Using ADAS to Future-Proof Roads—Comparison of Fog Line Detection from an In-Vehicle Camera and Mobile Retroreflectometer
| Autor: | Kelly Pitera, Ane Dalsnes Storsæter, Edward McCormack |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Lane departure warning system
Computer science Real-time computing 0211 other engineering and technologies ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology lcsh:Chemical technology Biochemistry Article Analytical Chemistry road maintenance 021105 building & construction 0502 economics and business In vehicle Future proof lcsh:TP1-1185 Electrical and Electronic Engineering retroreflectometer Instrumentation road infrastructure road asset management 050210 logistics & transportation 05 social sciences Atomic and Molecular Physics and Optics ADAS lane detection Line (geometry) automated driving |
| Zdroj: | Sensors, Vol 21, Iss 1737, p 1737 (2021) Sensors Sensors (Basel, Switzerland) Volume 21 Issue 5 |
| ISSN: | 1424-8220 |
| Popis: | Pavement markings are used to convey positioning information to both humans and automated driving systems. As automated driving is increasingly being adopted to support safety, it is important to understand how successfully sensor systems can interpret these markings. In this effort, an in-vehicle lane departure warning system was compared to data collected simultaneously from an externally mounted mobile retroreflectometer. The test, performed over 200 km of driving on three different routes in variable lighting conditions and road classes found that, depending on conditions, the retroreflectometer could predict whether the car’s lane departure systems would detect markings in 92% to 98% of cases. The test demonstrated that automated driving systems can be used to monitor the state of pavement markings and can provide input on how to design and maintain road infrastructure to support automated driving features. Since data about the condition of lane marking from multiple lane departure warning systems (crowd-sourced data) can provide input into the pavement marking management systems operated by many road owners, these findings also indicate that these automated driving sensors have an important role in enhancing the maintenance of pavement markings. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). |
| Databáze: | OpenAIRE |
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