## 1 Introduction
This idea has also been verified experimentally [16]. However, the approach mentioned above is only a success for the first natural frequency of the bridge. On the other hand, it is known that higher modal parameters are more sensitive to local stiffness changes. Thus, to extend this idea to find higher modal parameters, [PERSON] and [PERSON] [17] have enhanced this idea with the EMD (empirical mode decomposition) method to identify up to the seventh natural frequency of the bridge. The indirect approach inspires many researchers: [PERSON] et al. [18] added a vibration exciter on a traveling vehicle to improve the estimation accuracy. The authors [19] also examined the feasibility of estimating bridge mode shapes from the vibration responses  
Figure 1: The conceptual diagram of the drive-by bridge monitoring: The measured vibration data on a traveling vehicle is used to evaluate the bridge’s health. In this study, bridges are modeled as simple Euler–Bernoulli beam supported by pins. of several cargo trailers. The other frequency-based approaches [20] are made by [PERSON] et al. [21] and [PERSON] et al. [22], while the mode shape-based approaches are also studied by [PERSON] et al. [23] and [PERSON] et al. [24]. [PERSON] et al. [21] have verified the drive-by monitoring method for estimating the bridge's natural frequencies. They validate their findings by performing the tests over different running speeds, road profiles, and traffic conditions. The acceleration responses of a vehicle crossing the bridge are fitted with an accelerometer and a GPS device. In their experiment, the first natural frequency cannot be detected, while the second natural frequency is detected at the low speed of the monitoring vehicle. This inability to detect the natural frequency is attributed to the high speeds, the absence of heavy traffic, and the interference of road profile frequencies. This research generally concludes that the accuracy of extracted natural frequency becomes better as the bridge length increases, vehicle speed decreases, and the road profile is smooth. A similar trend can also be confirmed in the study of [PERSON] et al. [23]. Identifying the bridge's natural frequency is difficult because vehicle frequency and road roughness interfere with bridge frequencies. This issue has been addressed by [PERSON] et al. [20]. They use vehicle-bridge contact response, which eliminates vehicle frequencies, and a shaker fixed on the bridge to enhance bridge vibration. Applying these ideas could reduce road roughness frequencies from the obtained data. It has concluded that this combination is effective for general application since the shaker's frequency and location can be tuned up by dynamic amplification factor to meet various bridges. On the other hand, [PERSON] et al. [23] use a one-tractor-two-trailers system and measure the vibration data of the two trailers. The tractor is a shaker traveling on the bridge, while the trailers less susceptible to engine vibration are the observers of bridge vibrations in this scheme. Using residual vibration between two trailers can reduce the road roughness frequencies from the obtained data and extract the bridge vibration components. From the extracted data, bridge mode shapes can be estimated accurately. According to these previous studies, the feasibility of drive-by bridge monitoring has been increased. [PERSON] et al. [25] also show the applicability of this technology to short-span bridges, which means it can provide a solution to the vast demand for bridge inspections. As mentioned above, many drive-by monitoring approaches have estimated modal parameters under carefully limited conditions and have evaluated bridge health. Feature-value-based bridge health monitoring is associated with some challenges. When using features such as modal parameters for detecting and estimating bridge damages in vibration-based SHM, it is also necessary to verify not only their estimation accuracy but also the sensitivity of focused modal parameters to target damages.