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Computerised
Traffic Management
By Dr David Maddison, VK3DSM
If you are frustrated sitting in traffic now, you may take solace in the
fact that it could be far worse without computerised traffic management.
Australia is a world leader in many of the traffic management systems
Image source: https://unsplash.com/photos/aerial-photo-of-vehicles-on-highway-XICpU0Aulr0
described in this article.
S
treets and intersections with light
traffic, such as suburban and country roads, generally do not require
automated traffic flow control. They
might instead use Give Way signs, Stop
signs, or roundabouts to prevent traffic conflicts and keep traffic flowing.
However, beyond a certain level of
traffic flow, traffic lights are typically
installed to control traffic better and
prevent blockages.
Contrary to popular belief, traffic lights are not always beneficial.
Although traffic lights can reduce
the likelihood of T-bone collisions,
they can increase the likelihood of
14
Silicon Chip
rear-end collisions. For example, the
city of Philadelphia, USA, found that
“… replacing (traffic) signals by multiway stop signs on one-way streets is
associated with a reduction in crashes
of approximately 24%”.
Famous Dutch traffic engineer Hans
Monderman said that stripping all
traffic controls from a city resulted in
safer roads (www.wired.com/2004/12/
traffic). I have also observed that traffic seems to flow more smoothly when
a set of traffic lights is out of service.
Regardless of the benefits or drawbacks of traffic lights, we are stuck with
them. Given that, the best way to keep
Australia's electronics magazine
traffic moving is to coordinate them so
drivers are not forced to stop at every
intersection. There are levels of traffic management beyond that, intending to keep traffic flowing as fast and
smoothly as possible across an entire
road network.
Examples of other traffic control
strategies are variable speed limits,
lane direction changes, ramp entry
timings (metering), variable tolling
and even changing the traffic direction
of entire roads. As an example, some
motorway onramps in Sydney’s North
Shore change to offramps at certain
times of day, depending on demand.
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It is important to bear in mind that,
no matter how advanced any traffic management system is, if there is
insufficient physical road infrastructure to suit the demand, there will
still be slowdowns or stoppages. However, the severity of those problems
can sometimes be reduced with good
management.
This doesn’t just apply to cars,
motorbikes, trucks and coaches. Bad
traffic flow can also impede public
transport vehicles such as buses and
trams, as well as bicycle riders.
Modern electronic traffic management comes within the purview of
‘Intelligent Transport Systems’ (ITS).
ITS uses information and communications technologies, traffic sensors and
software to manage a road transportation system.
Cooperative ITS (C-ITS) involves
road users communicating with each
other, plus local and central traffic
management systems, to improve
safety and efficiency.
Adaptive traffic control is a means
by which traffic signal timing, variable speed limits, entry onto motorways (ramp metering), lane direction
changes and other techniques can be
varied to optimise traffic flows according to demand.
Loosely speaking, a “platoon” of
vehicles (or the French version of
the word, peleton) is a group of vehicles travelling together. More strictly
speaking, it refers to groups of vehicles
travelling very closely together as part
of an intelligent transportation system,
with a controlled distance between
them, much like the carriages of a train.
If platooning is fully automated, it
allows increased capacity on a given
road, reduces air resistance (lowers
fuel consumption) and reduces collisions, although it may result in lesser
driver attention. Adaptive cruise control (where a radar or camera is used
to keep a constant distance from the
vehicle in front) enables a primitive
form of platooning.
A major objective of traffic signal
coordination or “progression” is to
allow a group or platoon of cars travelling along a particular route to get a
highly desirable “green wave”, passing through many consecutive intersections without stopping. A motorist’s dream...
Important parameters
Before covering traffic management
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Silicon Chip
methods, we should explain what traffic flow parameters need monitoring
and possibly adjustment. The basic
variables to be dealt with and controlled as part of any traffic management strategy are as follows:
• Volume or traffic flow – the number of vehicles passing a fixed point,
measured in vehicles per hour.
• Speed – vehicle speed, instantaneous or average, either individually
or as a stream. It is typically measured
in kilometres per hour (km/h).
• Concentration or density – the
number of vehicles occupying a given
length of road at an instant in time,
measured in vehicles per kilometre
or metre.
• Headway – the interval between
vehicles passing a fixed point, measured in seconds per vehicle.
• Spacing or distance headway –
the distance between vehicles passing
a certain fixed point, typically measured in metres per vehicle.
• Occupancy – a measure of the proportion of time vehicles are stationary
at a specific point in a lane, such as
over a detector loop or other sensor. It
is reported as a percentage.
As part of any traffic management
system, a wide variety of sensors must
collect data like the above, to be analysed and acted upon in real time. They
can use techniques such as:
• A light beam that’s broken when
a vehicle passes.
• An inductive loop that detects the
metal of a vehicle above.
• Analysis of radar returns.
• Image analysis from a camera.
• Observations from within the traffic stream, such as via smartphones.
• Active vehicle identification,
such as at tolling points.
• Other methods, which we will
discuss later.
Traffic signals (traffic lights)
The modern traffic light or signal is the most fundamental form of
electronic traffic management. The
first traffic signals (for horse-drawn
vehicles) were installed in London
in 1868.
They used semaphore-style indicators; the first electric traffic lights were
installed in Cleveland, Ohio in 1912.
The first four-way, three-colour traffic
lights were installed in Detroit, Michigan in 1920.
All of those were manually controlled, but by 1922, traffic lights were
Australia's electronics magazine
controlled electronically by automatic timers, saving vast amounts of
labour. Australia’s first traffic lights
were installed in Sydney in 1933 (see
siliconchip.au/link/abu2). Additional
traffic lights were not installed in Australia until 1937.
Computers started to be used to
control traffic lights in the 1950s. In
1963, Toronto, Canada implemented
a computerised traffic light system
that controlled intersections across
the city with communication over
leased phone lines, using 1000 vehicle detectors.
That system was initially responsible for 500 intersections, with the
control computer able to handle 1164
intersections. However, Toronto was
rapidly expanding, and the computer
was running out of capacity, so the
system was upgraded in the early
1980s.
Also in 1963, SCATS (Sydney Coordinated Adaptive Traffic System)
started controlling eight intersections
in Sydney’s CBD. We’ll come back to
that system later.
At the most basic level, traffic signals can be either fixed-time or actuated. Fixed-time or interval-based
operation means the signals operate
according to a fixed sequence and
timing, repeating the same sequence
regardless of the number of vehicles
on each road. The timing of such signals may change according to a schedule. Such signals are now rarely used
in Australia.
Traffic-actuated or phase-based signals rely on the input from sensors,
such as an inductive loop in the road,
to determine timing and sequencing
and adjust their operation according
to traffic demand. That is for just one
set of signals for one isolated, non-
coordinated intersection. Beyond that,
sets of traffic signals at multiple locations can be coordinated to facilitate
the green wave.
Isolated traffic-actuated and fixedtime controls are now not generally
used in Australia since the increased
adoption of SCATS Master Isolated
(SMI) control.
A SCATS controller may be run in its
regular mode, linked to a regional computer as part of a wide-area traffic control system, or in an isolated mode for
single non-coordinated intersections.
When running a non-
coordinated
intersection, SMI still uses SCATSstyle adaptive algorithms.
siliconchip.com.au
Types of traffic light sequences
include:
• Fixed sequence that never varies.
• Tr a f f i c - a c t u a t e d s k i p p e d
sequence, where some sequences are
skipped if there is no traffic needing
a certain sequence.
• Variable sequence that uses near
real-time measurement of traffic via
detectors to constantly adjust timing
and sequences according to demand.
• Priority sequence, inserting a
sequence to accommodate a train,
bus or tram.
• Forced sequence, determined
by a master controller in a centrally-
coordinated system.
There is also emergency vehicle priority or ‘preemption’ where traffic signal phasing can be adjusted to facilitate the passage of emergency vehicles,
using techniques such as:
• In-vehicle transponder.
• Emergency sequences activated
from stations or facilities near traffic
signals to clear traffic.
• GPS tracking of an emergency
vehicle, communicated to a central
controller to implement appropriate
sequences as the vehicle arrives at
each intersection.
• A phone call to a central traffic
control office to implement appropriate sequencing along the emergency
vehicle route.
Traffic signal coordination
If you ever get a run of green lights
(green wave), it is likely the result of
traffic signal coordination to time the
length & duration of the green phases.
This concept is called “traffic signal
progression”; it is “the practice of coordinating the operations of two or more
signalised intersections” – see Fig.1.
The problem gets more complicated
the more sets of traffic lights are to be
coordinated, and even more complex
when considering crosswise traffic
flows. Crosswise traffic might experience increased delays in such a system. Pedestrian movements and other
road users also have to be considered.
Traffic signal terminology
Each possible legal trajectory of traffic at an intersection is called a movement. At a basic two-way intersection,
there can be 12 movements, with traffic in each approach being able to go
left, right or straight ahead.
A traffic signal phase is a set of traffic signal indications applying to vehicles or pedestrians, allowing simultaneous non-conflicting legal movements. For example, a phase might
Offset reference point is beginning of first co-ordinated phase yellow
Fig.1: traffic lights can be synchronised to avoid vehicles having to stop and go constantly, but there are limits to such
synchronisation. The purple and blue lines represent the outer limits of a green wave. Original source: www.kittelson.
com/ideas/pros-and-cons-of-signal-coordination/
siliconchip.com.au
Australia's electronics magazine
May 2024 17
Fig.2: an example of an intersection with three phases and parallel pedestrian
movement. Original source: https://austroads.com.au/ (Guide to Traffic
Management Part 9, page 81).
Fig.3: traffic light phases (intervals). Original source: https://austroads.com.au/
(Guide to Traffic Management Part 9, page 222).
Fig.4: the desired sequence of
operations for a four-way intersection,
which can be implemented in a
Programmable Logic Controller (PLC),
microcontroller or other means, or
in earlier times, electromechanically
with relays and timers.
have north-south traffic seeing green
in both directions while also allowing
left turns for both sets of traffic.
A particular phase in the sequence
can be skipped if there is no demand
for it; eg, a right turn phase could be
skipped if no cars are waiting to turn.
Fig.2 illustrates an intersection with
three phases.
Phase sequence is the order of
phases in a signal cycle. These may be
fixed or altered according to demand.
Signal groups are sets of individual lights that share the same colour
and are all activated for a particular
phase. They are identified by which
phase they belong to, such as the green
lights associated with phases A, B or
C in Fig.2.
A cycle is a complete rotation
through all possible phases. The cycle
time is the time taken to move through
all possible phases (sequences) at an
intersection.
An interval refers to the change
from one phase to another, either the
running phase interval (green) or the
clearance phase interval (yellow and
some red) – see Fig.3.
Phase split is the proportional of
cycle time a given phase is displayed.
Offsets are the time relationships
between green phases of successive
sets of signals when the system is
coordinated.
Vehicle detectors may obtain information for either ‘strategic’ or ‘tactical’ purposes. Strategic information is used to compute cycle length,
phase splits and signal offsets. Tactical
information is used to determine the
demand or duration of phases.
The traffic controller
Original source: https://
instrumentationtools.com/plc-based4-way-traffic-light-control-system/
18
Silicon Chip
Australia's electronics magazine
The traffic signal controller is the
heart of a set of traffic signals. Older
ones contained relays and mechanical timers, while modern types are
microprocessor-controlled and receive
inputs from various sources. They generate various outputs and communicate with other controllers and central
management systems.
Typical traffic signal sequencing is
shown in Fig.4, while the inputs, outputs and communications for a typical
controller are shown in Fig.5.
One Australian company making
traffic controllers is Aldridge Traffic
Controllers, now owned by Siemens
Mobility (siliconchip.au/link/abu1).
They designed and manufactured
the ATSC4 Adaptive Traffic Signal
siliconchip.com.au
Controller (Fig.6). It can manage up to
32 signal (phase) group displays with
up to 64 inputs from vehicles, pedestrians or emergency services.
It can operate in standalone mode
or as part of an Intelligent Transportation System such as SCATS. It can
communicate via Ethernet with a local
network or 4G modem, ADSL or PSTN
networks, supports VC6 SCATS protocol and DSRC (Dedicated Short Range
Communications, see later) and comes
with advanced software.
Preventing hazardous signal
combinations
It would be disastrous if all signals
at an intersection showed green simultaneously. This can be prevented by
interlocked switching and/or conflict
monitoring. For example, in relay- Fig.5: operation of a modern traffic signal controller. Original source: https://
controlled circuits, if one signal group austroads.com.au/ (Guide to Traffic Management Part 9, page 85).
shows green, the conflicting signal
◀ Fig.6: the ATSC4 Adaptive Traffic
groups are forced to red.
Signal Controller, which is
This can be done by methods like
SCATS compatible. Source: www.
cutting the power to conflicting green
aldridgetrafficcontrollers.com.au/
signals when one is activated. In solid-
products/traffic-signal-controllers/
state relay controlled systems, the outatsc4
puts must be monitored to ensure safe
signal groups and avoid unsafe groups,
as per Fig.7.
Traffic sensors
It is necessary to measure the traffic
flow to control traffic. There are various ways of doing that. Stationary
sensors can measure traffic flow, but
in other cases, the data comes from
vehicles. The latter example is known
as Floating Car Data (FCD). FCD can
also be used by Apps like Google Maps
and Waze to provide information about
road hazards such as accidents, construction works, potholes etc.
Automatic Number Plate
Recognition (ANPR)
ANPR is used for tolling and legal
compliance but can also provide traffic flow data. Optical character recognition is used along with algorithms
to locate the position of the number
plate in an image.
Bicycle and pedestrian counters
Some traffic management systems
include bicycle counters. Bicycles are
counted using much the same technology as cars. One example at Veloway
1 in Woolloongabba, Queensland is
shown on the Department of Transport’s website (siliconchip.au/link/
abu3). It uses a camera and artificial
siliconchip.com.au
Fig.7: safe and unsafe combinations of signals. Original source: https://
austroads.com.au/ (Guide to Traffic Management Part 9, page 88).
Australia's electronics magazine
May 2024 19
Fig.8: a pedestrian counting system in the City of Melbourne.
Source: www.pedestrian.melbourne.vic.gov.au/#date=26-022024&sensor=RMIT14_T&time=15
intelligence (AI) to classify traffic as
either pedestrians, cyclists or riders
of some other device.
There is a Pedestrian Counting
System in the City of Melbourne (see
siliconchip.au/link/abtq). It uses laser
or thermal sensors to record pedestrian movements. The sensors are
connected to a 4G wireless data transmission system, a central server and
a visualisation system. The data can
be seen with an online visualisation
tool at www.pedestrian.melbourne.
vic.gov.au (see Fig.8).
People-counting systems are also
used for measuring occupancy in
places such as shopping centres, entertainment venues, libraries, government buildings and retail stores.
Cameras
Software can be used to analyse
video streams from any source to
count and classify vehicle traffic. Such
cameras typically use AI and machine
learning (ML). An example is shown
in Fig.9.
Fig.9: analysing a video stream using the Camlytics software (https://camlytics.
com/). Some software does offline analysis, like this one, while others do it in
real-time. Source: https://camlytics.com/solutions/car-counting
Fig.10: how an inductive loop traffic sensor works. Original source: www.
researchgate.net/publication/287003681
20
Silicon Chip
Australia's electronics magazine
Mobile phone data (FCD)
Tracking mobile phone signals from
car users requires no roadside or other
infrastructure, and nearly all cars have
at least one mobile phone on board.
Privacy concerns aside, no specific
permission is required to do this, as
mobile phone towers already obtain
such data as part of their function.
Location and speed data is obtained
via triangulation of the phone signal
and hand-over data from tower to
tower. Collecting such data from large
numbers of phones enables traffic flow
to be monitored (and, incidentally,
pedestrian traffic).
Inductive loop sensors
Inductive loop traffic sensors have
an insulated wire loop or loops embedded in the roadway to detect traffic –
see Fig.10. You can often see where
they are because the road has been cut
and resealed to embed the wire. The
loop is energised at 10-200kHz. It acts
as a tuned circuit that changes in frequency when a mass of metal, such as
a car, is nearby.
This change in frequency is detected
by the associated electronics and interpreted as the presence of a vehicle.
One problem with such loops is that
they may not register the presence of
a small vehicle such as a motorcycle,
scooter or bicycle. We have also seen
siliconchip.com.au
cases where people stop short of the
sensor and never get a green light!
Figs.11 & 12:
the TIRTL
processor
(left) and
transmitter
(below).
Source:
CEOS Pty
Ltd.
GPS data (FCD)
Some phone apps like Google Maps
and Waze (now owned by Google)
upload GPS data, which is used for
various purposes, such as choosing
optimal routes to avoid traffic. In a
sense, it is ‘crowdsourced’ traffic data.
Infrared sensors
An example of an infrared traffic
sensor is the Australian-developed
TIRTL (The Infra-Red Traffic Logger)
– see Figs.11 & 12. It consists of an
infrared transmitter and receiver on
opposite sides of the road. As vehicles interrupt the beams, it can record
the number and type of vehicles, their
speed and which lane they are in.
The information can be logged for
statistical purposes or traffic control.
It can also be connected to a red light
and/or speed camera to record violations, detect over-height and overlength vehicles, be used for bus lane
enforcement and various other applications. Some of its operating modes
are shown in Fig.13.
It is a product of CEOS (www.ceos.
com.au/products/tirtl/) and is used in
twenty countries. Commercial sales
started in 2002.
Fig.13: some of the operating modes of the TIRTL. Original source: www.ceos.
com.au/products/tirtl/
Piezoelectric sensors
Piezoelectric material converts
stress into an electric charge, which
can be measured to detect a load such
as a vehicle. They can detect the number of vehicles, number of axles, vehicle speed and weight.
Pneumatic road tubes
These familiar devices, used on a
temporary basis for traffic surveys,
consist of one or more rubber tubes
across a road. They sense vehicles as
they drive over and compress air in
the tube, activating a switch in the
electronics box at the side of the road.
Software can determine the number of axles and speed of the vehicle,
plus the number of vehicles that pass.
With two tubes, the travel direction
can be sensed.
Radar sensors
Radar sensors measure road traffic
and perform tasks such as counting
and classification, incident detection,
wrong-way detection, ramp metering,
lane blockage detection and queue
siliconchip.com.au
Fig.14: lane-specific forward-looking radar detection using a smartmicro device
(right) compared to a side-mounted radar device (left).
Australia's electronics magazine
May 2024 21
Fig.15: the smartmicro-MLR MultiLane Radar detector mounted on a
pole. Source: www.yunextraffic.com/
wp-content/uploads/2023/06/YunexTraffic_Smartmicro-MLR_EN.pdf
length measurement, among others.
Objects such as pedestrians, bicycles,
motorbikes, passenger cars, transporters, short trucks and long trucks can
be sensed and classified.
One such device from smartmicro
(www.smartmicro.com) has multiple
forward-firing beams, can simultaneously detect 256 vehicles and provide
lane-specific detection for up to 12
lanes with a 500m range (see Fig.14).
The device (Fig.15) can also be used to
trigger speed and/or red light cameras.
Detecting emergency vehicles
A typical “emergency vehicle preemption” system involves an emitter
attached to an emergency vehicle, a
detector at a traffic signal and an optical signal processor. As an emergency
or other priority vehicle approaches a
signal, optical emissions are detected,
and the signals switch to green for the
emergency vehicle.
A typical installation is shown in
Fig.16, as per VicRoads specification
TCS 055-1-2005. VicRoads uses the
Tomar STROBECOM II emitter, detector and optical signal processor (see
siliconchip.au/link/abtr).
Fig.16: a typical emergency vehicle preemption system. Original source: www.
vicroads.vic.gov.au/-/media/files/technical-documents-new/its-specificationstcs/specification-tcs-055--emergency-vehicle-preemption.ashx
adjusting speed limits, changing freeway ramp entry timing etc. Products
that do this include:
Australian Integrated Multimodal
EcoSystem (AIMES)
AIMES is described as a “worldfirst living laboratory based on the
streets of Melbourne, established to
test highly integrated transport technology with a goal to deliver safer,
cleaner and more sustainable urban
transport outcomes”.
It is an experimental system by the
University of Melbourne, the Victorian
Department of Transport and Planning,
and industry partners.
It uses a mesh of individual smart
sensors to track pedestrians, cyclists
and traffic within a city’s transport
system of intersections, tramways, bus
routes and traffic signals. The goal is to
achieve more efficient and productive
use of transport infrastructure.
It is said to be the world’s first and
largest ecosystem for testing new transport management technologies, incorporating 100km of roads bounded by
Lygon & Hoddle Streets and Victoria
& Alexandra Parades in Melbourne.
Information from such a system could
be used to operate a driverless car or
improve pedestrian or cyclist safety.
A 2.5km test corridor along Nicholson Street in inner Melbourne with
comprehensive monitoring and sensors at every intersection provides
improved traffic flow and safety for all
types of vehicles and traffic.
The Nicholson Street intelligent
corridor integrates data from existing
sources such as CCTV footage, Bluetooth signals from personal devices,
the Sydney Coordinated Adaptive
Traffic System (SCATS), General Transit Feed Specification (GTFS) and sensors specifically installed for AIMES
– see Fig.17.
Vehicle re-identification (FCD)
Vehicles can be detected at one location and then at another location. This
enables travel time and speed to be
calculated between pairs or groups of
sensors. A vehicle can be sensed by the
MAC address of any Bluetooth device
in the car, by reading RFID serial numbers from devices such as toll tags or
using number plate recognition.
Traffic management systems
Once traffic data is collected, it
needs to be analysed and appropriate actions taken. Possible actions
include altering traffic signal timings,
22
Silicon Chip
Fig.17: the “Kapsch Intelligence Corridor”, featuring part of the AIMES
Nicholson Street “intelligent corridor” in Melbourne.
Australia's electronics magazine
siliconchip.com.au
Machine learning and analysis are
used to process CCTV images, then the
EcoTrafiX platform is used to visualise and manage sensor data. Cloudbased AI and predictive models are
also used.
According to Dr Neema Nassir, the
system uses “machine learning models that can optimise – through millions of simulation executions – the
best right-of-way allocation, or the
best green traffic light time allocation
for competing modes and competing
volumes”.
ARCADY
Assessment of Roundabout Capacity
and Delay from the Transport Research
Laboratory, UK (https://trl.co.uk/) is
used to model roundabouts and “...
predict capacities, queues, delays and
accident risk at roundabouts”.
COMPASS
This traffic management system in
Ontario, Canada, uses in-road traffic
sensors to measure the speed and traffic flow on freeways. The data goes to
a central computer so operators can
view the data and cameras. They use
the McMaster algorithm to change
message signs and speed limits.
Kapsch EcoTrafiX
This traffic visualisation and management platform (www.kapsch.net/
en) is from Austria; see Fig.18. It
includes traffic signal control, adaptive traffic control, event management,
traffic prediction, travel information,
data fusion and more.
Other Kapsch products used in
Australia and NZ are toll collection
systems in Melbourne, Sydney, Brisbane and Auckland using Dedicated
Short-Range Communications (DSRC),
video-based detection and classification and Automatic Number Plate Recognition (ANPR); the Nicholson Street
intelligent corridor and AIMES and the
Eastlink tolling system in Melbourne.
In Queensland, they demonstrated
a Cooperative Intelligent Transport
System (C-ITS) to send warning messages about road works to appropriately equipped vehicles.
MASSTR
Meadowlands Adaptive Signal System for Traffic Reduction (www.njsea.
com/transportation/masstr/) is an
adaptive traffic control system used
in the New Jersey (US) Meadowlands
area, coordinating 125 traffic signals.
It uses the Australian-designed SCATS
software and is its fourth-
l argest
deployment worldwide.
McMaster Algorithm
This is a widely used traffic congestion detection algorithm based on
the mathematical branch known as
catastrophe theory. Speed, flow and
lane occupancy (density) are analysed.
If there is a dramatic loss in speed
without a corresponding drop in flow
and density, that suggests an incident
has occurred.
MOVA
Microprocessor Optimised Vehicle
Actuation from the Transport Research
Laboratory (UK) was introduced in the
1980s for controlling isolated sets of
traffic signals.
NoTraffic
NoTraffic (https://notraffic.tech/),
founded in 2017 in Israel, is the
world’s first AI-powered traffic management platform that fuses data from
traffic sensors such as cameras, radar
and information from vehicles via V2X
(see later) and IoT technology with
artificial intelligence.
AI is used for NoTraffic’s computer
vision neural networks and traffic optimisation algorithms. NoTraffic can be
retrofitted at any intersection to connect it ‘to the cloud’. It can run in a
fully autonomous mode, communicating with other intersections, road
users and managers.
Managers establish intersection and
corridor policies with NoTraffic (see
Fig.19). AI is used to classify and manage traffic according to those policies
to maximise road capacity (see Fig.20).
NoTraffic also provides information
so traffic managers can better understand road networks by “understanding the root cause of traffic issues and
applying the most relevant and effective solutions on a case-by-case basis”.
NoTraffic can communicate with
connected vehicles via V2X to provide alerts and rerouting information
for accidents and hazards (see Fig.21).
Fig.18: the
Kapsch
EcoTrafiX
software.
Source:
NYSERDA
Department of
Transportation
siliconchip.au/
link/abu4
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May 2024 23
It operates in Arizona and California,
USA, among other places.
One recently demonstrated capability of the system is the ability to detect
a “red light runner” approaching an
intersection and warn drivers with a
green light going in other directions to
stop to avoid a collision (see https://
youtu.be/aEuyUY28qzc).
The NoTraffic video channel can
be found at www.youtube.com/<at>
NoTraffic
Fig.19: NoTraffic allows intersection policies to be set up on its dashboard.
OSCADY
Optimised Signal Capacity and
Delay is modelling software from the
Traffic Research Laboratory (UK) that
“calculates capacities, queues and
delays for isolated (uncoordinated),
traffic signal-controlled junctions. It
can evaluate a set of known signal timings, and optionally, it can optimise
stage (phase) lengths and/or cycle time
to minimise delay”.
PICADY
Priority Intersection Capacity and
Delay is modelling software from the
Traffic Research Laboratory (UK) for
the “prediction of capacities, queues,
delays and accidents at isolated priority junctions”.
Fig.20: NoTraffic uses AI to classify traffic types. Source: https://youtu.be/O_
Bpyuu_URI
Rayven
This Australian company offers an
IoT platform for a “traffic monitoring
and intelligent highway solution” to
integrate “infield devices, sensors,
third-party systems, and machinery
to deliver real-time and predictive
insights, as well as all-new capabilities to improve safety, maintenance,
and use.” It is primarily for monitoring rather than traffic management –
see siliconchip.au/link/abts
Fig.21: information that NoTraffic might display in a V2X-connected vehicle.
Source: https://youtu.be/O_Bpyuu_URI
SCATS
Sydney Coordinated Adaptive Traffic System was introduced in 1963 as
a pilot controlling eight intersections
in the Sydney CBD using valve-based
IBM equipment. By 1970, DEC PDP11 computers controlled intersections,
followed by microprocessor-based
traffic signal controllers in 1974.
SCATS is owned and developed by
Roads & Maritime Services (RMS) in
NSW. It is now used in many countries,
controlling 37,000 intersections, and
is considered one of the world’s leading adaptive traffic control systems.
4200 intersections in Sydney are
controlled by one SCATS system. In
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Victoria, SCATS controls over 4000
intersections in Melbourne, Ballarat,
Bendigo, Traralgon, Geelong and
Mildura. SCATS is used in another
150 cities in 27 countries, including
the USA, Brazil, Singapore, India,
Malaysia, Ireland, South Africa, Fiji
and China.
SCATS runs on Microsoft Windows via one or more regional controllers and a central manager computer. A central manager can control
64 regional controllers (regions). Each
regional controller can manage 250
traffic signal controllers (intersections)
for a total of 16,000 intersections.
There is plenty of redundancy, as
each regional controller can continue
to operate even if communication with
the central manager is lost. If regional
controllers fail, there is a fall-back
mode to local individual intersection
control by the local traffic signal controller.
The ATSC4 traffic signal controller
is specifically designed to work with
SCATS. SCATS controls three principal signal parameters: cycle time,
phase split and offset.
SCATS works at two levels: strategic and tactical. At the strategic level,
regional controllers receive data from
vehicle detectors to assess flow and
occupancy data and optimise cycle
length, phase splits and offsets for an
area (groups of intersections).
At the tactical level, individual traffic signal controllers use data from
local vehicle sensors to omit signal
phases if no vehicles are waiting. Even
though there is tactical local control,
ultimately, the system is coordinated
by the regional controllers.
SCATS uses a measurement known
as the degree of saturation (DS), a
measure of road capacity utilisation
determined by traffic sensors during
green phases. A figure over one means
there is insufficient green time to
satisfy demand and the road is congested. Cycle length is adjusted to
keep DS around 0.9. Phase splits are
also adjusted to keep the DS about
equal for different approaches to the
intersection.
When using a SCATS traffic signal
controller (eg, the ATSC4) for the first
time, the signal controller will provide
the initial default timings. Then the
SCATS regional controller will start
to adjust the timings (self-calibrate)
according to the traffic flow at that
junction. It will attempt to balance
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and coordinate flows between neighbouring junctions as demand requires.
SCATS can turn off coordination
between intersections if necessary,
such as during periods of light traffic when traffc at some intersections
might flow better without coordination.
SCATS can also prioritise the passage of certain vehicles, such as public
transport buses and trams. If a pedestrian presses a button to cross the road,
the signal phasing will be altered to
run the pedestrian phase. SCATS can
also be set for special events or other
special purposes.
VicRoads claims the following benefits from SCATS in Victoria: travel
times down by 21%, stops down by
40%, fuel consumption down by 12%
and fewer crashes due to smoother
traffic flow.
Fig.22 shows a SCATS interface
window. The pie chart (on the left)
shows the length of time for each
phase, while a map of the junction is
on the right, with the different signal
phases shown to its left.
SCOOT
The Split Cycle Offset Optimisation
Technique is an adaptive traffic control system for groups of traffic signals
that are close together. It was first introduced by the Traffic Research Laboratory (UK) in 1979. Its purpose is to
adjust signal timings based on input
from sensors to minimise delays. It is
used in 350 towns worldwide.
SURTRAC
Scalable Urban Traffic Control
(https://miovision.com/surtrac/) was
developed at Carnegie Mellon University in Pittsburgh, USA. It is an adaptive traffic control system that optimises traffic flows along corridors and
complex urban grid networks.
It uses artificial intelligence that
treats the “intersection control challenge” as a “single machine scheduling
problem” to optimise each intersection
and share information with neighbouring intersections, to enable coordination and control across the whole
network. The operational concept is:
1. Traffic conditions are established
from sensor data.
2. The appropriate traffic signal
phase schedule is computed for flow
optimisation at intersections.
3. The schedule is transmitted to
downstream intersections.
4. Rescheduling occurs every few
seconds.
It is used in Pittsburgh, USA and
Peterborough, Canada.
TRANSYT
(TRAffic Network StudY Tool)
This traffic modelling software was
introduced in 1967 by the Transport
Fig.22: a SCATS interface window. Source: www.aldridgetrafficcontrollers.
com.au/ArticleDocuments/230/Introduction_To_New_Generation_Scats_6_5.
pdf.aspx
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May 2024 25
Research Laboratory (UK) to optimise
signal timing and perform simulations for “designing, evaluating and
modelling everything from single isolated road junctions to large mixed
signal-controlled and priority control
traffic networks”.
The results from the modelling can
be used to optimise signal timing,
SCOOT timings, for performance prediction and platoon modelling.
UTC
Urban Traffic Control, from the Traffic Research Laboratory (UK), takes
data from SCOOT to coordinate traffic
signal controls over a wide area, such
as an urban road network.
Veronet
This traffic management system
uses artificial intelligence to manage
traffic and traffic signals, supporting
inflows and outflows for a city, and
optimising certain directions. It also
supports autonomous driving modes
for cars that support that mode. See
www.veronet.eu/home.html
Waze
This navigation software (Fig.23) is
“free” (because your data is the product). It is now owned by Google. It
collects vast amounts of user data for
driver navigation and other purposes.
However, traffic managers can also
feed that data to traffic management
software or use it to visualise traffic
flows, monitor conditions on key
routes and observe changes over time.
Heavy vehicle monitoring
in Australia
The National Heavy Vehicle Regulator operates a network of fixed digital cameras called the National Safety
Camera Network to monitor the movement of heavy vehicles by recording
number plate data. The network has
over 120 cameras covering more than
5800km of road across five jurisdictions with an average of 4.2 million
“sightings” per month.
According to their website, they
“use safety camera, registration, crash,
defect, intercept and infringement data
to generate profiling reports to identify
operators, vehicles, drivers and infrastructure of interest”.
There are also five mobile Automatic
Number Plate Recognition (ANPR)
cameras to detect the number plates
of passing heavy vehicles. Their website shows trailer-, vehicle- and dronemounted cameras. According to the
website, the mobile cameras are “used
to develop policies and programs to
increase road safety”.
Traffic Management Channel
The Traffic Management Channel
(TMC) is a worldwide system delivering digital traffic data via commercial FM broadcast stations that can
be displayed on a car’s built-in GPS
map system (or, in some cases, add-on
systems). It is incorporated into the
existing Radio Data System (RDS), typically used to transmit station identification and program information.
The protocols used for RDS-TMC
data are ALERT C or TPEG. Such data
can also be delivered via Digital Audio
Broadcasting (DAB) or satellite radio.
Information that can be delivered
relates to traffic events, containing an
event code, location code, expected
incident duration, affected extent and
any other relevant details.
Vehicle navigation systems can use
this data to generate an optimum route.
This system only requires the reception of an FM, DAB or satellite radio
signal from a cooperating broadcaster.
Intelematics Australia (www.
intelematics.com, owned by the
RACV) broadcasts encrypted RDSTMC data under the brand SUNA Live
Traffic to provide live traffic updates
to participating in-car navigation systems and compatible add-on GPS
devices. Originally, SUNA was only
transmitted via FM radio, but today,
it is also delivered over the mobile
data network.
According to the peak body for
advanced transport technology, ITS
Australia (https://its-australia.com.
au/), SUNA is used by 90% of vehicles in Australia and NZ.
According to ITS, their “road traffic
data is collected through thousands of
probes and sensors located on roads, in
vehicles and infrastructure” and “We
enrich our data using multiple proprietary sources and machine taught
algorithms”.
Intelematics has advised us that
SUNA will be discontinued.
In the past, Intelematics also maintained historical traffic databases that
could be used for future road and
traffic planning via the discontinued
software tool INSIGHT (siliconchip.
au/link/abtt).
The INSIGHT software tool allowed
visualisation of historic and present
real-time data of such parameters as
traffic volume or turning volume at
intersections over periods of 15 minutes, days, months or years. It allowed
the impact of various events or infrastructure changes to be determined.
VicRoads “Smarter Roads”
Fig.23: Waze data being used to manage traffic by the Port Authority of New
York and New Jersey. Source: https://support.google.com/waze/partners/
answer/10715145?hl=en
The VicRoads Smarter Roads program (see siliconchip.au/link/abu5)
includes CCTV, travel time sensors, live
travel information signs and pedestrian
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crossing sensors. There are 2500 CCTV
cameras covering most suburban traffic
signals in Victoria, used by the Traffics
Operations Centre to monitor traffic
incidents and traffic flows. There are
also 400 wireless travel time sensors
and 43 live travel time signs.
According to VicRoads, these cameras are not used for law enforcement purposes, and the video is not
recorded, so it is not available for evidentiary purposes, such as for accident
liability. However, that could change.
Pedestrian detectors determine the
number of pedestrians waiting to cross
the road & prevent unnecessary waiting (https://youtu.be/vyyN92qT6OY).
They also monitor roadside air quality.
Fig.24: Sydney’s WestConnex road and tunnel network use Smart Motorways
technologies. Source: www.westconnex.com.au/explore-westconnex/
WestConnex Smart Motorways
WestConnex private motorways
around Sydney (Fig.24) use “Smart
Motorways”, their proprietary name,
for technologies such as vehicle detection, CCTV cameras, ramp signalling,
lane use management and variable
speed limits.
Smart Motorways are designed to
operate and integrate with the rest of
the Sydney (non-WestConnex) road
network and the existing SCATS system. WestConnex Motorway operations are controlled from the Motorway Control Centre (MCC) shown in
Fig.25.
Self-driving vehicles
Australia’s laws do not currently
support autonomous vehicles on public roads; the National Transport Commission released a policy paper on the
subject in 2022. An Automated Vehicle Safety Law (AVSL) is proposed by
2026 (siliconchip.au/link/abtu).
In the USA, California allowed
driverless taxis in San Francisco, but
permission was suspended after an
accident with a pedestrian. Similar
laws are under development in several countries.
V2X
V2X or “vehicle-to-everything”
refers to communication to and from
a vehicle for traffic management and
other purposes. V2X incorporates concepts such as those listed below and
shown in Fig.26:
• V2D (vehicle-to-device): Apple
CarPlay or Google Android Auto.
• V2G (vehicle-to-grid): connecting
an EV to a smart electrical grid.
• V2I (vehicle-to-infrastructure): a
siliconchip.com.au
Fig.25: Australia’s largest Motorway Control Centre (MCC) at St Peters, Sydney,
with 60 panels. It provides monitoring and incident response for the M4, M8
and M5 East motorways. Source: www.westconnex.com.au/media-releases/
australia-s-largest-motorway-control-centre-supporting-westconnex-motorists/
Braess’ Paradox
Braess’ Paradox is the counter-intuitive idea that adding an extra road can
increase the average travel time. Conversely, closing roads can sometimes
decrease travel time (of course, that isn’t always true!). The idea is used in
traffic planning and management. For example, a section of road could be
opened or closed depending on traffic conditions.
The basic problem is that drivers don’t know what other drivers are going
to do. If a new, high-capacity road is opened, many drivers who would otherwise take different routes might decide to use that road, resulting in their
paths intersecting and generating heavy traffic and delays.
If a smaller number of the drivers took the new road while others
remained on the smaller roads, the average travel time could decrease, but
that would require either good luck or coordination.
It is also applicable in electrical networks, biological networks and even
sports; for example, the addition of a champion player might decrease the
team’s overall efficiency if there is an over-reliance on that player.
For more information, see the video on “The Spring Paradox” at https://
youtu.be/Cg73j3QYRJc
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May 2024 27
vehicle communicating with traffic
lights, parking meters etc.
• V2N (vehicle-to-network): comms
via WiFi or the mobile network for
remote diagnostics and monitoring.
• V2P (vehicle-to-pedestrian):
provide alerts from vehicles to
pedestrians’ smartphones, coordination with pedestrian crossings, prediction of pedestrian behaviour, automatic sounding of vehicle horn.
• V2V (vehicle-to-vehicle):
exchanging data with neighbouring vehicles, such as warning of
Fig.26: some examples of V2X communications in a country that drives on
the right-hand side of the road. Original source: www.researchgate.net/
publication/279765559
vehicles or pedestrians that cannot
be seen directly due to obstacles, or
an approaching emergency vehicle.
Information for V2X can be obtained
from various sensors, as shown in
Fig.27. Sensor data management and
communication are performed by the
V2X OBU (On-Board Unit). An example of a commercial OBU is shown in
Fig.28.
The original V2X technology was
based on WLAN (Wireless LAN) IEEE
802.11p, which is now incorporated
into IEEE 802.11. The term used by
the SAE (Society of Automotive Engineers) for this technology is DSRC
(Dedicated Short Range Communication). In Europe, it is known as ITS G5.
DSRC has a range of up to about
1km, supporting V2I and V2X. Unfortunately, the DSRC systems used in
Europe, Japan and the USA are incompatible. In Australia, DSRC uses the
5.9GHz band. Australian E-Toll tags
use RFID transponders with a DSRC
protocol.
DSRC can also be used for cooperative cruise control, cooperative collision warning, warning of an approaching emergency vehicle and warning of
a railway level crossing.
3GPP C-V2X uses mobile networks
for V2X communications. C-V2X also
uses the 5.9GHz band, like DSRC, for
short-range communications and has
about 25% better range than DSRC.
There is no restriction on range as
long as a mobile tower is nearby. It
supports V2I, V2V and V2N. It was
originally based on 3G but now uses
5G. DSRC and C-2VX are competing
technologies.
Variable tolling
Fig.27: vehicle sensors that might be used for V2X communications and other
purposes. OBU stands for On-Board Unit. Original source: www.researchgate.
net/publication/279765559
Some authorities advocate variable
tolling, supposedly to reduce congestion, as a form of traffic management.
Such a scheme operates on the Sydney
Harbour Bridge. According to Wikipedia, it has been minimally effective,
only reducing traffic by 0.19%.
Other management systems
Fig.28: a Commsignia ITS-OB4 V2X on-board
unit (OBU). An equivalent roadside unit can receive data from units like this for
traffic management purposes. Source: www.itsinternational.com/its2/products/
commsignia-gets-green-light-c-v2x-units
28
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Traffic management systems aren’t
just restricted to roads. Systems are
needed for air traffic management,
space traffic management (to ensure
satellites do not collide), rail traffic
management, sea and harbour traffic
management and even underwater
traffic management! Similar schemes
and approaches apply, but generally
with different sensors.
SC
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