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智能交通信号控制中英文对照外文翻译文献



智能交通信号控制中英文对照外文翻译文献



(
文档含英文原文和中文翻译
)



原文:


Intelligent Traffic Signal Control Using Wireless Sensor
Networks


athan and Vigneshwar. Santhanam

Abstract:
The growing vehicle population in all developing and developed countries
calls for a major change in the existing traffic signaling

systems. The most widely
used
automated
system
uses
simple
timer
based
operation
which
is
inefficient
for
non- uniform
traffic.
Advanced
automated
systems
in
testing
use
image
processing
智能交通信号控制中英文对照外文翻译文献

techniques
or
advanced
communication
systems
in
vehicles
to
communicate
with
signals and ask for routing. This might not be implementable in developing countries
as
they
prove
to
be
complex
and
expensive.
The
concept
proposed
in
this
paper
involves use of wireless sensor networks
to
sense presence of traffic near junctions
and
hence
route
the
traffic
based
on
traffic
density
in
the
desired
direction.
This
system does not require any system in vehicles so can be implemented in any traffic
system easily. This system uses wireless sensor networks technology to sense vehicles
and

a microcontroller based routing algorithm for traffic management.



Keywords:
Intelligent traffic signals, intelligent routing, smart signals, wireless sensor
networks.



I.

INTRODUCTION




The traffic density is escalating at an alarming rate in developing countries which
calls for the need of intelligent traffic signals to replace the conventional manual and
timer
based
systems.
Experimental
systems
in
existence
involve
image
processing
based
density
identification
for
routing
of
traffic
which
might
be
inefficient
in
situations
like
fog,
rain
or
dust.
The
other
conceptual
system
which
is
based
on
interaction
of
vehicles
with
traffic
signals
and
each
other
require
hardware
modification on each vehicle and cannot be practically implemented in countries

like India which have almost 100 million vehicles on road [1]. The system proposed
here involves localized traffic routing for each intersection based on wireless sensor
networks.
The
proposed
system
has
a
central
controller
at
every
junction
which
receives data from tiny wireless sensor nodes placed on the road. The sensor nodes
have
sensors
that
can
detect
the
presence
of
vehicle
and
the
transmitter
wirelessly
transmits the traffic density to the central controller. The controller makes use of the
proposed algorithm to find ways to regulate traffic efficiently.






II.

THE NEED FOR AN ALTERNATE SYSTEM




T
he
most
prevalent
traffic
signaling
system
in
developing
countries
is
the
timer
based
system.
This
system
involves
a
predefined
time
setting
for
each
road
at
an
智能交通信号控制中英文对照外文翻译文献

intersection. While this might prove effective for light traffic, heavy traffic requires an
adaptive system that will work based on the density of traffic on each road. The first
system
proposed
for
adaptive
signaling
was
based
on
digital
image
processing
techniques. This system works based on the captured visual input from the roads and
processing
them
to
find
which
road
has
dense
traffic.
This
system
fails
during
environmental interaction like rain or fog. Also this system in testing does not prove
efficient.
The
advanced
system
in
testing
at
Pittsburgh
[2]
involves
signals
communicating with each other and also with the vehicles. The proposed system does
not require a network between signals and vehicles and is a standalone system at each
intersection.


III.

THE PROPOSED SYSTEM




This paper presents the concept of intelligent traffic routing using wireless sensor
networks.
The
primary
elements
of
this
system
are
the
sensor
nodes
or
motes
consisting
of
sensors
and
a
transmitter.
The
sensors
interact
with
the
physical
environment while the transmitter pages the sensor

s data to the central controller.
This
system involves
the 4 x 2 array of sensor nodes in
each road. This
signifies 4
levels
of
traffic
and
2
lanes
in
each
road.
The
sensors
are
ultrasonic
or
IR
based
optical
sensors

which
transmits
status
based
on
presence
of
vehicle
near
it.
The
sensor
nodes
transmit
at
specified
time
intervals
via
ZigBee
protocol
to
the
central
controller
placed
at
every
intersection.
The
controller
receives
the
signal
and
computes
which
road
and
which
lane
has
to
be
given
green
signal
based
on
the
density of traffic. The controller makes use of the discussed algorithm to perform the
intelligent traffic routing.




IV
.

COMPONENTS INVOLVED IN THE SYSTEM







The proposed system involves wireless sensor networks which are comprised of
three
basic
components:
the
sensor
nodes
or
motes,
power
source
and
a
central
controller. The motes in turn are comprised of Sensors and transceiver module. The
sensors sense the vehicles at intersections and transceiver transmit the sensor

s data to
智能交通信号控制中英文对照外文翻译文献

the
central
controller
through
a
wireless
medium.
The
Power
source
provides
the
power needed for the sensor nodes and is mostly regenerative. The central controller
performs
all
the
computations
for
the
sensor
networks.
The
controller
receives
the
input from all sensors and processes simultaneously to make the required decisions.


s




Sensors are hardware devices that produce a measurable response to a change in a
physical condition like temperature or pressure. Sensors measure physical data of the
parameter
to
be
monitored.
The
continual
analog
signal
produced
by
the
sensors
is
digitized
by
an
analog-to- digital
converter
and
sent
to
controllers
for
further
processing.
A
sensor
node
should
be
small
in
size,
consume
extremely
low
energy,
operate in high volumetric densities, be autonomous and operate unattended, and be
adaptive
to
the
environment.
As
wireless
sensor
nodes
are
typically
very
small
electronic devices, they can only be equipped with a limited power source of less than
0.5-2
ampere- hour
and
1.2-3.7
volts.
Sensors
are
classified
into
three
categories:
passive
Omni-directional
sensors;
passive
narrow-beam
sensors;
and
active
sensors
[3].

The
sensors
are
implemented
in
this
system
placed
beneath
the
roads
in
an
intersection
or
on

the
lane
dividers
on
each
road.
The
sensors
are
active
obstacle
detectors that detect the presence of vehicles in their vicinity. The sensors are set in
four levels on each road signifying four levels of traffic from starting from the STOP
line. The fourth level indicates high density traffic and signifies higher priority for the
road
to
the
controller.
The
sensors
required
for
obstacle
detection
can
be
either
ultrasonic or Infrared LASER based sensors for better higher efficiency.




B. Motes




A mote, also known as a sensor node is a node in a wireless sensor network that is
capable
of
performing
some
processing,
gathering
sensory
information
and
communicating with other connected nodes in the network. The main components of
a sensor node are a microcontroller, transceiver, external memory, power source and
智能交通信号控制中英文对照外文翻译文献

one or more sensors [3].








Fig. 1 Block Diagram of a Mote



C.

Need for Motes



The
primary
responsibility
of
a
Mote
is
to
collect
information
from
the
various
distributed sensors in any area and to transmit the collected information to the central
controller for processing. Any type of sensors can be incorporated with these Motes
based
on
the
requirements.
It
is
a
completely
new
paradigm
for
distributed
sensing
and it opens up a fascinating new way to look at sensor networks.



D. Advantages of Motes

?

The core of a mote is a small, low- cost, low-power controller.

?

The controller monitors one or more sensors. It is easy to interface

all sorts of
sensors,
including
sensors
for
temperature,
light,
sound,
position,
acceleration,
vibration, stress, weight, pressure, humidity, etc. with the mote.


?

The
controller
connects
to
the
central
controller
with
a
radio
link.
The
most
common radio links allow a mote to transmit at a distance of about 3 to 61 meters.
Power
consumption,
size
and
cost
are
the
barriers
to
longer
distances.
Since
a
fundamental concept with motes is tiny size and associated tiny cost, small and
low-power radios are normal.

?

As motes shrink in size and power consumption, it is possible to imagine solar
power or even something exotic like vibration power to keep them running. It is
智能交通信号控制中英文对照外文翻译文献

hard
to
imagine
something
as
small
and
innocuous
as
a
mote
sparking
a
revolution, but that's exactly what they have done.

?

Motes are also easy to program, either by using serial or Ethernet cable to connect
to the programming board or by using Over the Air Programming (OTAP).


Fig. 2 Block Diagram of the Proposed System


E.

Transceivers






Sensor
nodes
often
make
use
of
ISM
band,
which
gives
free
radio,
spectrum
allocation and global availability. The possible choices of wireless transmission media
are
radio
frequency
(RF),
optical
communication
and
infrared.
Lasers
require
less
energy,
but
need
line-of-sight
for
communication
and
are
sensitive
to
atmospheric
conditions. Infrared, like lasers, needs no antenna but it is limited in its broadcasting
capacity. Radio frequency-based communication is the most relevant that fits most of
the
WSN
applications.
WSNs
tend
to
use
license-free
communication
frequencies:
173, 433, 868, and 915 MHz; and 2.4 GHz. The functionality of bothtransmitter and
receiver are combined into a single deviceknown as a transceiver [3].




To
bring
about
uniqueness
in
transmitting
and
receiving
toany
particular
device
various protocols/algorithms are devised. The Motes are often are often provided with
powerful transmitters and receivers collectively known as transceivers for better long
智能交通信号控制中英文对照外文翻译文献

range
operation
and
also
toachieve
better
quality
of
transmission/reception
in
any
environmental conditions.


F. Power Source





T
he
sensor
node
consumes
power
for
sensing,
communicating
and
data
processing. More energy is required for data communication than any other process.
Power
is
stored
either
in
batteries
or
capacitors.
Batteries,
both
rechargeable
and
non-rechargeable,
are
the
main
source
of
power
supply
for
sensor
nodes.
Current
sensors are able to renew their energy from solar sources, temperature differences, or
vibration. Two power saving policies used are Dynamic Power Management (DPM)
and Dynamic V
oltage Scaling (DVS). DPM conserves power by shutting down parts
of the sensor node which are not currently used or active. A DVS scheme varies the
power levels within the sensor node depending on the non- deterministic workload. By
varying
the
voltage
along
with
the
frequency,
it
is
possible
to
obtain
quadratic
reduction in power consumption.


G
.

Tmote Sky




Tmote
Sky
is
an
ultra
low
power
wireless
module
for
use
in
sensor

networks,
monitoring
applications,
and
rapid
application
prototyping.
Tmote
Sky
leverages
industry standards like USB and IEEE802.15.4 to interoperate seamlessly with other
devices.
By
using
industry
standards,
integrating
humidity,
temperature,
and
light

sensors, and providing flexible interconnection with peripherals, Tmote Sky enables a
wide
range
of
mesh
network
applications
[4].
The
TMote
is
one
of
the
most
commonly used motes in wireless sensor technology. Any type of sensor can be used
in combination with this type of mote.




Tmote Sky features the Chipcon CC2420 radio for wireless communications. The
CC2420
is
an
IEEE
802.15.4
compliant
radio
providing
the
PHY
and
some
MAC
functions
[5].
With
sensitivity
exceeding
the
IEEE
802.15.4
specification
and
low
power operation, the CC2420 provides reliable wireless communication. The CC2420
is highly configurable for many applications with the default radio settings providing
IEEE
802.15.4
compliance.
ZigBee
specifications
can
be
implemented
using
the
built-in

wireless transmitter in the Tmote Sky.

智能交通信号控制中英文对照外文翻译文献


Fig. 3 Tmote Sky



H. Tmote Key Features

?


250kbps 2.4GHz IEEE 802.15.4 Chipcon Wireless Transceiver

?

Interoperability with other IEEE 802.15.4 devices.

?


8MHz
Texas
Instruments
MSP430
microcontroller
(10k
RAM,
48k
Flash
Memory)

?

Integrated ADC, DAC, Supply V
oltage Supervisor, and DMA Controller

?

Integrated onboard antenna with 50m range indoors / 125m range outdoors

?

Integrated Humidity, Temperat
ure, and Light sensors

?

Ultra low current consumption

?

Fast wakeup from sleep (<6μs)

?

Hardware link
-layer encryption and authentication

?

Programming and data collection via USB

?

16
-pin expansion support and optional SMA antenna connector

?

TinyOS support

: mesh networking and communication implementation

?

Complies with FCC Part 15 and Industry Canada regulations

?

Environmentally friendly –
complies with RoHS regulations [4].


I.

ZigBee Wireless Technology




ZigBee is a specification for a suite of high level communication protocols using
small,
low- power
digital
radios
based
on
an
IEEE
802.15.4
standard

for
personal
area
networks
[6]
[7].
ZigBee
devices
are
often
used
in
mesh
network
form
to
transmit
data
over
longer
distances,
passing
data
through
intermediate
devices
to
reach more distant allows ZigBee networks to be formed ad- hoc, with no
智能交通信号控制中英文对照外文翻译文献

centralized control or high-power transmitter/receiver able to reach all of the devices.
Any
ZigBee
device
can
be
tasked
with
running
the
network.
ZigBee
is
targeted
at
applications
that
require
a
low
data
rate,
long
battery
life,
and
secure
networking.
ZigBee has a defined rate of 250kbps, best suited for periodic or intermittent data or a
single signal transmission
from a sensor or input device. Applications include wireless light switches, electrical
meters with in- home-displays, traffic management systems, and other consumer and
industrial
equipment
that
requires
short-range
wireless
transfer
of
data
at
relatively
low
rates.
The
technology
defined
by
the
ZigBee
specification
is
intended
to
be
simpler and less expensive than other WPANs, such as Bluetooth.


J.

Types of ZigBee Devices

ZigBee devices are of three types:

?

ZigBee Coordinator (ZC):

The most capable device, the Coordinator forms the
root of the network tree and might bridge to other networks. There is exactly one
ZigBee Coordinator in each network since it is the device that started the network
originally.

It stores information about the network, including acting as the Trust
Center
&
repository
for
security
keys.
The
ZigBee
Coordinator
the
central
controller is in this system.

?

ZigBee Router (ZR):

In addition to running an application function, a

device

can act as an intermediate router, passing on data from other devices.

?

ZigBee End Device (ZED):

It contains just enough functionality to talk to the
parent
node.
It
cannot
relay
data
from
other
devices.

This
relationship
allows
the node to be asleep a significant amount of the time thereby giving long battery
life.
A
ZED
requires
the
least
amount
of
memory,
and
therefore
can
be
less
expensive to manufacture than a ZR or ZC.


K.

ZigBee Protocols

The protocols build on recent algorithmic research to automatically construct a
low- speed ad-hoc network of nodes. In most large network instances, the network will
be a cluster of clusters. It can also form a mesh or a single cluster. The current ZigBee
智能交通信号控制中英文对照外文翻译文献

protocols
support beacon and non-beacon enabled networks.
In non-beacon-enabled
networks, an un-slotted CSMA/CA channel access mechanism is used. In this type of
network, ZigBee Routers typically have their receivers continuously active, requiring
a
more
robust
power
supply.
However,
this
allows
for
heterogeneous
networks
in
which some devices receive continuously, while others only transmit when an external
stimulus
is
detected.
In
beacon-enabled
networks,
the
special
network
nodes
called
ZigBee Routers transmit periodic beacons to confirm their presence to other network
nodes.
Nodes
may
sleep
between
beacons,
thus
lowering
their
duty
cycle
and
extending
their
battery
life.
Beacon
intervals
depend
on
data
rate;
they
may
range
from 15.36ms to 251.65824s at 250 kbps. In general, the ZigBee protocols minimize
the time the radio is on, so as to reduce power use. In beaconing networks, nodes only
need
to
be
active
while
a
beacon
is
being
transmitted.
In
non-beacon-enabled
networks,
power
consumption
is
decidedly
asymmetrical:
some
devices
are
always
active, while others spend most of their time sleeping.



V
.

PROPOSED ALGORITHM

A.

Basic Algorithm


Consider a left side driving system (followed in UK, Australia, India, Malaysia
and
72
other
countries).
This
system
can
be
modified
for
right
side
driving
system
(USA, Canada, UAE, Russia etc.) quite easily. Also consider a junction of four roads
numbered as node 1, 2, 3 and 4 respectively. Traffic flows from each node to three
other
nodes
with
varied
densities.
Consider
road
1
now
given
green
signal
in
all
directions.

智能交通信号控制中英文对照外文翻译文献


Fig. 4 Intersection Under Consideration

1)

Free left turn for all roads (free right for right side driving system).

2)

Check densities at all other nodes and retrieve data from strip sensors.

3)

Compare the data and compute the highest density.

4)

Allow the node with highest density for 60sec.

5)

Allowed node waits for 1 time slot for its turn again and the process is repeated
from step 3.


B.

Advanced Algorithm

Assume
road
three
is
currently
given
green
to
all
directions.
All
left
turns
are
always
free.
No
signals/sensors
for
left
lane.
Each
road
is
given
a
time
slot
of
maximum 60 seconds at a time. This time can be varied depending on the situation of
implementation. Consider 4 levels of sensors Ax, Bx, Cx, Dx with A having highest
priority
and
x
representing
roads
1
to
4.
Also
consider
3
lanes
of
traffic:
Left
(L),
Middle (M) and Right(R) corresponding to the direction of traffic. Since left

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