## 1 Introduction
[PERSON] and [PERSON] [18] proposed the use of frequency domain decomposition (FDD) as a more accurate alternative to fast Fourier transform (FFT) for bridge frequency identification in the presence of road roughness. In their review paper, [PERSON], [PERSON] [9] emphasized the challenge by the road surface profile on the extraction of the bridge dynamic properties. They also highlighted the influence of the vehicle's own frequency on the recorded signal by the vehicle. The vehicle's own response could overshadow bridge vibration, which would misrepresent the dynamic properties of the bridge. [PERSON], [PERSON] [19] derived a formula to compute the contact-point response from the response of the scanning vehicle. They demonstrated that the contact-point response could eliminate the vehicle response, which pollutes the recorded signal. Although the contact-point response has provided a more accurate response for the bridge, it still does not solve the issue of road roughness. [PERSON], [PERSON] [20] examined the use of the scanning vehicle in a stationary condition. They concluded that the stationary vehicle showed a higher mode of frequency and better visibility of bridge frequency than the vehicle in a moving condition. They mentioned that a stationary vehicle was not subjected to road roughness effects, thus providing better visibility than the moving vehicle. [PERSON], [PERSON] [21] computed the contact-point response of a stationary vehicle in a numerical simulation study considering different scenarios. They demonstrated how the contact-point response of the stationary vehicle was almost identical to the bridge response taken form a fixed sensor on the bridge. As the scanning vehicle encounters road roughness challenge while passing over the bridge, it is advised that the scanning vehicle should be investigated while it is in a stationary position [22]. Therefore, this paper introduces the use of a vehicle in a stationary condition for damage detection. This paper suggests that when BHM is conducted using the scanning vehicle, not only should the vibration of the moving be used, but the vibration of the vehicle in a stationary condition should also be considered. This paper demonstrates how the scanning vehicle in a stationary position can be used for bridge damage detection. When it comes to damage detection, bridge damage can be classified into four levels. The first level is the identification of damage existence, the second is determining the damage location, the third is determining the severity of the damage, and finally, estimating the remaining life service of the bridge [23]. The indirect method has been used extensively covering different levels of damage detection using a variety of methods. For example, [PERSON], [PERSON] [24] and [PERSON] and [PERSON] [25] used the scanning vehicle to detect the existence of bridge damage without determining the damage location. Meanwhile, [PERSON], [PERSON] [26] and [PERSON], [PERSON] [27] employed the indirect method to determine the damage and its location; however, they did not estimate the severity of the damage. [PERSON], [PERSON] [28] were also able to determine the damage location on the bridge using the scanning vehicle. They attempted to determine the severity of the damage, but they acknowledged that defect severity cannot be obtained by the proposed method. Other studies such as [PERSON], [PERSON] [29] used a scale bridge model to examine the efficiency of using a scanning vehicle for damage detection in short span bridges. They managed to detect damage location and severity using a method that relies on prior information of the undamaged bridge. In fact, among the proposed methods, most of the techniques require baseline information about the healthy state of the bridge to be able to detect damages. However, prior information about most bridges is usually not available [30]. On the other hand, there are some proposed techniques that do not require prior information of the intact bridge, such methods are called baseline-free methods.