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Hydroplaning risk evaluation plays a pivotal role in highway safety management. It is also an important component in the intelligent transportation system (ITS) ensuring human driving safety. Water-film is the widely accepted vital factor resulting in hydroplaning and thus continuously gained researchers’ attention in recent years. This paper provides a new framework to evaluate the hydroplaning potential based on emerging 3D laser scanning technology and water-film thickness estimation. The 3D information of the road surface was captured using a vehicle-mounted Light Detection and Ranging (LiDAR) system and then processed by a wavelet-based filter to remove the redundant information (surrounding environment: trees, buildings, and vehicles). Then, the water film thickness on the given road surface was estimated based on a proposed numerical algorithm developed by the two-dimensional depth-averaged Shallow Water Equations (2DDA-SWE). The effect of the road surface geometry was also investigated based on several field test data in Shanghai, China, in January 2021. The results indicated that the water-film is more likely to appear on the rutting tracks and the pavement with local unevenness. Based on the estimated water-film, the hydroplaning speeds were then estimated to represent the hydroplaning risk of asphalt pavement in rainy weather. The proposed method provides new insights into the water-film estimation, which can help drivers make effective decisions to maintain safe driving.

Highway pavements are usually monitored in terms of their surface performance assessment, since the major cause that triggers maintenance is reduced pavement serviceability due to surface distresses, excessive pavement unevenness and/or texture loss. A common way to detect pavement surface condition is by the use of vehicle-mounted laser sensors that can rapidly scan huge roadway networks at traffic speeds without the need for traffic interventions. However, excessive roughness might sometimes indicate structural issues within one or more pavement layers or even issues within the pavement foundation support. The stand-alone use of laser profilers cannot provide the related agencies with information on what leads to roughness issues. Contrariwise, the integration of multiple non-destructive data leads to a more representative assessment of pavement condition and enables a more rational pavement management and decision-making. This research deals with an integration approach that primarily combines pavement sensing profile and deflectometric data and further evaluates indications of increased pavement roughness. In particular, data including Falling Weight Deflectometer (FWD) and Road Surface Profiler (RSP) measurements are used in conjunction with additional geophysical inspection data from Ground Penetrating Radar (GPR). Based on pavement response modelling, a promising potential is shown that could proactively assist the related agencies in the framework of transport infrastructure health monitoring.

The pavement roughness is the main variable that produces the vertical excitation in vehicles. Pavement profiles are the main determinant of (i) discomfort perception on users and (ii) dynamic loads generated at the tire-pavement interface; hence its evaluation constitutes an essential step on a Pavement Management System. The present document evaluates two specific techniques used to simulate pavement profiles; these are the shaping filter and the sinusoidal approach, both based on the Power Spectral Density. Pavement roughness was evaluated using the International Roughness Index (IRI), which represents the most used index to characterize longitudinal road profiles. Appropriate parameters were defined in the simulation process to obtain pavement profiles with specific ranges of IRI values using both simulation techniques. The results suggest that using a sinusoidal approach one can generate random profiles with IRI values that are representative of different road types; therefore, one could generate a profile for a paved or an unpaved road, representing all the proposed categories defined by ISO 8608 standard. On the other hand, to obtain similar results using the shaping filter approximation, a modification in the simulation parameters is necessary. The new proposed values allow one to generate pavement profiles with high levels of roughness, covering a wider range of surface types. Finally, the results of the current investigation could be used to further improve our understanding on the effect of pavement roughness on tire pavement interaction. The evaluated methodologies could be used to generate random profiles with specific levels of roughness to assess its effect on dynamic loads generated at the tire-pavement interface and user's perception of road condition. RESUMEN La rugosidad del pavimento es la principal variable que produce la excitación vertical en los vehículos. Los perfiles de pavimento son los principales responsables de (i) la incomodidad percibida por los usuarios y, (ii) las cargas dinámicas generadas en la interfaz entre el neumático y el pavimento, de ahí que su evaluación constituye un paso esencial en un Sistema de Gestión de Pavimentos. El presente documento evalúa dos técnicas específicas utilizadas para simular perfiles de pavimento; estos son los filtros de forma y la aproximación sinusoidal, ambos basados en la Densidad de Potencia Espectral. La rugosidad del pavimento se evaluó utilizando el Indice Rugosidad Internacional (IRI), el cual es el índice más utilizado para caracterizar rugosidad del perfil longitudinal de una vía. En la presente investigación se definieron parámetros apropiados en el proceso de simulación para obtener perfiles de pavimento con rangos específicos de los valores de IRI utilizando ambas técnicas de simulación. Los resultados sugieren que el uso de la aproximación sinusoidal puede generar perfiles aleatorios con valores de IRI que son representativos de diferentes tipos de vías, por lo tanto, se podría generar un perfil para un pavimento nuevo o una vía sin pavimentar, cubriendo todas las categorías definidas por la norma ISO 8608. Por otro lado, para obtener resultados similares usando la metodología de filtro de conformación, es necesaria una modificación en los parámetros de simulación. Los nuevos valores propuestos permiten generar perfiles de pavimento con altos niveles de rugosidad, que cubren una gama más amplia de tipos de superficie. Por último, los resultados de la presente investigación se podrían utilizar para enriquecer lo que se conoce sobre el efecto de la rugosidad del pavimento en la interacción del pavimento de neumáticos. Las metodologías analizadas se podrían utilizar para generar perfiles aleatorios con niveles específicos de rugosidad (IRI) para evaluar su efecto sobre las cargas dinámicas generadas en la interfaz neumático-pavimento y la percepción del usuario del estado de la carretera.

The pavement roughness is the main variable that produces the vertical excitation in vehicles. Pavement profiles are the main determinant of (i) discomfort perception on users and (ii) dynamic loads generated at the tire-pavement interface, hence its evaluation constitutes an essential step on a Pavement Management System. The present document evaluates two specific techniques used to simulate pavement profiles; these are the shaping filter and the sinusoidal approach, both based on the Power Spectral Density. Pavement roughness was evaluated using the International Roughness Index (IRI), which represents the most used index to characterize longitudinal road profiles. Appropriate parameters were defined in the simulation process to obtain pavement profiles with specific ranges of IRI values using both simulation techniques. The results suggest that using a sinusoidal approach one can generate random profiles with IRI values that are representative of different road types, therefore, one could generate a profile for a paved or an unpaved road, representing all the proposed categories defined by ISO 8608 standard. On the other hand, to obtain similar results using the shaping filter approximation a modification in the simulation parameters is necessary. The new proposed values allow one to generate pavement profiles with high levels of roughness, covering a wider range of surface types. Finally, the results of the current investigation could be used to further improve our understanding on the effect of pavement roughness on tire pavement interaction. The evaluated methodologies could be used to generate random profiles with specific levels of roughness to assess its effect on dynamic loads generated at the tire-pavement interface and user’s perception of road condition. La rugosidad del pavimento es la principal variable que produce la excitación vertical en los vehículos. Los perfiles de pavimento son los principales responsables de (i) la incomodidad percibida por los usuarios y, (ii) las cargas dinámicas generadas en la interfaz entre el neumático y el pavimento, de ahí que su evaluación constituye un paso esencial en un Sistema de Gestión de Pavimentos. El presente documento evalúa dos técnicas específicas utilizadas para simular perfiles de pavimento; estos son los filtros de forma y la aproximación sinusoidal, ambos basados en la Densidad de Potencia Espectral. La rugosidad del pavimento se evaluó utilizando el Índice Rugosidad Internacional (IRI), el cual es el índice más utilizado para caracterizar rugosidad del perfil longitudinal de una vía. En la presente investigación se definieron parámetros apropiados en el proceso de simulación para obtener perfiles de pavimento con rangos específicos de los valores de IRI utilizando ambas técnicas de simulación. Los resultados sugieren que el uso de la aproximación sinusoidal puede generar perfiles aleatorios con valores de IRI que son representativos de diferentes tipos de vías, por lo tanto, se podría generar un perfil para un pavimento nuevo o una vía sin pavimentar, cubriendo todas las categorías definidas por la norma ISO 8608. Por otro lado, para obtener resultados similares usando la metodología de filtro de conformación, es necesaria una modificación en los parámetros de simulación. Los nuevos valores propuestos permiten generar perfiles de pavimento con altos niveles de rugosidad, que cubren una gama más amplia de tipos de superficie. Por último, los resultados de la presente investigación se podrían utilizar para enriquecer lo que se conoce sobre el efecto de la rugosidad del pavimento en la interacción del pavimento de neumáticos. Las metodologías analizadas se podrían utilizar para generar perfiles aleatorios con niveles específicos de rugosidad (IRI) para evaluar su efecto sobre las cargas dinámicas generadas en la interfaz neumático-pavimento y la percepción del usuario del estado de la carretera.

Pavement surface profiles induce dynamic ride responses in vehicles which can potentially be used to classify road surface roughness. A novel method is proposed for the characterisation of pavement roughness through an analysis of vehicle accelerations. A combinatorial optimisation technique is applied to the determination of pavement profile heights based on measured accelerations at and above the vehicle axle. Such an approach, using low-cost inertial sensors, would provide an inexpensive alternative to the costly laser-based profile measurement vehicles. The concept is numerically validated using a half-car roll dynamic model to infer measurements of road profiles in both the left and right wheel paths. Irish Research Council for Science, Engineering and Technology Seventh European Framework Project ASSET (Advanced Safety and Driver Support in Efficient Road Transport) Record must link to the DOI version - http://dx.doi.org/10.1016/j.jsv.2009.09.035. DG 08/07/10 ke,kpw.21/7/10

The unsealed road network is vital in maintaining community access to rural and isolated locations however is typified by the high operating cost associated. This document covers the key initiatives undertaken with respect to obtaining value for money benefits through implementing better maintenance management practices on the gravel road network within Toowoomba Regional Council (TRC) in Queensland, Australia. It could be envisaged that revised strategies will surely offer optimum financial and service level benefits. The primary aim of this strategic level exercise was to identify pavement profile including layer thicknesses and respective material types, whilst also covering geometric profile, existing pavement condition and drainage/shoulder status. Pavement Management Services (PMS, formally known as FUGRO-PMS) carried out these assessment using Ground Penetrating Radar survey and Visual imagery. Collected and processed data will be analyzed by TRC's strategic asset engineers to develop and introduce robust maintenance & renewal strategies, and also to develop short, medium and long term forward work programmes. Presented during Session 21: Low volume and Unsealed Roads, moderated by Stephen Gaj, at the 9th International Conference on Managing Pavement Assets (ICMPA9) in Alexandria, VA Includes conference paper and PowerPoint slides.