# Internet of Vehicles for Sustainable Smart Cities: Opportunities, Issues, and Challenges
## 1 Introduction
### Motivation  
Smart urban areas thrive in encouraging reliable economic growth and delivering a top-standard quality of life. The use of intelligent transport systems (ITSs) motivates urban areas to improve resource use while reducing pollution and effectively serving their community [5]. Employing smart tools like industrial control and urban traffic management is a way to ensure sustainable city growth today [6]. In a smart city, business leaders optimize technology for the benefit of residents' lives at work and on their commutes while making information readily available [7]. New vehicle models introduce innovative sensing and interactive capabilities along with improved social functionality. Vehicles  
Figure 1: The Internet of Vehicles ecosystem. that provide wireless sensing and communication play a key role in the development of smart cities. Different approaches and methods were studied to ease traffic congestion and improve traffic control for linked vehicles, offering motivation for evolving smart transport systems [8]. A plan for cooperative edge computing in the Social Internet of Vehicles (SloV) was employed to reduce traffic congestion while exploring new ideas in smart transportation systems [9]. With deep learning (DL) identification capabilities, the IoV achieves effective protection against possible threats [10]. The technology increases the safety and dependability of the public while protecting the user from accidents [11]. Smarter cities are significantly shaped by the traffic congestion control system that utilizes machine learning (ML) [12]. Multiple decentralized methods for managing traffic in vehicles serve to create a more stable network and decrease data packet loss while facilitating effective and trustworthy data transfer in a changing mobility environment [13]. The Internet of Autonomous Things (IoAT) represents a web of independent devices that function on their own and improve automation and data collection across different fields [14]. By integrating vehicles, transportation systems, and various smart objects within the city, the IoV contributes to creating a more sustainable urban environment in several ways [15]. In [16], the concept of utilizing vehicles as mobile sensors for road condition monitoring is introduced. Furthermore, an exhaustive review of authentication methods in smart transportation systems outlines a defined categorization and discusses key issues facing the field [17]. In [18], a new systematic literature review (SLR) methodology was presented for the examination of data-focused methods in the IoV. In [19], a taxonomy categorizes data dissemination techniques for the IoV into distinct classes: intelligent networking and traditional methods establish a clear organizing system for these methods in relation to IoV. A number of experts have introduced layered systems for the IoV aimed at helping to define and execute IoV systems. These designs allow for simple integration of diverse components and functions to facilitate efficient coordination and communication in the IoV system [20; 21; 22; 23; 24; 25; 26]. A three-layer model was laid out by both [20; 21] for the IoV that serves as a guide for its design and execution. In addition to [20], the studies in [21; 22] proposed a three-layered IoV architecture that differ slightly from the earlier work. Moreover, an architecture with three layers was introduced [23] for facilitating device-to-device (D2D) connections. In contrast to previous frameworks [24], CISCO introduced a four-layer IoV model focuses on services, infrastructure, operations and user-interface [25]. In addition, a unique variation of IoV architecture [26] and a four-layer model were introduced. The focus is directed towards the emerging era of the IoV, wherein vehicles themselves are equipped with a diverse range of sensors, effectively transforming into sensor nodes [27].