Details:

Creators:
Hu, Mengqi ; Wu, Yao-Jan ; Chen, Yang ; Yang, Shu
Hu, Mengqi ; Wu, Yao-Jan ; Chen, Yang ; Yang, Shu Less -
Corporate Contributors:
Mississippi State University. National Center for Intermodal Transportation for Economic Competitiveness
Subject/TRT Terms:
[+]
Decision Support Systems Intermodal Transportation Real Time Information
Resource Type:
Tech Report
Geographical Coverage:
United States
Corporate Publisher:
Mississippi State University. National Center for Intermodal Transportation for Economic Competitiveness
Abstract:
The transportation system in the United States is disjointed and inefficient as a result of the

different transportation modes in use and their respective industries which have developed

independently. In addition, public transportation is not well used in passenger trips compared to

other developed countries. For example, public transportation accounts for 20% of passenger trips

in large U.S. cities compared to 50% in Europe. Also, development of the passenger intermodal

transportation system has lagged behind development of the freight transportation system.

To improve utilization of intermodal transit and efficiency in the U.S, we developed an

intelligent decision support system for passenger travel decisions using real-time general transit

feed specifications (GTFS) data. In our system, an automatic data collection strategy was created

to collect GTFS and flight data across different platforms, and an “all-in-one” database was

designed to store the data. The database was used to: 1) construct intermodal transit networks using

a “node-link” scheme, and 2) estimate travel time and travel time reliability for links and transit

routes. Using this real-time data, a data-driven travel decision model was developed to determine

the best route based on passenger preferences. Several chance constraints were added in the

decision model to guarantee the reliability of the travel route under uncertainties. Additionally, a

user-friendly interface was developed in Python to allow travelers to plan their trips, and a

geographic information system (GIS), Google Earth, was employed to allow users to visualize the

optimized route options.

The proposed system was validated using real-time GTFS data collected in Tucson, AZ, and

Boston, MA. This validation demonstrated that the system can determine optimal travel routes for

passengers. In addition, three sets of sensitivity analysis experiments were developed to investigate

three model considerations: 1) the effect of chance constraints on path choice, 2) the effect of

confidence levels on path choice, and 3) the difference between weekend and weekday travel

planning. The results suggested that the optimal anticipated travel time increases with an

increasing on-time arrival confidence level, and walking is preferred by passengers instead of

transferring buses during peak hours. As an example, approximately 30% additional time serves

as a reference for allocating travel buffer time to ensure a higher on-time arrival confidence level

for transit trips to the Tucson International Airport.


Format:
PDF
Alternate URL:
http://www.ncitec.msstate.edu/wp-content/uploads/2013-13FR.pdf
Funding:
NCITEC Project No. 2013-13
Collection(s):
US Transportation Collection University Transportation Centers
Main Document Checksum:
[+]
urn:sha256:d544404ae5df9df9d86de64058b96baa4e490ff4dc3ad9fa97a6f6c83f8d4d54
Download URL:
https://rosap.ntl.bts.gov/view/dot/30725/dot_30725_DS1.pdf
File Type:

Supporting Files

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