## 1 Introduction
Predictive modeling and object identification assist the software with navigating traffic regulations and avoiding obstructions [13]. All these data are generated from one smart entity, which will create a challenge. Challenges exist to scalability such as scalability in data, scalability in throughput, scalability in power, and scalability in time response. Smart vehicles are a trending research area for many companies, labs, and researchers due to their anticipated benefits to the quality of life [14]. This type of driving relies partially on machines and is ruled by algorithms and embedded standards and regulation codes which give drivers more tools to enhance their experience. Security and real-time operations are an important factor in such applications, where the impact of any failure will influence lives. Each vehicle will be full of sensors to read the environment and act accordingly. The integration of multiple technologies will burden the central authorities regarding security threats [15]. Depending on the above, several questions come to mind, such as: How to create secure communication? How to avoid latency? How to reduce centralization? How to reduce power consumption? How to encourage nodes to act honestly? Such a large, complex CPS has many obstacles to overcome for full deployment such as interference conditions, traffic regulations, and complex V2V communications. The introduction of the blockchain DLTs, which have altered numerous aspects of our lives, has been one of the most revolutionary developments of the past few decades [16; 17]. These innovative methods of data storage and transaction processing have the potential to affect a broad range of industries, including banking, supply chain management, government, healthcare, and ITS [18]. DLT is a group of mechanisms and protocols governed by the consensus mechanism of participants through direct communication in an untrusted environment [19]. DLT has been proposed to resolve many issues of the current centralized paradigm of intelligent transportation and to provide a secure environment for its operations [20; 21]. ITS-VANETs need to acquire the characteristics of DLT such as decentralization, immutability, transparency, security, efficiency, and programmability in order to satisfy its requirements as a Complex Cyber-Physical System (CCPS) [22]. Other examples include real-time interaction, scalable architecture, automated operation, low power consumption and security. Increased trust, transparency, and security are just some of the ways in which DLT could change the face of ITS [23]. Certain conditions must be met before DLT-based ITS operations can be put into place. Already existing ledger structures and consensus algorithms need trade-offs in which some times security and privacy are strong but scalability is weak or scalability is high but security is low. Scalability: The volume of data related to transportation operations is expected to expand, and the system must be able to process a high volume of transactions and nodes. This is not the case in all DLTs. Some lack scalability such as Bitcoin. The paradigm is a fit for electronic cash systems but will cause an issue in term of scalability and hardware requirements if applied to ITS. Blockchain-Based Secure Data Exchange (BDESF) ITS is a secure and tamper-proof framework for data exchange and storage. It also prevents replay, Man-in-the-Middle (MiTM) weaknesses, impersonation, data leakage, and unwanted data updating with authentication and privacy measures. BDESF-ITS integrates smoothly with existing transportation systems. BDESF-ITS is a strong security mechanism for DLT applications to transportation security and privacy [24]. However, Practical Byzantine Fault Tolerance (PBFT) is suggested to be used in such a framework which will burden the network with the redundancy. Power consuming protocols are part of the scalability problem and need a pre-existing level of trust to be initiated.