Applications of Accessibility Analysis for Predicting Travel Outcomes Throughout the U.S.

Details

• Creators:
  McCahill, Chris ; Claros, Boris ; Brenneis, Michael ; Hughes, James ; Chitturi, Madhav
• Corporate Creators:
  University of Wisconsin--Madison. State Smart Transportation Initiative ; University of Wisconsin--Madison. Traffic Operations and Safety Laboratory
• Corporate Contributors:
  Center for Transportation, Equity, Decisions & Dollars (CTEDD). University of Texas ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  • Accessibility
  • Decision making
  • Interdisciplinary studies
  • Investments
  • Land use
  • Mathematical models
  • Metrics (Quantitative assessment)
  • Performance measurement
  • Public transit
  • State departments of transportation Travel behavior
• Publication/ Report Number:
  CTEDD 021-01
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report
• Corporate Publisher:
  Center for Transportation, Equity, Decisions and Dollars (CTEDD) (UTC)
• Description:
  Many transportation agencies, planning organizations, and local governments are interested in predicting travel outcomes like vehicle miles traveled (VMT) and transit ridership, yet most lack formal tools for evaluating the effects of individual decisions on travel behavior. However, improved access to data and computing capabilities are enabling more agencies to develop accessibility metrics—describing access to destinations by various modes—which are useful for characterizing the built environment and its potential impacts on travel behavior. This study presents numerous models in different geographic areas that provide strong evidence for the use of accessibility metrics in predicting VMT and transit ridership. A general trend among those models is that accessibility by walking and transit, relative to driving, corresponds with lower vehicle use and higher transit use. Vehicle ownership also plays a critical role. These methods could be applied by practitioners to gauge the potential impacts of transportation investments, parking policies, and other built environment changes on travel outcomes.
• Format:
  PDF
• Funding:
  69A3551747134
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/74125/dot_74125_DS1.pdf
• File Type:
  [PDF - 2.53 MB]
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:af6675180cef837a1a70abe27b0903459656fa9cf3176f34c48be9d5c7cfbed48d2d776a359d61ad758ebff026a0fd14ba578e4786a7974c2459319b19986335