This document discusses data-driven intelligent transportation systems (D2ITS). It begins with background on intelligent transportation systems (ITS) and how the increasing availability of data is enabling ITS to become more powerful and data-driven. The document then covers key topics like the classification of data in D2ITS, the framework of D2ITS, and modules for processing learning-driven data. It concludes that D2ITS has the potential to improve transportation systems by collecting and analyzing large amounts of data from various sources to optimize planning and provide real-time updates and predictive analysis.

1. Data-Driven Intelligent Transportation(D2ITS)
Systems
Rayan Nouh
Dankook University
Nov.2015
Survey
Junping Zhang, Member, IEEE, Fei-Yue Wang, Fellow, IEEE, Kunfeng Wang,Wei-Hua Lin, Xin Xu, and Cheng Chen

2. Outlines
Background
What is (ITS) ?
Potential Research in D2ITS
Data Classified in D2ITS
Framework of D2ITS
Critical Challenges in ITS
Why Data-Driven (D2ITS) ?
Conclusion
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3. 1. Junping Zhang, Member, IEEE,
2. Fei-Yue Wang, Fellow, IEEE,
3. Kunfeng Wang,
4. Wei-Hua Lin,
5. Xin Xu,
6. Cheng Chen
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION
SYSTEMS, VOL. 12, NO. 4, DECEMBER 2011
Authors
On this paper focuses on some of the key components
of D2ITS.
I. Development of D2ITS.
II. Discussing the functionality of D2ITS.
III. Discussing some deployment issues associated
with D2ITS.
IV. Future research for the development of D2ITS
Background 2016-03-17
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4. Background
Intelligent Transportation Systems (ITS) have emerged as an efficient way of improving the
performance of transportation systems, enhancing travel security, and providing more choices to
travelers.
The power of high technology such as IoT , data mining, big data and could computing, make a
significant change in ITS which is collected that much more data from a variety of sources and
can be processed into various forms to different stakeholders.
The availability of a large amount of data changing the ITS from a conventional technology-
driven system into a more powerful multifunctional data-driven intelligent transportation
system (D2ITS)
Wireless network offers a powerful and transformative opportunity to improving transportation
connectivity that further enables cooperative systems and dynamic data exchange using a broad
range of advanced systems and technologies.
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5. What is (ITS) ?
Transport
Safety
Transport
Productivity
Travel
Reliability
Informed
Travel
Choices
Environmental
Performance
Integrated application of advanced Technologies using computers, communications,
and advanced sensors to address the transportation problems.
Provide important information to travelers with improving the safety and efficiency
of the transportation system.
Infrastructure can be categorized based upon the implemented application of the
technology
ITS
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6. Why (ITS) ?
Transportation systems are a very important part of human activities..
Estimated average of 40% of the population spends at least 1 h on the road
each day..
Efficient way to improving the performance of transportation systems..
Enhancing travel security..
Save time and money..
ITS
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7. Technology in ITS
Inductive Loop Detection &
Sensing Technologies
Video Vehicle
Detection
Wireless
Communications
Computational
Technologies
Floating Car Data/
Cellular Data
ITS
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8. Critical Challenges of ITS
Traffic
Congestion
increased
everyday..
Social
Security
Productivity
&
International
Competition
,More Noise
increased
Air
pollution..
Use more
fuel..
Effect
Human
Health
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9. Why(D2ITS) ?
Data-Driven Intelligent Transportation System
“IoT” opened new opportunities to make
the existing transportation network far
more efficient and user friendly.
Power of multifunctional system use data-
driven intelligent transportation system .
Multisource real time traffic control
Learning algorithm driven to optimize the
traffic performance.
Directly UI user interface with people and
users of transportation systems.
Digital-age of transportation.
D2ITS
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10. Framework of D2ITS. 2016-03-17
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11. Optimize ITS to (D2ITS)
D2ITS Use the Power of Current Data!!
D2ITS generate new functions and
services in ITS
Data collected from multiple sources will
play the key role in ITS.
Data realize and extend the performance
of current (ITS) system.
D2ITS
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12. Six Primary Components in ITS
Advanced urban
transportation systems
Advanced
public
transportation
systems
Business vehicle
management
Advanced
transportation
management
systems
Advanced
vehicle
control
systems
Advanced
traveler
information
systems
The functions of these components can fully be
realized depends on how data are collected and
processed into useful information.
(D2ITS) will realize and extend the functions of
the six fundamental components of ITS.
ASIS
To Be
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13. Data classified & Process in D2ITS
Vision-Driven
MultiSource-
Driven
Learning-Driven
WhichisthemaincomponentofD2ITS,
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14. Data classified in D2ITS
Complementary in D2ITS
Vision-Driven
Multisource-Driven
GPS
Laser
Radar
seismic
Sensor
Ultraso
nic
Sensor
Mobile
Network
Meteorolog
ical sensor
others
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15. Data classified in D2ITS
Vision-Driven ITS
Vision-Based Devices which is recently generated huge data such as :
1. Video and Sensors cover a large group of information that can reflect, in the most
direct way, status of transportation systems can be used to detect on time-notification,
e.g., in case of vehicles accident, an important feature for ITS.
2 . Large number of applications in ITS are implemented with vision-driven
technologies, where input data are collected from video sensors, and output is used for
related applications in ITS.
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16. Data classified in D2ITS
A. Vision-Driven ITS
1. Tracking traffic object, vehicle and walking
detection..
2. Car license plates..
3. Vehicle density..
4. Traffic sign detection..
5. Lane tracking..
6. Traffic behavior analysis..
7. Statistical traffic data analysis..
B. Multisource-Driven ITS
1. Inductive-loop detectors..
2. Laser radar..
3. GPS system..
4. Mobile network
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17. ModuleProcess Data
Learning-Driven : D2ITS will use both real-time and historical data, some different modules can be
helpful to used in learning-driven ; Online Learning, Data Fusion, Rule Extraction and
Adaptive Dynamic Programming ADP-Based Learning Control..
Vision-Driven Multisource-Driven
Learning-Driven
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18. in D2ITSLearning-Driven-Data Process
Process
Module
Online
Learning
Data
Fusion
Rule
Extraction
Based
Learning
Control
Online Learning
used for traffic control, particularly for real-
time traffic control and transportation
system analysis.
Data Fusion
can effectively use multi source
driven to better analyze and
predict traveler behavior and
traffic dynamics.
Rule Extraction
This function use to explore the
relationship between the type of
roads and specific types of traffic
accidents to analysis and predict the
traffic network flow.
ADP-Based Learning
Control
Adaptive Dynamic Programming
this function will provide a basic
tool to releasing D2ITS with
online learning and performance
optimization in dynamic uncertain
conditions.
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19. Roadmap & Future Directions (D2ITS)
A roadmap for future directions for the development and deployment of D2ITS is described, emphasizing
the privacy-preserving, people-centric and scenario-oriented aspects of the system components
in D2ITS.
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20. Potential Research in D2ITS
Statistical analysis of the number of papers related to the D2ITS.
The result shows the following observations:
1) Vision and learning-driven ITS have received much attention from researchers
2) the number of papers related to learning issues around 23 research, and only 4of these papers
are closely related to the development of ITS .
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21. Conclusion
I. D2ITS is a very important field that can provide more functions and services to
improve our transportation systems.
II. D2ITS collect amounts of data from various sources to analyze and help with
planning, rerouting of traffic, providing real-time updates.
III. D2ITS create system that is constantly being optimized based on current and future
(predictive analysis) conditions.
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22. Thanks …
Rayan Nouh
Dankook University
Nov.2015