## 2 Methodology  
The present review study explored several databases of publications, including different search engines and sources, such as Scopus, ProQuest, and Google Scholar. The study first identified a wide range of academic articles, graduate theses, conference papers, and technical reports from state departments and government agencies, focusing on construction automation and innovation, engineering informatics, and transportation infrastructure management. To create an effective keyword search query for a broad topic such as CIM implementation in transportation infrastructure, it is essential to identify pertinent studies across various research domains in the field. Therefore, constructing a comprehensive search query that accurately captures various CIM tools and practices throughout the different stages of an infrastructure's lifecycle is crucial. Therefore, an iterative process using Python script was implemented to analyze the collected publications through keyword identification. Figure 1 depicts the process of creating search queries for identifying relevant CIM capabilities. The search query is mainly constructed from three clusters encompassing the lifecycle of the infrastructure including scoping and surveying, planning and design, and operation and maintenance. The term \"infrastructure\" in this query context refers to \"Highway\" and \"Bridge\", which are linked together using the ORcommand. Initially, key terms are extracted from the collected papers. Each cluster is further refined by reviewing the frequency and context in which related terms appear in the title. Utilizing different libraries for data processing and keyword exploration, the classification algorithm processed each collected publication's abstract to count the occurrence of combined keywords within a corresponding cluster. Each paper was required to contain at least one keyword from each identified cluster, rather than all keywords within. Following the clustering process, the findings were filtered by most keyword appearances to identify the most relevant publications. In cases where multiple topics achieved the maximum keyword count for a single publication, it was assigned to all such topics, capturing the multidisciplinary nature of some studies. Lastly, the classification for each publication was manually checked and confirmed to ensure methodical relevancy to the present study. This framework served as a foundation for a coherent and organized analysis, enabling a detailed assessment of the current state of the field and identification of emerging trends, gaps, and challenges. The conducted query analysis facilitates the identification of relevant studies while eliminating subjectivity from the process, contributing to a comprehensive understanding of CIM in infrastructure projects. Following the initial selection and examination, a detailed analytical framework was established to categorize the findings into five specific research topics representing different stages of a lifecycle. As fully illustrated in Figure 2, a systematic approach was employed for the selection and review of studies pertinent to CIM and its application in civil infrastructure. Initially, studies were assessed for relevance to civil infrastructure and CIM. The collected studies were initially assigned to three main stages during the infrastructure lifecycle (based on the predefined advanced level CIM maturity model provided by NCHRP), including scoping and surveying, planning and design, and operation and maintenance. From the scoping and surveying phase, the authors derived two thematic topics, namely _Advanced Surveying_ and _Geospatial Analysis_. This delineation is intended to concentrate on the initial stages of project development, allowing for a focused examination of the technical challenges and advancements within these preliminary phases both in terms of availability of tools and framework. The _nD modeling_ research topic delves into advanced CIM practices for the construction planning and design phase.