Variability of Gravel Pavement Roughness: An Analysis of the Impact on Vehicle Dynamic Response and Driving Comfort

Abstract

Gravel pavement has lower construction costs but poorer performance than asphalt surfaces on roads. It also emits dust and deforms under the impact of vehicle loads and ambient air factors; the resulting ripples and ruts constantly deepen, and therefore increase vehicle vibrations and fuel consumption, and reduce safe driving speed and comfort. In this study, existing pavement quality evaluation indexes are analysed, and a methodology for adapting them for roads with gravel pavement is proposed. We report the measured wave depth and length of gravel pavement profile using the straightedge method on a 160 m long road section at three stages of road utilization. The measured pavement elevation was processed according to ISO 8608, and the frequency response of a vehicle was investigated using simulations in MATLAB/Simulink. The international roughness index (IRI) analysis showed that a speed of 30–45 km/h instead of 80 km/h provided the objective results of the IRI calculation on the flexible pavement due to the decreasing velocity of a vehicle’s unsprung mass on a more deteriorated road pavement state. The influence of the corrugation phenomenon of gravel pavement was explored, identifying specific driving safety and comfort cases. Finally, an increase in the dynamic load coefficient (DLC) at a low speed of 30 km/h on the most deteriorated pavement and a high speed of 90 km/h on the middle-quality pavement demonstrated the demand for timely gravel pavement maintenance and the complicated prediction of a safe driving speed for drivers. The main relevant objectives of this study are the adaptation of a road roughness indicator to gravel pavement, including the evaluation of vehicle dynamic responses at different speeds and pavement deterioration states.

Study on the Influence of Suspension Parameters on Longitudinal Impact Comfort

“…e tire plays a decisive role in the accuracy of pulse road simulation. Considering the high input frequency of pulse road [15][16][17][18], only F-tire model and PAC2002 with Belt Dynamics tire model with high upper limit frequency can be selected for simulation [13,14]. Considering the relatively slow operation speed of F-tire model, PAC2002 with Belt Dynamics tire model was selected in this paper for simulation.…”

The Braking-Pressure and Driving-Direction Determination System (BDDS) Using Road Roughness and Passenger Conditions of Surrounding Vehicles

“…Vidas Žuraulis et al proposed that the existing pavement quality evaluation indexes be analyzed and a methodology for adapting them for roads with gravel pavement be created [20]. The goal of this study was to develop the methodology for gravel road quality evaluation concerning pavement deterioration and vehicle dynamic response, providing an appropriate maintenance indication for this pavement type.…”

Ride Comfort Prediction on Urban Road Using Discrete Pavement Roughness Index

“…The prediction of ride comfort based on pavement roughness indices has been widely studied in recent decades because of their strong correlation [2][3][4]. Relative studies focused mainly on developing correlations between the ride comfort and the pavement roughness indices by means of simulations or field tests.…”