supporting route choices via real-time visual traffic information and counterfactual arrival times

154 Pages·2017·2.69 MB·English

SUPPORTING ROUTE CHOICES VIA REAL-TIME VISUAL
TRAFFIC INFORMATION AND COUNTERFACTUAL
ARRIVAL TIMES
BYDAEHANKWAK
Adissertationsubmittedtothe
GraduateSchool—NewBrunswick
Rutgers,TheStateUniversityofNewJersey
inpartialfulfillmentoftherequirements
forthedegreeof
DoctorofPhilosophy
GraduatePrograminComputerScience
Writtenunderthedirectionof
BadriNath
andapprovedby
NewBrunswick,NewJersey
May,2017
ABSTRACTOFTHEDISSERTATION
ffi
Supporting Route Choices via Real-time Visual Tra c Information
and Counterfactual Arrival Times
byDaehanKwak
DissertationDirector: BadriNath
Mobility plays an integral role in modern lives, yet with the ever-expanding number of cars,
trafficcongestionposesvariousnegativeeffects,causingvasteconomicloss,airpollution,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
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theinformationsystem’srecommendedroute. Third,asdriverscannotassessandcomparetheir
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
systemsarenotconsistentwiththeirownpreviousdrivingexperiences.
Inthisdissertation,ourfocusistoexplorethesethreelimitations. First,wepresentacom-
parativeanalysisontherouterecommendationsgivenfromfourpopularonlinemapproviders:
Google Maps, HERE, MapQuest and Bing Maps. We analyze traffic data collected from all
fourofthedifferentmapprovidersfor71daysfortwocities,eachwithtwoorigin-destination
pairs. Statistical analysis show that the estimated travel times on identical routes are signifi-
cantly different among the map providers. This in itself has the potential to create uncertainty
inroutechoicesandtraveltimevariability,inadditiontoadecreaseinthecredibilityandcom-
pliance 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 So-
cial Vehicle Navigation. This system incorporates a secondary level of detail into the vehicle
navigationsystembyprovidingothersemanticallyrichinformationthatdriverscansharewith
oneanother. Thisuser-sharedvisualtrafficinformationassistsinthedecision-makingprocess
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 compari-
sonamongchosenandnon-chosenroutes,whichdeterminestheactualtraveltimesfromprobe
participatoryvehiclesonthenon-chosenroutes.
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The main conclusion of this dissertation is that existing navigation systems have limita-
tions 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.
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Acknowledgements
My deep gratitude first goes to Professor Liviu Iftode, who is no longer with us, but resting
in heaven. He has been a great mentor, guiding me through my graduate education, always
pushingmeforwardandmotivatingmeonmyresearchandstudies. Ihavebeenveryfortunate
to have an advisor, who has given me freedom to explore first on my own while at the same
time,teachingmetostriveforconstantimprovements. Hiscontinuoussupportforthelastseven
years at Rutgers has been tremendous and I will miss him dearly. I know he will be proud of
me.
I also want to thank Professor Badri Nath, for taking me under his wings and continuing
to support me by being available for discussions and providing helpful feedback for me. Our
discussions have turned out to be very constructive, and have helped me sort out the details
of my projects. His insights and advices have been invaluable. Professor Nath has provided a
wealthofbenefitstomeasIstruggledtocompletethiswork.
My gratitude extends to Professor Thu Nguyen and Professor Vinod Ganapathy as well.
Professor Thu has always been available for great conversations and guidance for my track
for Ph.D. and also job search advices. I have had the pleasure to work with Professor Vinod
Ganapathyand hehasconstantlyhelped, supported, and shownmeencouragementsalong the
way. IwouldalsoliketothankDr. StephenSmaldoneforhissupportandhelpasmyexternal
committeemember.
DuringmytimeatRutgers,Ihavehadthepleasureofworkingwithmanyexcellentpeople.
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My appreciation also goes out to my colleagues, Ruilin Liu, Nader Boushehrinejadmoradi,
Daeyoung Kim, and Hai Nguyen, whom I have had the pleasure to learn various things from.
IespeciallywouldliketothankRuilinLiuandDaeyoungKim,whohavehelpedmedaysand
nights on my experiments and research and showing great teamwork. Throughout my long
journeyallofthesepeoplehavecontributedtomakemyPh.D.lifespecial. Iamgratefultothe
staffofthedepartment,especially,CarolDiFrancesco,forassistingmeinmanydifferentways.
I also send my thanks to Gregory Hill, my supervisor, my mentor, and my friend. Getting
methroughmymilitaryservices,helpingmesetupatRutgers,reviewingmywork... Youhave
helped and supported me in endless ways. I greatly appreciate all of what you have done for
me.
Lastly,Iwouldliketothankmyparentsfortheirunconditionallove,patience,andsupport.
Theyaddontomypurposeandinspiration. Lastbutnottheleast,IamthankfultoAmberKim,
forherpatienceandlovewhileIwasworkingonmyPh.D.Idedicateandowemydissertation
tothem.
Thankyouall!!!
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Dedication
TowhomIoweeverything,mymotherandfather.
ToAmberKim,foryourlove,trust,andsupport.
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Table of Contents
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Dedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
ListofTables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii
ListofFigures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1. TravelInformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1.1. State-of-the-artonTravelInformation . . . . . . . . . . . . . . . . . . 2
1.2. RouteChoice . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.2.1. LimitationsinRouteChoice . . . . . . . . . . . . . . . . . . . . . . . 5
1.3. Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.4. SummaryofDissertationContributions . . . . . . . . . . . . . . . . . . . . . 8
1.5. ContributorstotheDissertation . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.6. OrganizationoftheDissertation . . . . . . . . . . . . . . . . . . . . . . . . . 11
2. ComparativeAnalysisonOnlineMaps . . . . . . . . . . . . . . . . . . . . . . . 12
2.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.2. BackgroundandRelatedWork . . . . . . . . . . . . . . . . . . . . . . . . . . 14
viii
2.3. ExperimentSetup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.4. DataDescription . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.5. DescriptiveStudy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.5.1. RecommendedRouteOptions . . . . . . . . . . . . . . . . . . . . . . 22
2.5.2. RoutesViewedbyDate . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.5.3. RouteChanges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.6. ComparativeStudy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.6.1. CaseofBestRoutes . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.6.2. CaseofIdenticalRoutes . . . . . . . . . . . . . . . . . . . . . . . . . 30
2.7. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3. Real-TimeVisualTrafficInformationforPre-tripRouteChoice . . . . . . . . . 35
3.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.2. RelatedWork . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
3.2.1. CollaborativeSharing . . . . . . . . . . . . . . . . . . . . . . . . . . 38
3.2.2. RoutePlanningviaTrafficCameras . . . . . . . . . . . . . . . . . . . 39
3.3. SocialVehicleNavigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.3.1. ExampleScenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.3.2. LayeredArchitectureModel . . . . . . . . . . . . . . . . . . . . . . . 42
3.4. SystemDesign . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.4.1. DesignConsideration . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.4.2. VehicularCloudClient . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.4.3. InternetCloudDesign . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.5. Prototype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
ix
3.5.1. Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
3.5.2. SystemUsageScenario . . . . . . . . . . . . . . . . . . . . . . . . . . 56
3.6. Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
3.6.1. DigestPerformance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
3.6.2. SystemPerformance . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3.7. QuestionnaireStudy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
3.7.1. DesignandOutline . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
3.7.2. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.8. UserStudy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
3.8.1. SetupandDesign . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74
3.8.2. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
3.9. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
3.10. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
4. CounterfactualTravelTimeInformationforPost-tripFeedback . . . . . . . . . 80
4.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
4.2. PreliminariesandMotivation . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
4.2.1. WhyCurrentInformationSystemsNeglectPostFeedback . . . . . . . 83
4.2.2. PotentialofPostFeedbackforChosen/Non-chosenRoutes . . . . . . . 84
4.2.3. UsageofPostFeedbackforChosen/Non-chosenroutes . . . . . . . . . 86
4.3. DeterminingCounterfactualTravelTime . . . . . . . . . . . . . . . . . . . . . 89
4.4. DoppelDriverOverview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
4.4.1. Preliminary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
4.4.2. Concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
x