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Optimizing Big Data Analytics for Connected Autonomous Vehicles and Smart Cities C1912


There is growing interest in the concept of a smart city and how these advanced technologies will improve the quality of living and make a city more attractive to visitors, commerce and industry. This course fills an unmet need for defining and explaining the relationship between connected and autonomous vehicles (CAVs) and smart city transportation. It is apparent that CAVs will achieve the best results when integrated with current and emerging urban infrastructure for transportation.

This course addresses such integration from technology, organizational, policy and business model perspectives. It seeks to explain to connected and autonomous vehicle designers, manufacturers, and associated OEMs, how CAVs will play a central role in the future urban transportation system. This will take account of the needs of infrastructure planners and operators, aligning these with CAV capabilities.

Participants will learn how CAV technology will revolutionize urban transportation will gain a detailed understanding of the role for smart vehicles within a smart city and an overall perspective on the needs, issues, problems and objectives being addressed by the development of advanced transportation elements. Participants will be able to create more effective designs and define smart mobility services that fit within the overall context of urban infrastructures.

The course will address three common challenges associated with the application of CAV technology to smart cities. These are: the use of big data and analytics techniques, establishing and maintaining suitable public-private partnerships, and aligning policy objectives with technology capabilities.


Learning Objectives
By attending this seminar, you will be able to:
  • Define the essential elements of smart cities from a transportation perspective
  • Describe smart city transportation services
  • Explore how multi-modal systems will shape future cities
  • Define the role of CAVs in a smart city
  • Explain the optimum operation of CAVs interact with urban infrastructure
  • Recognize the value of big data and analytics in urban transportation data transportation
  • Describe a list of smart city transportation applications that are enabled by interaction between the vehicle and infrastructure
  • Explain the overall benefits and costs of smart city transportation services
  • Distinguish the policy objectives and challenges associated with CAVs within a smart city
  • Associate possible CAV partnership arrangements with a smart city

Who Should Attend
The course is designed for CAV technology designers and developers, vehicle product managers, smart mobility services developers, CAVs service providers, associated software development engineers and OEM system developers and automotive manufacturers.

Prerequisites

It is expected that participants will have a minimum of 3 to 5 years’ experience in the design of onboard vehicle technology and the development and implementation of related smart mobility approaches.

Please bring a laptop and calculator with you to class.


DAY ONE
  • Introduction to the course and content overview
    • Course learning objectives
    • Course structure and content
    • Intended audience
  • What is a smart city?
    • The definition of a smart city
    • The objectives of a smart city
    • Smart city services
    • The importance of transportation to a smart city
    • Smart city transportation services
  • Connected and autonomous vehicles
    • Overview of connected and autonomous vehicle technology
    • The value of vehicle-infrastructure interaction
  • The role of connected and autonomous vehicles within a smart city
    • Technology framework - how do they fit?
    • Organizational framework - interaction with infrastructure operators and policymakers
    • Business framework - potential public-private partnerships
  • What is Big data?
    • The 6 dimensions of big data - volume, velocity, veracity, variety, type of data, variability, complexity
    • Moving effectively and efficiently from sensing data, converting it to information, extracting insight and understanding and developing appropriate strategies
    • The value and impact of big data on transportation and smart vehicles
  • Analytics
    • What are analytics?
    • The difference between analytics and reporting
    • Why analytics are valuable
  • Transportation analytics
    • Examples of transportation analytics
    • Defining analytics for specific transportation services
    • Analytics associated with connected and autonomous vehicles
DAY TWO
  • Transportation applications within a smart city
    • What is an application?
    • Why are applications important?
    • A range of applications that can be supported by CAVs within a smart city
    • Aligning applications to policy objectives
  • Smart data management for smart cities
    • Smart and not so smart data management
    • The essential elements of a smart data management system for smart city
    • How to incorporate CAVs within a smart data management system
    • How to approach the establishment of a smart data management system
  • Policy questions that can be addressed
    • An overview of smart city transportation policy issues
    • The relationship between policy and technology
    • Questions that can be addressed
    • Some example strategies to implement policy
  • Business model and organizational arrangements
    • Definition of business models
    • Definition of organizational arrangements
    • Some examples of business models
    • Some examples of organizational arrangements
  • Public-private partnerships
    • The role of the public sector and the role of the private sector
    • Important aspects of successful partnerships
    • How to establish a public-private partnership
    • How to sustain a public-private partnership
  • Course summary and discussion
    • Review course materials
    • Review of learning objectives
    • Discussion on course materials and practical application
    • Course evaluation and feedback
Robert McQueen

Robert Bob is a subject matter expert and an internationally recognized leader with in-depth practical experience in developing and managing advanced transportation technology and smart city planning. He has conducted consulting assignments in the USA, Asia Pacific, Middle East and Europe for both public and private sector clients on business plan development and the evaluation/assessment of new market opportunities related to advanced transportation technologies. These assignments have also involved the identification and establishment of strategic business relationships and alliances. He also has proven business acumen in the US state, local and federal market segments.

Bob has recently published a book entitled “Big Data Analytics for Connected Vehicles and Smart Cities” which addresses the use of advanced analytic techniques for probe vehicle data associated with CAVs within the context of smart city transportation. He is also the author of “Intelligent Transpiration System and Architecture” and “Advanced Traveler Information Systems.” 

Hotel & Travel Information

Fees: $1415.00
SAE Members: $1132.00 - $1274.00

1.3 CEUs
You must complete all course contact hours and successfully pass the learning assessment to obtain CEUs.

To register, click the Register button above or contact SAE Customer Service 1-877-606-7323 (724-776-4970 outside the U.S. and Canada) or at CustomerService@sae.org.

Duration: 2 Days
April 10-11, 2019 (8:30 a.m. - 4:30 p.m.) - Detroit, Michigan
April 17-18, 2019 (8:30 a.m. - 4:30 p.m.) - Troy, Michigan
June 20-21, 2019 (8:30 a.m. - 4:30 p.m.) - Troy, Michigan
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