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Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data
There are over four million miles of roads in the United States, and the prioritization of locations to perform maintenance activities typically relies on human inspection or semi-automated dedicated vehicles. Pavement markings are used to delineate the boundaries of the lane the vehicle is driving...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473332/ https://www.ncbi.nlm.nih.gov/pubmed/34577218 http://dx.doi.org/10.3390/s21186014 |
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author | Mahlberg, Justin A. Sakhare, Rahul Suryakant Li, Howell Mathew, Jijo K. Bullock, Darcy M. Surnilla, Gopi C. |
author_facet | Mahlberg, Justin A. Sakhare, Rahul Suryakant Li, Howell Mathew, Jijo K. Bullock, Darcy M. Surnilla, Gopi C. |
author_sort | Mahlberg, Justin A. |
collection | PubMed |
description | There are over four million miles of roads in the United States, and the prioritization of locations to perform maintenance activities typically relies on human inspection or semi-automated dedicated vehicles. Pavement markings are used to delineate the boundaries of the lane the vehicle is driving within. These markings are also used by original equipment manufacturers (OEM) for implementing advanced safety features such as lane keep assist (LKA) and eventually autonomous operation. However, pavement markings deteriorate over time due to the fact of weather and wear from tires and snowplow operations. Furthermore, their performance varies depending upon lighting (day/night) as well as surface conditions (wet/dry). This paper presents a case study in Indiana where over 5000 miles of interstate were driven and LKA was used to classify pavement markings. Longitudinal comparisons between 2020 and 2021 showed that the percentage of lanes with both lines detected increased from 80.2% to 92.3%. This information can be used for various applications such as developing or updating standards for pavement marking materials (infrastructure), quantifying performance measures that can be used by automotive OEMs to warn drivers of potential problems with identifying pavement markings, and prioritizing agency pavement marking maintenance activities. |
format | Online Article Text |
id | pubmed-8473332 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-84733322021-09-28 Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data Mahlberg, Justin A. Sakhare, Rahul Suryakant Li, Howell Mathew, Jijo K. Bullock, Darcy M. Surnilla, Gopi C. Sensors (Basel) Article There are over four million miles of roads in the United States, and the prioritization of locations to perform maintenance activities typically relies on human inspection or semi-automated dedicated vehicles. Pavement markings are used to delineate the boundaries of the lane the vehicle is driving within. These markings are also used by original equipment manufacturers (OEM) for implementing advanced safety features such as lane keep assist (LKA) and eventually autonomous operation. However, pavement markings deteriorate over time due to the fact of weather and wear from tires and snowplow operations. Furthermore, their performance varies depending upon lighting (day/night) as well as surface conditions (wet/dry). This paper presents a case study in Indiana where over 5000 miles of interstate were driven and LKA was used to classify pavement markings. Longitudinal comparisons between 2020 and 2021 showed that the percentage of lanes with both lines detected increased from 80.2% to 92.3%. This information can be used for various applications such as developing or updating standards for pavement marking materials (infrastructure), quantifying performance measures that can be used by automotive OEMs to warn drivers of potential problems with identifying pavement markings, and prioritizing agency pavement marking maintenance activities. MDPI 2021-09-08 /pmc/articles/PMC8473332/ /pubmed/34577218 http://dx.doi.org/10.3390/s21186014 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/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/). |
spellingShingle | Article Mahlberg, Justin A. Sakhare, Rahul Suryakant Li, Howell Mathew, Jijo K. Bullock, Darcy M. Surnilla, Gopi C. Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data |
title | Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data |
title_full | Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data |
title_fullStr | Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data |
title_full_unstemmed | Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data |
title_short | Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data |
title_sort | prioritizing roadway pavement marking maintenance using lane keep assist sensor data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473332/ https://www.ncbi.nlm.nih.gov/pubmed/34577218 http://dx.doi.org/10.3390/s21186014 |
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