Automatic Train Control System using Wireless Sensor Networks

Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References

Automatic Train Control System for Railwaysusing Wireless Sensor Network

Prakhar Bansal2011CS29

under the guidance of

Prof. M.M. Gore

Computer Science and Engineering DepartmentMotilal Nehru National Institute of Technology Allahabad,

Allahabad, India

June 11, 2013

Prakhar Bansal, MNNIT Allahabad 1 / 66

Automatic Train Control System


Table of Contents

1 Motivation

2 Introduction to Present Railway Signalling Architecture

3 Field Study

4 Thesis ContributionsProposed ArchitectureAlgorithms

5 Simulation ImplementationTinyOS, nesC and TOSSIMSensor Motes and Sensor BoardsRouting ProtocolsSimulation Experiences and Results

6 Conclusion and Future Work

7 References




Table of Contents

1 Motivation


3 Field Study




7 References




MotivationWhy Railways?

Figure: i.) Railways as a Transportation ii.) Frequency of Rail Accidentsiii.) Need of Sustainable Transport Solution




MotivationRailways as a Transport

Railways as a Passenger Solution

44446 million passengers travel globally/year via railways [1].

6.8% people travel via rail all over the world [1].

24 million people/day travel via rail in India [2].

Japan, China and Russia has high passenger modal split of29%, 31.7% and 41.1% respectively [3].

Railways as a Carriage Solution

5439 mtk goods is carried via rail globally in 2011 [1].

IR carries 2.8 million tons of freight/day [4].

USA and Russia has rail freight modal share of 88.8% and67.9% respectively [5].




MotivationAccidents Rate

Old technology and manual signalling in most countries.

More than 1000 people die per year globally [6].

715 people die and 1118 injured in last 3 years in 49 accidentsin India [2].

Mostly accidents happen due to manual errors in signalling,lack of visibility, communication faults and derailments [5].

Trains usually run out of schedule and even get canceled inwinter season due to low visibility.




MotivationNeed for Sustainable Transport

Figure: (a) CO2 Emissions [7] Figure: (b) Energy Consumption [7]




MotivationNeed for Sustainable Transport

Table: CO2 Emissions [7]

Rail 48.8 gram/passenger/km

Roads 418 gram/passenger/km

Navigation 200 gram/passenger/km

Aviation 316 gram/passenger/km

Table: CO2 Emissions in India in the period 1998-2009 [8]

Rail 8 million tons

Roads 128 million tons

Navigation 18 million tons

Aviation 4 million tons




Table of Contents

1 Motivation


3 Field Study




7 References




Present Railway Signalling Architecture

Figure: General Signalling Boards





Figure: Color Light Signals





Figure: Semaphore Signals





Figure: Convergence and Divergence Signals





Figure: Shunting and Repeater Signals




Successfully Deployed WSN Projects

Smart-Grid Project [9]: entire process from generation,transmission, distribution of electricity to integration ofrenewable and alternative energy sources, is handled bywireless sensors.

Microsoft SensorMap [10]:

100s of mini weather stations deployed in schools throughoutSingapore.sensor grid, to automatically collect and aggregate the weatherdata in real time.studies correlation between the weather patterns and denguefever.

CodeBlue [11]: wireless sensors for medical care.

Ultra-wideband sensing and communication for biomedicalapplications [12].




Table of Contents

1 Motivation


3 Field Study




7 References




Field StudyInteraction with Senior Section Engineer, North Central Railways

Figure: Ghaziabad Train ControlRoom c©Indian Railways [13]

Figure: Typical Train Control Roomc©Indian Railways [13]




Study Findings

Lots of mechanical equipments used [14].

Completely depends on manual expertise.

As traffic increasing, needs good computerized managingsolutions.

Route relay interlocking installed only on busy stations.




WSN Suitability to Railways

Huge scope of wsn in railways [15].

Think about station master itself getting incoming trainreadings via sensors.

No need for manual signalling.

Train itself asks for clearance to next block head, no need tostop and wait.

Accurate location information without GPS.




Use of Self-recharging Batteries from Vibrations

Piezoelectric vibrational energy harvester (PZeh) are used.

Generates 40mW on an average with a peak operation of0.3W, when shaken gently.

Generates 280mW with a peak operation of 2.0W, whenshaken vigorously.

Micaz mote processor consumes 8mA in Active mode and<15µ A Sleep mode.

Micaz mote radio consumes 19.7mA in Receiving mode,17.4mA TX, 0dBm, 20µA Idle mode, voltage regular ON and1µA Sleep mode, voltage regulator OFF.




Table of Contents

1 Motivation


3 Field Study




7 References




Proposed Architecture

Figure: Train Running Signalling using WSN





Figure: Convergence and Divergence using WSN





Figure: WSN based Interlocking




Table of Contents

1 Motivation


3 Field Study




7 References




Train Running Algorithms

Algorithms

Algorithm 1: Configuration Phase - Learning the BHs

Algorithm 2: Configuration Phase - Learning the CHs

Algorithm 3: Train Event Detection: Seeking Clearance byBHs

Algorithm 4: Data Aggregation and Forwarding: Data to CHs

Algorithm 5: Topology Updation and Maintenance




Algorithm 1

Algorithm 1 Configuration Phase: Learning the BHs

BH/Station broadcasts a ‘configuration message’CM with aBHdistance = 1Ru is the set of nodes that receive the CM messagefor each u ∈ Ru do

i=0if BHdistanceu > BHdistanceCM and

firstsendingu[BhIDCM ]==true and isBH==false thennextbhu[i] ← BhIDCM

nexthopu[i] ← NIDCM

BHdistanceu ← BHdistanceCM + 1NIDCM ← TOS NODE IDBHdistanceCM ← BHdistanceunode u broadcast the modified CM msgfirstsendingu[BhIDCM ] ← falsei++

elsenode u discards the received CM message

end ifend for




After Algorithm 1

Figure: After Blockhead Configuration




Algorithm 2

Algorithm 2 Configuration Phase: Learning the CHs

Clusterhead broadcasts a Clusterhead Declaration Message(CDM) with a TTL valueRu is the set of nodes that receive the CDM messagefor each u ∈ Ru doif TTL 6= 0 and u ∈ BH thenif CDM− > ID /∈ CHQueueu thenadd(CHQueueCH , CDM− > ID)TTL← TTL− 1node u broadcasts modified CDM message

end ifelse

node u discards the received CDM messageend if

end for




After Algorithm 2

Figure: After Clusterhead Configuration




Algorithm 3

Algorithm 3 Train Event Detection and Seeking for Clearance

Ru is the set of nodes that detect trainfor each u ∈ Ru do

if TrainDetectedu == true and DoubleLane==true thenif flagu == 0 then

// critical sectionsend clearance signalflagu = 1

end ifelse

send wait signalend ifif TrainDetectedu == true and DoubleLane==false and

stationu == true thenif flagu == 0 and flagNextStationu == 0 then

// critical section




Algorithm 3

Algorithm 3 Train Event Detection and Seeking for Clearance(cont.)

send clearance signalflagu = 1flagNextStationu = 1

end ifelse

send wait signalend ifif TrainLeavesu == true and DoubleLane==true then

send clearance signal to neighboring BHend ifif TrainLeavesu == true and DoubleLane==false and

stationu == true thensend clearance signal to neighboring station

end ifend for




Algorithm 4

Algorithm 4 Data Aggregation and Forwarding

Ru is the set of BH/Stationfor each u ∈ Ru do

Each BH/Station periodically sends the list of train to all CHsin the queue

Packet.msg ← TrainInfouadd(Packet.ID[ ], TOS NODE ID)//The BH/Station, when receives the list from other

BHs/Stations, it aggregates the data and then forwards itif Packet Received then

buffer=buffer∪PacketPacket ← bufferforwards Packet

end ifend for




Algorithm 5

Algorithm 5 Topology Updation and Maintenance

if train list not received by CH or partial list is received thenrestart algorithm 1 and 2

end if




Table of Contents

1 Motivation


3 Field Study




7 References




TinyOS, nesC and TOSSIMTinyOS

TinyOS

Free, open-source, BSD-licensed OS designed for low-powerembedded distributed wireless sensor devices [16].

Developed by University of California, Berkeley, Intel Researchand Crossbow Technology.

Designed to support the concurrency intensive operationsrequired by networked sensors with minimal hardwarerequirements.

Written in nesC programming language.




TinyOS, nesC and TOSSIMnesC and TOSSIM

nesC

Network embedded systems C, C optimized to supportcomponents and concurrency [17].Component based, event driven programming language usedto build application for TinyOS platform.Components are wired together to run applications onTinyOS.Programs = software components (connected statically viainterfaces).

TOSSIM

Simulates entire TinyOS applications [18].Replaces components with simulation implementations.2 interfaces: c++ and python.




Table of Contents

1 Motivation


3 Field Study




7 References




Sensor Motes and Sensor BoardsMICAz Mote

Figure: MICAz Sensor Mote c©Crossbow Technology, USA [19]




Sensor Motes and Sensor BoardsMICAz Mote

2.4 GHz mote for enabling low-power wireless sensor networks.

IEEE 802.15.4 compliant Radio frequency transceiver.

Radio, resistant to RF interference and provides inherent datasecurity.

Atmel128L, low power microcontroller.

51-pin expansion connector.

High speed (250 Kbps), hardware security (AES-128).




Sensor Motes and Sensor BoardsSensor Boards

MTS400CA

Acceleration: dual-axis acceleration sensor.Atmospheric pressure: barometric pressure sensor.Light: ambient light sensor.Humidity and temperature: relative humidity and temperaturesensor.

MDA100CB

Light: light sensor and photocell.92 unconnected soldering points.51-pin connector.




Table of Contents

1 Motivation


3 Field Study




7 References




Routing Protocols

Collection Tree Protocol

Collecting data from motes.One or more collection trees is built, each of which is rootedtowards the specified destination.When a node has data which needs to be collected, it sendsthe data up the tree, and it forwards collection data thatother nodes send to it after aggregating, or suppressingredundant transmissions.




Routing Protocols

Dissemination

It is used to maintain consistency across the network.The dissemination service tells nodes when the value changes,and exchanges packets so it will reach eventual consistencyacross the network.

Blip

BLIP, the Berkeley Low-power IP stack, is an implementationin TinyOS of a number of IP-based protocols.Internet of things.




Routing Protocols

Tymo

TYMO is the implementation on TinyOS of the DYMO[Dynamic MANET On-demand] protocol, a point-to-pointrouting protocol for MANET.TYMO, packet format is changed and implemented on top ofthe Active Message stack of TinyOS.Reactive protocol, DYMO does not explicitly store thenetwork topology.Nodes compute a unicast route towards the desireddestination only when needed using RREQ and RREP packets.




Table of Contents

1 Motivation


3 Field Study




7 References




Simulation ExperiencesInitial Design I

Figure: Initial Design with 1000 NodesPrakhar Bansal, MNNIT Allahabad 49 / 66



Simulation ExperiencesInitial Design II

Figure: Design with Clearance Points along Stations but not alongJunctions with 100 Nodes




Simulation ExperiencesDesign with BHs but not Intermediate Nodes

Figure: Introduction to Block System with 100 NodesPrakhar Bansal, MNNIT Allahabad 51 / 66



Simulation ExperiencesDesign with BHs with Intermediate Nodes

Figure: Revised Block System Architecture with 115 NodesPrakhar Bansal, MNNIT Allahabad 52 / 66



Simulation ExperiencesFinal Architecture: BHs + CHs + Intermediate Motes

Figure: Present Architecture with 125 NodesPrakhar Bansal, MNNIT Allahabad 53 / 66



Simulation ExperiencesTopology Framework with respect to Allahabad Junction

Figure: Topology Framework with respect to Allahabad Junction




Simulation Experiences and ResultsResults with Variable Number of Nodes

Figure: (a) Energy Consumptionwith Variable Number of Nodes

Figure: (b) Success Rate withVariable Number of Nodes




Simulation Experiences and ResultsResults with Variable Frequency of Trains across Allahabad Junction

Figure: (a) Energy Consumptionwith Variable Frequency of Trainsacross Allahabad Junction

Figure: (b) Success Rate withVariable Frequency of Trains acrossAllahabad Junction




Simulation Experiences and ResultsDiscussions

In our work we used the energy model where the radiodissipates energy E = 50 nJ/bit to run the transmitter orreceiver circuitry and εamp = 100 pJ/bit/m2 for the transmitamplifier to achieve an acceptable SNR [20].

Simulation maximum duration is 10000 seconds and it runs 8rounds/set of nodes.

Topology is generated randomly in each run when doingsimulation for variable number of nodes and it is fixed forsimulation across Allahabad junction.

The success rate is currently decreasing as the number ofpackets increase in the network. This is due to collisions ofmessages. This needs to be improved.




Table of Contents

1 Motivation


3 Field Study




7 References




Conclusion

This could be a revolution in railway technology.

Trains can run efficiently and accurately as any error can beeasily detected.

Trains can run in low visibility as sensors would take care ofthis.




Future Work

Integration with Internet of things evolution using Blipeffectively.

Security as false messages can be spread by attackers;authenticity and confidentiality could be introduced usingcryptographic solutions.




Table of Contents

1 Motivation


3 Field Study




7 References




References I

World Bank Data. http://data.worldbank.org/indicator/IS.RRS.TOTL.KM.

[Online; last accessed June 10, 2013].

Anil Kakodkar, E. Sreedharan, N.Vedachalam, “Report of High Level Safety Review Committee,” Ministry

of Railways, Government of India, February, 2012.

Hiroumi Soejima, “Railway Technology in Japan Challenges and Strategies,” Japan Railway and Transport

Review, September, 2003.

Pawan Bansal, “Speech by Railway Minister,” Ministry of Railways, Government of India, February, 2012.

Sam Pitroda, Deepak Parekh and M.S. Verma, “Report of the Expert Group for Modernizaion of Indian

Railways,” Ministry of Railways, Government of India, February 2012.

Amitabh Agarwal, “Human Interface in Railway Safety? A New Dimension,” Ministry of Railways,

Government of India, 2007.

Jean-Pierre Loubinoux, “Keeping Climate Change Solutions on Track The Role of Rail,” International Union

of Railways, March 2012.

Tan Yigitcanlar, Lawrence Fabian and Eddo Coiacetto, “Challenges to Urban Transport Sustainability and

Smart Transport in a Tourist City: The Gold Coast, Australia,” The Open Transportation Journal, 2008.

Murtala Aminu Bamanga, “Wireless Sensor Network Applications in Smart Grid,” University of sussex, 2012.



http://data.worldbank.org/indicator/IS.RRS.TOTL.KM


References II

Suman Nath, Jie Liu, and Feng Zhao, “SensorMap for Wide-Area Sensor Webs.”

http://atom.research.microsoft.com/sensewebv3/sensormap/.[Online; last accessed on June 10, 2013].

Matt Welsh, “CodeBlue: A Wireless Sensor Network for Medical Care and Disaster Response,” Harvard

University, 2005.

“Ultra-wideband Sensing and Communication for Biomedical Applications.”

http://www.sussex.ac.uk/crg/projects/wsn/uwbsens/, University of Sussex.[Online; last accessed June 10, 2013].

Karan Desai, “Akamai Technologies, Inc..” http://www.quora.com/India/

How-does-the-inside-of-control-room-of-Indian-railways-look-like-How-do-the-guys-in-the-control-room-communicate-with-the-engine-driver/.

[Online; last accessed on June 10, 2013].

Mr. Alok Sehgal. Senior section engineer, North Central Railways, Allahabad railway station.

Yamato Fukuta, “Possibility of Sensor Network Applying for Railway Signal System,” IEEE conference, 2008.

P. Levis and D. Gay, TinyOS Programming.

New York, NY, USA: Cambridge University Press, 1st ed., 2009.

David Gay, Philip Levis, Matt Welsh and David Culler, “The nesC Language: A Holistic Approach to

Networked Embedded Systems,” 2002.



http://atom.research.microsoft.com/sensewebv3/sensormap/

http://www.sussex.ac.uk/crg/projects/wsn/uwbsens/

http://www.quora.com/India/How-does-the-inside-of-control-room-of-Indian-railways -look-like-How-do-the- guys-in-the-control-room-communicate-with-the-engine-driver/

http://www.quora.com/India/How-does-the-inside-of-control-room-of-Indian-railways -look-like-How-do-the- guys-in-the-control-room-communicate-with-the-engine-driver/


References III

P. Levis, N. Lee, M. Welsh, and D. Culler, “Tossim: accurate and scalable simulation of entire tinyos

applications,” in Proceedings of the 1st international conference on Embedded networked sensor systems,SenSys ’03, (New York, NY, USA), pp. 126–137, ACM, 2003.

Crossbow Technology, “Micaz Specification.”

www.openautomation.net/uploadsproductos/micaz_datasheet.pdf.[Online; last accessed June 10, 2013].

Leandro Aparecido Villas, Azzedine Boukerche and Heitor Soares Ramos,, “DRINA: A Lightweight and

Reliable Routing Approach for In-Network Aggregation in Wireless Sensor Networks,” vol. 62, IEEETransactions on Computers, April 2013.



www.openautomation.net/uploadsproductos/micaz_datasheet.pdf


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Automatic Train Control System using Wireless Sensor Networks

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