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A vehicle-to-infrastructure based dynamic merge assistance method for mixed traffic with manual vehicle, connected vehicle, and automated vehicles in highway merging section

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TitleInfo
Title
A vehicle-to-infrastructure based dynamic merge assistance method for mixed traffic with manual vehicle, connected vehicle, and automated vehicles in highway merging section
Name (type = personal)
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Jiang
NamePart (type = given)
Xiaowen
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Xiaowen Jiang
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author
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Jin
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Peter Jing
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Peter Jing Jin
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Advisory Committee
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chair
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WANG
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HAO
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HAO WANG
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Advisory Committee
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internal member
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NamePart (type = family)
Liu
NamePart (type = given)
Xiang
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Xiang Liu
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Advisory Committee
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internal member
Name (type = personal)
NamePart (type = family)
Lee
NamePart (type = given)
Joyoung
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Joyoung Lee
Affiliation
Advisory Committee
Role
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outside member
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Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
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School of Graduate Studies
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school
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Text
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theses
OriginInfo
DateCreated (encoding = w3cdtf); (keyDate = yes); (qualifier = exact)
2019
DateOther (qualifier = exact); (type = degree)
2019-05
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2019
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
Merging activities on the highway can cause significant recurrent and non-recurrent bottleneck congestion and is a severe issue in traffic operations. The efficient enhancement of highway merging activities has been considered as a major task in highway management research and practice. Some macroscopic active traffic management (ATM) methods have been proposed to mitigate bottleneck congestion. In recent years, microscopic dynamic merging assistance (DMA) methods have been proposed as efficient methods to improve the mobility and safety in merging maneuver. These proposed methods have been serving their roles as effective merge control methods for decades. Despite some positive outcomes of these existing methods in the improvement of the highway merge traffic, there are still some gaps for new merge assistance methods to catch. Recent developments and deployments of Automated Vehicle (AV) technologies and Connected Vehicle (CV) technologies such as Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication provide new opportunities for developing more efficient merge assistance methods. This leads the new wave of Connected-Automated-Vehicle (CAV) based DMA methods.
This dissertation proposes a microscopic CAV V2I-based Dynamic Merge Assistance (DMA) method for mixed types of vehicles including manual vehicle (MV), manually controlled connected vehicle (CV) and connected automated vehicle (CAV). The research starts from a comprehensive review of existing merge assistance methods and the evolution of microscopic DMA mechanisms and algorithms. Then integrated partial coordination merging control algorithm based on a pairing between mainline gaps and on-ramp merging vehicles (vehicle-gap pair) is proposed. The vehicle-gap pair is determined by a prediction of their merging potential, and the merging potential is predicted according to their instantaneous virtual trajectories (IVT) which are generated from the instantaneous lane speed profiles (ISP) of both mainline and onramp which consists of all detected vehicles’ location and speed at each time frame. The pairing scenario varies with different combinations of vehicle types (i.e., MV, CV, CAV) involved in a merging maneuver. These scenarios involve vehicles with different features in terms of control, sensing, and communication. Thus, a set of 4-level pairing criteria is proposed to fit the DMA method in the universal traffic environment with mixed vehicle types. The pairing process is then followed by a coordination car-following control specifically designed for different vehicle types. The coordination car-following control maintains the mainline gaps for the paired on-ramp vehicle and guarantees the on-ramp vehicle can catch up with the paired gap safely and smoothly. Different control mechanisms are proposed based on the observability, controllability, and the availability of communication in different vehicle combinations which is aligned to the 4-level pairing scenarios.
A VISSIM simulation is built based on the traffic flow data collected from the I-35 corridor in Austin TX with multiple merging and weaving sections. The proposed DMA model is implemented through a VISSIM Application Programming Interface (API) named external drivers’ model (ETM). The safety performance of merging is evaluated by time-to-collision (TTC) and critical gap size (gap between mainline following vehicle and lane-changing on-ramp vehicle). The mobility performance is evaluated by average travel time and speed contour map in the whole simulation area including on-ramp, mainline merging area and mainline upstream. The proposed method is found to have a promising performance in both mobility and safety impact, especially on the on-ramp traffic during peak hours.
Subject (authority = local)
Topic
Connected and Automated Vehicle
Subject (authority = RUETD)
Topic
Civil and Environmental Engineering
Subject (authority = LCSH)
Topic
Traffic engineering
Subject (authority = LCSH)
Topic
Traffic flow
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Title
Rutgers University Electronic Theses and Dissertations
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ETD_9849
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application/pdf
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text/xml
Extent
1 online resource (xiii, 97 pages) : illustrations
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
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Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
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NjNbRU
Identifier (type = doi)
doi:10.7282/t3-8kmk-z165
Genre (authority = ExL-Esploro)
ETD doctoral
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The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Jiang
GivenName
Xiaowen
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Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2019-04-12 14:41:35
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Name
Xiaowen Jiang
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Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
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Author Agreement License
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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Copyright protected
Availability
Status
Open
Reason
Permission or license
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