An Automated Pavement Marking Retroreflectivity Condition Assessment Method Using Mobile LiDAR and Video Log Images-Reference-Cited by-同舟云学术

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An Automated Pavement Marking Retroreflectivity Condition Assessment Method Using Mobile LiDAR and Video Log Images

Published:2024-06 Issue:2 Volume:30 Page:
ISSN:1076-0342
Container-title:Journal of Infrastructure Systems
language:en
Short-container-title:J. Infrastruct. Syst.

Author:

Hou Qing¹^ORCID,Ai Chengbo²^ORCID,Boudreau Neil³

Affiliation:

1. Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Univ. of Massachusetts, Amherst, MA 01003. ORCID:

2. Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. of Massachusetts, Amherst, MA 01003 (corresponding author). ORCID: .

3. Assistant Administrator for Traffic and Safety, Highway Division, Massachusetts Dept. of Transportation, Boston, MA 02116.

Publisher

American Society of Civil Engineers (ASCE)

Link

https://ascelibrary.org/doi/pdf/10.1061/JITSE4.ISENG-2390

Reference24 articles.

1. Ai, C. 2013. A sensing methodology for an intelligent traffic sign inventory and condition assessment using GPS/GIS, computer vision and mobile LiDAR technologies. Atlanta: Georgia Institute of Technology.

2. An automated sign retroreflectivity condition evaluation methodology using mobile LIDAR and computer vision

3. Pavement Marking Retroreflectivity Estimation and Evaluation using Mobile Lidar Data

4. Statistical Validation of the Effect of Lateral Line Location on Pavement Marking Retroreflectivity Degradation

5. FHWA (Federal Highway Administration). 2009. “Manual on uniform traffic control devices for streets and highways.” Accessed January 16 2023. https://mutcd.fhwa.dot.gov/index.htm.

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