Technical Papers
Sep 12, 2024

Exploring the Role of Sponsoring Agencies in Shaping the MUTCD Using Supervised and Unsupervised Text Mining

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 150, Issue 11

Abstract

Preparing the Manual on Uniform Traffic Control Devices (MUTCD) involves gathering inputs from various public and the National Committee on Uniform Traffic Control Devices (NCUTCD) sponsoring agencies. The NCUTCD assists in developing standards, guidelines, and warrants for traffic control devices and practices employed to regulate, warn, and guide traffic flow on roadways. This organization advises the Federal Highway Administration (FHWA) and other relevant agencies on suggested updates and interpretations to the MUTCD and other nationally recognized standards. Examples of such sponsoring agencies include AASHTO, ASCE, Institute of Transportation Engineers (ITE), American Highway Users Alliance (AHUA), National Association of City Transportation Officials (NACTO), National Association of County Engineers (NACE), International Bridge, Tunnel and Turnpike Association (IBTTA), and American Traffic Safety Services Association (ATSSA). Other national and regional agencies have also been invited to provide feedback on the draft manual. Although all comments are considered valuable, those from federal agencies may hold more weight due to their expertise in specific subject matters. This study utilized text-mining techniques to analyze the comments from the sponsoring agencies, aiming to identify commonalities and distinct features in their feedback. The main question addressed was whether each agency effectively represented its interests and if there were shared interests among them. The study also explored the suggestions, questions, and recommendations raised by each agency. The findings revealed that some concerns were shared among agencies, although in most cases, they represented individual interests. Specifically, some agencies shared a common interest in speed limits, whereas others had similar topics concerning signs and markings. Other shared interests are bike lanes, 85th percentile speed, and pedestrian- and bus lane–related topics. This study’s insights into the interests and concerns of various MUTCD sponsoring agencies can aid in creating more effective, engaging, collaborative, and well-rounded technical documents. As a limitation, this study only used the current MUTCD revision comments, and hence the results reflect only recent concerns from the agencies.

Practical Applications

The Federal Highway Administration collects comments from both the general public and NCUTCD sponsoring agencies for modifying the MUTCD. This study used the comments from the NCUTCD sponsoring agencies submitted by May 2021 and conducted supervised and unsupervised text mining analysis to understand any available patterns, differences, or commonalities in the agencies’ concerns in shaping the MUTCD. The findings indicate the presence of various shared interests among the agencies and some specific features that were specific to the agencies. In addition, it was observed that the majority of the agencies have a great concern for the safety and well-being of society by showing a common interest in safety influencing factors such as speed, road signs, and the definition and use of the 85th percentile speed. This understanding can foster greater collaboration among the agencies, leading to more well-rounded and comprehensive guidelines.

Get full access to this article

View all available purchase options and get full access to this article.

Data Availability Statement

Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.

References

AASHTO. 2023. “American association of state highway and transportation officials.” Accessed June 10, 2023. https://www.transportation.org/home/organization/.
AHUA (American Highway Users Alliance). 2022. “American highway users alliance.” Accessed March 21, 2022. https://www.highways.org/.
Alduayj, S. S., and K. Rajpoot. 2018. “Predicting employee attrition using machine learning.” In Proc., 2018 13th Int. Conf. on Innovations in Information Technology, IIT 2018, 93–98. New York: IEEE. https://doi.org/10.1109/INNOVATIONS.2018.8605976.
Arteaga, C., A. Paz, and J. W. Park. 2020. “Injury severity on traffic crashes: A text mining with an interpretable machine-learning approach.” Saf. Sci. 132 (Dec): 104988. https://doi.org/10.1016/j.ssci.2020.104988.
ASCE. 2022. “American Society of Civil Engineers.” Accessed April 13, 2022. https://www.asce.org/.
ATSSA (American Traffic Safety Services Association). 2021a. “ATTSA submits 120 comments for feedback to proposed MUTCD.” Accessed August 27, 2021. https://atssadev.atssa.com/Technical-Services/Temporary-Traffic-Control/atssa-submits-120-comments-for-feedback-to-proposed-mutcd.
ATSSA (American Traffic Safety Services Association). 2021b. “ATTSA submits 120 comments for feedback to proposed MUTCD.” Accessed February 20, 2023. https://atssadev.atssa.com/.
Benoit, K., K. Watanabe, H. Wang, P. Nulty, A. Obeng, S. Müller, and A. Matsuo. 2018. “Quanteda: An R package for the quantitative analysis of textual data.” J. Open Source Software 3 (30): 774. https://doi.org/10.21105/joss.00774.
Broyhill, T., C. Tan Esse, and L. Ward. 2002. “Innovative traffic control devices—The rulemaking process and public comments (Part II).” ITE J. 72 (2): 24–26.
Dobbin, K., and R. Simon. 2011. “Optimally splitting cases for training and testing high dimensional classifiers.” BMC Med. Genomics 4 (Apr): 1–8. https://doi.org/10.1186/1755-8794-4-31.
FHWA (Federal Highway Administration). 2009. Manual on uniform traffic control devices (MUTCD). Washington, DC: FHWA.
Hawkins, G. 2015. “The MUTCD turns 80: Time for a makeover?” Inst. Transp. Eng. J. 85 (11): 14–16.
Humphrey, A., W. Kuberski, J. Bialek, N. Perrakis, W. Cools, N. Nuyttens, H. Elakhrass, and P. A. C. Cunha. 2022. “Machine-learning classification of astronomical sources: Estimating F1-score in the absence of ground truth.” Mon. Not. R. Astron. Soc. Lett. 517 (1): L116–L120. https://doi.org/10.1093/mnrasl/slac120.
Hunter, S. 2014. “A novel method of network text analysis.” Open J. Mod. Ling. 4 (02): 350–366. https://doi.org/10.4236/ojml.2014.42028.
IBTTA (International Bridge, Tunnel and Turnpike Association). 2022. “International Bridge, Tunnel & Turnpike Association.” Accessed June 1, 2022. https://www.ibtta.org/about-us.
ITE (Institute of Transportation Engineers). 2022. “Institute of Transportation Engineers.” Accessed June 1, 2022. https://www.ite.org/about-ite/about-ite/.
Jewell, S. 2017. Future of the MUTCD. West Lafayette, IN: Purdue Univ.
Joachims, T. 1998. “Text categorization with support vector machines: Learning with many relevant features.” In Proc., European Conf. on Machine Learning, 137–142. Berlin: Springer. https://doi.org/10.1007/bfb0026683.
Kutela, B., C. Kadeha, R. T. Magehema, R. E. Avelar, and P. Alluri. 2023. “Leveraging text mining approach to explore research roadmap and future direction of wrong-way driving crash studies.” Data Inf. Manage. 8 (1): 100044. https://doi.org/10.1016/j.dim.2023.100044.
Kutela, B., N. Novat, and N. Langa. 2021. “Exploring geographical distribution of transportation research themes related to COVID-19 using text network approach.” Sustainable Cities Soc. 67 (Apr): 102729. https://doi.org/10.1016/j.scs.2021.102729.
Muraina, I. 2022. “Ideal dataset splitting ratios in machine learning algorithms: General concerns for data scientists and data analysts.” In Proc., 7th Int. Mardin Artuklu Scientific Research Conf. Ankara, Turkey: Institute of Economic Development and Social Research.
NACE (National Association of County Engineers). 2023. “National Association of County Engineers.” Accessed April 5, 2024. https://www.countyengineers.org/.
NACTO (National Association of City Transportation Officials). 2023. “National Association of City Transportation Officials.” Accessed June 1, 2022. https://nacto.org/.
NCUTCD (National Committee on Uniform Traffic Control Devices). 2022. “Public and professional awareness of the principles of safe traffic control devices and practices.” Accessed May 1, 2022. https://ncutcd.org/.
Paniati, J. F. 2021. “Setting a new course for the MUTCD.” J. Inst. Transp. Eng. 91 (7): 6.
Paranyushkin, D. 2012. Visualization of text’s polysingularity using network analysis. Berlin: Nodus Labs.
Pranckevičius, T., and V. Marcinkevičius. 2017. “Comparison of naïve Bayes, random forest, decision tree, support vector machines, and logistic regression classifiers for text reviews classification.” Baltic J. Modern Comput. 5 (2): 221–232. https://doi.org/10.22364/bjmc.2017.5.2.05.
Santelli, F., G. Ragozini, and M. Musella. 2020. “What volunteers do? A textual analysis of voluntary activities in the Italian context.” In Studies in classification, data analysis, and knowledge organization, edited by D. F. Iezzi, D. Mayaffre, and M. Misuraca, 265–276. Cham, Switzerland: Springer Nature. https://doi.org/10.1007/978-3-030-52680-1_21.
Sokolova, M., N. Japkowicz, and S. Szpakowicz. 2006. “Beyond accuracy, F-score and ROC: A family of discriminant measures for performance evaluation.” In Proc., Australasian Joint Conf. on Artificial Intelligence, 1015–1021. Berlin: Springer.
Wieser, M., K. Schöffmann, D. Stefanics, A. Bollin, and S. Pasterk. 2023. “Investigating the role of ChatGPT in supporting text-based programming education for students and teachers.” In Proc., Int. Conf. on Informatics in Schools: Situation, Evolution, and Perspectives. Cham, Switzerland: Springer Nature. https://doi.org/10.1007/978-3-031-44900-0_4.

Information & Authors

Information

Published In

Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 150Issue 11November 2024

History

Received: Nov 13, 2023
Accepted: May 2, 2024
Published online: Sep 12, 2024
Published in print: Nov 1, 2024
Discussion open until: Feb 12, 2025

Permissions

Request permissions for this article.

ASCE Technical Topics:

Authors

Affiliations

Assistant Research Scientist, Texas A&M Transportation Institute, 701 N Post Oak Ln., # 430, Houston, TX 77024. ORCID: https://orcid.org/0000-0002-5450-1623. Email: [email protected]
Graduate Research Assistant, Florida International Univ., 10555 W Flagler St., Miami, FL 33174 (corresponding author). ORCID: https://orcid.org/0000-0003-2697-4199. Email: [email protected]
Subasish Das, Ph.D. [email protected]
Assistant Professor, Texas State Univ., 601 University Dr., San Marcos, TX 78666. Email: [email protected]
Lucy Kapaya [email protected]
Undergraduate Student, Univ. of Dodoma, Kikuyu Ave., Dodoma 41218, Tanzania. Email: [email protected]
Elizabeth Tarimo [email protected]
Undergraduate Student, Dept. of Statistics, Eastern Africa Statistical Training Centre, Dar es Salaam 35103, Tanzania. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share