Characterisation and variabilities of aerosols produced by tyres rotating on wet surfaces

Understanding the formation and behaviour of aerosols generated by vehicles traveling on wet surfaces is crucial due to their impact on vehicle soiling, visibility, and autonomous driving. These aerosols can reduce visibility for other drivers, contribute to traffic accidents, and reduce the operational capabilities of sensors for driving assistance systems and future autonomous vehicles. Despite the importance of understanding the physical properties of these aerosols is crucial for testing and validating sensors for environmental perception and recognition, field data on this topic is scarce. The formation and behaviour of these aerosols are complex. A fraction of the trailing droplets and ligaments originates directly from the tyres, while the remainder is generated upon the impact of the particles ejected from the tyres with the vehicle’s surfaces, resulting in either coalescence or further disintegration. Aerodynamic forces also significantly influence the formation of these aerosols. Although experimental studies have investigated the droplet field around rotary atomisers, there is little published information on the droplet size distribution and volume fraction of the aerosols around wet tyres under real-like conditions. This work aimed to characterise the aerosols produced by commercial tyres rotating on wet surfaces. Measurements of droplet size distribution, volume fraction, and contrast degradation were conducted under controlled conditions using optical methods and a test rig. The rig allowed for testing with variations in water depth, rotational velocity, and tyre tread pattern, with measurements taken at various distances from the tyre surface. The results indicate that the mean droplet size (arithmetic) correlates with the tyre's rotational speed but is only weakly influenced by water depth or tyre tread pattern. In contrast, the volume fraction is significantly affected by all of these factors, while contrast degradation is influenced, though weakly, by the tested variables.