ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS)
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Transcript of ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS)
ADVANCED TRAFFIC CONTROL ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS TECHNIQUES FOR FREEWAY SYSTEMS
(AND URBAN NETWORKS)(AND URBAN NETWORKS)
by Prof. Markos Papageorgiouby Prof. Markos Papageorgiou
Dynamic Systems and Simulation Dynamic Systems and Simulation
Laboratory, Laboratory,
Technical University of Crete, Chania, Technical University of Crete, Chania, GreeceGreece
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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OUTLINEOUTLINE1. Introduction 2. Motorway (Freeway) Traffic Control3. Ramp Metering4. Route Information and Guidance5. Variable Speed Limits6. Urban Signal Control7. Integrated Urban-Freeway Traffic Control8. Motorway Traffic Surveillance9. Other Control Tools
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Who are we?Who are we?
Dynamic Systems and Simulation Laboratory (DSSL)
(~ 15 Professors, Researchers, PhD/MSc Students) at the Technical University of Crete
also acting occasionally as professional engineers.
1. INTRODUCTION1. INTRODUCTION
What is our Background?What is our Background?• Automatic ControlAutomatic Control• Electrical EngineeringElectrical Engineering• Industrial EngineeringIndustrial Engineering• Civil EngineeringCivil Engineering
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ExperienceExperience
• 30 years of high-quality research in traffic flow modelling 30 years of high-quality research in traffic flow modelling and controland control
• Numerous successful implementationsNumerous successful implementations
• High number of research or implementation contracts: High number of research or implementation contracts: national, EC, companies, national, EC, companies,
authorities authorities worldwideworldwide. .
• October 2008: October 2008: IEEE Outstanding ITS Research AwardIEEE Outstanding ITS Research Award
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Concepts Concepts Algorithms Algorithms Software for traffic flow Software for traffic flow
modelling, surveillance, route guidance, traffic control modelling, surveillance, route guidance, traffic control
(freeway + urban)(freeway + urban)
What We DoWhat We Do
What we What we Don’tDon’t Do Do
Our Usual Partners Our Usual Partners
Implementation hardware, System integrationImplementation hardware, System integration
• Road authoritiesRoad authorities
• Local Consultants/University groupsLocal Consultants/University groups
• Local System IntegratorsLocal System Integrators
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Our PrinciplesOur Principles
• Theoretical soundness: Theoretical soundness: There is nothing more practical than a There is nothing more practical than a
good theorygood theory
• Practical Usefulness.Practical Usefulness.
• General Applicability, InteroperabilityGeneral Applicability, Interoperability
• Highest Efficiency: deep understandingHighest Efficiency: deep understanding
• Practicability: Practicability: As simple as possible, as complex as necessaryAs simple as possible, as complex as necessary..
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Automatic Control LoopAutomatic Control Loop
Disturbances
Outputs
Measurements
Goals
REAL WORLD
COMPUTER
ProcessInputs
ControlStrategy
DataProcessing
ActuatorsSensors
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O-D,demand,
environment
Minimizationof total
travel time
URBAN NETWORK
COMPUTER
Flows,Occupancies
Total travel time Urban Traffic Flow
ControlStrategy
A.I.D.,Estimation,Prediction
TrafficLights Loop
Detectors
Example: Urban traffic control system
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Minimization of Total Time SpentMinimization of Total Time Spent
Maximization of (Early) Exit RatesMaximization of (Early) Exit Rates
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Simple Queuing SystemsSimple Queuing Systems• Demand > Capacity Demand > Capacity Queuing Queuing
• Capacity Capacity ≠ f (Queuing)≠ f (Queuing) Delay depends on DDelay depends on D−−C only!C only!
Water SystemsWater SystemsMore inflow More inflow Higher Pressure Higher Pressure Higher Higher
OutflowOutflow
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Traffic NetworksTraffic Networks• Congestion degrades the infrastructure (capacity)Congestion degrades the infrastructure (capacity)
Local link demand exceeds local capacity Local link demand exceeds local capacity
Local congestion degrades local capacityLocal congestion degrades local capacity
Accelerated increase Accelerated increase of congestionof congestion
Further capacity Further capacity degradationdegradation
... until generalized network congestion... until generalized network congestionalthoughalthough
Demand << Nominal network capacity Demand << Nominal network capacity
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Conclusion:Conclusion: Generalized traffic congestion is not Generalized traffic congestion is not
only due to high demand.only due to high demand.
Congested Motorway Networks:Congested Motorway Networks: Expensive Expensive
infrastructure capacity not fully available at the infrastructure capacity not fully available at the
only time it is actually needed, i.e. the peak time it is actually needed, i.e. the peak
periods!periods!
Goal: Goal: Operate motorway and urban networks Operate motorway and urban networks
optimallyoptimally
(as (as controllable systems) systems)
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Motorways were originally conceived to Motorways were originally conceived to provide virtually unlimited mobility to provide virtually unlimited mobility to road users, but …road users, but …
2. MOTORWAY (FREEWAY) 2. MOTORWAY (FREEWAY) TRAFFIC CONTROLTRAFFIC CONTROL
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Man has reached to the moon but …Man has reached to the moon but …
… … even ants were taught by evolution to address even ants were taught by evolution to address their transportation problems more efficiently, their transportation problems more efficiently, seeseeI.D. Couzin and N.R. Franks: “Self-organized lane formation and optimized traffic flow in army ants”, Proc. R. Soc. Lond. B (2003) 270, 139–146
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Available Motorway Control MeasuresAvailable Motorway Control Measures Ramp metering (RM):Ramp metering (RM): valuable; limited valuable; limited
storage spacestorage space Variable speed limits (VSL):Variable speed limits (VSL): improved improved
safety; no system improved efficiencysafety; no system improved efficiency Route guidance (RG):Route guidance (RG): best under incident- best under incident-
caused congestioncaused congestion Vehicle-infrastructure integration (VII):Vehicle-infrastructure integration (VII):
promising; emergingpromising; emerging
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Prerequisite for efficient traffic control:Prerequisite for efficient traffic control:Understanding the reasons for infrastructure Understanding the reasons for infrastructure degradation!degradation!
(Latent) Motorway bottleneck location:(Latent) Motorway bottleneck location:Capacity upstream > Capacity downstreamCapacity upstream > Capacity downstream
Bottlenecks are candidates for Bottlenecks are candidates for congestion appearance:congestion appearance:– on-ramp mergeon-ramp merge– geometry (lane drop, grade, curvature, geometry (lane drop, grade, curvature,
tunnel, …)tunnel, …)– weavingweaving– speed limitsspeed limits– over-spilling off-rampsover-spilling off-ramps
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Two Main Reasons for Motorway Infrastructure Two Main Reasons for Motorway Infrastructure DegradationDegradation
1. Capacity Drop (CD)1. Capacity Drop (CD)
CD not well-understood but is deemed CD not well-understood but is deemed to occur due to vehicle accelerationto occur due to vehicle acceleration
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2. Blocking of Off-Ramps (BOR)2. Blocking of Off-Ramps (BOR)
off-ramp flow reduced: vehicles bound off-ramp flow reduced: vehicles bound for the off-ramp contribute to for the off-ramp contribute to accelerated congestion increase!accelerated congestion increase!
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3. RAMP METERING3. RAMP METERING
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Why Ramp MeteringWhy Ramp Metering1st Answer
qin
d
qcon
no control
nc rmcap cons s
s ncs in con
q qT TT
T q d q
e.g. qcon = 0.95 qcap ; qin+d = 1.2 qcap
sΔT 20%̂
(veh/h)
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2nd Answer
q in
d
q cap
)dq(1 cap
q cap d
γ q in
q in
d
q cap
nc
s
rms
ncs
sT
TTT
Note: Note: On-ramp queue should not On-ramp queue should not interfere with surface street interfere with surface street traffic.traffic.
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Further reasons
•Influence driver route choiceInfluence driver route choice
•Utilisation of reserve capacity on parallel arterialsUtilisation of reserve capacity on parallel arterials
• Increased traffic safety (less congestion, safer merging)Increased traffic safety (less congestion, safer merging)
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When is ramp metering less helpful?
Exit flow problemsExit flow problems
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Local Control IssuesLocal Control Issues
q cap
q out
o cr o out
Demand-Capacity(Feedforward)
r
qinoout
qcap
r(k) = qcap - qin (k-1)
Note: oNote: ocr cr less sensitive than less sensitive than qqcapcap (e.g. under adverse (e.g. under adverse weather conditions)weather conditions)
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Sample from Glasgow Implementation of ALINEASample from Glasgow Implementation of ALINEA
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• Real-time estimation of oReal-time estimation of ocrcr
• Real-time estimation of ramp queueReal-time estimation of ramp queue
• Ramp queue managementRamp queue management
• Various traffic-light policiesVarious traffic-light policies
• Switch on/off logicSwitch on/off logic
. . .. . .
Many additional toolsMany additional tools
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Why Coordinated Ramp Metering?Why Coordinated Ramp Metering?
No ramp queue constraints No ramp queue constraints
•Little efficiency improvement via coordination Little efficiency improvement via coordination
•Equity ?Equity ?
•Realistic ?Realistic ?
•DiversionDiversion
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• Full ramp Congestion Full ramp Congestion “merely” retarded “merely” retarded
• Equity: badEquity: bad
Limited ramp storage capacity: Limited ramp storage capacity:
significant improvement of both efficiency significant improvement of both efficiency andand equity via equity via appropriate coordinationappropriate coordination
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• Rule-based central controlRule-based central control
• employs (modified) ALINEA at each on-rampemploys (modified) ALINEA at each on-ramp
• Master/Slave ramps for increased storage space Master/Slave ramps for increased storage space
• High efficiency High efficiency (depending on available ramp storage space)(depending on available ramp storage space)
HERO: Ramp Metering coordination algorithmHERO: Ramp Metering coordination algorithm
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ALINEA Field ImplementationsALINEA Field Implementations
• Boulevard PBoulevard Péériphriphéérique, Paris, Francerique, Paris, France• A6, Ile-de-FranceA6, Ile-de-France• A10, Amsterdam, NetherlandsA10, Amsterdam, Netherlands• Glasgow, ScotlandGlasgow, Scotland• A94, Munich, GermanyA94, Munich, Germany• UK Highways Agency ramp metering roll-outUK Highways Agency ramp metering roll-out• Tel Aviv, IsraelTel Aviv, Israel
. . .. . .
>100 ramps in Europe (even w/o our involvement)>100 ramps in Europe (even w/o our involvement)
StatusStatus: Mature tool, ready for immediate implementation: Mature tool, ready for immediate implementation
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HERO/ALINEA Field ImplementationsHERO/ALINEA Field Implementations
• A6, Ile-de-France (simplified)A6, Ile-de-France (simplified)
• Ile-de-France network (~ 80 ramps)Ile-de-France network (~ 80 ramps)
• A10, Amsterdam, Netherlands (~ 40 ramps)A10, Amsterdam, Netherlands (~ 40 ramps)
• Monash Freeway, Melbourne, Australia (6Monash Freeway, Melbourne, Australia (665 ramps)65 ramps)
StatusStatus: Mature tool, ready for immediate implementation: Mature tool, ready for immediate implementation
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4. ROUTE 4. ROUTE INFORMATION AND INFORMATION AND
GUIDANCEGUIDANCE Multi-origin, multi-destination, multi-route per O-D pair. Multi-origin, multi-destination, multi-route per O-D pair. Fixed direction signs: shortest path in absence of congestionFixed direction signs: shortest path in absence of congestion Rush hoursRush hours Changing demands, weather conditions, exceptional events, Changing demands, weather conditions, exceptional events,
incidentsincidents
underutilisation of infrastructureunderutilisation of infrastructure
congestion, delays, reduced safety, increased fuel congestion, delays, reduced safety, increased fuel
consumption, environmental pollutionconsumption, environmental pollution
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VMS (Variable Message Signs) or two-way communication with VMS (Variable Message Signs) or two-way communication with
equiped vehiclesequiped vehicles Real-time information: Real-time information:
– – Drivers’ knowledgeDrivers’ knowledge
– – Message lengthMessage length
– – Decision efficiencyDecision efficiency
– – System controllabilitySystem controllability
– – Travel time or queue length: drivers’ stress (e.g. BP in Paris) Travel time or queue length: drivers’ stress (e.g. BP in Paris)
but also basis for route choicebut also basis for route choice
– – Instantaneous (estimation) or predicted informationInstantaneous (estimation) or predicted information
Route guidanceRoute guidance
– – Control strategyControl strategy
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Our Concept: Simple feedback-based route Our Concept: Simple feedback-based route guidanceguidance
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Automatic Control of VMS in Aalborg, DenmarkAutomatic Control of VMS in Aalborg, Denmark
Main goalMain goal: efficient crossing (northbound or southbound) of : efficient crossing (northbound or southbound) of
Limfjorden via BRIDGE (urban) or TUNNEL (motorway)Limfjorden via BRIDGE (urban) or TUNNEL (motorway)
Particularly in presence of incidents, road works etc.Particularly in presence of incidents, road works etc.
116 loop detectors; 14 VMS in front of important bifurcations116 loop detectors; 14 VMS in front of important bifurcations
Sample time: 1minSample time: 1min
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Two display modes (no real-time switch) Two display modes (no real-time switch)
– – Delay informationDelay information
– – Route RecommendationRoute Recommendation
Operational constraints:Operational constraints:
– – Information is the most accurate availableInformation is the most accurate available
– – Route recommendation according to user optimum principleRoute recommendation according to user optimum principle
– – No incompatible VMS displaysNo incompatible VMS displays
– – Police report inputPolice report input
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Aalborg network with VMS positions indicated.Aalborg network with VMS positions indicated. Bold black lines represent detector equipped segments.Bold black lines represent detector equipped segments.
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VMS control modes: Delay information (a) and route guidance (b).VMS control modes: Delay information (a) and route guidance (b).
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Automatic Control of VMS in the Interurban Scottish Highway NetworkAutomatic Control of VMS in the Interurban Scottish Highway Network
Motorway/Expressway NetworkMotorway/Expressway Network
Geographically extended (Geographically extended ( predictions necessary) but less predictions necessary) but less
complex in topology.complex in topology.
VMS: Combination of Information and Route RecommendationVMS: Combination of Information and Route Recommendation
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VMS Plans pre-approved (some 200)VMS Plans pre-approved (some 200)
Predictive/Feedback Strategy (Smith-Predictor type)Predictive/Feedback Strategy (Smith-Predictor type)
Off-line simulationsOff-line simulations
ImplementationImplementation
Dummy ControlDummy Control
Evaluation/ComparisonEvaluation/Comparison
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The Scottish interurban networkThe Scottish interurban network
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Glasgow integrated traffic controlGlasgow integrated traffic control
Also involved: Boulevard PAlso involved: Boulevard Péériphriphéérique travel time information rique travel time information
systemsystem
StatusStatus: Mature for implementation: Mature for implementation
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5. VARIABLE SPEED 5. VARIABLE SPEED LIMITSLIMITS
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Increasingly popular control measure with many applications Increasingly popular control measure with many applications
worldwide.worldwide.
Several evaluations indicate substantial safety improvements Several evaluations indicate substantial safety improvements
(– 30 % accidents)…(– 30 % accidents)…
… … but no efficiency improvements (e.g. no reduction of travel but no efficiency improvements (e.g. no reduction of travel
times)times)
Why?Why?
5. VARIABLE SPEED 5. VARIABLE SPEED LIMITSLIMITS
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1) Very simple threshold-based control strategies1) Very simple threshold-based control strategies
An example An example of VSL of VSL switching switching logic.logic.
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
5151The VSL switching logic at the Monash Freeway.The VSL switching logic at the Monash Freeway.
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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2) VSL impact on aggregate traffic flow not well known2) VSL impact on aggregate traffic flow not well known slope decreaseslope decrease
oocrcr increase increase
cross-pointscross-points
capacity increase(?)capacity increase(?)
capacity decreasecapacity decrease
(a)
(b)
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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3) Difficult fine-tuning of thresholds3) Difficult fine-tuning of thresholds
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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1) Automatic Fine-Tuning AFT21) Automatic Fine-Tuning AFT2
New ToolsNew Tools
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
5555AFT2 simulated application for VSL control.AFT2 simulated application for VSL control.
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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2) Different inputs: Slope of flow-occupancy curve2) Different inputs: Slope of flow-occupancy curve
3) Feedback-based VSL upstream of bottlenecks 3) Feedback-based VSL upstream of bottlenecks
as mainstream controlas mainstream control
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as ramp metering substituteas ramp metering substitute
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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No field-tested VSL control strategy availableNo field-tested VSL control strategy available
Discussions with a road authority ongoingDiscussions with a road authority ongoing
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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6. URBAN SIGNAL 6. URBAN SIGNAL CONTROLCONTROL
Most available signal control strategies are less suitable Most available signal control strategies are less suitable under under
saturated traffic conditionssaturated traffic conditionsQueue spillback Queue spillback – – Wasting of green timeWasting of green time – – Increased delays (all Increased delays (all movements)movements) – – Blocked exitsBlocked exits – – Accelerated queue increaseAccelerated queue increase – – Queue spillbackQueue spillback . . . . . . – – Serious infrastructure Serious infrastructure degradationdegradation . . .. . . – – Gridlock: Infrastructure breaks Gridlock: Infrastructure breaks downdown
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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Traffic congestion = Traffic congestion =
temporarily and locally d > smaxtemporarily and locally d > smax
++
lack of efficient controllack of efficient control
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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The TUC strategyThe TUC strategy
TUC Strategy
Controldecisions
Controldecisions
Signal Plans
PriorityPlans
Traffic Lights
URBAN ROAD NETWORK
Mea
sure
men
t dat
a
Data Processing
Offset Control
methodology:decentralized feedbackcontrol law
aim:coordination of mainstages of successivejunctions along arterials
Split Control
methodology:multivariable linear-quadratic control law
aim:minimization of risk ofoversaturation andqueue spillback
Cycle Control
methodology:feedback algorithm(P-regulator)
aim:cycle adjusting to themaximum saturationlevel
Public Transport Priority
methodology:rule-based algorithm
aim:provide priority to publictransport vehicles
Based on modern control and Based on modern control and
optimisation methodsoptimisation methods Efficient under saturated Efficient under saturated
traffic conditions as welltraffic conditions as well Simple, easy to implementSimple, easy to implement One measurement per linkOne measurement per link One communication with One communication with
central computer per cycle.central computer per cycle.
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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TUC field-applicationsTUC field-applications
a) Chania, Greece (23 junctions) a) Chania, Greece (23 junctions)
4A 4B 5 7 8
6
14
9 10 11
D3
O21
L7
O3 D4
L8
L9
L10
L11
L12
O4 D5
L13L14
L15L63
L16
O5D6
O6
D7
D14
L17
L18
L34
L35
L36
O14
D15
D24
O24
L37
L38
O15
D16
O16
L53
L54
L55
D17
D23
L56
L57
O22
L48
L41L40
L39
D20
L50L51
L4
16A
O7D8
L19
L20 16B
O8
13
12
L21
L22
O9D9
L23
L24
L25
O10D10
O11
D11
L27L28 L26
18O12
O13O23D13
D12
2A 2B
3A 3B
17
O2
L6
D2
L58
L59
L60
D19
D18
O17
L49
L47
O18
L43 L42
O1
D22
O20
1A
1B
1C
D1
L1
L2
L62L61
L45 L44
L46
O19D21
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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b) b) Southampton, Southampton, UK (53 UK (53 junctions)junctions)
6 b5 6 a
1 6
1
4
2
3 7
P 1 0 2 1 4
J 1 0 2 3 1
1 5
J 1 0 2 2 1
J 1 0 2 1 1
J 1 0 2 4 1
9
8
1 0
1 8
1 7
1 9
2 0 a
2 0 b
1 1
1 2
1 4
J 1 0 1 2 1
J 0 9 1 2 1
P 0 9 1 1 4
J 0 9 1 1 1
P 0 9 1 2 4
J 0 9 1 3 2
J 1 0 3 1 1
J 0 9 1 3 1
J 1 0 3 2 1
J 1 0 3 3 1
J 1 0 3 4 1
J 1 0 3 5 1
J 1 0 1 1 1
1 3
J 1 0 3 6 1
P 1 0 1 2 4
1
2
3
45
67
9
8
1 01 1
1 2
1 3
1 4
1 5
1 6
1 7
1 8
1 9
2 0
2 1
2 2
2 3
2 4
2 62 5
2 7 2 8
3 13 0
2 9
3 2
3 3
3 6 3 7
3 5
3 4
3 8 3 9
4 2
4 3
4 0
4 1
4 4
4 54 6
4 7
4 8
5 0
5 5
5 3
5 4
5 6
5 7
5 8
6 2
6 0 6 1
6 7
6 3
6 4 6 5
6 8 6 9
6 6
7 0
7 1 7 2
7 3
7 57 4 7 6
7 8
7 7
7 9
4 9
5 25 1
5 9
( b )
5 4
5
6 7
1 8
1 7
1 9
3 4
1 0 a
1 6
1 5
2
1
2 0
8 9
2 1 2 32 2
1 4 1 3 a
1 2 1 1
2 5
2 4
2 7
2 6
2 9
2 8 a 3 2
3 1
3 0
3 4
3 5
3 3
3 7
3 6 a
1
2
34
5
6
7
8
9
1 0
1 1
1 2
1 3
J 0 4 1 2 2
J 0 4 1 2 1
P 0 4 1 3 4 J 0 4 1 3 1
J 0 4 1 4 1
1 0 b
P 0 4 1 5 6
P 0 4 1 5 4
P 0 4 1 5 7
P 0 4 1 5 5
1 4
J 0 7 3 2 2
J 0 7 3 6 1
J 0 7 3 1 1
J 0 7 1 8 1
J 0 7 3 3 1
1 51 6
1 7
1 8
1 9
2 0
2 1
2 2
2 3
2 4
2 5
2 6
1 3 b
2 8 b
3 6 b
J 0 7 3 4 1
J 0 7 1 1 1
J 0 7 1 2 1
J 0 7 1 3 1 J 0 7 1 4 1 J 0 7 1 5 1
J 0 7 1 6 1 J 0 7 1 7 1
P 0 7 1 9 4
P 0 7 1 9 5
J 0 7 3 5 1
J 0 7 3 8 1
P 0 7 3 7 4
P 0 7 4 1 5
P 0 7 4 1 4 J 0 7 4 1 1
P 0 7 4 2 5
J 0 7 4 2 1
P 0 7 4 2 4 J 0 7 2 2 1
2 7
2 8
2 9
3 0
3 1
3 3 3 2
3 4
3 5
3 6
3 7
3 8 3 9 4 0
J 0 7 3 7 1
J 0 7 2 1 1
4 1
J 0 7 3 2 1
4 2
4 3
4 44 54 6
4 7
4 8
4 9
5 05 1
5 2
5 3
5 5
5 6
5 8 5 7
5 9 6 0
6 1
6 2
6 3
6 4
6 5
6 6
6 7
6 8
6 97 0
7 17 2
7 3
7 47 5
7 6
7 77 8
7 9
8 0
8 1
8 2 8 3
8 4
8 5
8 6
8 7
8 8
8 9
9 0
9 1
9 2
9 3
9 4
9 5
9 6
9 7
9 8
9 9
1 0 0
1 0 2 1 0 3 1 0 4 1 0 5
1 0 6
1 0 7
1 0 8
1 0 1
1 0 9
1 1 1 1 1 2
1 1 31 1 4
1 1 5
1 1 6
1 1 7
1 1 8 1 1 9 1 2 0
1 2 1
1 2 2
1 2 3
1 2 4
1 2 5
1 2 6
1 2 7
1 2 8
1 2 9
1 3 0
1 3 4
1 3 5
1 3 3
1 3 1
1 3 2
1 3 6
1 4 0 1 4 1 1 4 2
1 4 3
1 3 9
1 4 5
1 4 6
1 4 7
1 4 8
1 3 7 1 3 8
1 4 4
1 1 0
( a )
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
6464
c) Munich, Germany (25 junctions)c) Munich, Germany (25 junctions)1 3 1
5
14
13
12
10
11987654 16
1719
20
21
24
22
23
25
26
27
2
Inn
ere
-Wie
ne
r st
r
Orle
an
s
18
Zweibrucken srt.Rosenheimer srt
3a
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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Independent evaluation report: Independent evaluation report:
The demonstrations proved that TUC is a robust and credible The demonstrations proved that TUC is a robust and credible
signal control strategy, both as a stand-alone system, as insignal control strategy, both as a stand-alone system, as in
Chania and Southampton, and as a hybrid system. Despite Chania and Southampton, and as a hybrid system. Despite
its limited fine tuning, TUC stood up very well against the its limited fine tuning, TUC stood up very well against the
well-established and well-fine-tuned resident systems of the well-established and well-fine-tuned resident systems of the
test networks, which have very different characteristics with test networks, which have very different characteristics with
regard to network layout, detector locations within the links regard to network layout, detector locations within the links
and traffic behaviour.and traffic behaviour.
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
6666
Glasgow, ScotlandGlasgow, Scotland
MacaMacaé, Brazil (in final implementation phase)é, Brazil (in final implementation phase)
Athens, Greece (planned)Athens, Greece (planned)
Tel Aviv and Jerusalem, Israel (feasibility studies)Tel Aviv and Jerusalem, Israel (feasibility studies)
StatusStatus: Mature tool; ready for immediate implementation: Mature tool; ready for immediate implementation
Other TUC ApplicationsOther TUC Applications
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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– – Main control measures:Main control measures:
7. INTEGRATED URBAN-7. INTEGRATED URBAN-FREEWAY TRAFFIC CONTROLFREEWAY TRAFFIC CONTROL
Ramp meteringRamp metering Signal controlSignal control VMSVMS
in metropolitan areas.in metropolitan areas.
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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– – Drivers perceive the overall network as an entity Drivers perceive the overall network as an entity
– – Aims:Aims:
Harmonise actions of various control measuresHarmonise actions of various control measures Avoid antagonistic actionsAvoid antagonistic actions Maximize synergyMaximize synergy
– – Several de facto implementations but very few Several de facto implementations but very few
methodological approaches:methodological approaches:
Optimisation-based (LP)Optimisation-based (LP) Optimal controlOptimal control LQ control: LQ control: IN-TUCIN-TUC
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
6969
Urban Traffic Control
methodology:application of linear-quadratic control
aim:balancing of vehicleswithin urban links
Ramp Metering
methodology:application of ALINEAlocal feedback controllaw
aim:maintainance ofmainstream occupancyat desired level
CORRIDOR NETWORK
Urban Traffic Lights VMSsOn-Ramp Traffic
Lights
sign
al p
lans
VM
Ss d
ispl
ays
sign
al p
lans
Sign
Common measurement data
Controldecisions
Controldecisions
IN-TUC Strategy
VMS Control
methodology:application offeedback control
aim:equalization of traveltimes betweenalternative routes
Functional architecture of IN-TUC strategyFunctional architecture of IN-TUC strategy
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
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The Glasgow Site & the GoalThe Glasgow Site & the Goal
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
7171
Effect of Control on Road Throughput and on Journey TimesEffect of Control on Road Throughput and on Journey Times
Time period: 16:00 – 17:00
Road Throughput Journey Times
veh/hr Percentage Change sec Percentage Change
Base Case
Ramp Metering
UITC UITC and VMS
Base Case
Ramp Metering
UITC UITC and VMS
Motorway 36721 +5 +6 +6 210 5 * *
Urban Diversion Routes
3087
+13
+20
+23
440
+4
*
+1
Urban Network 20157 –3 –10 –6 1174 * 11 15
Total Network 60324 +2 * * 1567 2 –10 –13
** Not statistically significantNot statistically significant
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
7272
8. MOTORWAY TRAFFIC 8. MOTORWAY TRAFFIC SURVEILLANCESURVEILLANCE
RENAISSANCE RENAISSANCE
State prediction algorithm
Traffic state prediction
Boundary value prediction
.1Kk , ,1k ),(ˆp d
)(ˆ kx
network trafficstate estimation
State estimation algorithmComplete image of the currentnetwork state (estimation)(including non-measured inflows and outflows)
Motorway network( indicatesmeasurement locations)
Real-timemeasurements
)(ky
)(ˆ kx
pKk , ,1k ),(ˆ x Travel-time prediction, queue-tail prediction etc.
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
7373
Definition of queue(threshold of density)
Parameter estimation forfundamental diagram(yes / no)
Travel timeestimation
Traffic stateprediction
Travel timeprediction
Boundary valueprediction
Traffic measurements(flow, speed, occupancy)
incident report
Prediction horizon (Kp)
Queue tailestimation
Traffic detector specifications: location type (video/loop) kind of measurements sampling rate
Visualization
Queue tailprediction
Historicaldata
Currentqueue tails
Instantaneoustravel times
Future queuetails
Experiencedtravel times
Global user options
Module-orienteduser options
Real-timeinputs
Outputs
Automaticincident
alarmIncident alarm
)(ˆ kx
)(ˆ x
Routespecification
Network specifications: global model parameters network topology link characteristics
Definition of queue(threshold of density)
Operation parameterspecifications: output frequency noise variances
Module-orienteduser options
Traffic stateestimation
Traffic stateprediction
Traffic measurementand user option
processing
Traffic measurement processing: smoothing (yes/no) plausibility limits
pKkk , ,1
Traffic stateestimation
Possible erroror warninginformation
Structure of RENAISSANCEStructure of RENAISSANCE
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
7474
A92, Munich, Germany (7 km)A92, Munich, Germany (7 km)
A3, Napoli,-Salerno (100 km)A3, Napoli,-Salerno (100 km)
AntwerpAntwerp
StatusStatus: Mature tool (estimation); ready for immediate: Mature tool (estimation); ready for immediate
implementationimplementation
RENAISSANCE ApplicationsRENAISSANCE Applications
ADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECEADVANCED TRAFFIC CONTROL TECHNIQUES FOR FREEWAY SYSTEMS (AND URBAN NETWORKS), DSSL, TUC, GREECE
7575
Real-time toll plaza controlReal-time toll plaza control
9. OTHER CONTROL TOOLS9. OTHER CONTROL TOOLS
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Simulation Example: Work ZoneSimulation Example: Work Zone
M = 3 μ = 1; capq = 2,300 veh/h