Chapter
Mar 18, 2024

Measuring Social Equity in Pavement Conditions Using Big Data

Publication: Construction Research Congress 2024

ABSTRACT

Pavement condition significantly impacts a region’s socioeconomic status by affecting safety, economic effectiveness, and environmental aspects. The condition of the pavement directly impacts crash rates, fuel consumption, and pollution levels, necessitating equitable access for all, regardless of socioeconomic characteristics. We measured social equity in pavement condition by comparing pavement condition, represented by International Roughness Index (IRI), with community demographics. Analyzing more than 8 million records from Highway Performance Monitoring System (HPMS) data across multiple years, we established links between pavement quality and socioeconomic factors. We found that areas with higher proportion of African American, linguistically isolated population, and disadvantaged neighborhoods—in terms of housing/transportation—have lower access to high-quality pavement regardless of controlling factors such as region, road type, and traffic. Furthermore, a predictive classifier confirmed the influence of sociodemographic factors on pavement quality classification (good, acceptable, poor), emphasizing the need for social equity integration in pavement maintenance planning.

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REFERENCES

Bills, T. S. (2022). “Advancing the practice of regional transportation equity analysis: a San Francisco Bay area case study.” Transportation, 1–26.
Behbahani, H., Nazari, S., Kang, M. J., and Litman, T. (2019). “A conceptual framework to formulate transportation network design problem considering social equity criteria.” Transportation research part A: policy and practice, 125, 171–183.
Cavallaro, F., Bruzzone, F., and Nocera, S. (2020). “Spatial and social equity implications for High-Speed Railway lines in Northern Italy.” Transportation Research Part A: Policy and Practice, 135, 327–340.
Coleman, N., Esmalian, A., and Mostafavi, A. (2020). “Equitable resilience in infrastructure systems: empirical assessment of disparities in hardship experiences of vulnerable populations during service disruptions.” Natural Hazards Review, 21(4), 04020034.
Corley-Lay, J. (2014). “Pavement performance measures: How states see good, fair, and poor.” Transportation Research Record, 2431(1), 1–5.
Delbosc, A., and Currie, G. (2011). “Using Lorenz curves to assess public transport equity.” Journal of Transport Geography, 19(6), 1252–1259.
Erfani, A., and Cui, Q. (2021). “Natural Language Processing Application in Construction Domain: An Integrative Review and Algorithms Comparison.” Computing in Civil Engineering.
Erfani, A., and Cui, Q. (2022). “Predictive risk modeling for major transportation projects using historical data.” Automation in Construction, 139, 104301.
Erfani, A., Hickey, P. J., and Cui, Q. (2023). “Likeability versus Competence Dilemma: Text Mining Approach Using LinkedIn Data.” Journal of Management in Engineering, 39(3), 04023013.
Erfani, A., Zhang, K., and Cui, Q. (2021). “TAB bid irregularity: Data-driven model and its application.” Journal of Management in Engineering, 37(5), 04021055.
FHWA (Federal Highway Administration). (2014). “Status of the Nation’s Highways, Bridges, and Transit: 2004 Condition and Performance.” <https://www.fhwa.dot.gov/policy/2004cpr/chap3b.cfm>.
France-Mensah, J., Kothari, C., O’Brien, W. J., and Jiao, J. (2019). “Integrating social equity in highway maintenance and rehabilitation programming: A quantitative approach.” Sustainable Cities and Society, 48, 101526.
Gillespie, J. S., and McGhee, K. K. (2007). “Get in, get out, come back! What the relationship between pavement roughness and fuel consumption means for the length of the resurfacing cycle.” Transportation Research Record, 1990(1), 32–39.
Hickey, P. J., Erfani, A., and Cui, Q. (2022). “Use of LinkedIn Data and Machine Learning to Analyze Gender Differences in Construction Career Paths.” Journal of Management in Engineering, 38(6), 04022060.
InfoPave. Federal Highway Administration (website). (2020). Accessed January 7, 2021. https://infopave.fhwa.dot.gov/CLIMATETOOL.
Januschowski, T., Gasthaus, J., and Wang, Y. (2019). “Open-Source Forecasting Tools in Python. Foresight” The International Journal of Applied Forecasting, 55.
Khan, A., Waris, M., Panigrahi, S., Sajid, M. R., and Rana, F. (2021). “Improving the performance of public sector infrastructure projects: Role of project governance and stakeholder management.” Journal of Management in Engineering, 37(2), 04020112.
Kothari, C., France-Mensah, J., and O’Brien, W. J. (2022). “Developing a Sustainable Pavement Management Plan: Economics, Environment, and Social Equity.” Journal of Infrastructure Systems, 28(2), 04022009.
Lee, J., and Madanat, S. (2017). “Optimal policies for greenhouse gas emission minimization under multiple agency budget constraints in pavement management.” Transportation Research Part D: Transport and Environment, 55, 39–50.
Lee, J., Nam, B., and Abdel-Aty, M. (2015). “Effects of pavement surface conditions on traffic crash severity.” Journal of Transportation Engineering, 141(10), 04015020.
Martens, K., Bastiaanssen, J., and Lucas, K. (2019). “Measuring transport equity: Key components, framings and metrics.” In Measuring transport equity (pp. 13–36). Elsevier.
Mohammadi, P., Rashidi, A., Malekzadeh, M., and Tiwari, S. (2023). “Evaluating various machine learning algorithms for automated inspection of culverts.” Engineering Analysis with Boundary Elements, 148, 366–375.
Nahmias-Biran, B. H., Sharaby, N., and Shiftan, Y. (2014). “Equity aspects in transportation projects: Case study of transit fare change in Haifa.” International Journal of Sustainable Transportation, 8(1), 69–83.
Pritchard, J. P., Zanchetta, A., and Martens, K. (2022). “A new index to assess the situation of subgroups, with an application to public transport disadvantage in US metropolitan areas.” Transportation research part A: policy and practice, 166, 86–100.
Rawls, J. (2009). A theory of justice: Revised edition. Harvard university press.
Roy, A., and Law, M. (2022). “Examining spatial disparities in electric vehicle charging station placements using machine learning.” Sustainable Cities and Society, 83, 103978.
Surahyo, M., and El-Diraby, T. E. (2009). “Schema for interoperable representation of environmental and social costs in highway construction.” Journal of Construction Engineering and Management, 135(4), 254–266.
Thomopoulos, N., Grant-Muller, S., and Tight, M. R. (2009). “Incorporating equity considerations in transport infrastructure evaluation: Current practice and a proposed methodology.” Evaluation and program planning, 32(4), 351–359.
Timilsina, G. R., Hochman, G., and Song, Z. (2020). “Infrastructure, economic growth, and poverty: A review.”.
Titus-Glover, L. (2021). “Reassessment of climate zones for high-level pavement analysis using machine learning algorithms and NASA MERRA-2 data.” Advanced Engineering Informatics, 50, 101435.
US DOT. (2021). “Summary of Public Comments Received on the Department of Transportation’s Request for Information on Transportation Equity Data,” <https://www.transportation.gov/sites/dot.gov/files/2021-11/>.
Yan, H., Yang, N., Peng, Y., and Ren, Y. (2020). “Data mining in the construction industry: Present status, opportunities, and future trends.” Automation in Construction, 119, 103331.
Zhang, C., and Ma, Y. (2012). Ensemble machine learning: Methods and applications. Boston, MA: Springer Science and Business Media.

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Construction Research Congress 2024
Pages: 23 - 32

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Published online: Mar 18, 2024

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Abdolmajid Erfani [email protected]
1Research Scientist, Build America Center and Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park. Email: [email protected]
Jina Mahmoudi [email protected]
2Research Scientist, Build America Center and Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park. Email: [email protected]
Qingbin Cui [email protected]
3Professor and Director, Build America Center and Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park. Email: [email protected]

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