Infosys > Case Studies > IIC Connected Vehicle Urban Traffic Management Testbed

IIC Connected Vehicle Urban Traffic Management Testbed

Infosys Logo
 IIC Connected Vehicle Urban Traffic Management Testbed - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Edge Analytics
  • Analytics & Modeling - Machine Learning
  • Infrastructure as a Service (IaaS)
Applicable Industries
  • Transportation
Applicable Functions
  • Logistics & Transportation
Use Cases
  • Vehicle Telematics
The Challenge

Road congestion and strained transportation networks are persistent concerns associated with the rapid urbanization of developing and developed economies. A 2015 study1 reported that travel delays due to traffic congestion led to the waste of 3.1 billion gallons of fuel and a loss of nearly 7 billion extra hours to travelers during rush hour traffic, with a nationwide cost of around $160 billion, or $960 per commuter. Alleviating traffic congestion, in addition to improving safety, is leading public and private organizations to explore new mobility paradigms such as ride-share autonomous vehicles. GOAL The goal of the Connected Vehicle Urban Traffic Management (CVUTM) testbed is to create a smart road traffic ecosystem featuring connected vehicles using vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) technologies, sensor fusion, industrial IoT platforms, cloud infrastructure, and edge analytics. This testbed will serve to preempt road congestion, automatically detect unusual eventson the road, and enable cooperative movement of traffic. In due course, both autonomous and non-autonomous vehicles will participate in this ecosystem with a goal of minimizing road congestion and improve overall improving motorist and pedestrian safety.

The Solution

*This is an IIC testbed currently in progress.* LEAD MEMBERS Infosys SUPPORTING COMPANIES Bosch Software Innovations, Real-Time Innovations (RTI) CLOUD SERVICE PROVIDER Microsoft MARKET SEGMENT Transportation (Connected Vehicles, Cooperative Traffic Movement, Shared Autonomous Mobility) FEATURES • The ability to integrate insights from connected vehicles with V2V/V2I technologies and cloud analytics to provide both a microscopic and macroscopic view of road congestion that will augment existing capabilities. • The ability to employ sensors and machine learning algorithms to automatically detect unusual events on the road and use this data to preempt road congestion, and provide such insights to motorists. • The ability to integrate IoT and connected vehicle technologies to enable cooperative movement of traffic and prevent road congestion for both non-autonomous and autonomous vehicles. TESTBED INTRODUCTION This testbed is focused on realizing an IIoT-enabled end-to-end smart mobility ecosystem that is augmented with cloud analytics, edge analytics, machine learning techniques, and V2V/V2I technologies. One of the many prerequisites for efficient movement of private and public autonomous traffic is the ability to evaluate, preempt and prevent road congestion, automatically identify unusual events on the road, and allow for cooperative point-to-point travel. We will adopt a phased approach towards realizing these goals. Directions and instructions regarding routes to take and recommendations on speed for each stretch of the road are provided by the cloud-enabled industrial internet system to the motorist. In due course, when fully autonomous vehicles are introduced into the system they will use this information and perform necessary speed changes and course corrections automatically without the need for driver intervention. MARKET CHALLENGES Widespread adoption of connected vehicle technology is essential for the CVUTM ecosystem to realize its ultimate vision. However, the adoption of CV technologies will follow market needs, and may start in smaller towns and cities and gradually spread to larger metros and states. Although a few auto OEMs are rolling out vehicles with V2V capabilities, federal mandates around CV technologies will benefit the larger adoption of the CVUTM ecosystem. TECHNICAL CHALLENGES A critical technology that enables the usage scenarios described in the testbed is the road-side unit. Adequate coverage of neighborhoods, streets, and highways with road-side units is essential for successful adoption of the CVUTM ecosystem. Meanwhile, other technologies such as LTE Direct and 5G that will allow for direct communications are also being considered to support inter-vehicular connectivity. Nevertheless, this testbed will serve as a stepping stone toward larger deployments of the CVUTM ecosystem at the level of a town, city or state, and serve as a proving ground for integrated industrial internet and existing or newer connected vehicle technologies.

Data Collected
Fuel Consumption, Gas Emissions, Traffic Congestion Levels, Traffic Flow, Vehicle Location Tracking
Operational Impact
  • [Product Improvement - User Experience]
    Address Smart City Urban mobility needs, which include improved overall driving experience, reduced lost time in traffic, and improved well-being and health of citizens owing to decreased emissions.
  • [Management Effectiveness - Real Time Information]
    Provide insights into the functioning of a connected vehicle-IIoT integrated architecture at the scale of a neighborhood, municipality, and city.

Case Study missing?

Start adding your own!

Register with your work email and create a new case study profile for your business.

Add New Record

Related Case Studies.

Contact us

Let's talk!
* Required
* Required
* Required
* Invalid email address
By submitting this form, you agree that IoT ONE may contact you with insights and marketing messaging.
No thanks, I don't want to receive any marketing emails from IoT ONE.

Thank you for your message!
We will contact you soon.