Document Type
Dissertation
Degree
Doctor of Philosophy (PhD)
Major/Program
Civil Engineering
First Advisor's Name
Mohammed Hadi
First Advisor's Committee Title
Committee chair
Second Advisor's Name
Albert Gan
Second Advisor's Committee Title
Committee member
Third Advisor's Name
Zhenmin Chen
Third Advisor's Committee Title
Committee member
Fourth Advisor's Name
L. David Shen
Fourth Advisor's Committee Title
Committee member
Fifth Advisor's Name
Xia Jin
Fifth Advisor's Committee Title
Committee member
Sixth Advisor's Name
Yan Xiao
Sixth Advisor's Committee Title
Committee member
Keywords
Connected vehicle, Traveler information system, CV market penetration, Travel time estimation, Volume estimation
Date of Defense
10-4-2017
Abstract
Traveler information systems play a significant role in most travelers’ daily trips. These systems assist travelers in choosing the best routes to reach their destinations and possibly select suitable departure times and modes for their trips. Connected Vehicle (CV) technologies are now in the pilot program stage. Vehicle-to-Infrastructure (V2I) communications will be an important source of data for traffic agencies. If this data is processed properly, then agencies will be able to better determine traffic conditions, allowing them to take proper countermeasures to remedy transportation system problems under different conditions.
This research focuses on developing methods to assess the potential of utilizing CV data to support the traveler information system data collection process. The results from the assessment can be used to establish a timeline indicating when an agency can stop investing, at least partially, in traditional technologies, and instead rely on CV technologies for traveler information system support. This research utilizes real-world vehicle trajectory data collected under the Next Generation Simulation (NGSIM) program and simulation modeling to emulate the use of connected vehicle data to support the traveler information system. NGSIM datasets collected from an arterial segment and a freeway segment are used in this research. Microscopic simulation modeling is also used to generate required trajectory data, allowing further analysis, which is not possible using NGSIM data.
The first step is to predict the market penetration of connected vehicles in future years. This estimated market penetration is then used for the evaluation of the effectiveness of CV-based data for travel time and volume estimation, which are two important inputs for the traveler information system. The travel times are estimated at different market penetrations of CV. The quality of the estimation is assessed by investigating the accuracy and reliability with different CV deployment scenarios. The quality of volume estimates is also assessed using the same data with different future scenarios of CV deployment and partial or no detector data. Such assessment supports the identification of a timeline indicating when CV data can be used to support the traveler information system.
Identifier
FIDC004062
ORCID
https://orcid.org/0000-0002-7852-5945
Recommended Citation
Iqbal, Md Shahadat, "Data Support of Advanced Traveler Information System Considering Connected Vehicle Technology" (2017). FIU Electronic Theses and Dissertations. 3495.
https://digitalcommons.fiu.edu/etd/3495
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