The slides provide a quick overview of the Intelligent Autonomous Transportation trend. The slides provide summary information, a list of trends to watch and links to additional resources

1. © 2016 IBM Corporation
IBM Market Development & Insights
Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution.
Intelligent Autonomous Transportation
IBM HorizonWatch 2016 Trend Brief – External Version
Bill Chamberlin, Principal Client Research Analyst / IBM HorizonWatch Community Leader
May 11, 2016

2. © 2016 IBM Corporation
IBM Market Development & Insights
Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution.
About This HorizonWatch Emerging Trend Brief
2 Intelligent Transportation: HorizonWatch 2016 Emerging Trends Brief (External version)11May2016
 Purpose: The slides provide a quick overview of the Intelligent Autonomous
Transportation trend. The slides provide summary information, a list of trends to watch
and links to additional resources
 How To Use This Report: Use these slides as a learning document and a springboard
to further research and reading on this trend. You may want to view the slides in
slideshow mode so you can easily follow the links
 Available on Slideshare: The latest version of this file (and other HorizonWatch Trend
Reports for 2016) will be available publically on Slideshare at
http://www.slideshare.net/horizonwatching
 Please Note: This report is based on internal IBM analysis and is not meant to be a
statement of direction by IBM nor is IBM committing to any particular technology or
solution.

3. © 2016 IBM Corporation
IBM Market Development & Insights
Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution.
About Intelligent Autonomous Transportation Systems
Intelligent Transportation Systems (ITS) combine
information and communication technologies used in
transportation and traffic management systems. ITS
includes telematics and communications between
vehicles (vehicle-to-vehicle) and physical locations
(vehicle-to-infrastructure). This also includes the use of
information and communication technologies (ICT)
between all type of transportation vehicles (i.e. cars,
trains, ships, planes).
An autonomous car is a robotic vehicle that is designed
to travel between destinations without a human operator.
Sensor-based solutions and connected-vehicle solutions
are the two main technologies required to enable
autonomous vehicles to remain safely on the road.
• The senor based solutions include lane-keeping and
warning systems, adaptive cruise control, back-up
alerts and parking assistance.
• Connected-vehicle solutions enable real-time
communication between vehicle-to-vehicle (V2V) and
Vehicle-to-Infrastructure (V2I).
3 Intelligent Transportation: HorizonWatch 2016 Emerging Trends Brief (External version)11May2016
“Intelligent Transportation System (ITS) is a
combination of information and communication
technologies used in transportation and traffic
management systems, which improve the
safety, efficiency, sustainability of
transportation networks and reduce traffic
congestion.” MarketsandMarkets Intelligent Transportation
System - Analysis & Forecast to 2015 - 2020
“Imagine how a fully functional Internet of
Things (IoT) system will transform the
transportation industry. Think about a
transportation system where people, vehicles
(of all types) and the transportation corridor
infrastructure (roads, air, water, rail, etc.) are all
connected via a massive collection of IoT
networks.” IBM
“Intelligent mobility builds on the foundation of
intelligent transportation to address key goals of
the automotive industry: Save lives, save the
environment, and reduce commuting effort..”
Frost & Sullivan The Future of Intelligent Mobility and its
Impact on Transportation

4. © 2016 IBM Corporation
IBM Market Development & Insights
Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution.
Intelligent Autonomous Transportation Trends to watch in 2016
1. Safety will emerge as a key selling point for
autonomous vehicles. The majority of vehicle
crashes are the result of human error so collision
avoidance systems are in demand.
2. Reducing the cost of autonomous vehicles.
Features such as collision avoidance systems are
costly, making these systems out of range for many
consumers. The cost of safety products will reduce as
they become more standardized and regulated.
3. Advanced Transportation Management Systems
(ATMS). Today ATMS are used for traffic monitoring,
traffic signal controlling, incident monitoring and
automated warnings. Tomorrow, these systems will
monitor and control all traffic for both autonomous and
human operated vehicles.
4. Vehicles & IoT: The vehicle of the future will be an
sensor-based IoT network on wheels. A key trend to
watch is vehicle to vehicle communications and vehicle
to ATMS communications.
5. Vehicle Ownership: Consumers begin to question
whether they will need to own a car in the future of
autonomous cars
4
“The auto industry is poised for more
change in the next five to ten years than
it’s seen in the past 50.” Mary Barra, CEO,
General Motors
“There is a need for a unified approach
that reaps benefits across safety, fuel
economy and better flow of traffic. This
can only be done when vehicles are not
only automated, but are capable of
communicating with each other, have a
better sense of eco-driving and embrace
new mobility modes to achieve leaner
commuting.” Frost & Sullivan The Future of
Intelligent Mobility and its Impact on Transportation
Financial Times: Driverless cars: When
robots rule the world
Intelligent Transportation: HorizonWatch 2016 Emerging Trends Brief (External version)11May2016

5. © 2016 IBM Corporation
IBM Market Development & Insights
Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution.
Intelligent Transportation Adoption Challenges
1. LIDAR technology is expensive. LIDARs are
sensors that monitor their surrounding area by shinning
lasers on an object and measuring the time until it
bounces back. Autonomous car manufacturers will
need to reduce the cost of this technology to make
autonomous cars more affordable and to create a mass
market.
2. Security and privacy challenges. Transportation
dynamics indicate that people will increasingly rely on
Uber-like companies for future transportation needs. As
such, customers’ route and related personal
identification data will become property of these new
transportation entities. Security will become a key issue
for these companies and their customers as data
economies emerge around transportation.
3. Cost to modernize infrastructures. Cities will need
to adopt digital systems for smart transportation to
support autonomous vehicles. Autonomous vehicles
will need to communicate with sensors located in traffic
lights, traffic management systems, road sensors,
smart grids, and many other elements of public
infrastructure to effectively operate.
5
“Imagine what would happen if hackers
took over a city’s transportation grid and
turned all of the traffic signals red.” Kurtis
McBride via Roads&Bridges article: A brave new
world
The World Bank: Advances and
Challenges in “Intelligent Transportation”
Intelligent Transportation: HorizonWatch 2016 Emerging Trends Brief (External version)11May2016
U.S. GAO: Vehicle-to-Infrastructure
Technologies Expected to Offer Benefits,
but Deployment Challenges Exist

6. © 2016 IBM Corporation
IBM Market Development & Insights
Note: This report is based on internal IBM analysis and is not meant to be a statement of direction by IBM nor is IBM committing to any particular technology or solution.
Selected Additional Resources
 IBM: IoT: The engine that will transform transportation
 IBM: Digital disruption and the future of the automotive industry
 IBM: Intelligent transport: A path to smarter mobility
 European Commission on Mobility and Transport
 Intel: Intelligent Transportation: Make Driving Safer and More Efficient
 Intel: Building an Intelligent Transportation System with the Internet of
Things
 Intelligent Transportation Society of America: Knowledge Center
 ITS World Congress: 24th World Congress on Intelligent Transportation
Systems
 Grand View Research: ITS Market Size To Reach $38.68 Billion By
2020
 Mass Transit Mag: Mapping IoT into Today’s Urban Transportation
Systems
 Singapore: Smart Mobility 2030 Strategic Plan
 U.S. Department of Transportation Strategic Plan
 U.S. Department of Transportation: Research
 Wikipedia: Intelligent transportation system
 The World Bank: Toolkit on Intelligent Transport Systems for Urban
Transport
6 Intelligent Transportation: HorizonWatch 2016 Emerging Trends Brief (External version)11May2016
“Connected cars are mobile
mega sensors, even more so
than smartphones, with a wide
range of sensors, including
cameras, radar, sonar, and
Lidar as well as vehicle-specific
equipment such as ESP,
temperature sensors, and lights
producing large amounts of
data.” ABI Research
IBM: IoT: The engine that will transform
transportation