Advanced decision modeling for real time variable tolling : development and testing of a data collection platform.

Details

• Creators:
  Hanley, Paul ; Sikka, Nikhil ; Yu, Hai ; Ma, Suyun
• Corporate Creators:
  University of Iowa. Public Policy Center
• Corporate Contributors:
  United States. Dept. of Transportation. Research and Innovative Technology Administration
• Subject/TRT Terms:
  • Drivers
  • Decision making
  • Automatic data collection systems
  • Mathematical models
  • Real time information
  • Smartphones
  • Travel behavior
  • Variable tolls
• Publication/ Report Number:
  25-1121-0001-478
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Corporate Publisher:
  Mid-America Transportation Center
• NTL Classification:
  NTL-HIGHWAY/ROAD TRANSPORTATION-HIGHWAY/ROAD TRANSPORTATION ; NTL-PLANNING AND POLICY-PLANNING AND POLICY
• Abstract:
  Our current ability to forecast demand on tolled facilities has not kept pace with advances in decision sciences and ; technological innovation. The current forecasting methods suffer from lack of descriptive power of actual behavior because ; of the simplifications used in current economic decision models. These simplifications are in part due to the historical ; limitations on data collection. Today, we are seeing advances in the data collection technology that captures naturalistic ; behavior and this study is seeking to develop and test such technology. This will be the first phase of a naturalistic driving ; study on the topic of variable road tolling and decision making. ; This investigation extends the state of knowledge of decision modeling under risk and ambiguity by developing a ; mobile data collection platform for the capturing of naturalistic choice outcomes, associated environmental states, decision ; makers’ self-articulated perceptions of risk and assessments of ambiguity, and socio-economic attributes. This ; software/hardware development is the first step in advancing our ability to forecast future revenue sources in ; transportation. The data collection platform will be used in an extending study and will allow the study team to obtain ; insights for developing, testing and implementing new behavioral models that explicitly describe how we use imprecise ; information—in this case, ambiguous information signaled by variable toll lane charges—that are superior to those ; obtained to date. ; To support the empirical observations of driver choice of diverting to HOT or non-HOT lanes in real-time, this ; study documents the development and testing of an in-vehicle perception acquisition device. The device is based on smartphone ; technology and its software is designed using the latest IOS release. Drivers will be able to upload the software ; application onto their existing smartphone or tablet. The widespread acceptance and use of smartphones and tablets allows ; the collection and transmission of decision data collected in real-time without installing or altering the drivers’ vehicles in ; any manner. This both increases the convenience—and perhaps the use of the application—and reduces the cost of data ; collection.
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• Format:
  PDF
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/23389/dot_23389_DS1.pdf
• File Type:
  [PDF - 1.59 MB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:09d65a0a0c7bcf9db1f7082a452b36dc302ef77b00b8dfa8cfbde88a41254f3233f007fd210c7949ade092c1d50514c3e8d6470ea3b5fe56e7a0cbbd51e53e10