Details:

Creators:
Hanley, Paul ; Sikka, Nikhil ; Yu, Hai ; Ma, Suyun
Hanley, Paul ; Sikka, Nikhil ; Yu, Hai ; Ma, Suyun Less -
Corporate Creators:
University of Iowa. Public Policy Center
Corporate Contributors:
United States. Dept. of Transportation. Research and Innovative Technology Administration
Subject/TRT Terms:
[+]
Automatic Data Collection Systems Decision Making Drivers 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.


Format:
PDF
Collection(s):
US Transportation Collection University Transportation Centers
Main Document Checksum:
[+]
urn:sha256:7b6ce1d5f4038cb2cadbb8be5357fe1c640d691e0e65c58b974f46cfa4087a12
Download URL:
https://rosap.ntl.bts.gov/view/dot/23389/dot_23389_DS1.pdf
File Type:

Supporting Files

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