Characterization of road surfaces using three near-infrared diode lasers

Abstract

Rapid road network expansion has heightened the importance of surface condition information for traffic accident prevention and route optimization. This article introduces a laser diode-based sensor that identifies seven surface conditions and accurately measure ice, water, and snow film thicknesses on roads. An optical module was developed to detect weak optical signals based on the characteristic absorption spectrum of the target surface. The module used three laser diodes (1310, 1440, and 1550 nm wavelengths) as light sources. Additionally, a road classification algorithm that is adaptable to foggy weather was developed using a multi-wavelength processing protocol. The sensor was subjected to numerous calibration and performance verification experiments. During thick foggy measurements, the processed spectra displayed a maximum variation of 2.372% across a 600 to 25,000 m visibility range with a relative standard deviation of only 0.328%. This demonstrated effective weakening of the effects of visibility variations. During winter field testing, the sensor classified road conditions effectively and accurately measured ice, snow, and water film thicknesses, with a correlation coefficient of 0.97444. The accuracy of the measurements was less than 0.5 mm. The sensor’s effectiveness for long-term field-based road testing has been verified.

Keywords:

• Diode laser
• infrared spectrometry
• multi-wavelength processing
• optical sensor
• road surface condition

Acknowledgment

We thank David MacDonald, MSc, from Liwen Bianji (Edanz) (www.liwenbianji.cn/) for editing the English text of a draft of this manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Key Research and Development Projects in Anhui Province, China under Grant 1908085MD114.