Date of Award:
5-2020
Document Type:
Dissertation
Degree Name:
Doctor of Philosophy (PhD)
Department:
Civil and Environmental Engineering
Committee Chair(s)
Ziqi Song
Committee
Ziqi Song
Committee
Patrick Singleton
Committee
Michelle Mekker
Committee
Haitao Wang
Committee
Marvin W. Halling
Abstract
Compared with conventional human-driven vehicles (HVs), AVs have various potential benefits, such as increasing road capacity and lowering vehicular fuel consumption and emissions. Road infrastructure management, adaptation, and upgrade plays a key role in promoting the adoption and benefit realization of AVs. This dissertation investigated several strategic infrastructure planning problems for AVs. First, it studied the potential impact of AVs on the congestion patterns of transportation networks. Second, it investigated the strategic planning problem for a new form of managed lanes for autonomous vehicles, designated as autonomous-vehicle/toll lanes, which are freely accessible to autonomous vehicles while allowing human-driven vehicles to utilize the lanes by paying a toll. This new type of managed lanes has the potential of increasing traffic capacity and fully utilizing the traffic capacity by selling redundant road capacity to HVs. Last, this dissertation studied the strategic infrastructure planning problem for an infrastructure-enabled autonomous driving system. The system combines vehicles and infrastructure in the realization of autonomous driving. Equipped with roadside sensor and control systems, a regular road can be upgraded into an automated road providing autonomous driving service to vehicles. Vehicles only need to carry minimum required on-board devices to enable their autonomous driving on an automated road. The costs of vehicles can thus be significantly reduced.
Checksum
2db4e531549fe3132e43228da4c02843
Recommended Citation
Liu, Zhaocai, "Strategic Infrastructure Planning for Autonomous Vehicles" (2020). All Graduate Theses and Dissertations, Spring 1920 to Summer 2023. 7734.
https://digitalcommons.usu.edu/etd/7734
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