Big Data Analytics for Connected, Autonomous Vehicles and Smart Cities

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. They 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.

What Will You Learn

By successfully participating in this seminar, you will be able to:
  • Describe a smart city
  • Explain the initiatives for smart cities in the USA
  • Discuss essential features of a smart city from a mobility perspective
  • Describe smart city mobility services
  • Explain the features and likely impacts of connected and autonomous vehicles
  • Define the role of autonomous vehicles in a smart city
  • Describe the characteristics of big data and analytics
  • Identify some examples of interactions between automated driving systems and smart mobility services
  • Describe an integrated urban mobility approach
  • Explain future trends in mobility for connected and autonomous vehicles

Is This Course For You

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.

Materials Provided

This data is not available at this time

Course Requirements

This data is not available at this time


  • Introduction and Course Overview
    • Introduction to course
    • Course learning objectives
    • Course agenda
  • Smart Cities
    • The definition of a smart city
    • The objectives of a smart city
    • Smart city mobility services
    • The importance of transportation to a smart city
    • Smart city planning
    • Investment evaluation
    • Challenges
    • Opportunities
    • Data definition of a smart city
  • Group Discussion: Mobility in Smart Cities
    • The need for smart cities
    • People aspects of smart cities
    • Smart city objectives
    • The role of the car
    • Challenges and opportunities related to connected and autonomous vehicles
  • Smart Mobility
    • The role of mobility in a smart city
  • Connected Vehicles
    • The evolution of electronics within automobiles
    • The connected vehicle defined
    • The autonomous vehicle defined
    • The likely evolution of autonomous vehicles
  • Automated Driving Systems (Autonomous Vehicles)
    • The evolution of Automated Driving Systems
    • The essential features of Automated Driving Systems
    • Examples of Automated Driving Systems
    • Challenges associated with Automated Driving Systems
    • A proposed implementation plan for Automated Driving Systems
  • Group Discussion: Connected and Autonomous Vehicles
    • The importance of mobility and smart cities
    • Implementation timescale for connected and autonomous vehicles
    • Challenges associated with the introduction of Automated Driving Systems
    • Opportunities associated with Automated Driving Systems
    • Automated Driving Systems within the bigger picture for urban mobility

  • Big Data?
    • How to get the most value from big data
    • The evolution of big data
    • Big data defined
    • Big data for transportation
    • Smart data management
    • Smart data management challenge
  • Analytics
    • What are analytics?
    • The difference between analytics and reporting
    • Urban analytics
    • Smart mobility use cases
    • Examples of transportation analytics
    • Defining analytics for specific transportation services
    • Analytics associated with connected and autonomous vehicles
  • Transportation Analytics
    • Examples of transportation analytics
    • Defining analytics for specific transportation services
    • Analytics associated with connected and autonomous vehicles
  • Group Discussion: Automated Driving System Challenges
    • Mixed traffic
    • Graceful degradation
    • Field testing
    • Policy
  • Connected and Autonomous Vehicles as Part of the Bigger Picture
    • Managing transportation as a single system 
    • Essential features of single system transportation management
    • Data combinations
    • Connected and autonomous vehicles within the smart mobility context
    • Interactions between one connected, autonomous vehicles and smart mobility services
  • What's Next?
    • Future objectives-based transportation optimization
    • Transportation as a single system
    • Solution optimization
    • Service optimization
    • Applications of artificial intelligence
    • Smart data management
    • The sentient city
  • Group Discussion: Business Models, Artificial Intelligence and Evolution
    • Possible business models for mobility as a service
    • Examples of artificial intelligence applications
    • The evolution of Automated Driving Systems