Year: 2024
Type: conference-paper
Abstract: As autonomous vehicles continue to revolutionize transportation, addressing challenges posed by adverse weather conditions, particularly during winter, becomes paramount for ensuring safe and efficient operations. One of the most important aspects of a road safety inspection during adverse weather is when a limited lane width can reduce the capacity of the road and raise the risk of serious accidents involving autonomous vehicles. In this research, a method for improving driving challenges on roads in winter conditions, with a model that segments and estimates the width of the road from the perspectives of Uncrewed aerial vehicles and autonomous vehicles. The proposed approach in this article is needed to empower selfdriving cars with up-to-date and accurate insights, enhancing their adaptability and decision-making capabilities in winter landscapes.
Source: IEEE Smart World Congress (SWC)
Institution: University of Oulu
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Funder: European Commission
OpenAlex ID: W4408794369