mobility of vehicles poses difficulties in achieving effective video communication for entertainment purposes, primarily due to the Doppler effect. This finding underscores the need for innovative solutions to mitigate the impact of mobility on video streaming in VANETs.

In another effort to preserve bandwidth while streaming video in VANET, Ref. [33] presents a cross-layer path-selection scheme for video streaming over VANETs. The authors address the challenges of dynamic network topology and varying link conditions in VANETs, which can affect video streaming quality. They propose a novel path-selection scheme that considers both network-layer metrics, such as link quality and stability, and application-layer metrics, such as video quality and delay. The scheme aims to optimize the selection of paths for video download from the roadside unit, considering the current network and application conditions. The effectiveness of the proposed scheme is evaluated through simulations, demonstrating its potential in improving video streaming performance over VANETs.

Similar to [33,34] proposes a cross-layer path selection scheme for video streaming over VANETs. The authors address the challenges posed by dynamic network topology and varying link conditions in VANETs, which can adversely affect video streaming quality in terms of Peak Signal-to-Noise Ratio (PSNR). They propose a novel path-selection scheme that considers both network-layer metrics, such as link quality and stability, and application-layer metrics, such as video quality and delay. The scheme in [34] aims to optimize the selection of paths for video download from the roadside unit, taking into account the current network and application conditions. The simulation results of the path selection scheme demonstrate the effectiveness of the proposed approach in improving video streaming performance over VANETs.

Both articles [33,34] address the issue of video streaming over VANETs and propose solutions to improve streaming performance. The first article focuses on a cross-layer path selection scheme that considers both network-layer and application-layer metrics for path optimization. Its goal is to enhance video streaming performance by selecting the most suitable paths for video download based on current network and application conditions. In contrast, the second article emphasizes Quality of Experience (QoE)-aware routing, where QoE-related metrics are considered alongside traditional network metrics in the routing decision-making process. Its goal is to enhance the overall video streaming experience by dynamically selecting the best routes that meet the QoE requirements of the video stream. Both articles utilize simulations to evaluate the effectiveness of their proposed approaches. However, neither of these articles discusses the use of audio images as a means of reducing bandwidth in VANET multimedia transmission.

To enhance the Quality of Experience within a network by improving the peak signal-to-noise ratio while transmitting video, Ref. [35] proposes an adaptive video streaming scheme for highway VANETs that utilizes inter-vehicle relays to boost video streaming performance. The primary objective of this scheme is to provide an optimal streaming experience by dynamically adjusting the video quality in real time to align with the available network bandwidth. This is accomplished through dynamic adaptation of the video quality and the utilization of relay vehicles to mitigate channel impairments and enhance the reliability of video delivery. By adapting to changing network conditions, it efficiently utilizes network resources, enabling the vehicle to stream video. Simulated results illustrate the effectiveness of the adaptive video streaming scheme in achieving improved video quality and reduced packet loss in highway VANETs. However, a drawback of this study is that it only tested the scheme with three vehicles. Similarly, Refs. [35,36] explore the challenges of video streaming in VANETs and propose a multilayer video encoding approach to manage Quality of Service (QoS) in this environment. The authors also pointed out the dynamic nature of VANETs, which can result in varying network conditions and limited resources. The multilayer video-encoding scheme aims to adaptively adjust video quality based on network conditions and available bandwidth. The results demonstrate the effectiveness of this approach in achieving improved video quality and enhanced Quality of Service (QoS) in VANETs. Particle swarm optimization (PSO) has recently been used to optimize video transmission in VANETs. This algorithm is a population-based optimization algorithm inspired by the social behavior of bird flocking and fish schooling [37]. In PSO, a group of particles represents potential solutions to an optimization problem, and these particles explore the search space by adjusting their positions and velocities based on their own experiences and information from other particles [37]. Also, the investigation of Particle Swarm Optimization (PSO) utilization for video streaming services over vehicular ad hoc networks (VANETs) is presented in [38]. Work performed by [38] focuses on improving video transmission efficiency and quality in dynamic vehicular environments. The authors introduce a PSO-based algorithm, which effectively optimizes the selection of relay vehicles for video data transmission in VANETs. The PSO algorithm as presented by [38] operates through an iterative process that involves updating particle positions and velocities, following specific rules aimed at converging toward the optimal solution [39,40].

Despite the importance of multimedia transmission in VANETs, there are practical considerations and implementation challenges to address [41]. There is a need for VANET system design and architecture to accommodate the requirements of multimedia transmission [42], ensuring efficient data exchange, synchronization, and integration with existing communication technologies.

Among the challenges faced in DSRC networks is the limited bandwidth, which directly impacts packet loss and the need for error resilience [43]. DSRC networks are prone to packet loss and errors caused by channel conditions and interference. It is imperative to develop robust error-resilience techniques and packet-loss-recovery mechanisms specifically tailored for multimedia data to ensure the integrity of the transmitted content [43]. As ascertained by [43], multimedia applications, such as video streaming and live navigation, require a lot of bandwidth, which can constrain the amount of multimedia data that can be transmitted. Another challenge is the stringent Quality of Service (QoS) requirements of DSRC applications [44]. In support of addressing Quality of Service (QoS) issues in VANETs, it has been underscored that more concentrated research is warranted [45]. The architecture includes mechanisms for cluster formation, cluster head selection, and QoS provisioning based on factors such as vehicle speed and network congestion, which demonstrates its effectiveness in improving QoS by reducing packet loss and enhancing network stability.

Multimedia applications in DSRC networks face significant challenges in meeting low-latency and high-reliability requirements due to limited bandwidth and the dynamic nature of vehicular environments. Moreover, these applications are susceptible to errors introduced by noise, interference, and fading. Their study, Ref. [46], focuses on evaluating the performance of safety applications in DSRC vehicular ad hoc networks, with a specific emphasis on fading. Fading refers to variations in the received signal strength caused by obstacles, interference, or distance between vehicles. Understanding the impact of fading on safety applications is crucial for enhancing road safety and accident prevention.

The findings from [46] underscore the challenges posed by fading in vehicular ad hoc networks and highlight the necessity for robust communication mechanisms to mitigate its effects. The authors propose adaptive transmission power control and diversity techniques as potential solutions to address fading and enhance the reliability of safety applications. Therefore, in order to ensure reliable and efficient communication for enhancing road safety, DSRC networks must be designed to be error-resilient and consider the correction of fading effects.

Security and privacy concerns need to be addressed to protect the integrity and confidentiality of transmitted multimedia data [47]. The inclusion of images, videos, and audio in DSRC could facilitate better traffic management, driver decision-making, and vehicle detection. Emergency notifications, traffic monitoring, and roadside incident management could help improve safety if modalities are in place for the efficient transmission of multimedia data [48,49].

In searching for possible approaches to solving technical resource challenges in VANETs, Ref. [49] attempts to address the unique challenges faced by VANETs and proposes a protocol designed to tackle these issues. The primary goal of the protocol is to ensure the dependable and efficient transmission of messages between vehicles within VANETs. The protocol operates on the principle of message broadcasting, where messages are disseminated to all nodes in the network. Upon receiving a message, and as a means of a security check, each node verifies if it is the intended recipient and discards it otherwise.

Additionally, multimedia, such as video, image, or audio-visual transmission, could contribute to collision avoidance, cooperative awareness, road safety, and passenger services. Overcoming implementation challenges and addressing practical considerations are necessary to fully realize the benefits of multimedia transmission in VANETs.

There is a need to study and seek ways to address these challenges in VANET multimedia transmission. Gaining deeper insights into these issues will make it possible to optimize the system for effective, efficient, and reliable communication of multimedia content within VANET. This entails examining bandwidth requirements, managing latency, and ensuring the reliable delivery of multimedia data. All of these factors impact the overall performance and Quality of Service provided. By exploring and understanding these challenges related to the key metrics as presented in Table 1, researchers can develop effective strategies for optimizing compression techniques, adapting to varying network conditions, and establishing robust protocols to ensure the efficient and timely transmission of multimedia content.

Table 1. Metrics of Study in VANET Multimedia Transmission.

Metric Category	Description
Bandwidth Efficiency	Evaluating the efficiency of multimedia compression and transmission techniques with limited bandwidth [50,51].
QoS and QoE Assessment	Measuring Quality of Service (QoS) and Quality of Experience (QoE) metrics, including latency and video quality [51].
Error Resilience Metrics	Assessing the effectiveness of error resilience mechanisms in maintaining multimedia data integrity.
Security and Privacy	Evaluating security and privacy measures to ensure the confidentiality and integrity of multimedia content [52].
Fading Impact Analysis	Studying the impact of signal fading on multimedia transmission and proposing solutions for mitigation [53].
Technical Resource Optimization	Developing protocols and strategies to optimize multimedia transmission in the face of resource constraints.

Table 1. Metrics of Study in VANET Multimedia Transmission.

Metric Category	Description
Bandwidth Efficiency	Evaluating the efficiency of multimedia compression and transmission techniques with limited bandwidth [50,51].
QoS and QoE Assessment	Measuring Quality of Service (QoS) and Quality of Experience (QoE) metrics, including latency and video quality [51].
Error Resilience Metrics	Assessing the effectiveness of error resilience mechanisms in maintaining multimedia data integrity.
Security and Privacy	Evaluating security and privacy measures to ensure the confidentiality and integrity of multimedia content [52].
Fading Impact Analysis	Studying the impact of signal fading on multimedia transmission and proposing solutions for mitigation [53].
Technical Resource Optimization	Developing protocols and strategies to optimize multimedia transmission in the face of resource constraints.

4. Opportunities and Open Research Areas in VANET Multimedia

In recent years, there has been a growing recognition of the importance of multimedia transmission in VANETs. The ability to transmit multimedia data, which include images, videos, or audio-visual content, could bring several significant benefits to enhance communication, safety, and efficiency in vehicular networks. Figure 4 provides an overview of the opportunities for multimedia in VANETs. One of the key aspects highlighting the importance of multimedia transmission is to provide drivers with real-time information about traffic conditions, road closures, and other hazards. Current Traveler Information Messages (TIMs) provide situation awareness to drivers; however, they are only text-based. Researchers have been searching for ways to optimize notifications to drivers without congesting the DSRC VANET. This is particularly crucial in light of bandwidth restrictions inherent in VANETs, which can become more pronounced as vehicles move farther away from roadside units (RSUs). The communication speeds may experience fluctuations as vehicles traverse varying distances from RSUs, necessitating efficient protocols and technologies to ensure the reliable and timely dissemination of critical information. DSRC V2X is a wide topic, and the opportunities discussed in this section are only geared toward the transmission of data from the roadside unit to the vehicle, also known as Infrastructure to Vehicle (V2I), as shown in Figure 5.

In contemporary studies, video transmission within DSRC VANET poses the challenge of consuming excessive bandwidth and congestion, while pre-programmed images that are populated within the dashboard in the case of TIMs only show a repeated image with only a beep. The research area in real-time dissemination of short audio-visual information has been largely ignored. Transmitting and presenting real-time audio-visual information about actual incidents could help drivers be aware of the real situation and mitigate risk, thereby helping to reduce road accidents. For example, a short audio-visual clip could be used to warn drivers of upcoming curved road hazards or to provide a view of the road ahead with audio warnings. Emergency notifications and public safety are other critical areas where audio-visual transmission plays an essential role.

The use of audio-visual transmission in DSRC, specifically in the Infrastructure-to-Vehicle (I2V) context, presents various opportunities and advantages. Firstly, it offers a richness of information by combining visual and auditory modalities, providing a comprehensive representation of the environment. By integrating textual information with images, audio-visual transmission enables drivers to quickly understand critical details and make informed decisions, enhancing situational awareness and overall road safety. Moreover, audio-visual transmission contributes to the bandwidth economy in DSRC. Given the limited availability of bandwidth, conveying essential information in a compact yet meaningful manner becomes crucial. Instead of transmitting full-motion videos or high-resolution images, audio-visual transmission can effectively communicate important details using concise visual cues and accompanying audio prompts. This approach optimizes bandwidth utilization, reduces network burden, and ensures efficient communication within bandwidth-constrained vehicular environments.

Mitigating driver distraction is another significant benefit of audio-visual transmission. While images and videos can provide detailed information, they also have the potential to distract drivers and divert their attention from the road. In contrast, audio-visual transmission delivers pertinent information in a non-intrusive manner. By presenting tangible information through audio prompts and minimalistic visual cues, it minimizes driver distraction while still providing valuable context and awareness. Drivers have varying visual acuity and may differ in their familiarity with complex visual displays.

Audiovisual transmission could offer a more inclusive way to communicate with drivers. By using both auditory and visual elements, it ensures that all drivers, regardless of their abilities or language skills, can receive important information. The audio-visual transmission offers significant opportunities in DSRC, as it provides a richer information experience, economizes bandwidth, mitigates driver distraction, and enhances accessibility and universality. These advantages make audio-visual transmission a promising research area in vehicular communication systems, aiming to improve communication efficiency, driver safety, and overall driving experience.

4.1. Overcoming Technical Challenges

In the field of multimedia transmission, several key challenges have been identified by researchers. These primarily include the large amount of data and the need for effective resource management, both of which require in-depth study. One of the main needs is to allocate bandwidth resources effectively for multimedia dissemination. This may involve focusing more on the use of advanced compression techniques and adaptive streaming protocols.

In addition, there is a critical need to optimize the delivery of static audio image-based information. This involves a careful balance between conserving resources and ensuring clear content delivery. Another important requirement is for context-aware resource management. This involves developing smart algorithms that can adapt to changing network conditions, user preferences, and content needs. In unpredictable network conditions, it is crucial to ensure reliable multimedia delivery, a key aspect of Quality of Service (QoS) assurance. This highlights the importance of using adaptive mechanisms and error-resilient coding schemes.

Furthermore, real-time applications require minimizing latency. This involves a detailed examination of protocols and computational models that meet strict time constraints. Areas such as edge-computing integration and priority-based content delivery are included in this exploration. After careful examination, these challenges point towards a new era where innovative strategies and solutions will significantly contribute to achieving efficient multimedia communication within vehicular environments.

4.2. FM-Based Drivers’ Image Notification in VANET

In [54], the research investigates a driver alert system that utilizes visual notifications transmitted through the FM radio broadcasting network. The study investigates an approach to providing warning messages to drivers using images, aiming to enhance situational awareness and road safety. In this research, the authors propose a system where warning messages are conveyed to drivers through images rather than traditional text-based messages. The images are transmitted over the FM radio broadcasting infrastructure, which allows for broader coverage and reach to a wide range of vehicles equipped with FM receivers. The study explores the technical implementation of the system and evaluates its real-time effectiveness in delivering vital information to drivers. However, it is worth noting that the FM radio, while widely accessible, is not designed for disseminating VANET-related information. Its broad coverage area may inadvertently lead to the transmission of unsolicited messages.

Unlike the dedicated nature of DSRC vehicular ad hoc networks (VANETs), FM radio lacks the tailored communication capabilities required to transmit critical notifications precisely to specific sections of the town, such as those facilitated by roadside units (RSUs) in VANETs. Secondly, the limited range of FM radio antennas may lead to inconsistent and uneven coverage, potentially resulting in some vehicles not receiving vital warnings in time, as expected by [54]. In contrast, the infrastructure of DSRC VANETs, with its RSUs strategically placed in proximity to roadways, ensures comprehensive coverage and efficient message dissemination. This targeted approach optimizes the delivery of audio-visual notifications, enhancing situational awareness for drivers within the VANET environment.

4.3. Video Streaming Techniques in VANETs

The authors in [55] thoroughly examine challenges and present viable solutions for real-time video transmission in vehicular ad hoc networks (VANETs), particularly in the context of assisted driving applications. Their specific emphasis lies in vehicle-to-vehicle (V2V) communication, advocating for the utilization of the IEEE 802.11p standard, purpose-built for vehicular communication. Researchers explore the viability of real-time video transmission and conduct a comprehensive analysis of the system’s performance, taking into account factors like delay, throughput, and video quality. The proposed research aligns well with the study by [55], as it also addresses the challenges of multimedia transfer in VANETs, with a specific emphasis on static audio-visual datasets, with an advantage in terms of bandwidth in comparison to video streaming and image transfer through beacon messages. While [55] concentrates on real-time video transmission using the IEEE 802.11p standard, it overlooks the underlying transmission bandwidth issues that arise due to large data transmission.

Despite the resource challenges faced by [56] in conducting vehicle-to-pedestrian (V2P) communications, researchers have shown that the transmission of essential messages and audio warnings can enhance situational awareness and promote safer interactions between vehicles and pedestrians in DSRC. Compared to video, which consumes more bandwidth due to the transmission of visual data [57], audio-visual messages can effectively convey information using fewer network resources. This is particularly important in DSRC, where bandwidth is a valuable and limited resource. Effectively addressing these challenges and optimizing multimedia transmission techniques can unlock the full potential of multimedia transmission in VANETs, leading to substantial improvements in the safety and efficiency of vehicular transportation.

The use of audio-visual communication in DSRC has the potential to align not only with the goal of providing efficient and effective communication; however, as emphasized by [58], it can facilitate easy identification and help the public engage in identifying criminals during emergency notifications while ensuring driver safety and minimizing distractions. By leveraging the combination of pictures, text, and audio, audio-visual communication, it offers a promising solution that strikes a balance between conveying valuable information and maintaining the driver’s focus on the road, all while utilizing less bandwidth.

4.4. Batch Transmission and Reconstruction of Audio-Visual Information

In DSRC VANETs, various types of messages are transmitted to facilitate communication among vehicles and infrastructure units. These messages include Basic Safety Messages (BSMs), Emergency Warning Messages, Traffic Information Messages (TIMs), Cooperative Awareness Messages (CAMs), Roadside-to-Vehicle Messages (RSMs), Infrastructure-to-Vehicle Messages (IVMs), Probe Data Messages, and vehicle-to-infrastructure Messages (VIMs). Each message serves a distinct purpose within the VANET context, encompassing safety-related information exchange, traffic management, and value-added services. These messages play a pivotal role in providing drivers with critical updates on traffic congestion, road closures, and other vital road conditions. However, to prevent interference with the bandwidth utilization of these essential messages, efficient image compression and batched transmission methods become imperative. Consequently, at the receiving end, the decompression of these batches becomes necessary. This approach is essential due to the adverse consequences that arise from transmitting large images in their entirety, such as network congestion and inefficient resource allocation.

In the landscape of vehicular ad hoc networks (VANETs), where efficient data exchange is paramount, the conventional methods of image compression face unique challenges. These challenges arise due to the stringent bandwidth constraints and the need for real-time communication. In this context, it is imperative to explore innovative compression techniques that not only build upon established methods like JPEG that use Discrete Cosine Transform (DCT) to transform spatial image data into the frequency domain but also focus on other compression techniques [59]. One such groundbreaking approach worth investigating is the integration of two powerful signal processing techniques: Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD) [60]. These techniques, renowned in the field of image processing, offer a novel perspective on image compression within VANETs.

DWT excels in breaking down an image into multi-resolution components, capturing both frequency and spatial information simultaneously [61]. This inherent ability makes it well-suited for the diverse characteristics of vehicular images, which often exhibit variations in both content and resolution. Similarly, the SVD is renowned for its capacity to reduce image dimensionality while preserving essential image features. It achieves this by identifying and retaining the most significant singular values and their corresponding vectors. This selective preservation of information aligns with the goal of efficient image transmission in bandwidth-constrained VANETs.

The batch transfer involves partitioning images into smaller packets for sequential transmission, thereby reducing congestion and efficiently utilizing network resources. Upon receipt of the image packets, the image-reassembly process is used to reconstruct the complete image using specific protocols or algorithms. By implementing these techniques, DSRC VANET devices may effectively compress images, transfer them in batches, and reassemble them at the receiving end.

The need for faster image decompression on the receiving end is driven by several critical factors. Firstly, timeliness is of utmost importance in VANETs, where real-time communication is required to ensure effective decision-making and response. When compressed images are transmitted, it becomes crucial to decompress them quickly at the receiving end to maintain the timeliness of the information. Any delays in decompression can hinder the intended purpose of the image, such as conveying important road conditions or emergency alerts. Secondly, the user experience plays a significant role in VANET applications, which often involve visual content intended for presentation to vehicle occupants or road users.

A smooth and seamless user experience relies on the timely delivery and decompression of images. Slow decompression processes can result in visual artifacts, blurriness, or distorted images, thereby degrading the quality and user perception of the conveyed information. Faster decompression enables timely processing, enhancing the overall effectiveness and performance of such applications. From a network efficiency standpoint, faster image decompression reduces the time that network resources are occupied. This facilitates quicker access to the decompressed images by other vehicles or infrastructure units, enabling more efficient utilization of the network resources. Faster decompression contributes to reduced network congestion and ensures smoother data flow within the VANET environment.

4.5. Multimedia Transmission in TIMs

TIMs play a crucial role in improving transportation safety and facilitating efficient communication between vehicles in a VANET. The SAE J2735 DSRC message set specifies the types of messages that can be transmitted over the DSRC network, including TIMs. TIMs are designed to provide drivers with real-time information about traffic conditions, road hazards, and other important events on the road in a textual format. They are generated by government agencies such as the Traffic Management Center (TMC). This information is then forwarded to the vehicle through the roadside unit, helping drivers make informed decisions about their route and driving behavior, leading to improved traffic flow and reduced congestion. TIMs are an essential component of the DSRC message list, providing drivers with important information to improve transportation safety.

TIMs are broadcast in DSRC using a specific type of message called the Service Advertisement Message (SAM). The SAM is a periodic broadcast message that is transmitted by the roadside unit (RSU) to all nearby vehicles within its transmission range. The SAM message contains information about the available services and data that can be accessed by the vehicles, including TIMs. The SAM message also provides information about the RSU’s location and other relevant details. Once the SAM message is received by a vehicle’s On-Board Unit (OBU), the vehicle can then request the desired services, such as TIMs, by sending a request message to the RSU (roadside unit). The RSU then responds by transmitting the requested data to the OBU. The format used for TIMs depends on the type of information being transmitted and the specific requirements of the application.

Overall, DSRC provides an efficient and reliable way to broadcast TIMs to vehicles in a vehicular ad hoc network, allowing for real-time communication between vehicles and infrastructure to enhance transportation safety and efficiency. The frequency of SAMs within a VANET can vary depending on the specific implementation and settings of the system. Typically, SAM messages are broadcast periodically at a fixed time interval, such as every 100 milliseconds or 1 second. The exact frequency of SAM messages within a VANET can be adjusted based on factors such as the expected traffic density and the required response time for services and messages. The goal is to ensure that SAM messages are transmitted frequently enough to provide timely and reliable service to the vehicles while avoiding unnecessary network congestion.

In the United States, the Federal Communications Commission (FCC) has designated a 5.9 GHz frequency band for the use of Dedicated Short-Range Communications (DSRCs) in vehicular ad hoc networks (VANETs). The DSRC standard SAE J2735 prescribes a default interval of 100 milliseconds for the periodic broadcast of Service Advertisement Messages (SAMs). However, an emerging trend promises to augment these networks’ capabilities even further. This trend involves the integration of Artificial Intelligence (AI) into the framework of Traveler Information Messages (TIMs) in VANETs. This integration represents a significant opportunity for progress, with the potential to transform incident detection and notification processes. By leveraging AI algorithms for image recognition and data analysis, the system can autonomously identify and categorize incidents based on visual data from cameras. This not only expedites TIM generation and improves its accuracy but also enables dynamic adjustment of TIM content and urgency in response to real-time traffic conditions and incident severity. This enhancement not only amplifies the efficiency of TIM dissemination but also situates VANETs at the cutting edge of transportation technology innovation, thereby attracting AI experts to contribute their expertise to this field.

4.6. Audio-Visual Transmission

TIM contains various types of information such as current traffic conditions, incidents, weather conditions, and other relevant data that can affect the driver’s journey. These messages are orchestrated to provide drivers with real-time traffic updates and enable them to make informed decisions about their route and driving behavior, thus improving safety and reducing travel time. However, effectively disseminating TIM while ensuring accuracy and minimizing network congestion presents significant challenges. Despite these challenges, TIM offers diverse applications, including real-time traffic updates, congestion warnings, road weather information, hazard alerts, work zone notifications, speed limit advisories, and image-enhanced notifications.

Numerous studies have been conducted to assess the performance of Traffic Information Messages (TIMs) in Vehicle-to-Everything (V2X) communication within vehicular ad hoc networks (VANETs). TIMs can achieve high message-delivery rates and low latency, although accuracy can be influenced by factors such as communication range and signal interference. The efficient dissemination of TIM messages, while ensuring accuracy and minimizing network congestion, poses challenges in VANETs. Therefore, it is imperative to devise dissemination protocols that can effectively deliver TIM messages in a timely and reliable manner. Ensuring accuracy involves addressing factors such as the reliability of data sources, message-aggregation techniques, and the presence of signal interference.

In a similar vein, one potential approach to enhancing TIM is to incorporate compressed images, which can be transmitted in batches, providing drivers with image-enhanced notifications. To achieve this, it is crucial to develop dissemination protocols that effectively address challenges related to network congestion and signal interference. These protocols should allow for the efficient compression of images, enabling their proper transmission within the VANET environment. Upon reception, the images can be reassembled in the On-Board Unit (OBU), offering enhanced visual information to the drivers. Furthermore, it is essential to conduct thorough evaluations to assess the impact of TIM on overall traffic efficiency, driver behavior, and road safety. This evaluation process will further enhance the effectiveness of TIM in VANET environments, ensuring its successful integration and utilization.

In summary, evaluating the performance of TIM in V2X communication has highlighted the importance of delivering messages accurately and efficiently. Considering the challenges posed by network congestion and signal interference, incorporating compressed images into TIM messages, transmitted in batches, presents a viable solution for enhancing TIM’s capabilities. Developing dissemination protocols that address these challenges will optimize the transmission of compressed images in VANETs. Moreover, conducting comprehensive evaluations will enable a thorough assessment of TIM’s impact on traffic efficiency, driver behavior, and road safety, thereby enhancing its overall effectiveness in VANET environments.

4.7. Artificial Intelligence at the Edge for Automotive Internet of Things

The integration of Artificial Intelligence (AI) into VANETs for multimedia applications presents a myriad of opportunities, especially in the domain of audio-visual enhanced emergency notification systems. These systems have the potential to assist in capturing, comparing, and making decisions regarding the location of wanted fugitives, as demonstrated in Figure 6. This convergence represents a significant advancement in the automotive Internet of Things ecosystem, leveraging AI at the edge. One prominent application involves utilizing AI algorithms to analyze data captured by roadside cameras, specifically focusing on pedestrian and road user detection [58]. This innovative approach, as detailed in the article by [58], places emphasis on the integration of AI for precise pedestrian detection through camera systems. The researchers underscore the pivotal role of C-V2X communication in this context and highlight how AI-powered camera systems can significantly bolster pedestrian detection capabilities.

However, this integration is not without its challenges. One of the primary hurdles lies in the need for robust and real-time AI processing capabilities at the edge. Processing complex multimedia data in real time demands high computational power, which may pose constraints in resource-limited edge devices. Additionally, ensuring the security and privacy of sensitive visual data is of paramount importance, necessitating robust encryption and authentication mechanisms.

Furthermore, the seamless integration of AI algorithms with existing VANET infrastructure requires careful calibration and synchronization. The models need to be trained on diverse and representative datasets to ensure accurate and reliable performance across varied real-world scenarios. Additionally, addressing potential as shown in Figure 6, biases in AI algorithms is crucial to ensure the fair and unbiased detection of pedestrians and road users from diverse demographic backgrounds. While the integration of AI into VANETs for multimedia applications offers immense potential, it also presents unique challenges. Overcoming computational limitations, ensuring data security and privacy, and fine-tuning AI models for diverse scenarios are key areas of focus. With diligent research and development efforts, the convergence of AI and VANETs stands poised to revolutionize transportation safety and efficiency.

In the context of VANET, there are opportunities to utilize the information obtained from roadside units (RSUs) along with images captured by roadside cameras, employing AI algorithms to search for wanted persons and wanted license plates. By comparing the information from both RSUs and roadside cameras, the system can contribute to the apprehension of criminals.

Another relevant study, presented in [62], introduces an analysis system that assesses the risk level of pedestrian–vehicle interactions using drone videos. The research focuses on leveraging drone technology to capture videos of these interactions and subsequently analyzes them to determine the associated risk level. The authors propose an automated system that extracts pertinent features from the videos and employs machine-learning techniques to classify and evaluate the risk level of each interaction. This research emphasizes the potential of using drone videos and data analysis to enhance pedestrian safety, providing valuable insights into the risk factors inherent in pedestrian–vehicle interactions. Further exploration is needed to investigate how AI can be utilized to compare drone-captured videos with roadside videos and audio-visual received from roadside units within the VANET framework. Such integration of AI capabilities would facilitate the classification and detection of individuals, thus aiding in their swift apprehension within the DSRC emergency notification system.

Using OBU cameras or roadside cameras to capture and analyze the license plates of road users is another potential integration into the DSRC VANET. In their research, the authors of [63] present a machine-learning algorithm that automates vehicle classification and license plate detection. The study focuses on addressing the challenges related to vehicle identification and license plate recognition within the context of wireless communications and mobile computing. The authors propose a machine-learning-based approach that utilizes advanced algorithms to accurately classify vehicles and automatically detect license plates and even humans [64,65,66]. There is a need to explore methods of consolidating images from drones, RSUs, and other sources and utilize AI to detect criminals and alert authorities. By harnessing the power of machine learning, these innovations have the potential to streamline the vehicle identification process and improve the efficiency of license plate detection [67], thereby aiding in the apprehension of criminals.

Finally, crowd-sourcing images from vehicles for new services, such as GPS-free positioning based on dash-board cameras, is another area where multimedia in VANETs could blossom. In, Ref. [68] we proposed new SAE J2735 messages to support image retrieval from vehicles for real-time training of machine learning models.

5. Conclusions

The paper identifies and discusses the challenges associated with multimedia transmission, including Quality of Service, resource availability, and signal interference. It emphasizes the need for efficient dissemination protocols to ensure the timely and reliable delivery of multimedia messages in dynamic vehicular environments. One notable opportunity presented in the review is the use of image transmission for image-enhanced TIMs and emergency notifications. The review paper goes beyond technical considerations by exploring the advantages and applications of image transmission in VANETs. It emphasizes the potential of image-enhanced TIMs to enhance public emergency notifications and enable comprehensive communication. The Dedicated Short-Range Communication (DSRC) architecture uses a variety of protocols to manage its functions, crucially employing the IEEE 802.11p standard at the Physical (PHY) and Media Access Control (MAC) layers. This standard manages access to the shared communication medium within DSRC networks and helps prevent collisions among vehicles. The DSRC system also efficiently allocates specific channels for control- and safety-related communications. The integration of multimedia capabilities into Vehicle-to-Everything (V2X) communication offers promising applications like in-vehicle infotainment, advanced driver assistance systems, telematics, and more. However, bandwidth limitations pose a challenge, particularly in the transmission of multimedia content.

This paper also discusses the importance of addressing the issues related to multimedia transmission in vehicular communication systems and suggests an efficient compression method. This is crucial for the development of multimedia applications in these systems. The recommendations given, if put into practice, could greatly improve the efficiency and reliability of communication systems in vehicular ad hoc networks (VANETs). This could result in better safety, efficiency, and emergency response capabilities in changing vehicular environments. Furthermore, the paper offers a novel viewpoint, underlining the potential of image transmission to improve Traveler Information Messages (TIMs) and emergency alerts. It also highlights the significant role of Artificial Intelligence (AI) in enhancing information distribution, providing a thorough understanding of this area. This paper serves as a useful reference for both researchers and practitioners who are working on developing practical solutions for multimedia transmission in vehicular ad hoc networks.