Abstract

Transportation infrastructure plays a pivotal role in driving economic growth and improving the quality of life. Understanding its equity implications is crucial for informed decision-making on future investment toward equitable outcomes. However, traditional infrastructure planning focused on economic efficiency overlooks broader socioeconomic impacts on diverse regions and social groups. In addition, equity evaluation often relies on methods such as conventional statistical analysis or targeted interviews or surveys, which lacks an AI-enabled capacity to achieve comprehensive equity impact evaluation and prediction.

In this talk, Prof. Chen highlights his research approach by examining the intricate relationship between socioeconomic disparity and infrastructure investment within US cities. By applying deep-learning to the Social Vulnerability Index (SVI) from the Centers for Disease Control and Prevention (CDC) and Census infrastructure expenditure data, he examines the potential implications of the Infrastructure Investment and Jobs Act on socioeconomic equity through shifts in funding allocations. These findings reveal a compelling narrative: a shift from an equality-focused to an equity-driven allocation of infrastructure investment among municipalities engenders an enhancement in socioeconomic performance. He will also showcase other examples of equity impact evaluations utilizing novel methods to assess walkability, and smart city development.

Bio

Zhenhua Chen is an Associate Professor in City and Regional Planning at the Ohio State University. He is currently a visiting scholar at the University of Cambridge, a board member, and the conference chair of the International Association for China Planning. His research interests include infrastructure planning and policy, risk and resilience assessment, and big data analytics.

Dr. Chen has authored and edited five books covering diverse topics, including "Chinese Railways in the Era of High Speed" (Emerald, 2015), "Economic Consequence Analysis of Disasters: The E-CAT Software Tool" (Springer, 2017), and "Big Data for Regional Science" (Routledge, 2017). His extensive publication record includes over 80 articles in esteemed peer-reviewed journals such as Transportation Research Part A, Part D, Transport Reviews, Journal of Transport Geography, Transportation, Transport Policy, Journal of Air Transport Management, Accident Analysis and Prevention, Travel Behavior and Society, Environment Research Letters, Risk Analysis, International Journal of Disaster Risk Reduction, Land Use Policy, Journal of Regional Science, Annals of Regional Science, Papers in Regional Science, Computer Environment and Urban Systems, Economic Systems Research, Applied Geography, Journal of Planning Education and Research, European Planning Studies, Landscape and Urban Planning, Sustainable Cities and Society, Socio-Economic Planning Sciences, Economic Development Quarterly, and Applied Economic Perspectives and Policy.

Recognized for his scholarly contributions, Dr. Chen has received numerous awards, including the Geoffrey Hewings Award, Lumley Research Award, William Miernyk Research Metal, Charles Tiebout Prize, Benjamin Stevens Fellowship, and the Best Dissertation Award from the International Association of Regional Science. His research has been supported by various agencies, including the US Department of Agriculture, Ohio Department of Transportation, Lincoln Institute of Land Economy, Ford Motor Company, and the Risk Institute at OSU.

Advancing Transportation Equity Planning through AI-Enabled Analytics