Avoiding bus bunching: From theory to practice
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Transcript of Avoiding bus bunching: From theory to practice
AvoidingBusBunching:FromTheorytoPractice
Department ofTransport EngineeringandLogisticsPontificiaUniversidadCatólicadeChile
Jointworkwith:JuanCarlosMuñozandFelipeDelgado
Outline
• Thebusbunchingproblem
• Proposedcontrolstrategy
• Simulationresults
• PilottestresultsandImplementationChallenges
• Conclusions
Motivation:Efficiencyintheuseofroadspace
www.BRT.cl
Whatcanwesayabouttheuser?
• Perceiveswaitingtimeandwalkingtimetwiceasimportantastraveltimeinsidethevehicle.
• Avoidstransferring,speciallyiftheyareuncomfortable
• Needsareliableexperience
• Requestsaminimumcomfortexperience
• Requestsinformation
• Needstofeelsafeandsecure
Whatcanwesayaboutbusservice?
Busiscriticaltoprovideagooddoor-to-doortransitalternativeformanyjourneys:
• Muchhighernetworkdensityandcoveragethanrail
• Greaterflexibilityinnetworkstructure
• Lowmarginalcostforserviceexpansion
BUT as traditionally operated, it also has serious limitations:
• Low-speed• Subject to traffic congestion• Unreliable• Harder to convey network to the public• Negative public image
MetroAttributes
Actions
IncreaseSpeed
Regular Headways
Maindrivers
IncreaseCapacity
IncreaseFrequency
•Segregated ways/lanes•Reducedwell times
•Farepaymentoff-bus•Buseswithmultipledoors
•Increase distance between stations•Expressservices•Trafficsignalpriorityandpriorityatintersectons•Improvedheadwayregularity
Fast ComfortLow waits Reliable
RicardoGiesen©
Bus
Bus
Stop Stop
Waiting Passengers
WaitingPassengers
Bus Operations without Control
RicardoGiesen©
BusBusStop Stop
a small perturbation…
Waiting Passengers
WaitingPassengers
Bus Operations without Control
RicardoGiesen©
Bus
Bus
Stop Stop
While one bus is still loading passengers the other bus already left its last stop
Bus Operations without Control
RicardoGiesen©
Bus
BusStop Stop
Bus Operations without Control
RicardoGiesen©
BusBus
Stop Stop
Without bus control, bus bunching occurs!!!
Bus Operations without Control
Transantiago,Santiago,Chile
Cambridge,MA
Time-spacetrajectoriesLine210
Busbunchingisasevereproblem
§ Most passengers wait longer than they should for crowded buses
§ Put pressure in the authority for more buses
§ Reduces reliability affecting passengers and operators
Idea:ControlStrategiestoAvoidBusBunching!
SolvingBusBunching:ScheduleControl
• Buseshavetoadheretostaticschedulesinstopsorcontrolpoints
• Usefulforlowfrequency(<5buses/hour)lineswithoutcongestion:nottherealityofmajorurbancities.
• KPI:• Punctualityindicatorthatmeasurestheadherencetoaschedule.
• Pros:• Easytoimplement&tounderstandbydriver.
• Transparentforusers.
• Cons:• Notusefulforhighfrequencyorcongestedlines
• Excessiveslackinschedules
• Dynamicsuggestionstoincrease/decreasespeed&holdingatstopsandterminals
• Severalcontrolstrategiesintheliterature,latelysomedeveloped&implemented:
• RecentadvancementsonICTs
• Lowerhardware&communicationcosts
• Challenges:• Makingasmartsolutionrobustenoughtoscale
• Drivercompliance
• KPI:• Headwaydeviationincontrolpointsalongtheroute
• Waitingtimes,Busloads
• Santiago:ICR®ularityfines
SolvingBusBunching:HeadwayControl
PreviousWorkonHoldingStrategies
Reference PH PD and RT Overtaking OF Veh. Cap. Control Points Buses Sol. method
Ding y Chien (2001) Multiple Deterministic Prohibited Vh ignored CMS One OPT
Eberlein et al (2001) Multiple Deterministic Prohibited Wfirst ignored PSS Multiple Heuristic
Hickman (2001) One Stochastic Allowed Wfirst+Win-veh ignored PSS One OPT
Zhao et al (2003) One Stochastic Prohibited Wfirst+Win-veh ignored CMS One Heuristic
Sun y Hickman (2004) Multiple Deterministic Prohibited Wfirst+Win-veh ignored PMS Multiple Heuristic
Zolfaghari et al (2004) Multiple Deterministic Prohibited Wfirst+Wextra considered CSS Multiple Meta-heuristic
Puong y Wilson (2004) Multiple Deterministic Prohibited Wfirst+Win-veh+Wextra considered CMS Multiple OPT
NewIdea:BoardingLimits
Turnquist and Blume (1980) pioneer work on threshold policy for holding buses
Innovations
1.- Decisionvariables:HoldingBoardingLimits
Passengers allowed to board
Passengerspreventedfrom
boarding
This can be used even when at less thanphysical capacity in order to increase operatingspeed.
2.- Buscapacityincorporatedwithoutresortingtobinaryvariables
SystemCharacteristics
Thesystemiscomposedby:
One-wayloopTransitcorridor.
Operatedbyasingleservice.
N stops.
K homogeneousbuses.
StateVariables
Real Time information about:
Bus position.
Bus loads.
# of Passengers waiting at each stop.
However,wecouldworkwithestimations…
andinpracticethereisnoalternative
Model:Assumptions
Someinformationabouttripdestinations.
Dwelltime:dominatedbyboardings.
Busesserveallstopsandovertakingisnotallowed.
Every time a bus reaches a stop:
How much to hold it?
Should we prevent some passengers from boarding?
Solve a rolling horizon optimization problem to take those single decisions
1
2
N/2
N-1NCurrentSituation
Busarrives atastop
Model:Problemdefinition
1
2
N/2
N-1NCurrentSituationOptimizePredicting
Model:Problemdefinition
Every time a bus reaches a stop:
How much to hold it?
Should we prevent some passengers from boarding?
Solve a rolling horizon optimization problem to take those single decisions
1
2
N/2
N-1NCurrentSituation
Apply decision
Model:Problemdefinition
Every time a bus reaches a stop:
How much to hold it?
Should we prevent some passengers from boarding?
Solve a rolling horizon optimization problem to take those single decisions
3. Model: Objective Function
1 2 3 4,kn knfirst in veh extrah w
Min W W W PEq q q q-× + × + × + ×
Experiment:SimulationScenarios
Highfrequencytransitsystemscenario(headway~2min.)
Highpassengerdemand(buscapacitiescanbereached)
One-wayloopTransitcorridorwith30Stopsand29TrafficLights(inbothways)
Competingflow700veh/h
Mainflow900veh/h
Saturationflow1800veh/h
Parameter ValueCycletime 72 sec
Greentimeforbusapproach 40 sec
Offsetsbetweentrafficlights 23 secMaximumextension 4 sec
Nocontrol
Spontaneousevolutionofthesystem.
Busesaredispatchedfromtheterminalassoonastheyarriveoruntiltheyreachthedesignedheadway.
Noothercontrolactionsaretakenalongtheroute.
ProposedModel
Solvetherollinghorizonoptimizationmodelincludingholding,boardinglimitsandgreenextension
Experiment:SimulatedStrategies
5. Simulation Results
30 runs for every combination of strategies and scenarios
Each run represents 2 hours of bus operation.
15 minutes “warm-up” period.
Variability is introduced in the simulation experiment.
Results:SimulationFramework
Simulator AMPL Solver
State variables
ControlAction
NoControl ProposedWfirst 7636.32 1438.62Std.Dev. 649.36 146.56%reduction -81.16Wextra 6218.71 1010.52Std.Dev. 2265.24 82.04%reduction -83.75Win-veh 175.32 1561.34Std.Dev. 31.69 77.3%reduction 790.55Wt_light 4052.81 2965.1Std.Dev. 88.27 110.27%reduction -26.84Total 18083.16 6975.58Std.Dev. 2600.63 275.12%reduction -61.42
SimulationResults:TransitUsers
SimulationResults:BusLoads
72
SimulationResults:CycleTimes
Results:Vehiclecap.constraints&mediumfrequency
0-5min. 5-10min. morethan10min.Nocontrol 78.90 17.52 3.58Tresholdcontrol 89.26 9.80 0.95HRT 92.46 7.50 0.04HBLRT 93.74 6.19 0.07
%ofpassengersthathavetowaitbetween:
ResearchConclusions
– We have a tool for effectively reducing bunching of buses in a BRT.
– The tool is fast enough for real-time applications.
– The proposed control strategy outperform simple control ruleswith saving up to 61.4% for transit users.
– Boarding Limits are only attractive in high demand and highfrequency scenarios.
– Severely improve comfort and reliability for transit users.
– Reduction on vehicle cycle times allow for reductions on fleet sizeor improvements on level of service.
Weshoulddoit!
PilotProjectContext
• In2012afineschemewasimplementedintheSantiagotransitsystem(Transantiago):üGuaranteefrequencyandregularitycompliance
üRegularityfinesifbusheadwayexceedsthreshold
üAveragemonthlysystemfines(2012):$USD2.3million
• Thefineschemeevidencedthelackofavailabletoolsinthemarkettoregularizeheadwaysonhighfrequencyservices
Howdoesthemodeloperate?
Busservice
t
Servicestartsoperating
t=0
t=to
Optimizationmodel
Datacollection Instructionstobusoperator
Holdingtime/Departure
time
Current serviceconditions (buspositions,etc)
t=2to
Timeintervalbetweenoptimizations
Optimizationmodel
Holdingtime/Departure
time
Current serviceconditions (buspositions,etc)
Pilotstudies
• Duetothesuccessofthemodelinsimulationenvironment,aSantiagobusoperatorcompanywaswillingtotry.
• Pilotstudieswithservice210(SubusChile):
üNovember2012(Pilot1)andApril2013(Pilot2)
OptimizationModel
Monitorsat24busstop
ControlInstruction:Busdeparturetime
TextmessagingBusdriver
Busdeparturetime
Directcommunication
210PilotPlan
• Exampleofbusbunchingin210service:
Service210Characteristics
• Highdemand(48,000passengers/day)
• Highfrequencyservice(abusevery3-4minutes)
• Completeroute(inbound+outbound):135stopsand56kmlong
• Inmorningpeak:upto60busesoperatinginservice
• Oneoftheworstserviceintermsofuser evaluationofTransantiago
• Servicewithhighfareevasion
Pilotstudies
Pilotstudies:results• Morningpeakperiod(6:30-9:30)fines210-outboundservice($CLP):
$10,000
$30,000
$50,000
$70,000
$90,000
$110,000
USD1=CLP670
Pilotstudies:results
Bustrajectories (distance vstime)day without control
Pilotstudies:results
Pilotstudies:resultsLine210
• Surprisingly,uservalidations(demand)increasedby20%duringthepilotplans
– Reductionofuserevasion:“passiveevasion”
• Nosignificanteffectsonbusfrequencyandcycletimes
INNOVATIVE TECHNOLOGICAL SOLUTIONS FOR TRANSIT SYSTEMS
WWW.TRANSITUC.COM
FelipeDelgado,RicardoGiesen,JuanCarlosMuñoz
PedroLizana
Headwaycontrolsoftware
GPSdata:buslocation
BuslocationWebservice
BusOperator/Agency
Controlinstruction
Webservice
GPSdevice
Controlinstruction
User smartphone AppOnlinevisualization tool
APCdata:demanddata
Real-timebustraveltimepredictor
Datacollectionsmartphone App
Demand data
Transit UC
TechnologicalPilotPlans
• Objective:Sendcontrolinstructionsdirectlytobusdriverusingabusconsole-tablet
• Subus-Chile(210service)
üControlinstructions:holdingbusesatstopsandskipstops
üTheyalreadyhaveindustrialconsolesinstalledintheirbuses:usedwithaitinerary-basedcontrolsystemthathasbeenineffectiveinpeakperiods
Softwareinputinformation• Statictransitsystemdata:
– Busservices,operatingprograms,busstoplocations,etc.:datainformatGeneralTransitFeedSpecification(GTFS)
• Real-timebuspositions:– GPSalreadyinstalledinbuses– TabletAppGPS
• Demanddata:– Passivesmartcardinformation:ODmatricesandbusstoparrivalrates
• Segmentspeeds:– Combinationofreal-timespeeds(fromGPSdata)withhistorical
speeds:researchonArtificialNeuralNetwork(ANN)andBayesianNetworksalgorithms
210PilotPlan– Busconsole
210PilotPlan– Busconsole
• Screenshotofholdinginstructionatbusstop:
Holdingtimecountdown
Currentstop
Copyrights:Mobius
• Screenshotofholdinginstructionnotcarriedoutbybusdriver:
210PilotPlan– Busconsole
Helpamoreregularoperation:departstopatindicatedtime
Copyrights:Mobius
210PilotPlan:TechnicalChallenges
• SomebuseshaveGPSdatadelayedinupto3minutes(withaGPSpulseevery30seconds):Hardtopredictwherethebusiscurrentlylocated.
• VeryrigidconsoleApp(developedbyothercompany):insomecasestheconsoledoesnotconnectandnosugestionsaredisplayedtodrivers.
210PilotPlan- HumanChallenges
• Somedriversliketobunchupwithpreviousbusessofewpeopleloadtheirbusesandworkshortershifts
• Somedriversbandalizedtheirconsoles:companyhadtoputaplasticlayerontopofthescreen(notanymoretouchscreen)
• Usersfrustatedbythecurrentlevel-of-servicethatdonotliketobeheldatbusstops(driversthreatenedtobebeatenbyusers;userskickingbusandwindows;etc)
210PilotPlan:CompanyChallenges
• Thecompanyhasanexistingschedule-basedcontrolsystem(withverylowcredibilitybetweendrivers)thatinteractswithourheadway-basedsystem.
– Possibleconfusioninformationtodrivers
• Companydidnotprovideanyincentivesfordrivertoimproveregularity.
PedroLizana,CEOTransitUC
RicardoGiesen
RESULTSPILOTTESTTRANSMILENIO:DUAL84
Service84,Transmilenio
Howtomeasureregularity?
• Waitingtimeatstopscanbeexpressedas:
• Thefirsttermdependsonthefrequencyofbuses(1/H),whichisafunctionofthenumberofbuses(n)andthecycletime(Tc).
H=Tc/n
• Thesecondtermdependsonthevariabilityoftheheadwaysbetweenbuses.ThiscanbeimprovedusingBuzzAssist.
E(W ) = E(H2 )
2E(H )=E(H )2
+Var(H )2E(H )
Transmilenio PrePilot Results
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
3% 3% 13% 13% 23% 23% 33% 33% 43% 43% 53% 53% 63% 63% 73% 73% 83% 83% 93% 93%
Pre-Pilot1:3/16withControlvs.3/17withoutcontrol
Var.sincontrol
Fijosincontrol
Var.concontrol
Fijoconcontrol
ControlPoint
Waitin
gtim
e[m
in]
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
3% 3% 13% 13% 23% 23% 33% 33% 43% 43% 53% 53% 63% 63% 73% 73% 83% 83% 93% 93%
PrePilot2:4/14with Controlvs.4/21withoutcontrol
Var.sincontrol
Fijosincontrol
Var.concontrol
Fijoconcontrol
ControlPoint
Waitin
gTime[m
in]
Transmilenio PrePilot Results
140
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
3% 3% 13% 13% 23% 23% 33% 33% 43% 43% 53% 53% 63% 63% 73% 73% 83% 83% 93% 93%
Pilot:5/26withControlvs.5/25withoutcontrol
Var.sincontrol
Fijosincontrol
Var.concontrol
Fijoconcontrol
ControlPoint
Waitin
gTime[m
in]
Transmilenio PilotResults
Results:CycleTime(onedirection)
141
0
10
20
30
40
50
60
70
80
90
100
Cycle
Tim
e(m
in)
TpoCicloconControl(14Abril+26Mayo)
TpoCiclosinControl(21Abril+25Mayo)
With control: Average Cycle Time=63.4minandSt.Dev.=5.6minWithoutcontrol: Average Cycle Time=69.5minandSt.Dev.=11.8min
Promisingresults
• Moreregularity
• Lessfines
• Moredemand
• However…driversdonotfollowinstructions,implementationchallenges…
AVOIDING BUS BUNCHING
DevelopedAppforIndustrialConsoletoProvideDriverAssistance
ImplementationinRedbus,Transdev
• 61linesand600+buses
• Approx.300,000dailypaidtrips(bip!)with~ 25%fareevasion
0
1
2
3
4
5
6
7
0 5 10 15 20 25
Fine
s
Distance from origin [km]
Regularityfinesforeachbusoperatorcompany(DICTUC,2016)
U1
U2
U3
U4
U5
U6
U7
Dispatchingatterminalsisnotregular
SynopticFleetcontrol&monitoring
CommercialDispatcherComplywithfrequency,regularityandindicatorsSmartdispatcher
TerminalDispatcherOpening&closingofdrivershiftsNoncommercialmovements
ConsoleDriverassistanceOn-routeregularity
TrainingDispatchers & drivers
DemandPerstop&lineLoadprofileFareevasionsupervision
UsersReal-timeupdatestousers
SurveyingPassengercountingApp
Regularity
Regularity
Evasion
• Controlcenteroperatorshaveaccesstoalivesynoptictovisualizebuses,theirbusbunchingavoidanceinstructions,changetheirstatusandsendmessagestodriveranddispatchers.
CAD/AVL
• DispatchershaveaccesstoawebandAndroidmobileappDispatchApp,thatinformsthemofreal-timeregularityindicatorsandgivesthemsmartdispatchtimesuggestionsinordertoincreasetheregularityofeachline.
Smartdispatcher
• Avoidingbusbunchingwithschedulesorwithastate-of-artheadwaycontrolalgorithm
Stopping busbunching!
DriverAssistance• Driversreceivethroughanindustrialtablet,real-timeupdates,messagesfromthecontrolcenter,andautomatizedsuggestiontoincreaseheadwayregularity.
• Driverscanalsomodifyexpeditionparameters,suchasthecommercialstatusoftheexpeditionandthelineassignedtothebus.
• IndustrialtabletisaruggedizeddevicewithAndroidOS.IthasembeddedaGPSreceiverandGSMcommunicationmodule,thereforeitisflexibleenoughtoadapttodifferentneeds.
Ok Hold Go faster Slow down
• All59servicesavailablewiththeheadwaydispatchingmodule
• B22/B14lineswith25industrialtabletsinstalledinbuses
Redbus Project
Results ProjectRedbus
$- $0.10
$0.20
$0.30
$0.40
$0.50
$0.60
$0.70
$- $20,000$40,000$60,000$80,000$100,000$120,000$140,000$160,000$180,000$200,000
Mar-16 Apr-16 May-16 Jun-16 Jul-16 Aug-16 Sep-16
HeadwayRegularityFines
TotalFines Fines/Expedition
• Real-timeupdates¬ificationsofbusarrivaltimes,buslocationandbusloads• Multimodalrouteplanner• Userscanevaluatethequalityofservice
Apata:SustainablemobilityAppfortransit+bikeusers
WehaveintegratedBusAssist toanelectronicfarecollectionsystemtoestimatethedemandofeverylineandstop:
• Howmanyusersboardandpay,alightandevadeateachstopatanyperiodoftheday
• Loadprofiles• Givesuggestionstomonitorandsupervisefareevasion
DemandAnalysis
NewChallenges…andOpportunities
• MorecompaniesaroundtheglobeareinterestedonimprovingtheirLOSusingoursolutions
• Howtoimprovetheperceptionofdrivers?
• Howtocommunicatewiththedriver?Imageorvoice?
• Howtopresenttheinformationinthemonitor?
• Gamificationtoimprovecompliance?
– OngoingresearchprojectFONDECYTEngineeringandDesign.
AvoidingBusBunching:FromTheorytoPractice
Department ofTransport EngineeringandLogisticsPontificiaUniversidadCatólicadeChile
Jointworkwith:JuanCarlosMuñozandFelipeDelgado