Relationship Between Slipperiness Coefficient and Pavement Skid Resistance Performance

I. Introduction

Meteorological conditions significantly impact the safe operation of transportation. Adverse weather such as rain, snow, and freezing can reduce the pavement friction coefficient, thereby negatively affecting highway traffic and driving safety. The main factors leading to the reduction of the pavement friction coefficient are standing water caused by rainfall and road icing caused by rain and snow. Therefore, rapidly detecting the skid resistance performance of road surfaces under severe weather conditions, and promptly disseminating this information to drivers, enables vehicles to adjust their speed in time, ensuring adequate braking distance and vehicle stability, or allowing them to choose alternative routes. This can effectively prevent and reduce traffic accidents.

Commonly used test methods for measuring the pavement friction coefficient include the pendulum friction tester, the transverse force coefficient test system, and the dynamic rotary friction tester. With the continuous development of road monitoring technology, non-contact road surface state sensors have been applied to pavement measurement, leading to the introduction of the concept of the pavement slipperiness coefficient. The pavement slipperiness coefficient utilizes infrared spectroscopy. Based on the differences in light absorption by different areas of the pavement, it distinguishes the road surface state, such as dry, wet, snow-covered, or icy. Through comprehensive analysis of the pavement surface state and detection depth, it derives an evaluation index representing the degree of pavement slipperiness. This evaluation index is called the slipperiness coefficient (G). This coefficient is used to characterize the pavement's skid resistance performance and has the same significance as the friction coefficient.

The infrared remote sensing road state detector is based on spectroscopy for close-range remote sensing of the road surface. It has a built-in infrared emitter aimed at a selected position on the road surface. The emitted light is reflected from the measured location back to the receiver for integration, distinguishing the specific wavelength reflections caused by water, snow, and ice on the road surface, thereby outputting the pavement slipperiness coefficient index.

II. Slipperiness Coefficients Under Different Pavement Conditions

2.1 Effect of Standing Water on Slipperiness Coefficient

As shown in Figure 1, as the depth of standing water increases, the pavement slipperiness coefficient gradually decreases. During the growth stage of water depth from 1 to 5 mm, the slipperiness coefficient drops significantly from 0.80 to about 0.50. Subsequently, as the water depth continues to increase, the decrease in the slipperiness coefficient diminishes and levels off. Measurements taken with a pendulum friction tester on the pavement show that when the water depth is less than 1 mm, the pendulum value ranges from 60 to 70, indicating good skid resistance. When the water depth is between 1 and 6 mm, the friction coefficient ranges from 60 to 50, indicating a decline in pavement skid resistance. At this point, transmitting the corresponding slipperiness coefficient to vehicles on the road can alert drivers to take measures such as reducing speed and maintaining a safe distance to improve driving safety.

2.2 Effect of Snow Cover on Slipperiness Coefficient

As shown in Figure 2, the slipperiness coefficient continuously decreases with increasing snow thickness, and the magnitude of the decrease is substantial, dropping from 0.80 to 0.10. Data analysis reveals: when the snow thickness is less than 0.40 mm, the slipperiness coefficient is above 0.60; when the snow thickness is between 0.40 and 1.00 mm, the slipperiness coefficient remains around 0.40; when the snow thickness exceeds 1.00 mm, the slipperiness coefficient plummets to about 0.10, and with further increases in snow thickness, it generally fluctuates within a narrow range around 0.10.

When the snow thickness is less than 1.00 mm, the measured pendulum value is between 40 and 60. When the snow thickness exceeds 1.00 mm, the measured pendulum value falls between 20 and 40.

2.3 Effect of Ice Formation on Slipperiness Coefficient

As shown in Figure 3, the slipperiness coefficient decreases sharply with increasing ice thickness. This decreasing trend is significantly more pronounced compared to the conditions of standing water and snow. When the ice thickness reaches 0.10 mm, the slipperiness coefficient has already decreased to about 0.50. When the ice thickness reaches 0.40 mm, the coefficient drops to about 0.30. When the ice thickness reaches 0.80 mm or more, the slipperiness coefficient falls to about 0.1. A phenomenon similar to that observed under snow cover is that when the ice thickness exceeds 0.80 mm and continues to grow, the slipperiness coefficient essentially remains stable, fluctuating within a narrow range around 0.10. Corresponding pendulum values measured on the icy pavement using the pendulum tester are mostly below 30, with the lowest recorded around 20. At this point, the slipperiness coefficient is generally maintained at about 0.10, indicating that the pavement has become quite slippery and its skid resistance is virtually lost. Timely warnings should be issued, and measures such as traffic closure or the application of de-icing salts should be taken to ensure traffic safety.

III. Relationship Between Slipperiness Coefficient and Friction Coefficient (Pendulum Value)

As shown in Figure 4, the smaller the pavement slipperiness coefficient, the smaller the pavement pendulum value, and the poorer the pavement skid resistance performance. Conversely, a larger pendulum value indicates a larger slipperiness coefficient and better skid resistance. Therefore, the slipperiness coefficient can be used to characterize the pavement's skid resistance performance.

IV. Conclusions and Recommendations

4.1 Conclusions

(1) The slipperiness coefficient gradually decreases with increasing depth of standing water. The reduction in the slipperiness coefficient due to standing water is limited to a certain range. When the water depth exceeds 5.00 mm, the slipperiness coefficient decreases to about 0.50 and levels off.

(2) The slipperiness coefficient continuously decreases with increasing snow thickness, dropping from 0.80 to 0.10. When the snow thickness reaches 1.00 mm or more, the slipperiness coefficient decreases to 0.10 and then fluctuates slightly.

(3) The slipperiness coefficient declines sharply and rapidly with increasing ice thickness. When the ice thickness reaches 0.10 mm, the slipperiness coefficient has already dropped to about 0.50. When the ice thickness reaches 0.80 mm or more, the slipperiness coefficient falls to about 0.10 and then fluctuates within a small range.

(4) The applicable range of the pavement slipperiness coefficient G is determined to be 0.10 to 0.80. Based on this coefficient, pavement skid resistance performance can be classified into four levels.

4.2 Recommendations

In practical engineering applications, the pavement slipperiness coefficient can be monitored using a combination of road state detectors installed permanently beside the road at specific sections and vehicle-mounted road state detectors for full coverage. Under severe weather conditions, the pavement slipperiness coefficient can be monitored in a timely manner. The collected slipperiness coefficient G data can be uploaded via wireless internet transmission technology. After analysis and processing, the pavement skid resistance level can be promptly disseminated to drivers. This allows drivers to take necessary measures based on different skid resistance levels, ensuring driving safety under adverse weather conditions and reducing the occurrence of traffic accidents.