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PhD Defense by Wenwen Zhang

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THE SCHOOL OF CITY AND REGIONAL PLANNING


GEORGIA INSTITUTE OF TECHNOLOGY

Under the provisions of the regulations for the degree

DOCTOR OF PHILOSOPHY

on Monday, May 8, 2017
2:00 – 4:00 PM
in the Economic Development Building Room 235

will be held the

DISSERTATION DEFENSE
 
for
 
Wenwen Zhang

"Interactions between Land Use and Transportation in the Era of Shared Autonomous Vehicles: a Discrete Event Simulation Model"
 
The Examiners Are:

Dr. Subhrjit Guhathakurta, Chairperson
Dr. Steven French
Dr. Ram Pendyala, School of Civil Engineering
Dr. Richard Fujimoto, School of Computational Science & Engineering
Dr. Bistra Dilkina, School of Computational Science & Engineering
 
Faculty and students are invited to attend this examination.


Abstract:

We are on the cusp of a new era in mobility given that the enabling technologies for autonomous vehicles (AVs) are almost ready for deployment and testing. This promising technology once married with the sharing economy is set to give birth to a new travel mode – Shared Autonomous Vehicles (SAVs), a taxi service without drivers. Recent studies have explored the feasibility, affordability, environmental benefits, and parking demand of the system in hypothetical grid-base cities. Despite these rapidly proliferating studies, to date, it remains unclear how this affordable and environmentally friendly travel mode will interact with existing land uses in the city. This work attempts to fill in these gaps by answering the following research questions:

·             How much parking will we need and where are they located after the introduction of the SAV system?

·             How will the SAV system influence residential location choices?

·             How will the SAV system alter the spatial agglomeration of firms in the region?

 

This dissertation addresses the above research questions by simulating the operation of SAVs in the Atlanta Metropolitan Area, using the real transportation network with calibrated link-level travel speeds, travel demand origin-destination matrix, and synthesized household profiles. This real world data-driven SAV model is used to determine the spatial distribution of parking demand under different parking price scenarios, including free parking, entrance based parking and time based parking scenarios. The results can provide information to support amendments to existing parking land use policies in the future.

 

The study explores the second question by integrating SAV simulation model with residential location choice models to reveal the shifts in residential location preferences in the era of SAVs. The results can contribute to the formulation of new land development policies to curb urban sprawl after the coming of SAVs. The dissertation addresses the third question by combining SAV simulation model with firm location choice models by industry sector. The new choices are then simulated via agent based relocation choice model. The simulation outcomes add new knowledge to the potential impacts of SAV on commercial and industrial land in the region.

 

Status

  • Workflow Status:Published
  • Created By:Tatianna Richardson
  • Created:03/31/2017
  • Modified By:Tatianna Richardson
  • Modified:03/31/2017

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