6718 / Research on Vehicle Running Performance on Paved Roads Covered with Falling Volcanic Ash

Paper presented at the 11th Asia-Pacific Regional Conference of the ISTVS


Title: Research on Vehicle Running Performance on Paved Roads Covered with Falling Volcanic Ash

Authors: Junya Yamakawa, Ryosuke Eto, Yasuhiro Ichikado, Mitsuhiro Yoshimoto, Tatsuji Nishizawa, Tomohiro Kubo, and Hiroyuki Yamada

Abstract: Japan has many active volcanoes, and a large eruption can cause ash fall over a wide area. The accumulation of volcanic ash on paved roads affects the driving of vehicles. Therefore, we collected data by driving over volcanic ash spread on paved roads with a vehicle equipped with instruments that can measure the force applied to the running tires. Three types of volcanic ash with different grain sizes and thicknesses of 1 cm, 5 cm, and 10 cm were used. Experiments were conducted at constant speeds of 10 to 40 km/h and at rapid acceleration and deceleration. Data were collected not only on flat straight roads but also on curved roads with a radius of 30 m. In addition to the tire's longitudinal and side forces and the normal load, the camber angle, rotational speed, and ground speed were measured. The slip ratio can be obtained from the difference between the tire rotation speed and the ground speed. Further, since the ground speed of the tire is measured in two directions, the longitudinal and lateral directions of the tire, the sideslip angle of the tire can be calculated. From these data, the characteristics of rolling resistance, driving force, and side force on an ash-fall road surface can be obtained. This paper describes the driving roads on which the experiments were conducted and the effects of volcanic ash on driving by processing the tire data obtained. As the thickness of the volcanic ash increases, the rolling resistance increases, but as the driving speed increases, the rolling resistance tends to decrease. The relationship between the sideslip angle and lateral force can be obtained by processing the data for turn, and these effects are investigated using Gaussian process regression, which takes into account several variables such as sideslip angle, camber angle and normal load.

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