## 6 Conclusions  
In this study, we aimed to determine changes in the quality of gravel pavement overtime during the service life of a road, in line with the level of surface roughness and pavement excitation on vehicle response and driving comfort. The roughness of the experimental 160 m section of road with gravel pavement was measured continuously three times by adopting the 3 m straightedge method: (1) two days after pavement maintenance (blading), (2) three weeks after pavement maintenance, and (3) assessing the worst pavement quality before maintenance. The measurement results showed that the road quality continuously deteriorated with an increase in pavement roughness. Pavement elevation spectral density disclosed several fractures in the roughness log-log plot, which meant variations in pavement waviness. For the worst pavement quality (PS-3), a dominance of short waves of approximately 0.5 m in length was found (lowest standard deviation), which was compatible with the corrugation phenomenon of the transverse ripples formed. Furthermore, such a wavy pattern was found to cause unsprung mass (USM) resonant excitation of the vehicle before the worst road quality was achieved. Spatial frequency conversion to temporal was done to analyse vehicle dynamic responses at different driving speeds. Although the specific fractures of surface power spectral density (PSD) characteristics remained, for the worst pavement quality state, in particular, the speed-affected frequencies shifted to higher bands. Speed is mostly related to driving safety, and therefore the dynamic load coefficient (DLC), as the indicator of tyre-pavement interaction and vehicle stability, was determined considering the analysed pavement states. Even quarter car simulations of driving at a low speed (<30 km/h) showed that the DLC reached values higher than 0.15 but did not exceed 0.3 when the proportion of wheel contact loss increased rapidly. However, the DLC undesirably increases at a low speed of 30 km/h on the worst pavement quality and a high speed of 90 km/h on the middle-quality pavement. Even though most countries have a speed limit of 70 km/h on gravel pavement, the potential wheel contact force loss draws attention to timely road maintenance. Variations in driving comfort sensation and the indirect prediction of wheel-pavement interaction complicate a driver's selection of safe driving speed. Therefore, vehicle active chassis systems should be continuously developed for better performance on a specific road such as variable roughness gravel pavement. In consonance with the estimated vehicle suspension response to the investigated type of gravel pavement, IRI values have been found to rarely correspond to the actual level of pavement roughness. Therefore, this worldwide single-number indicator used for road maintenance planning is not appropriate for unpaved pavements with unsteady waviness. Absolute IRI values do not provide reliable results that can be used for safe speed estimation. However, calculating the IRI at a speed range of 30-45 km/h shows an increase in the values corresponding to the deteriorating pavement state. Thus, the IRI values calculated at a low speed (30 km/h) are suitable for assessing gravel pavement condition and road maintenance planning. The achieved results can be used to assist operators responsible for ensuring road quality and for decision making about road maintenance, to analyse the effects of unpaved roads on vehicle driving stability and comfort, and to support the performance of active safety systems, drivers, road maintenance planners, and road supervisors. Future experimental and theoretical studies should focus on vehicle dynamic response measurements and driver comfort evaluation in different driving modes under varying pavement states. Continuous research should also investigate higher-order frequency bands related to the issues of tyre dynamics and active vehicle safety control while driving on unpaved roads.