How Do Digital Twins Help Reduce Traffic Congestion?

Traffic congestion is a pervasive issue in urban areas worldwide, causing delays, increasing fuel consumption, and significantly contributing to air pollution. Although the pandemic led to a temporary decrease in traffic, the problem persists, with Americans losing an average of 26 hours last year to road congestion. In India, the situation is even more critical with its rapidly growing urban population. Cities like Bengaluru and Mumbai are notorious for their traffic snarls, frustrating commuters and leading to significant economic losses and increased air pollution. The transportation sector accounts for 27% of global greenhouse gas emissions, exacerbating climate change and degrading air quality. In India, the contribution of automobiles to total air pollution is reported to be between 40-80%, and for Delhi's ambient air quality, the transport sector's contribution is estimated as high as 72% (Source - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4746948/). Addressing this crisis requires innovative solutions that go beyond traditional traffic management methods, such as continuous major infrastructure changes, promoting public transportation, or implementing congestion pricing. 

To combat these growing traffic issues, Fabrik utilises machine learning and real-time data collected from a wide range of infrastructure sensors and create a digital twin to first assess existing traffic conditions. We aggregate static and dynamic data from sources like Digital Elevation Models (DEM), infrastructure CAD, operating procedures, traffic controllers, vehicle counters, open-sources data for weather and traffic density, and data on accidents. The digital twin is applied at a local intersection level to help grass root teams determine the deployment of resources over the next 24-48 hours. The grass roots approach leads to a more accurate representation of infrastructure over a few blocks allowing us to scale the solution better.

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What are Digital Twins?

Digital twins are dynamic, digital replicas of physical systems—such as a city's traffic network—that use real-time data to simulate, predict, and optimize performance. These sophisticated models are powered by data collected from various sensors and devices, providing a comprehensive, up-to-date view of traffic conditions. By leveraging advanced analytics and machine learning, digital twins enable city planners and traffic managers to test different scenarios and implement data-driven strategies to improve traffic flow and reduce congestion.

Case Study: Introducing safety performance function for road networks

Implementing Digital Twins for Accidents on Highways

Indian highways see ~ 2,00,000 deaths a year and that number should reduce. This is a great opportunity to cutting edge technologies like digital twins to create a prediction algorithm that predicts the likelihood of an accident at any point along the highway across the country. There are many challenges with this approach:

1. Availability and access to accident data.
2. Accepted standard for capturing and reporting across the country.
3. Getting updated data for other static and dynamic sources of data.

Impact of digital twins

The algorithm ingests these data sources to predict the likelihood of an accident in the next twelve months. For individual police stations with limited resources, this application helps deploy resources effectively to reduce the likelihood of accidents at accident hotspots.

Digital Twins for Indian Traffic Conditions

Fabrik is actively working with a few government agencies to implement digital twin technology, leveraging our extensive experience in smart city solutions. Our collaboration focuses on integrating digital twins into existing urban infrastructure to create a comprehensive and efficient traffic management system. We aim to streamline data collection and analysis, enhance real-time decision-making capabilities, and develop tailored strategies for each city's unique traffic challenges. Fabrik's expertise in deploying cutting-edge technologies ensures that the solutions we provide are not only innovative but also practical and scalable, allowing for seamless implementation across various urban environments.

TL;DR

Digital twins represent a transformative approach to traffic management, offering significant benefits in terms of reduced congestion, lower emissions, and improved urban mobility. By harnessing real-time data and advanced analytics, cities can implement smarter, more efficient traffic management strategies. As India grapples with its traffic challenges, digital twins offer a promising solution to create more sustainable and liveable urban environments.

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