VANETs from Theory to Practice (VTP 2012) San Francisco, California, USA June 25th , 2012

1. FRIEND: A Cyber-Physical System for
Traffic Flow Related Information
aggrEgatioN and Dissemination
Samy El-Tawab, Stephan Olariu and Mohammad Almalag
Old Dominion University
Department of Computer Science
Norfolk, Virginia, USA
VANETs from Theory to Practice (VTP 2012)
San Francisco, California, USA
June 25th , 2012
VTP 2012, San Francisco, CA, USA Samy El-Tawab June 25th, 2012

2. Agenda
 Introduction
 Motivation
 Cyber-Physical System
 Node Definition
 Data Required
 Communication
 Incident Detection
 Information Dissemination and Propagation
 Simulation and Evaluation
 Classification of Applications
 Conclusion
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3. Introduction
 Vehicular Ad-Hoc Network (VANET) is a
type of Mobile Ad-hoc Network that allows
communications between nearby vehicles
and between vehicles and “roadside
infrastructure”.
 We need an Intelligent Transportation
System (ITS) that can alert drivers to traffic-
related events and weather/road conditions.
 Car manufacturers are offering new
applications: Internet access, Traffic
information, movie download…etc.
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* Photo Credit : http://media.nowpublic.net/images

4. Motivation
 Several applications have been proposed to solve a problem in traffic.
 By integrating resources and capabilities at the nexus between the cyber
and physical worlds, FRIEND will contribute to aggregating traffic flow
data collected by the huge fleet of vehicles on our roads into a
comprehensive, near real-time synopsis of traffic flow conditions.
 FRIEND
 it is built on existing infrastructure
 provide accurate information about traffic flow and can be used to
propagate this information
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5. Cyber-Physical System – Node Definition
 Smart Cat's Eye (SCE)
new functionality on top of cat's eye retro-reflectors
 The cat’s eye nodes are deployed uniformly along the road on both sides
 Increase the functionality of the cat's eye nodes by
A short-range radio transceiver
A metal detector sensor
A simple embedded processor
Waterproof and unbreakable: solar panel
 With these additions the cat's eyes form a network that can be used to
Detect traffic parameters
Infer the occurrence or imminence of traffic events
Disseminate the information about average speed and density (number of
vehicles per time period) to the other nodes of the network.
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6. Cyber-Physical System- More Node Definition
 Roadside Unit (RSU)
 consist of a small computing center connected with a solar panel, rechargeable
battery and communication capability
 deployed at regular intervals
 the role of the RSUs is to collect and aggregate traffic-related information from
the passing cars as well as by interchanging information, on an intermittent
basis with adjacent RSUs
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7. Cyber-Physical System- Extra Node Definition
 Moving nodes which are vehicles:
 Radar
 Electronic Stability Control (ESC)
 Cameras
 Event Data Recorder (EDR)
 Global Positioning System (GPS)
 Smart Wheels
 Communication Capability (DSRC)
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8. Cyber-Physical System -
Data Collection and Information to maintain
 Vehicles keep track of:
 Speed
 Acceleration
 Position
 Lane change
 Headway distance
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9. Data Exchange and Communication between
FRIEND’s Nodes
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10. FRIEND - Incident Detection
 Using RSU(s) and/or SCE(s).
 RSU(s) receive a report from EDR (taking into account privacy and
security) about any lane change occurs in previous segment of the
highway.
 A threshold of lane changing in a certain position conclude an existing of
blocking incident.
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11. FRIEND – Information Propagation
 Our idea of information propagation depends on two main
factors: traffic density and the duration of an accident or event.
 The longer it takes to clear the event, the further the information needs
to be propagated.
 The denser the traffic, the faster it will back up.
 Propagate information as a function of density and time.
 Drivers would like to receive information that affects their
decision rather than just notification about incidents that will
be solved by the time they reach this point on the highway
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12. FRIEND – Information Propagation
Stage I : Direct propagation
 Our system divides the area behind an incident into two stages. It defines
stage I as the area behind the incident where the cars need to be notified in
order to prevent a Secondary Accident.
 The longer the accident stays, the more often we send messages to coming
vehicles.
 We focus on the first goal which notifying vehicles with short distance to
an accident.
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13. FRIEND – Information Propagation
Stage I : Direct propagation
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14. FRIEND – Information Propagation
Stage I : Direct propagation
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15. FRIEND – Information Propagation
Stage II : Tracking Head and Tail of an event
 We define a Head of the accident and a Tail of the accident. The head of
the accident is the place where is the source of the backup exists (xh0,yh0).
 In case of a slow movement of vehicles after accident is clear. Head is
updated with new values of (xh1, yh1). Also, Tail is updated if the backup
exceed D (specific distance from data management centers)
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16. FRIEND – Information Propagation
Stage II : Tracking Head and Tail of an event
Distance Backward the accident
0
G1 (HEAD) G2 G3 Gi (TAIL)
Accident Cleared, Vehicles are moving faster than backup
0
G1 G2 (HEAD) G3 Gi (TAIL)
Accident Cleared, Vehicles are moving slower than backup
0
G1 G2 (HEAD) G3 Gi+1 (TAIL)
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17. Simulation and Evaluation
 We evaluate our frame work using ONE simulator , which is the
Opportunistic Network Environment simulator
 It allows to visualize both mobility and message passing in real time in its
graphical user interface.
 ONE can import mobility data from real-world traces or other mobility
generators. It can also produce a variety of reports from node movement to
message passing and general statistics
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18. Evaluations
 In evaluation, simulation data is analyzed to get the optimal value of
number of SCE needed to communicate together to detect vehicles.
 To detect all vehicles moving with maximum speed of 55mile/hr, we
expected that the larger the size of node, the more able to detect the
vehicles on the highway.
 At the same time, we cannot increase the size more than 4 nodes as it will
disconnect nodes and prevent communication.
 Four nodes in a range of 100 meters are sufficient to detect all vehicles.
VTP 2012, San Francisco, CA, USA PhD Proposal El-Tawab
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19. Examples of Applications
 Incident Detection
 Traffic Monitoring
 Weather Alert System
 Traffic Information
 Data Center
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* Photo Credit :http://www.roadtraffic-technology.com/

20. Classification of Applications
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21. Conclusion
 We presented a new cyber-physical system called FRIEND for incident
detection on highways and dissemination of information.
 We described our nodes definition and how incident detection is done.
 We explained the technique of tracking the Head and Tail of a backup and
how information propagation is handled.
 We provided application classification in VANET.
VTP 2012, San Francisco, CA, USA PhD Proposal El-Tawab
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22. Questions?
Please visit the Intelligent Networking and Systems (iNetS)
Research Group in the Department of Computer Science at Old
Dominion University: http://www.cs.odu.edu/~inets/
Samy El-Tawab (tel@cs.odu.edu)
VTP 2012, San Francisco, CA, USA PhD Proposal El-Tawab
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*Photo Credit: http://blog.doostang.com