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Supporting route choice via real-time visual traffic information and counterfactual arrival times

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TitleInfo
Title
Supporting route choice via real-time visual traffic information and counterfactual arrival times
Name (type = personal)
NamePart (type = family)
Kwak
NamePart (type = given)
Daehan
NamePart (type = date)
1979-
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Daehan Kwak
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author
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Badri
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Badri Nath
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Advisory Committee
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chair
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Ganapathy
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Vinod
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Vinod Ganapathy
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Advisory Committee
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internal member
Name (type = personal)
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Nguyen
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Thu
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Thu Nguyen
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Advisory Committee
Role
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internal member
Name (type = personal)
NamePart (type = family)
Smaldone
NamePart (type = given)
Stephen
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Stephen Smaldone
Affiliation
Advisory Committee
Role
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outside member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB)
school
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Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (qualifier = exact)
2017
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2017-05
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2017
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
Mobility plays an integral role in modern lives, yet with the ever-expanding number of cars, traffic congestion poses various negative effects, causing vast economic loss, air pollution, and commuter stress. As live traffic information is becoming ubiquitous, route guidance systems are used to inform drivers of route capacities to avoid traffic congestion. Navigation systems compare several different routes and provide the user with options to choose from, from a list of best possible route recommendations. Drivers’ route choice decisions are typically based on the route that minimizes their travel cost (e.g. travel time). However, there are three main limitations for route guidance and information systems. First, as travel time reliability plays an influential role in the driver’s route choice decision-making, the difference in the travel time estimations and/or recommended routes may vary across navigation systems, which can contribute to the uncertainty in the route choice. Second, as the estimated travel time is the dominant deciding factor in route choice, the impact of uncertain, inaccurate, and variable travel time estimations can render it useless, negatively influencing the drivers’ compliance to the information system’s recommended route. Third, as drivers cannot assess and compare their actual route choice to the non-chosen foregone alternatives, they face frequent dilemmas over their route-choice decisions, especially when route alternatives recommended by navigation systems are not consistent with their own previous driving experiences. In this dissertation, our focus is to explore these three limitations. First, we present a comparative analysis on the route recommendations given from four popular online map providers: Google Maps, HERE, MapQuest and Bing Maps. We analyze traffic data collected from all four of the different map providers for 71 days for two cities, each with two origin-destination pairs. Statistical analysis show that the estimated travel times on identical routes are significantly different among the map providers. This in itself has the potential to create uncertainty in route choices and travel time variability, in addition to a decrease in the credibility and compliance with the map provider’s route choice. Second, to complement the deciding factors (e.g., Estimated Time of Arrival (ETA)) in route decisions, we propose a system called Social Vehicle Navigation. This system incorporates a secondary level of detail into the vehicle navigation system by providing other semantically rich information that drivers can share with one another. This user‐shared visual traffic information assists in the decision‐making process and also improves the efficacy in route determinations. Third, we introduce a rationale for counterfactual thinking in route choice, where drivers receive feedback information about the actual travel times on forgone alternatives (i.e. non-chosen routes), so that at the end of the day, drivers have the ability to exercise reinforced learning and self-assessments of their route choices. We propose DoppelDriver, a system that offers a direct, actual travel time comparison among chosen and non-chosen routes, which determines the actual travel times from probe participatory vehicles on the non-chosen routes. The main conclusion of this dissertation is that existing navigation systems have limitations and can potentially introduce uncertainty in route choice. To support and improve the driving experience, we address the use of visual traffic information for pre-trip route choice and the use of counterfactual travel times as post-choice feedback information on the forgone alternatives.
Subject (authority = RUETD)
Topic
Computer Science
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Title
Rutgers University Electronic Theses and Dissertations
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ETD
Identifier
ETD_8205
PhysicalDescription
Form (authority = gmd)
electronic resource
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application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xv, 139 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Traffic congestion
Subject (authority = ETD-LCSH)
Topic
Automobile drivers
Subject (authority = ETD-LCSH)
Topic
Transportation, Automotive
Note (type = statement of responsibility)
by Daehan Kwak
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3X3519V
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

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The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Kwak
GivenName
Daehan
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2017-05-09 15:01:29
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Name
Daehan Kwak
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Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
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Author Agreement License
Detail
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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DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2017-05-31
DateTime (encoding = w3cdtf); (qualifier = exact); (point = end)
2017-11-30
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Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after November 30th, 2017.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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