Traffic on 10th Avenue in Manhattan.

Traffic on 10th Avenue in Manhattan. Credit: Bloomberg/Jeenah Moon

This guest essay reflects the views of Timothy Menard, founder and chief executive of LYT, a traffic management company that uses artificial intelligence and machine-learning solutions for public transit, emergency vehicles, and snowplows.

Gov. Kathy Hochul’s decision to “pause” congestion pricing means drivers on Long Island and throughout the New York City region will avoid an added toll to enter Manhattan’s central business district. It also means residents and business owners likely will pay in the form of fare hikes and/or service cuts for public transit options.

Now, it’s time to focus on alternatives — new, budget-friendly, traffic-easing solutions that can benefit local residents, drivers and businesses.

New York has an opportunity to serve as a benchmark for how a large urban region can reinvent itself into a model of a modern transportation network. That requires thinking outside the box and leveraging technology already in use in other urban centers like Seattle and San Francisco, both of which have seen significant improvement in traffic flow and reduced congestion.

Using advanced technologies would help New York reduce traffic, enhance existing transportation systems in a low-budget approach, and create more equity in the transit system by enhancing public transportation options. By employing intelligent traffic management that uses AI and data to prioritize public transport vehicles such as city buses over private cars and trucks, cities like New York can improve the efficiency and reliability of public transit. And these technologies can be expanded in the future to include ride-share vehicles.

Technologies such as transit signal priority (TSP) and adaptive traffic signals can significantly improve traffic flow. TSP allows buses and trams to communicate with traffic signals via cloud technology to extend green lights or shorten red lights, reducing stop-and-go conditions and improving travel times for those vehicles.

To make this system work, New York will require use of a ground transportation-specific version of the air traffic control tower at Kennedy Airport used for planes. Even though many different brands, sizes, and shapes of planes are used for air travel, air traffic control is necessary to direct them safely from gate to gate both on the ground and in the air.

On the city’s roads, a similar cloud-based “control tower” technology platform can be used to systematically view each mobility provider (car, bus, rail, etc.) and adjust traffic signals for each so they all move in constant harmony and rhythm with each other, especially through traffic intersections.

Key to this system is the integration of traffic signals and intersections with the flow of traffic, which changes based on events, work-hour vehicle demand, weather patterns, and the prioritization of emergency response vehicles that need to move freely through certain corridors to get to an injured person, fire, or crime scene.

This cloud-enabled, transit-prioritizing technology can be scaled and adapted to different transit modes and city sizes, even urban centers like New York. Whether it’s prioritizing buses in a small city or managing a complex network of trams and buses in a metropolitan area, the technology is versatile and can grow with the city’s needs. In 2023 alone, TSP technology saved 9,107 hours (a 48% reduction) by reducing red-light wait times for transit buses in nine localities including Seattle, Boston, Toronto, and Tempe.

Investing in technologies like transit prioritization can be more cost-effective in the long run without the expense and time delays of new construction, and allows cities to take a prescriptive approach to solving traffic, as opposed to a reactionary approach. This contrasts with a congestion pricing-only approach, which primarily generates revenue rather than directly improving transportation infrastructure.


 THIS GUEST ESSAY reflects the views of Timothy Menard, founder and chief executive of LYT, a traffic management company that uses artificial intelligence and machine-learning solutions for public transit, emergency vehicles, and snowplows.


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