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Intelligent Autonomous Transportation: IBM HorizonWatch 2016 Trend Brief

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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

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Intelligent Autonomous Transportation: IBM HorizonWatch 2016 Trend Brief

  1. 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. 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. 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. 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. 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. 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

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