Document Type



Doctor of Philosophy (PhD)


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


Connected vehicle, Traveler information system, CV market penetration, Travel time estimation, Volume estimation

Date of Defense



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.






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