Developing a Methodology to Identify Non-Normative Key Destinations for Transportation Planning

• Published in: Transportation research record Vol. 2678; no. 1; pp. 749 - 759
• Main Authors: Horiuchi, Julianna, Zimmer, Alissa, Reginald, Monisha, Gartsman, Anna, Brown, Connor, Limprevil, Drefnie, De Jesus Martinez, Carolyn
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.01.2024
• Subjects: planning and analysis; decision-making; transportation equity; data and data science; location-based services; big data; public transportation
• ISSN: 0361-1981; 2169-4052
• DOI: 10.1177/03611981231172509

Medium- to long-range planning processes generally aim to fix deficiencies in the current transportation network by better distributing existing resources or acquiring new resources. This requires some way of defining better service patterns, including identifying priority places to and from which the network will increase connectivity. Typically, identifying these priority places happens through project-specific outreach efforts, sometimes with the support of job density or population data. This paper discusses a process for leveraging confirmatory public outreach and combining it with location-based services data (or other sources of multi-modal travel data, e.g., household travel surveys) to create an iteratively developed and reproducible methodology for identifying key destinations. This method allows an agency to minimize outreach fatigue by only conducting periodic public outreach on the subject, rather than asking the same baseline questions for every individual planning project. Additionally, this method better bolsters equity by moving away from normatively selected destinations (which tend to be traditional job centers with 9-to-5 commuters) and supporting more high-participation outreach efforts in the future. Ultimately, this paper makes the case that the output of outreach in a data-informed planning process should be a replicable methodology, not a static list.