Skip to content
Research Article Open access CC BY 4.0

Research on the Monocular Ranging Method of the Leading Vehicle in Multi-weather

Yong Tian, Quancai Li, Shuman Guo, Gongrou Fu, Shichang Wang, Junkai Guo

Journal of Scientific Research and Reports · pp. 61–72 · Published 28 Jun 2021

10.9734/jsrr/2021/v27i530390

Abstract

In order to improve the accuracy of the monocular distance measurement of the vehicle in front under sunny, cloudy, rainy, snowy, and foggy weather, an improved pixel-mapping monocular distance measurement method is proposed. This method is based on eight-connected domains to detect the front vehicle, obtain the line pixels of the target vehicle in the image, and fit the image line pixels to the corresponding real longitudinal distance function, and combine the fitted function with the internal and external parameters of the camera. An improved pixel-mapping monocular ranging model is obtained. Set up a test environment under different weather to verify the feasibility of the algorithm. The results show that in the four environments, the detectable distances are within 70m, 60m, 30m, and 40m respectively; the error of the improved pixel-mapping monocular ranging method is reduced by 0.6% on average compared with before the improvement, up to 0.92% ; The improved algorithm ranging errors under the four weathers are 1.8513%, 2.6987%, 4.0137%, and 2.5795% respectively, which achieves the purpose of improving the accuracy of the monocular distance measurement of the vehicle in front under multiple weather conditions.

Multi-weather front vehicle monocular ranging pixel mapping

Cited by 0

No indexed citations yet.

Article metrics

Real usage data collected on this platform.

0

Page views

0

PDF downloads

0

Outbound clicks

0

Citations

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

No views recorded yet.

Traffic sources

Referring site, by host.

No traffic recorded yet.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.