Wet Pavement Surface Research Articles

Analysis and mitigation of hydroplaning risk considering spatial-temporal water condition on the pavement surface

ABSTRACT Wet pavement surface on rainy days poses a challenge for traffic safety as it greatly impacts the safe driving speed and increases the hydroplaning risk. This study proposed a new approach to analyse and mitigate hydroplaning risk on roadways based on spatial-temporal water conditions and hydroplaning speeds. A theoretical analysis was conducted to predict the spatial-temporal water film depth under dynamic rainfall profile, considering the effects of roadway slope and pavement surface texture. The tire-water-pavement interaction model was then used to predict hydroplaning speeds of vehicles driving on different traffic lanes. According to the hydroplaning and traffic flow speeds, the spatial and temporal pattern of roadway hydroplaning risk was analysed. Considering traffic flow speeds, rainfall intensity, roadway geometry, and surface condition, the probability of hydroplaning occurrence at different times of rainfall and separate traffic lanes can be estimated using the proposed approach. Finally, the variable speed limits (VSL) approach was proposed to mitigate hydroplaning risk, which can be determined based on the hydroplaning threshold probability and the design speed limit of the roadway section.

Estimating the Potential of Skid Incident at Airport Runway – A Case Study

Skid resistance or friction on airport pavement plays an essential role in runway safety to ensure safe stopping distance. It also provides safety margins during take off and landing of aircraft especially in directional control by reducing the occurrence of overrun and veer-off incidents. The friction between pavement and tire is related to multiple factors such as pavement surface characteristics (microtexture and macrotexture), material intruded between tire and pavement surface (water, snow, and contaminants), tire conditions (types, wear, and inflation pressure), and vehicle operating conditions (vehicle speed and whether the wheel is rolling or locked). Skid incidents due to wet pavement surface at airport runway is a major concern especially in regions of wet-tropical climate countries such as Malaysia. Thus, this study was undertaken to measure the potential of skid incident at airport runway by collecting data on pavement surface characteristics. Field data collection on pavement surface microtexture was conducted using the British Pendulum Tester at a local airport runway to obtain data for the estimation of the skid number (SN). Due to constraints, pavement surface macrotexture test was unable to be conducted at site. However, the pavement surface macrotexture was able to be estimated based on previous research. The potential of the skid incident was estimated by calculating the SN using the aircraft’s touch down speed at the airport runway, varies from 50 to 70 knots (57.5 – 80.6 mph or 92.6 – 129.6 km/h). The results of the estimation indicated that the possibility of the skid incident occurrence was high. This study provides useful insights for airport authority to investigate the potential of overrun and veer-off incidents of aircraft at the airport runway.

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Analysis of severe and non-severe traffic crashes on wet and dry highways

This study examined the effects of several variables associated with geometric, environmental, and drivers' demographic factors on the likelihood of occurrences of traffic crashes on two and four-lane urban and rural highways. Among the variables tested, the key factors contributing to the crash are used as input variables to Poisson and negative binomial regression models. Four separate datasets representing severe and non-severe crashes occurred on dry and wet pavement surfaces are used to develop their respective models. The results of the analysis showed that the common principal determinants influencing both severe and non-severe crashes occurred on dry and wet pavement surfaces on the selected highways are AADT (Annual Average Daily Traffic) and TADT (Truck Average Daily Traffic). The posted speed limits were found to be significant only for non-severe crashes occurred on wet pavement surfaces. The urban-rural designation of the segments was found to be a key factor for non-severe crashes occurred on dry pavement surfaces. Macrotexture and IRI (International Roughness Index) were critical determinants for non-severe dry pavement, and severe wet pavement crashes respectively.

Evaluation of Vehicle Braking Performance on Wet Pavement Surface using an Integrated Tire-Vehicle Modeling Approach

Water film on a pavement surface greatly increases vehicle accident rates on rainy days. The simple use of a lower friction coefficient to evaluate the vehicle braking performance oversimplifies the contact mechanism between the tire and the pavement, and the use of a pure single tire model simulating hydroplaning was not able to reflect actual vehicle braking-cornering behaviors. This paper proposes an integrated tire-vehicle model to evaluate vehicle braking performance based on Persson’s friction theory, a tire hydroplaning finite element model, and a vehicle dynamic analysis. The friction coefficients between the tire and the pavement were calculated theoretically from the pavement surface morphology and the tire rubber properties; the tire hydrodynamic forces were obtained mechanistically from the hydroplaning model with different water film thicknesses and were used as inputs for calculating the braking distances in a vehicle model. The calculated friction coefficients and braking distances were verified using the field test results. A case study was conducted to illustrate the approach and evaluate the vehicle braking performance on straight and curved road sections. The results show that both longitudinal braking distances and lateral slip distances should be considered in the evaluation of vehicle braking performance.

Analysis of Nonsevere Crashes on Two- and Four-Lane Urban and Rural Highways: Effects of Wet Pavement Surface Condition

This study examines the effects of wet pavement surface conditions on the likelihood of occurrences of nonsevere crashes in two- and four-lane urban and rural highways in Alabama. Initially, sixteen major highways traversing across the geographic locations of the state were identified. Among these highways, the homogenous routes with equal mean values, variances, and similar distributions of the crash data were identified and combined to form crash datasets occurring on dry and wet pavements separately. The analysis began with thirteen explanatory variables covering engineering, environmental, and traffic conditions. The principal terms were statistically identified and used in a mathematical crash frequency models developed using Poisson and negative binomial regression models. The results show that the key factors influencing nonsevere crashes on wet pavement surfaces are mainly segment length, traffic volume, and posted speed limits.

Real-time crash prediction for expressway weaving segments

Weaving segments are potential recurrent bottlenecks which affect the efficiency and safety of expressways during peak hours. Meanwhile, they are one of the most complicated segments, since on- and off-ramp traffic merges, diverges and weaves in the limited space. One effective way to improve the safety of weaving segments is to study crash likelihood using real-time crash data with the objective of, identifying hazardous conditions and reducing the risk of crashes by Intelligent Transportation Systems (ITS) traffic control. This study presents a multilevel Bayesian logistic regression model for crashes at expressway weaving segments using crash, geometric, Microwave Vehicle Detection System (MVDS) and weather data. The results show that the mainline speed at the beginning of the weaving segments, the speed difference between the beginning and the end of weaving segment, logarithm of volume have significant impacts on the crash risk of the following 5–10min for weaving segments. The configuration is also an important factor. Weaving segment, in which there is no need for on- or off-ramp traffic to change lane, is with high crash risk because it has more traffic interactions and higher speed differences between weaving and non-weaving traffic. Meanwhile, maximum length, which measures the distance at which weaving turbulence no longer has impact, is found to be positively related to the crash risk at the 95% confidence interval. In addition to traffic and geometric factors, wet pavement surface condition significantly increases the crash ratio by 77%. The proposed model along with ITS, e.g., ramp metering, Dynamic Message Sign (DMS), and high friction surface treatment can be used to enhance the safety of weaving segments in real-time.

Evaluation of Driver Perception–Reaction Time under Rainy or Wet Roadway Conditions at Onset of Yellow Indication

The research presented in this paper characterizes the impact of a wet pavement surface and rainy weather conditions on driver perception–reaction time (PRT) at the onset of the yellow indication on the approach to a high-speed signalized intersection. An in-vehicle differential Global Positioning System was used in a controlled field environment. Three hundred eighty-four data records for all drivers who stopped at the onset of the yellow indication were available for analysis. The minimum time to intersection (TTI) ranged from 2.35 s to 5.71 s. Statistical analyses were used to quantify the effects of the TTI, grade (uphill or downhill), gender, and age (<40 years, 40 to 59 years, and ≥60 years) on driver PRT. The study demonstrated that driver PRT increases as TTI increases. A longer PRT was found when vehicles traveled along an upgrade section, given that the driver was typically accelerating when the yellow indication was initiated. No gender differences were found in PRT, and no statistically significant differences were found between different age groups. Furthermore, the study demonstrated that driver PRT increased under conditions of a wet pavement surface and rainy weather as compared with clear weather conditions over the entire TTI range.

Designing Yellow Intervals for Rainy and Wet Roadway Conditions

The research presented in this paper quantifies and models the impact of wet pavement surface and rainy weather conditions on driver perception-reaction times (PRTs), deceleration levels, and traffic signal change interval durations. A total of 648 stop-run records were collected as part of the research effort for a 72 km/h (45 mi/h) approach speed where participant drivers encountered a yellow indication initiation at different distances from the intersection. The participant drivers were randomly selected in different age groups (under 40 years old, 40 to 59 years old, and 60 years of age or older) and genders (female and male). Using the gathered data, statistical models for driver PRT and deceleration levels were developed, considering roadway surface and environmental parameters, driver attributes (age and gender), roadway grade, approaching speed, and time and distance to the intersection at the onset of yellow. Inclement weather yellow timings were then developed and summarized in lookup tables as a function of different factors (driver age/gender, roadway grade, speed limit, precipitation level, and roadway surface condition) to provide practical guidelines for the design of yellow signal timings in wet and rainy weather conditions. The results indicate that wet roadway surface conditions require a 5 percent increase in the change interval and that rainy conditions require a 10 percent or more increase in the duration of the change interval. These recommended change durations can also be integrated within the Vehicle Infrastructure Integration (VII) initiative to provide customizable driver warnings prior to a transition to a red indication.

Measurement of visibility loss due to splash and spray: porous, SMA and conventional asphalt pavements

Road traffic accidents are a major problem for the safety, well-being and economies of Southeast Asian countries. In Thailand, many accidents are caused by environmental or road conditions. Poor visibility on wet pavement is a major cause of accidents. Accumulated water on wet pavement surfaces creates the ‘splash and spray’ effect, resulting in visibility loss. The main objective of this study is to develop simple methods for measuring and comparing visibility loss between conventional dense-graded asphalt, stone mastic asphalt (SMA) and porous asphalt (PA) pavements. The light reduction method (LRM) and the colour changing method (CCM) were found to be the most appropriate tests for the measurement of visibility loss. Test results from both methods reveal that visibility loss is significantly greater for the conventional dense-graded pavement than for the SMA and PA pavements. Models for predicting the percentage of visibility loss were also developed and can be useful for improving road safety.

Exploratory Analysis of Accelerated Wear Testing to Evaluate Performance of Pavement Markings

Wear testing of pavement markings in the United States is commonly performed by AASHTO's National Transportation Product Evaluation Program. The pavement markings evaluated in this program are applied in a transverse manner along existing roadways, and a variety of objective measures are collected over a 2-year period. This paper reports the findings from an exploratory study on using the Model Mobile Load Simulator, third scale (MMLS3), to evaluate pavement marking performance along transverse test sections. Accelerated trafficking on wet and dry pavement surfaces was applied on sections of markings consisting of various waterborne paint products, marking thicknesses, and bead types and densities. Pavement marking retroreflectivity measurements were recorded at various stages of MMLS3 trafficking and compared with measurements of a test deck consisting of the same pavement markings subjected to live traffic. The findings suggest that the MMLS3 can consistently replicate the degradation pattern of the various pavement markings with regard to loss of retroreflectivity as a function of traffic passages. Performance varied among the various types of markings, with higher retroreflectivity observed for thicker markings with higher bead densities. Trafficking on wet pavement surfaces accelerated the degradation of the markings’ retroreflectivity.