## 2 Overview of Drive-by Condition Assessment of Railway Track and Vehicle  
The dynamic responses of both the vehicle and the track are closely linked and rely on the physical and geometric properties of each subsystem's components. In terms of track components, factors such as the mass, stiffness, and damping of its main components and their interfaces, as well as the track's irregularity profile, have a direct impact on the dynamic responses of the vehicles [20]. Regarding the influence of vehicle components, the dynamic responses of the vehicle are directly related to the stiffness and damping of the suspension systems, as well as the mechanical properties of the car body, bogies, and wheelsets [21; 22]. Thus, it is expected that damage to the track or vehicle might cause detectable changes in vehicle responses. The main idea behind assessing the condition of railway vehicles and tracks based on embedded monitoring systems lies in the development of methodologies capable of distinguishing responses associated with a scenario of damage from those associated with a health condition. Adopting this approach, particularly for the track, holds great significance as it enables the monitoring of extensive stretches of track, with just a handful of sensors installed on a limited number of vehicles. Besides the benefits mentioned above, implementing the drive-by concept in practice requires the development of robust signal-processing methods that can accurately differentiate between changes in dynamic responses caused by damage and those induced by external factors, such as environmental and operational disturbances. The acceleration responses measured on the vehicle can be influenced by various factors, such as temperature variations, wind, track irregularities, vehicle speed, and weight, among others. Therefore, it is crucial to have robust damage indicators and distinguish these external interferences from those caused by damage for any detection methodology to be feasible [19; 23; 24]. Concerning track and vehicle damage detection through onboard instrumentation, several authors have worked on numerical and experimental studies, and many different \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Reference**} & \multicolumn{2}{c}{**Bridge Subsystem**} & \multirow{2}{*}{**Railway Track**} & \multirow{2}{*}{**Railway Vehicles**} \\ \cline{2-2} \cline{4-4}  & **Highway** & & & **Railway** & **Subsystem** \\ \hline [PERSON] et al. [10] & – & – & ✓ & ✓ \\ \hline [PERSON] et al. [11] & – & – & ✓ & – \\ \hline [PERSON] \& [PERSON] [12] & ✓ & – & – & – \\ \hline [PERSON] et al. [13] & ✓ & – & – & – \\ \hline [PERSON] et al. [14] & – & – & ✓ & ✓ \\ \hline [PERSON] \& [PERSON] [15] & ✓ & – & – & – \\ \hline [PERSON] et al. [16] & – & – & – & ✓ \\ \hline [PERSON] et al. [17] & ✓ & – & ✓ & – \\ \hline [PERSON] et al. [18] & ✓ & – & ✓ & – \\ \hline [PERSON] et al. [19] & ✓ & – & – & – \\ \hline
**Present** & **Part I** & – & ✓ & – & – \\ \hline
**work** & **Part II** & – & – & ✓ & ✓ \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Main topics addressed by the state-of-the-art review articles found. methodologies have been proposed. In these studies, the feasibility of detecting different types of damage was assessed as well as different strategies for overcoming the aforementioned operational and environmental interferences. This part of the review article provides a detailed overview of several of these recent studies identified by the authors. The article layout is illustrated in Figure 1 through a comprehensive flowchart. To enhance clarity, the article is divided into subsections, based on the type and/or region of the defect that needs to be located. Specifically, for the identification of track damage, the works were categorized into three subsections (i) track irregularities' assessment, (ii) rail condition-based assessment, and (iii) rail supporting components' condition-based assessment.