Hyper Smart Transportation: Big Data, Virtualization, and Systemization
The traffic congestion, safety, pollution and other urbanization challenges Intelligent Transportations Systems (ITS) of the future will need to address are well documented. The ITS industry so far has approached the problems in a rather incremental way through solutions such as traveler information systems such as variable message signs, intelligent traffic signs, urban tolling, traffic monitoring, and management operations centers, and some timid efforts to introduce electrification. These are essentially non-structural solutions, merely fighting symptoms instead of the root causes of the urbanization issues. These plans will no longer be sufficient as the issues are spiraling out of control, especially in developing regions like Asia and Latin America where traffic congestion issues are threatening to limit or at least slow down further economic growth. Moreover, current ITS technologies are too expensive and an investment governments will not be able to maintain in a scalable way.
This reports aims at looking into the future, thinking out of the box, beyond the known tools and methodologies currently developed by ITS ecosystem participants. In particular, this report will be centered on three areas:
•The use of big data and advanced analytics in an ITS context
•Virtualization of physical roadside transportation infrastructure
•A systems approach to transportation management
The report also evaluates which connectivity, analytics, cloud platform, security, and identity technologies will be required for enabling the above mentioned new paradigms. In particular, the potential of DSRC, 4G, 5G, peer-to-peer, meshed, and centralized network topologies are assessed in terms of latency, availability, and economic feasibility.
- 1. TRANSPORTATION CHALLENGES WILL REQUIRE A NEW APPROACH
- 2. BIG DATA TSUNAMI AND ANALYTICS
- 2.1. The Connected Car as a Mobile Mega Sensor
- 2.2. Car OEMs and Suppliers Are Joining the Connected Car and ITS Analytics Ecosystem
- 2.2.1. Toyota
- 2.2.2. Volvo
- 2.2.3. PSA
- 2.2.4. Porsche Automobil Holding SE
- 2.2.5. VW - Data Lab
- 2.2.6. Tesla - Hadoop
- 2.2.7. Continental - eHorizon
- 2.2.8. SWARCO
- 2.2.9. Google
- 2.3. The Aggregation Issue
- 3. VIRTUALIZATION OF SMART ROADSIDE INFRASTRUCTURE
- 3.1. The Current Smart Transportation Approach Is Prohibitively Expensive
- 3.2. Saving Costs through In-vehicle and Cloud-based Virtualization Technologies
- 3.3. A Hard Choice for Governments
- 4. A SYSTEMS APPROACH TO SMART TRANSPORTATION
- 4.1. High-level Definition of a System
- 4.2. A Systems Approach for Smart Transportation
- 4.3. Smart Transportation System Components
- 4.3.1. Traffic Management - Variable Message Signs and Intelligent Traffic Lights
- 4.3.2. Dynamic Electronic Toll Collect (ETC)
- 4.3.3. Remotely Controlled Dynamic Routing
- 4.3.4. Autonomous Vehicles
- 4.4. Beyond Transportation
- 5. TECHNOLOGICAL REQUIREMENTS
- 5.1. V2X Low Latency Communications: DSRC versus 4G and 5G Cellular
- 5.1.1. DSRC
- 5.1.2. 4G - LTE
- 5.1.3. 5G
- 5.1.4. DSRC and Cellular Coexistence
- 5.2. Cloud-based versus Peer-to-peer Connectivity
- 5.3. Guaranteed Availability
- 5.4. Security and Identity Management
- 5.5. Connectivity and Cloud-connected Car Platforms
- 5.6. Data Analytics and Artificial Intelligence
Charts
- Real-time Traffic Information B2B Revenues by Region, World Market, 2010 to 2019
- Traffic Management System Revenues by Region, World Market, 2010 to 2019
- ETC Revenues by Region, World Market, Forecast: 2012 to 2019
- Driverless Vehicle Shipments by Region, World Market, Forecast: 2017 to 2035
- V2V OEM and Aftermarket Shipments by Region, World Market, Forecast: 2012 to 2027
- OEM-connected Car Cellular Connectivity Shares, World Market, Forecast: 2011 to 2020
Figures
- Big Data Traffic Information Service
- Cloud-based Sharing of Road Friction Data
- Systems Diagram
- Smart Mobility Diagram