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Comprehensive Arterial Traffic Control for Fully Automated and Connected Vehicles

Azadi, Farzaneh (2022) Comprehensive Arterial Traffic Control for Fully Automated and Connected Vehicles. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Considering the environmental concerns and space limitations of urban infrastructure, construction of new roads and broadening of the existing ones are not accepted practices for managing the ever-growing traffic demand. The current traffic management methods (e.g., traffic signals) in urban networks focus on the resolution of traffic conflicts at urban intersections. However, such an approach sometimes turns intersections into bottlenecks resulting in loss of efficiency, increased risk of the traffic crashes, and negative environmental impacts. Connected and Autonomous Vehicles (CAVs) are seen to revolutionize urban transportation and bring efficiency and safety benefits to the transportation users. However, the full extent of CAV benefits will not be achievable unless the traffic control systems are rethought from the roots.
The goal of this Ph.D. research is to investigate the impact of flexible organization of traffic flows on efficiency and safety of urban networks, in a fully automated and connected transportation environment. This study proposes a robust control concept, called Combined Flexible Lane Assignment and Reservation-Based Intersection Control (CFLARIC) system, which allows vehicles in the traffic stream to utilize, when not endangering the other road users, any part of the paved road surface. The control strategy used in CFLARIC works through discretization of space and time in the entire network, which enables CFLARIC to resolve the conflicts both along the links between intersections and within intersection boundaries. A microsimulation tool called Flexible Arterial Utilization Simulation Modeling (FAUSIM) has been developed in NetLogo to model such flexibility.
The performance of various CFLARIC scenarios is evaluated through a comparison with Fixed-Time Control (FTC) and Full Reservation-based Intersection Control (FRIC) on both hypothetical and filed-like urban arterials, under various traffic demand conditions. Furthermore, delay and surrogate conflict predictive models are developed to examine the performance of a Reservation-based Control strategies in a flexible automated traffic network. Lastly, the flexible traffic lane assignment has been addressed as a network optimization problem, where an optimal lane assignment schema is achieved by using metaheuristic algorithms. Findings show that the CFLARIC brings significant benefits, in terms of efficiency and reduction of vehicular conflicts, for various traffic demands and infrastructure conditions.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Thesis AdvisorStevanovic,
Committee MemberAlavi, Amir
Committee MemberVandenbossche, Julie
Committee MemberVidic,
Committee MemberMagalotti, Mark
Date: 10 June 2022
Date Type: Publication
Defense Date: 21 March 2022
Approval Date: 10 June 2022
Submission Date: 3 April 2022
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 148
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Civil and Environmental Engineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Innovative traffic management, Automated intersection control, Autonomous and connected vehicles, Reservation-based intersection control, Flexible lane-assignment
Date Deposited: 10 Jun 2022 18:34
Last Modified: 10 Jun 2022 18:34


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