Ageing of asphalt binders leads to evolution of pavements mechanical performances, due to changes in their rheological behaviour and in the binder composition. Ageing leads to a hardening of asphalt, mainly due to the oxidation of the asphalt binder itself. Oxidation rate is influenced by several parameters, namely outside temperature, ultraviolet (UV) radiation and intrinsic characteristics of the mixture constituents. In order to assess physical and chemical characteristics of the binders in aged pavements, mixture samples of several centimetres in thickness are usually cored from the field. Binders are extracted from these asphalt samples. This process of extraction is typical but it does not allow differentiating bulk and surface characteristics. Indeed, only the surface binder is exposed to UV rays and weathering. In order to assess the ageing of only the surface layer, to verify, for instance the influence of ageing on adhesion characteristics, it is necessary to extract and recover only the surface asphalt binder. A new test protocol, presented in this paper, has been developed to fulfil this purpose. This protocol consists in sampling only small particles at the surface layer, extracting the binder from the particles and performing Fourier transform infrared spectroscopy (FTIR) tests to assess the ageing of the binder. As the quantity of binder is very small, a specific FTIR test method is used. This method consists in keeping the binder diluted in the solvent and placing the solution in the ray of the spectrometer to perform the measurement. This new method has been compared to a more typical one, which consists in applying the binder on a transparent plate after having extracted the binder from the solvent. Once it has been checked that the two methods provide the same results for three kinds of binders, surface ageing tests have been performed. Two different ageing processes were considered: an ageing on site and an accelerated ageing protocol using a climate chamber named Weatherometer (SUNTERTXXL+). In this chamber, temperature, humidity and rain are controlled. The comparison between the ageing in the laboratory and the field allowed correlating both processes to establish an accelerator factor with respect to the increase in carboxyl group.

This paper describes the conception of a high level, compact, scalable, and long autonomy perception and localization system for autonomous driving applications. Our benchmark is composed of a high resolution lidar (128 channels), a stereo global shutter camera, an inertial navigation system, a time server, and an embedded computer. In addition, in order to acquire data and build multi-modal datasets, this system embeds two perception algorithms (RBNN detection, DCNN detection) and one localization algorithm (lidar-based localization) to provide real-time advanced information such as object detection and localization in challenging environments (lack of GPS). In order to train and evaluate the perception algorithms, a dataset is built from 10,000 annotated lidar frames from various drives carried out under different weather conditions and different traffic and population densities. The performances of the three algorithms are competitive with the state-of-the-art. Moreover, the processing time of these algorithms are compatible with real-time autonomous driving applications. By providing directly accurate advanced outputs, this system might significantly facilitate the work of researchers and engineers with respect to planning and control modules. Thus, this study intends to contribute to democratizing access to autonomous vehicle research platforms.

The paper presents an experimental study conducted to evaluate the feasibility of using accelerometers as an indirect means to estimate water depths on road surfaces. It makes use of the vibration of the vehicle’s wheel arch due to water droplets projected by a tire rolling on a wet road surface. A trailer equipped with a wheel and towed by a van was used. The test setups to spread water on the road surface and before the test wheel, measure the water depth and visualize the water spray are described. The test program, conducted on a test track closed to the traffic, includes three surfaces and two speeds. Visualization of water flows by means of high-speed cameras makes it possible to choose a suitable location for the accelerometers. It turns out that signals provided by the accelerometers are affected by the trailer’s movement; a filtering method has been successfully developed to remove noises. Results show a tight relationship between the mean amplitude of accelerometric signals and actual water depths. Discussions are made in terms of effects of the vehicle speed and the road surface texture. Perspectives for using the developed system to improve passenger safety under autonomous driving conditions are presented.