Keeping the flow
How AI and machine learning are reshaping how transit systems move patterns By Timothy Menard
O
f the many ways artificial intelligence (AI) and machine learning are poised to improve modern life, the promise of impacting mass transit is significant.
The world is much different compared with the early days of the pandemic, and people around the world are again leveraging mobility and transit systems for work, leisure, and more.
Across the US, traditional mass transit systems including buses, subways and personal vehicles have returned to struggling through gridlock, rider levels and congestion. But advanced AI and machine learning solutions built on cloud-based platforms are being deployed to reduce these frustrations. Transportation is one of the most important areas where modern AI provides a significant advantage over conventional algorithms used in traditional transit system technology. AI promises to streamline traffic flow and reduce congestion for many of today’s busiest roadways and thoroughfares. Smart traffic light systems and the cloud technology platforms they operate on are now designed to manage and predict traffic more efficiently, which can save a lot of money and create more efficiencies not only for the cities themselves, but also for individuals. AI and machine learning today can process highly complex data and traffic trends and suggest optimum routing for drivers in real-time based on specific traffic conditions. As a result of drastically improved processing power, transit system technologies are now used in various IoT (Internet of Things) devices to achieve real-time image recognition and prediction that took place in legacy data centers during the last half century. This new decentralized-focused architecture helps increase the implementation of machine learning and AI.
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COMMERCIAL CONSTRUCTION & RENOVATION — ISSUE 5, 2022
