Evaluating Mobile LiDAR Intensity Data for Inventorying Durable Tape Pavement Markings

Good visibility of lane markings is important for all road users, particularly autonomous vehicles. In general, nighttime retroreflectivity is one of the most challenging marking visibility characteristics for agencies to monitor and maintain, particularly in cold weather climates where agency snowplows remove retroreflective material during winter operations. Traditional surface-applied paint and glass beads typically only last one season in cold weather climates with routine snowplow activity. Recently, transportation agencies in cold weather climates have begun deploying improved recessed, durable pavement markings that can last several years and have very high retroreflective properties. Several dozen installations may occur in a state in any calendar year, presenting a challenge for states that need to program annual repainting of traditional waterborne paint lines, but not paint over the much more costly durable markings. This study reports on the utilization of mobile mapping LiDAR systems to classify and evaluate pavement markings along a 73-mile section of westbound I-74 in Indiana. LiDAR intensity data can be used to classify pavement markings as either tape or non-tape and then identify areas of tape markings that need maintenance. RGB images collected during LiDAR intensity data collection were used to validate the LiDAR classification. These techniques can be used by agencies to develop accurate pavement marking inventories to ensure that only painted lines (or segments with missing tape) are repainted during annual maintenance. Repeated tests can also track the marking intensity over time, allowing agencies to better understand material lifecycles.

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Publication Details

Journal
Sensors
Published
2024-10-17
DOI
https://doi.org/10.3390/s24206694
Citations
1
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.82

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article

Evaluating Mobile LiDAR Intensity Data for Inventorying Durable Tape Pavement Markings

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1 citations
Sensors
Remote Sensing and LiDAR Applications
0.82
article

Evaluating Mobile LiDAR Intensity Data for Inventorying Durable Tape Pavement Markings

Joan Carles Bruno, Mona Hodaei, Darcy M. Bullock, Ayman Habib, Aser M. Eissa, Zach DeLoach, Gregory L. Brinster
article en
1 citations

Abstract

Good visibility of lane markings is important for all road users, particularly autonomous vehicles. In general, nighttime retroreflectivity is one of the most challenging marking visibility characteristics for agencies to monitor and maintain, particularly in cold weather climates where agency snowplows remove retroreflective material during winter operations. Traditional surface-applied paint and glass beads typically only last one season in cold weather climates with routine snowplow activity. Recently, transportation agencies in cold weather climates have begun deploying improved recessed, durable pavement markings that can last several years and have very high retroreflective properties. Several dozen installations may occur in a state in any calendar year, presenting a challenge for states that need to program annual repainting of traditional waterborne paint lines, but not paint over the much more costly durable markings. This study reports on the utilization of mobile mapping LiDAR systems to classify and evaluate pavement markings along a 73-mile section of westbound I-74 in Indiana. LiDAR intensity data can be used to classify pavement markings as either tape or non-tape and then identify areas of tape markings that need maintenance. RGB images collected during LiDAR intensity data collection were used to validate the LiDAR classification. These techniques can be used by agencies to develop accurate pavement marking inventories to ensure that only painted lines (or segments with missing tape) are repainted during annual maintenance. Repeated tests can also track the marking intensity over time, allowing agencies to better understand material lifecycles.

SensorsVol. 24(20)
Indiana Department of Transportation (US), Purdue University West Lafayette (US)
Indiana Department of Transportation
Climate action
Openalex Percentile: Top 30%
Remote Sensing and LiDAR Applications
0.82
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