This slide covers the basic technique and supporting technology for implementing soft computing techniques in traffic engineering.

1. DEPARTMENT OF CIVIL ENGINEERING
SARDAR VALLABHBHAI NATIONAL INSTITUTE OF TECHNOLOGY
SURAT– 395007, GUJARAT, INDIA
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https://github.com/rsouza/MMD

2.  What is soft computing?
 Hard computing vs. Soft computing
 Techniques of soft computing
 Soft computing in Traffic Engineering
 Conclusion
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3.  It is based on human mind
 It deals with uncertainty and partial truth
efficiently
 When enough information of problem is not
available, it is used
 It is mimicing the consciousness learning
from experiences
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4. Hard Computing Soft computing
It is conventional analytical
method
It deals with biased truth to
achieve robustness
It depends on binary logic and
collection of programs
It depends on fuzzy logic, neural
computing and probability
reasoning
It needs list of instruction to be
feeded
It has its own set of instructions
It needs accurate information It can deal with noisy information
It performs sequential calculations It can perform parallel calculations
It generates accurate answers It computes approximate solutions
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5. The various methods of soft computing includes:
 Fuzzy logic methods
 Neural networks
 Machine learning
 Probabilistic reasoning
These are the methods applied to collected data,
for which different hardware are used.
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6. Hardware which are generally used to collect
data:
 Wireless sensors
 Multimedia devices
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7. Traffic engineering deals with functional part of
transportation rather than infrastructures, so it
includes:
 Traffic flow
 Road geometry and markings
 Traffic signs
 Traffic lights
This presentation covers some of the
application of soft computing techniques.
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8.  Innovative solution relating different modes
of transport to make safer and efficient
network
 It combines telecommunication, electronics,
information technology and traffic
engineering methods
 It helps in passenger safety, reduction in
transit time and fuel consumption.
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9. Different types of ITS’s:
 Advance traffic management system
 Advanced travellers information system
 Advanced public transportation system
 Advanced vehicle control system
 Commercial vehicle operation system
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10. Main focus if ITS include:
 Monitoring of climatic conditions
 Monitoring technical condition and safety
 Preventing collision situation
 Obstruction recognition
 Alert driver
 Informing drivers
 Stop flow of traffic
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11. Some examples of ITS:
 CCTV
 Weather stations
 Traffic sensors
 Electronic toll collection
 GPS
 Anti-collision radar
 Lightning control in tunnels
https://ortus.io/images/CCTV-Cameras-1.jpg https://qph.ec.quoracdn.net/main-qimg-
c1356deceacca0040336b028537766f0
https://i.ytimg.com/vi/FU_pY2sTwTA/maxresdefault.jpg
https://tech50plus.com/wp-
content/uploads/2014/08/radar.jpg
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12.  Here either special sensors are used or
PDA’s other gadgets are used.
 Wireless sensors are used for Human
Sensing and Crowd sourcing for mobility of
vehicle.
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13. Human sensing:
 It is required to solve the congestion problem
in public places like station, airports,
stadium.
 Data is obtained using GPS, Bluetooth, WSN
(smart dust)
 By studying data we can get the human
density for giving area and can distribute the
traffic flow.
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14. Crowd sourcing for studying user habits:
 Main goal is:
1. Public transportation monitoring
2. Citizen profiling
3. Support for user’s travel plan
 For this beacons are set up in bus and bus
station which can read users position in real
time.
 This method can give more precise
information if network is denser.
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15.  By studying the behavior we will be able to
reduce the travel time and cost by using
most efficient path.
Source: Danilo Cianciullia, Gerardo Canforaa, Eugenio Zimeo “Beacon-based context-aware architecture for crowd sensing public transportation
scheduling and user habits”
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16.  It used wireless accelerometers to study
traffic volume and vehicle classification.
 To eliminate noisy data advanced algorithms
are developed.
 The system consists of wireless sensors,
gateways, cellular network, cloud storage.
 Researcher can get real-time data remotely.
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17.  IoT system can be easily installed on road
shoulders, it has lower maintenance cost,
time and labour.
Source: Yucheng Huang, Linbing Wang, Yue Hou, Wei Zhang, Yinning Zhang “A prototype IOT based wireless sensor network for traffic
information monitoring” Elsevier B.V.
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18.  Nowadays many companies around the
world are in race to develop suitable self-
driving vehicle.
 To make vehicle autonomous, we must
embed its computer with the ability of
decision making.
 For this we have two different methods:
1. Fuzzy logic
2. Neural Network
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19.  Soft computing is efficient to obtain results
using various electronic devices.
 Artificial intelligence can handle various
traffic problem easily.
 Nowadays small wireless device called
“smart dust” are used as data transmitter.
 As discussed almost all the traffic related
problems can be solved using soft
computing techniques.
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20.  A.D. Masegosa, E. Onieva, P. Lopez-Garcia, E. Osaba
“Applications of Soft Computing in Intelligent Transportation
Systems”
 Danilo Cianciullia, Gerardo Canforaa, Eugenio Zimeo “Beacon-
based context-aware architecture for crowd sensing public
transportation scheduling and user habits” Procedia Computer
Science 109C (2017) 1110–1115.
 Erel Avineri “Soft Computing Applications in Traffic and Transport
Systems: A Review” Advances in Soft Computing 1, 17–25 (2005)
 Lucia Janušová, Silvia Čičmancová “Improving Safety of
Transportation by Using Intelligent Transport Systems” Procedia
Engineering 134 ( 2016 ) 14 – 22.
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21.  Lykov Stanislav, Yasuo Asakura, Shinya Hanaoka “Positioning in
Wireless Sensor Network for Human Sensing Problem”
Transportation Research Procedia 21 (2017) 56–64.
 N.R. Yusupbekov, A.R.Marakhimov, H.Z.Igamberdiev, Sh.X.
Umarov Application of softcomputing technologies to the traffic
control system design problems.
 Stanislav Lykova , Yasuo Asakuraa , Shinya Hanaokab Positioning
in Wireless Sensor Network for Human Sensing Problem.
 Yucheng Huang, Linbing Wang, Yue Hou, Wei Zhang, Yinning
Zhang “A prototype IOT based wireless sensor network for traffic
information monitoring” Elsevier B.V.
 Article from web “http://studymafia.org/soft-computing-seminar-and-
ppt-with-pdf-report/”
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