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Intelligent Urban Transport Management
System
Assignment 4
Name Muhammad bin Ramlan
Matrix No. P57600
Subject KA 6423
Session 2012/2013
Lecturer Prof Ir Dr Riza Atiq O.K. Rahmat

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Question
Your hometown administrator wants to install an Urban Traffic Management System.
You are given a task to evaluate the following systems:
SCATs
SCOOT
ITACA
MAXBAND
UTOPIA-SPOT
BALANCE
RONDO (Rolling horizoN based Dynamic Optimization of signal)

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Answer
1. SCATs
Introduction
In 2010, As of December 2010, SCATS has been distributed to 145 cities in 24
countries worldwide controlling more than 33,500 intersections.Aldridge Traffic
Controllers (ATC) are an RTA authorised Distributor of the world leading SCATS™
Urban Traffic Management Control (UTMC) System.ATC have a large team of
SCATS™ Urban Traffic Management System qualified technical personnel to
support customers in the design, deployment and implementation of the SCATS™
system including the supply of its own Traffic Signal Controllers giving clients a total
system solution.
The SCATS™ Urban Traffic Management System is a MS-Windows based software
solution that works in a tiered fashion via 1 or more Regional Controllers (RC) that
means traffic authorities are getting a highly redundant and therefore resilient system
for maximum visibility and control of traffic.ATC have designed its latest generation
of Traffic Signal Controller to be compatible with SCATS™ to provide traffic
authorities with a single supplier solution for complete Urban Traffic Management
Systems.

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Application
Most of Highway operator in Malaysia using SCATS to control their traffic lights in
urban area. These very popular SCATS are an area wide traffic management system
that operates under the Windows environment. It controls the cycle time, green splits
and offsets for traffic control intersections and mid-block pedestrian crossings. With
the inclusion of vehicle detectors, it can adaptively modify these values to optimize
the operation to suit the prevailing traffic. Alternatively, it can manage intersections in
fixed-time mode where it can change plans by time of day, day of week. It is
designed to coordinate traffic signals for networks or for arterial roads.
Intersection connections to a regional traffic control computer can be permanent or
may be on-demand using dial-in or dial-out facilities. Each regional computer can
manage up to 250 intersections. A SCATS system can have up to 64 regional
computers.
Monitoring is provided by a graphical user interface. Up to 100 users can connect to
a SCATS central manager at the same time. Up to 30 users can connect to a single
regional computer simultaneously. Performance monitoring, alarm condition
notification and data configuration facilities are included. SCATS automatically
collect alarm and event information, operational and performance data and historical
data. SCATS operate automatically but operation intervention is provided for use in
emergencies.
Benefit
The popular concept is that coordinating traffic signals is simply to provide green-
wave progression whereby a motorist travelling along a road receives successive
green signals. While this is one of the aims, the principal purpose of the control
system is to minimise overall stops and delay and, when traffic demand is at or near
the capacity of the system, to maximise that capacity (throughput) and minimise the
possibility of traffic jams by controlling the formation of queues.
Can be upgraded or expanded to meet changing requirements, other applications
can be integrated into the system and provides details/reports of traffic flows for
other planning purposes.SCATS enable a hierarchical system of fall back operation
in the event of temporary communications failure. Such equipment faults are
monitored by the system

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2. Scoot
Introduction
SCOOT is the world's leading adaptive traffic control system. It coordinates the
a
operation of all the traffic signals in an area to give good progression t vehicles
to
through the network. Whilst coordinating all the signals, it responds intelligently and
continuously as traffic flow changes and fluctuates throughout the day. It removes
the dependence of less sophisticated systems on signal plans, which have to be
expensively updated.

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Application
Information on the physical layout of the road network and how the traffic signals
control the individual traffic streams are stored in the SCOOT database. Any
adaptive traffic control system relies upon good detection of the current conditions in
real-time to allow a quick and effective response to any changes in the current traffic
situation.
SCOOT detects vehicles at the start of each approach to every controlled
intersection. It models the progression of the traffic from the detector through the
stop line, taking due account of the state of the signals and any consequent queues.
The information from the model is used to optimize the signals to minimize the
network delay.

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The operation of the SCOOT model is summarized in the diagram above. SCOOT
obtains information on traffic flows from detectors. As an adaptive system, SCOOT
depends on good traffic data so that it can respond to changes in flow. Detectors are
normally required on every link. Their location is important and they are usually
positioned at the upstream end of the approach link. Inductive loops are normally
used, but other methods are also available.
When vehicles pass the detector, SCOOT receives the information and converts the
data into its internal units and uses them to construct "Cyclic flow profiles" for each
link. The sample profile shown in the diagram is color coded green and red
according to the state of the traffic signals when the vehicles will arrive at the stop
line at normal cruise speed. Vehicles are modeled down the link at cruise speed and
join the back of the queue (if present). During the green, vehicles discharge from the
stop line at the validated saturation flow rate.
The data from the model is then used by SCOOT in three optimizers which are
continuously adapting three key traffic control parameters - the amount of green for
each approach (Split), the time between adjacent signals (Offset) and the time
allowed for all approaches to a signaled intersection (Cycle time). These three
optimizers are used to continuously adapt these parameters for all intersections in
the SCOOT controlled area, minimizing wasted green time at intersections and
reducing stops and delays by synchronizing adjacent sets of signals. This means
that signal timings evolve as the traffic situation changes without any of the harmful
disruption caused by changing fixed time plans on more traditional urban traffic
control systems.
Benefit
Throughout its life SCOOT has been enhanced, particularly to offer an ever wider
range of traffic management tools. The traffic manager has many tools available
within SCOOT to manage traffic and meet local policy objectives
SCOOT detectors are positioned where they will detect queues that are in
danger of blocking upstream junctions and causing congestion to spread
through the network
SCOOT will continuously monitor the sensitive area and smoothly impose
restraint to hold traffic in the specified areas when necessary.
SCOOT naturally reduces vehicle emissions by reducing delays and
congestion within the network. In addition it can be set to adjust the
optimisation of the signal timings to minimise emissions and also provide
estimations of harmful emissions within the controlled area

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3. ITACA
Introduction
ITACA - An Intelligent Traffic Area Control Agent. It has an Adaptive Subsystem that
operates with a traffic model and produces Cycle Split and Offset times for a
centralized area of traffic control. These times minimize delay and stops of traffic
moving in the area.ITACA provides real time urban traffic control by computing the
best solution for every intersection and continuously adapting signal sequences to
match traffic demand.
The ITACA Intelligent Adaptive Traffic Control System uses real time traffic flow
data, obtained from detectors located in the field, to model traffic line-ups at every
stop line. It then continuously adjusts traffic signal parameters (cycle, split and offset)
at every intersection in order to minimize the number of stops and delays throughout
the street network within the ITACA system's control.
The system produces small and frequent changes in traffic control parameters that
smoothly adapt the traffic control plan to evolving changes in traffic demand. In this
way, the negative effects on the network that otherwise would be caused by plan
changes - such as flow disturbances and time delays in re-establishing flow - are
avoided.

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Application
Currently (as per 2011) there are 150 numbers of junctions that had been installed
with traffic signals in Putrajaya. There are junctions that are fully operated, while
some were operated in ‘Flashing Amber' and a few others are still under construction
(ducting and cabling works in progress).
An the latest news in Malaysia for greater KL done by Special Task Force to
Facilitate Business (Pemudah) said the initiatives included enforcing the towing of
vehicles of traffic offenders and implementing traffic monitoring using Sydney''s
Coordinated Area Traffic System (SCATS) and Intelligent Traffic Adaptive Control
Area (ITACA) to further enhance traffic flow.
In opposite to the traditional system, the ITACA introduce enhancement to every 5
seconds on carry on a time of collection and processing to the transportation data.
All produces the corresponding parameter to each street intersection to distinguish
the treatment. (In system has each street intersection in entire network accurate
position, therefore system all collects information from each street intersection all
neighbors street intersection). Each several cycles on have carried on a time of
adjustment according to the system computed result to each stature region cyclical
length, namely cyclical adjustment.
Each cycle all carries on the assignment adjustment according to the system
computed result to each street intersection different green light time, namely the
green letter compares the adjustment. Each cycle all starts the time according to the
system computed result to each street intersection cycle to carry on the adjustment
namely phase adjustment. It may act according to the transportation expert's
experience and carries on the optimization to the system. Under this condition, it will
introduce the ITACA system from following several aspects. Firstly, the system
structure systems control divides into three ranks: The first level is the control center,
it and the street intersection machine connects through the region controller. The
second level is region controller CMY. The third level is street intersection controller
RMY. The system structure following chart shows:
ITACA is the intellectualized auto-adapted transportation control system, this system
by the real-time control way work, and can most greatly expand to 4,800 street
intersections controls.

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Center control level.
The general center control level is composed by a control server and the
client.
The center control level installs ITACA software, realizes the communication
function, the database handling and function, the software start and software
stops the function.
The Central computer system is connected continuously with region control
machine maintenance communication, and then through region control
machine and street intersection machine maintenance communication.
The region control machine transmission and the receive data and the control
command, the central computer may in any time and the region control
machine exchange information.
ITACA software gathers the information involves:
The street intersection machine reports to the police starts to report to the
police the conclusion with the street intersection machine.
Street intersection machine active status change.
The street intersection machine interior saves control form condition and
change situation
The region control machine reports to the police starts to report to the police
the conclusion with the region control machine.
Region control machine condition change
Vehicles detector condition and examination data.
When ITACA auto-adapted pattern, the system inquires to the detector wheel
with clear zero works every 5 seconds to carry on time.
To ITACA software may the manual start or the automatic start.
Under two methods, ITACA software all defers to the quite same not less than step
start. After ITACA software stops the movement, all street intersections machine can
automatically degrade to locally control the pattern, according to in advance the local
transportation control plan automatic movement which compiles in various street
intersections machine. After ITACA software restarts, it can automatically succeed
with the central computer connected all equipment connects the system, before
cannot because starts in ITACA software some equipment already add the electricity
work but to need them to restart. After ITACA software starts successfully, the entire
transportation control system will be able automatically local to control the pattern
from the street intersection machine to cut to the ITACA software control pattern, will
safeguard the entire transportation network to be at the optimizing control condition
as necessary.

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Benefit
Has included the auto-adapted traffic signal control system in the existing new
technical method, it is the intelligent transportation control system core. It uses the
auto-adapted traffic signal control system, may reduce the transportation in the
existing path to support stops up with the driving delays, reduces the traffic accident
the formation rate and the mortality rate, simultaneously may cause the energy the
consumption reduction, reduces the pollution degree.
TelventTráfico y Transporte (original SaincoTrafico) took is engaged in the
transportation control for a long time the well-known company and the Spanish
Oviedo university cooperation, in summarizes in the foundation which the
predecessor experiences, developed in 1990 has developed set of auto-adapted
traffic signals control system ITACA (Intelligent Traffic Adaptive Control of Areas) the
system. This system is based on the coil real-time collection data, in the computer
module the simulation real-time optimization movement, and real-time issues the
transportation control command, achieves the best transportation control effect the
advanced system. The ITACA system in the world many cities success movement,
the performance is outstanding, in domestic city and so on Beijing, Wuhan has the
small scale application, in the near future also in other city large-scale uses.

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4. MAXBAND
Introduction
Maxband is a bandwidth optimization program that calculates signal timing plans on
arterials and triangular networks. MAXBAND produce cycle lengths,offset, speeds
and phased sequences to maximize a weighted sum of bandwidths. The primary
advantage of MAXBAND is the freedom to provide a range for the cycle time and
speed. The lack of incorporated bus flows and limited field tests are disadvantages
of MAXBAND

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5. UTOPIA-SPOT
Introduction
The increasing traffic volume requires an integrated and balanced approach to traffic
management. The aim is to improve traffic over the whole area by minimizing travel
time for private traffic, while giving priority to public transport. In creating a better flow
of vehicles, it leads to energy savings, a reduction of emissions and a welcome
increase in safety. Urban Traffic Optimization by Integrated Automation (UTOPIA) is
widely regarded as one of the most advanced adaptive traffic signal control systems
available worldwide that has been successfully deployed in many places in Europe.
UTOPIA operates on distributed intelligence. The processing capabilities at
intersection level enable a swift response to the traffic volumes at the intersections.
This makes UTOPIA ideal for flexible traffic control and priority to specific identified
traffic, like public service vehicles.
Application
The power of UTOPIA is prediction. UTOPIA estimates how the traffic situation will
develop and calculates the best possible strategy. The ‘best strategy’ is based on a
so-called ‘cost function’ method. The cost function weighs issues such as delay time,
the number of stops and specific priority requirements. Taking into account the effect
on adjacent intersections, the distributed control is optimised for each intersection in
the network. All intersections communicate the expected traffic flow to neighbouring
intersections, allowing for a long prediction horizon.
E

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Benefit
Keeps the flow going;
Manages timely public transport;
Fully adaptive, adjusts to the traffic situation;
Realizes strategic traffic policy objectives;
Dynamic priority levels for public transport vehicles;
Tuned and tested in lab situation before installation on-site;
Open communication infrastructure.

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6. BALANCE
Traffic Computer Basel
Basel, the third-largest city in Switzerland, is an important European hub. More
than 700.000 people live in the metropolitan area. Many enterprises are based in
Basel, the city is a center for trade and culture and an intersection of the traffic
routes between Switzerland, Germany and France. Consequently, there is a lot of
traffic on Basel's roads and the highways around the city.
Basel's traffic computer, however, was built in 1979. Its technology is out-of-date and
does no longer meet today's demands. GEVAS software thus built up a new OCIT-
compatible traffic center in Basel together with Bergauer AG. The new traffic
computer communicates with the light signal systems via standardized OCIT
interfaces. As well, remote recording of light signal states and remote supply of the
control units are possible. In addition, the new center is connected to a superordinate
control system, which is a central window to the electronically facilities of the Swiss
national streets.
Traffic-Adaptive Network Control BALANCE
GEVAS-Roadshow in Düsseldorf, Berlin, Frankfurt and Munich
In a series of roadshows, GEVAS software presented traffic adaptive network control
BALANCE to experts and professionals from Germany and Austria. The events took
place in Düsseldorf, Berlin, Frankfurt and Munich.
Traffic-adaptive network control currently is a topic of many discussions in circles of
experts. New model-based methods like BALANCE offer optimal Green Waves and
are able to adapt signal programs to different traffic situations in an anticipatory way.
The traffic flow is therefore improved significantly. It wanted to give first-hand
information on the potential of traffic-adaptive network control BALANCE and on how
it can be integrated into existing systems. Out-of-date or overstrained signal
programs cause overall economic damage each day. With network control,
constantly increasing traffic in metropolitan areas can be handled. Air pollution and
traffic noise are reduced as well. Theirpilot project in Hamburg and the
implementation of BALANCE in the TRAVOLUTION project in Ingolstadt have
already shown how good traffic-adaptive network control works in practice. It is
important to stress that network control BALANCE can be integrated into existing
infrastructure without any problemand clearly reduces the user's expenses.

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7. RONDO
Introduction
Figure above shows a typical scenario that arises in Rondo when using destination
routing based on finding the shortest path. Traffic from nodes A to C and from nodes
B to C flows along a common set of network segments. With explicit routing through
MPLS tunnels, the data from node B to C can be rerouted to a longer but more lightly
congested path. The ability to monitor the global state of the network coupled with
the fine control afforded by MPLS makes congestion control possible in Rondo.
Application
Rondo uses a feedback loop to govern the behavior of traffic in the network core. It
manages the flows that originate and terminate between various PoPs (Points of
Presence) in the network by directing these flows into the multiple pathways that are
created using MPLS Label Switched Paths. These LSPs serve as conduits through
the network that are unaffected by the local optimization strategy of shortest path
routing. Rather, Rondo optimizes performance based on global traffic considerations
in the network.

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System Components
Rondo is composed of the major parts shown in Figure 2 above.
In the remainder of this paper, we will describe each element with emphasis on the
data collection subsystem and the analysis engine.
1) Physical Network
The experimental network is a set of 10 MPLS-enabled counters and
interconnections patterned after a much-scaleddown representation of a major
service provider’s network backbone as depicted on their web site. We note that the
provider has 2500 PoPs worldwide so our model has only rough equivalence to
reality. However, even with only ten routers, our network exhibits complex and often
fascinating behaviors. Routers are connected with 10-megabit links, which makes
possible the creation of realistic overloadconditions. Each router models a PoP
(Point of Presence) on the network where customer nodes are attached. In Rondo,
each node attached to a PoP is a PC that sends and receives packets.
The network uses a combination of Cisco® 3620 and 3640 series routers. The
release of Cisco’s IOS (Internet Operating System) available on our routers allows
only destination - based selection of MPLS tunnels. -Cisco is a registered trademark
of Cisco Systems, Inc. Upgrades will ultimately allow selection of the tunnels based
on other parameters in the IP packet.
2) Programmable Load Generators and Loading Strategy
We use a collection of PCs programmed to generate time-varying loads similar to
those expected in an operational network. Background network traffic on the network

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is constant in time and is generated by commercially available packet generators.
Loads are carefully crafted to cause a buildup of congestion that does not have an
overall steady state solution, and are designed to stress the given physical topology.
3) Data-Collection System
The data-collection system uses a variety of devices and techniques to monitor the
conditions in the network. These include both active and passive methodologies that
capture such characteristics as throughput, loss, delay and jitter. Data collection, a
key part of Rondo, uses an extensible architecture to provide rapid processing of
data under time constraints for its collection, reduction and transmission. Data flow
from the network probes through the collection system to the analysis engine with
little latency and to archival storage at a lower priority. Data are retained in a
database system for other applications such as service-level management that do
not require rapid data processing. We describe this part of the system in detail
below.
4) Data Model and Database
Rondo uses the database for a variety of classes of information including physical
and logical network topology, configuration information and archived measurement
data. The algorithms, displays and other components are driven by the information
described by this model, and as such, the organization of this model is crucial to the
effectiveness of Rondo. The model, which is important for other applications, is
realized in a relational database. The most important function of the database is to
hold the state of the network topology, which changes as the system reroutes LSPs
to alleviate congestion. The analysis and reroute engine periodically updates the
topology as the network is reconfigured.
5) Analysis and Rerouting Engine
This element of the system contains techniques for detecting congestion in a
network and altering the existing traffic flows to eliminate an overload condition. The
engine is designed to focus on more than link utilization, which is the most basic
metric of network performance. Utilization indicates the level of activity between
network elements and is often viewed as a measure of network congestion. This
view is too simple when one considers the classes of traffic that flow over an IP
network. High utilization of a link is one form of congestion, but others might include
excessive delay, jitter or high packet loss, all of which could happen at relatively low
levels of link utilization. These are measures of congestion that seriously affect
proposed services in next-generation IP networks, including voice and video. The
engine is designed use any measurable quantity as an indication of a network
problem that needs correction.
6) MPLS Configuration and Control
Rondo relies on MPLS to form explicit paths through the core network. Explicit paths
allow precise control over the placement of traffic flows within the routed domain of

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Rondo. All traffic in Rondo flows through explicitly routed MPLS tunnels, which
specify each node along a path from the ingress to egress routers. The network
configuration is initially optimal in the sense that all tunnels travel via the shortest
path in the network. Once established, packets enter the MPLS tunnels as a function
of their destination address and are delivered to the egress router.
Rondo thus uses MPLS as a mechanism for packet forwarding that is not directly
aware of quality of service. Mixing packets with different levels of quality of service in
an LSP is possible though but limits the effectiveness of available controls. Once the
initial explicit paths are established, the analysis and reroute engine operates to
reroute packets through a path established by a new MPLS tunnel, which may no
longer be the shortest path. This action currently takes place via IOS commands that
are issued from the controller. When MPLS traffic-engineering MIBs become
available, the controller will use SNMP to establish the new routes.
System Operation
The analysis and rerouting engine is in overall control of the system. The engine
communicates with the data collection system to establish a schedule of network
measurements. As the data collection system takes each measurement, it notifies
the analysis and rerouting engine of the presence of new data. The engine combines
the new data with the current system configuration and previous data to decide on
the appropriateness of rerouting an MPLS tunnel. If a move is appropriate, the
analysis engine reconfigures the network through the LSP configuration control and
updates the network state in the database.
As we discuss in the following, the route of the new MPLS tunnel does not
necessarily preserve overall network optimality. Rather our goal is to reroute traffic
as quickly as possible to minimize the congestion at the expense of achieving a
theoretical optimum over the whole network. Global optimization might imply moving
many or even all the routes in the network. The strategy in Rondo is to move from
one to a few MPLS tunnels over a period of a few minutes with minimal disruption to
network traffic.