Intelligent Cooperative Sensing
for Improved traffic efficiency
IoT CoAP Plugtests™ & Workshop
Nov 27, 2012 – Sophia Antipolis
Introduction
• Cooperative
p
V2X communications and cellular networks are
enabling closed loop interaction between vehicles/drivers and
the transportation infrastructure.
• Enabling technologies are entering their mature phase,
phase ee.g.,
g
traffic flow sensors and IEEE 802.11p
• There is still the need of a complete integrated solution that can
take the most benefits from a real-time analysis of the data
gathered and appropriate reaction on the transportation system
• This requires decentralized aggregation and decision for robust
and timely decisions to be taken
• An additional and significant improvement can be brought by
pro-active decision
d
making
k processes, withh the
h integration off
predictive models running in real-time alongside the reaction
schemes
Nov 27, 2012 – Sophia Antipolis
IoT CoAP Plugtests™ & Workshop
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Intelligent Transport Systems
•
Challenges:
–
–
–
–
•
Permanent congestion on highways and urban centres
Energy waste
CO2 emissions
Impact on public health and accidents rate
Forecast growth in transport:
– congestion costs will increase by about 50% by 20501
•
Main objectives:
– Transport efficiency
• Less congestion
– More
M
safety
f
• Less accidents
– Energetically sustainability
• Less CO2 emissions
•
Intelligent Transportation Systems (ITS) should play the role in contributing to
tangible results quickly and efficiently.
[1] Transport White Paper (March 2011)
Nov 27, 2012 – Sophia Antipolis
IoT CoAP Plugtests™ & Workshop
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The goals
• ICSI aims:
– To address simultaneously the challenges raised by
the
h ITSS
– To give a qualitative leap towards the future mobility
• ICSI platform goals are:
– merging and integration of heterogeneous data
sources into a common system
– provisioning
i i i off a set off advanced
d
d tools
l for
f control,l
monitoring, simulation and prediction of traffic
Nov 27, 2012 – Sophia Antipolis
IoT CoAP Plugtests™ & Workshop
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The vision (1/2)
• Todayy ITSs are often composed
p
byy vertical and closed subsystems which do not provide interfaces for direct access to
third parties.
–A
Aggregation
i and
d iintegration
i off d
data provided
id d b
by diff
different
sub-systems operating in the same area is very difficult in
practice
– The situation is bound to become worse in the future as the ICT
infrastructure in transportation become bigger and more
complex
p
• In ICSI, the interaction between heterogeneous data sources
is achieved:
– providing a common layer for data distribution
– distributing the intelligence for decision making from humans in
control centers to machines composing the ICT infrastructure
Nov 27, 2012 – Sophia Antipolis
IoT CoAP Plugtests™ & Workshop
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The vision (2/2)
The M2M interaction
between sensors (e.g.,
traffic flow) and
actuators (e.g., variable
message signs) will be
enabled with local
scope.
– Scalability
– Reliability
– Bounded reaction
times
– Cooperative sensing
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IoT CoAP Plugtests™ & Workshop
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Sub--systems
Sub
CS
RS
VS
PS
Central Sub-system
– stores and elaborates data from the peripheral sub-systems and provides
feedbacks/actions
Road-side Sub-system
– also called Road-Side Unit (RSU)
– is positioned along the road for collecting measurements through sensors, actuating
feedbacks and acting as a gateway for vehicle communications
– variable message signs
signs, EV charging spots
spots, etc.
etc
Vehicle Sub-system
– also called On-Board Unit (OBU)
– resides into the car and can be equipped with sensors and wireless networking
equipment for V2X communications.
Personal Sub-system
– is embedded in p
portable devices
v
used byy pedestrians
p
and citizens
– is involved with the collection of news, travel information and other kinds of
information
– Smartphones, tablets, e-book readers, etc.
Nov 27, 2012 – Sophia Antipolis
IoT CoAP Plugtests™ & Workshop
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Overlay networks
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IoT CoAP Plugtests™ & Workshop
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Peer--2-Peer overlays
Peer
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Network architecture
VS
VS
RS
•
VS
PS
The system relies on local
distributed storage and
intelligence which
operates on a limited
geographical scale where
data are distributed and
processed in real-time
without the need to contact
the
h centrall sub-system.
b
Nov 27, 2012 – Sophia Antipolis
IoT CoAP Plugtests™ & Workshop
PS
RS
VS
10
Network architecture
9 No Aggregation
9 ~10
10 millis
VS
VS
RS
•
•
•
PS
GW
ICSI uses the concept of “gateway”
(GW) to indicate a logical entity that
operates on a local scope
GW offers capabilities similar to
those provided by the CS:
–
–
–
–
•
VS
data storage
event processing
alarms
etc.
PS
GW
RS
VS
GW handles data for a limited
number of components in an area
RS can act as a GW
Nov 27, 2012 – Sophia Antipolis
IoT CoAP Plugtests™ & Workshop
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Network architecture
9 Low aggregation
9 ~100
100 millis
VS
VS
RS
GW
VS
PS
GW
GW
GW
Local area
Local area
GW
GW
•
Each GW is logically
connected to:
–
GWs in the same local area,
which handle data relevant to
its served sensors and actuators.
•
•
•
Service
Context
Resource constraints
PS
GW
RS
VS
L l area
Local
GW
GW
Nov 27, 2012 – Sophia Antipolis
IoT CoAP Plugtests™ & Workshop
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Network architecture
9 Med. aggregation
9 ~10
10 secs
VS
VS
RS
GW
VS
PS
GW
GW
GW
Local area
Local area
GW
GW
GW
GW
•
Each GW is logically
connected to:
–
Global area
GWs outside its local area,
which might still need to
received data or provide
commands, for instance:
•
•
PS
GW
congestion on a main road
segment might have cascade
effects on very large areas
drivers far away might benefit
from having an early warning
by being redirected along
alternative paths.
Nov 27, 2012 – Sophia Antipolis
IoT CoAP Plugtests™ & Workshop
GW
RS
VS
L l area
Local
GW
GW
13
Network architecture
9 High aggregation
9 ~100
100 secs
VS
VS
RS
GW
VS
PS
GW
GW
GW
Local area
Local area
GW
GW
GW
GW
•
Each GW is logically
connected to:
–
CS in order to provide
integrated and aggregated
data for:
•
•
Global area
PS
CS
GW
long-term optimizations
statistical uses
GW
RS
VS
L l area
Local
GW
GW
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IoT CoAP Plugtests™ & Workshop
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Gateway
•
GW implements dynamic and adaptive
algorithms
l i h able
bl to provide
id real-time
l i
decisions based on the infrastructure and
traffic situation (context/resourceawareness):
– Cooperative Learning Unit (CLU)
•
The GW is in charge of:
– Taking decisions autonomously in response
to traffic conditions ((context,, resource
constraints)
– Integrating information from the WSN and
GWs
– Identifying of abnormal traffic situations
– Suggesting contingency and actions plans to
improve the traffic flow and travel
management strategies
•
•
Nov 27, 2012 – Sophia Antipolis
IoT CoAP Plugtests™ & Workshop
The GWs will be updated with new traffic
models and contingency plans by the Traffic
Manager Center (TMC) placed into the CS
A Decision Support System in the CS will
update and improve traffic models and
contingency plans on the base of
information reported by the GWs (results of
previously actions taken)
15
Real--world
Real
• Nowadays:
y
PS
PS PS
RS
VS
RS
PS
VS
VS
PS
RS
VS
RS
PS PS
VS
VS
Nov 27, 2012 – Sophia Antipolis
PS
VS
– Many vehicles equip an OnBoard Unit
– Some Road-Side
Road Side Units are
already deployed on
highways and main roads
(VMSs, flow sensors, speed
traps, semaphores, etc.)
– Smartphone, tablets, e-books
and others personal devices
are commonly used by
people
• Available devices lack of
network architecture and
service platform
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Connected--world
Connected
• Protocols
– IEEE 802.11p
PS
PS PS
RS
• Multi-Channel
• Real-Time MAC
• Fail-safe (replication)
VS
RS
PS
VS
VS
PS
RS
VS
RS
PS PS
VS
VS
Nov 27, 2012 – Sophia Antipolis
PS
VS
–
–
–
–
IEEE 1609
IEEE 802.15.4
IETF 6LoWPAN
IETF CoAP
• Architectures
– ETSI ITS
– ETSI M2M
– Etc.
Etc
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ICSI--world
ICSI
•
Global Area
PS
GW
– Local cloud is connected with a GW
– Local areas are defined dynamically
on the base of the running service, the
current context and the resource
constraints
– Global area enables inter-area
communications and connects CS and
GWs
VS
PS PS
RS
PS
VS
PS
RS
VS
Local area
VS
GW
PS
•
VS
•
PS PS
VS
VS
Nov 27, 2012 – Sophia Antipolis
In ICSI:
•
ICSI offers a set of intelligent
services on top of main ITS and
M2M architectures
Intelligent services support intelligent
application for Intelligent Transport
Systems!
Awareness:
– Service
– Context
– Resource
R
constraints
i
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Service--Awareness
Service
Global Area
Global Area
PS
GW
VS
VS
GW
PS PS
RS
PS
VS
PS
RS
VS
PS
VS
Local area
VS
GW
PS PS
VS
VS
Nov 27, 2012 – Sophia Antipolis
GW
VS
VS
VS
IoT CoAP Plugtests™ & Workshop
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Context and Resource Awareness
Global Area
Global Area
VS
VS
GW
GW
GW
GW
Local
area
GW
GW
VS
VS
VS
Nov 27, 2012 – Sophia Antipolis
GW
GW
GW
GW
VS
VS
VS
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ETSI ITS sub
sub--systems
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ICSI over ETSI ITS (1/4
(1/4))
GW
VS
PS
Personal ITS station
VS
1
2
4
7
VS
RS
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IoT CoAP Plugtests™ & Workshop
*
3
5
8
0
A
6
B
9
#
R
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ICSI over ETSI ITS (2/4
(2/4))
Roadside ITS station
ITS-S host
Roadside ITS-S gateway
ITS S router
ITS-S
ITS-S border router
GW
ITS station-internal network
Proprietary roadside network
RS
RS
VMS
RS
VS
VS
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ICSI over ETSI ITS (3/4
(3/4))
CS
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ICSI over ETSI ITS (4/4)
Applications
ICSI
Facilities
Security
Manag
gement
Networking & Transport
Access
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IoT CoAP Plugtests™ & Workshop
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ICSI protocol stack
ICSI
A li ti
Application
Layer
ICSI Applications
DATEX2 Applications
ETSI ITS Applications
MA+ FA + SA
ICSI
Service
Layer
ICSI
Logical
Layer
DATEX2 Adaptation
ETSI ITS Adaptation
Service-dependent Sub-Layer
S1
S2
S3
Sn
Service-Independent Sub-Layer
ETSI M2M
IPSO FW
…
DATEX2 Adaptation
ETSI ITS Adaptation
MA + FA + SA
ETSI M2M
ICSI
Ph sical
Physical
Layer
IPSO FW
…
WebServices
CoAP/HTTP
UDP/TCP
IP
MAC
PHY
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UDP/TCP
IP
IoT CoAP Plugtests™ & Workshop
ETSI ITS
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Model--View
Model
View--Presenter (MVP)
View
Application
Feedback/Actions
Application
View
Updates
P
Presenter
t
S i
Service
S i
Service
Model
Logical
Logical
Physical
Physical
Physical
S
GW
Area
GW
P
Presenter
t
Model
Physical
Data
IoT CoAP Plugtests™ & Workshop
Model
1.
SEPARATION
The business logic is
held by the Presenter
2.
DECOUPLING
Presenter mediates
between the View and
the Model
3.
TESTABILITY
Passive View exposes
a single interface
S
Data
Nov 27, 2012 – Sophia Antipolis
Manipulates
Fires
events
27
Thank you for your attention!