Tal Kreisler is the CEO and Co-Founder of NoTraffic, a platform that digitizes road infrastructure management, allowing cities to manage their entire grid at the push of a button.
NoTraffic transforms intersections into intelligent hubs capable of real-time traffic management. Their AI-powered platform leverages edge computing to process data locally, ensuring rapid response to changing traffic conditions. The technology includes V2X capabilities for connected and autonomous vehicles and accommodates non-connected vehicles and vulnerable road users (VRUs), providing a comprehensive view of traffic dynamics. NoTraffic is currently operating in more than 25 U.S. states and in Canada, serving millions of drivers per day.
Can you give us a brief overview of NoTraffic and what inspired you to develop an AI-powered mobility platform?
NoTraffic is a first-of-its-kind AI-powered mobility platform, that transforms outdated intersections into smart, cloud-connected hubs. The platform leverages AI, edge computing technologies and V2X communication to optimize traffic flow, reduce congestion, and enhance road safety, while significantly lowering carbon emissions.
The idea behind NoTraffic stemmed from a simple yet frustrating experience experienced by one of our Co-Founders, Uriel Katz, who found himself sitting stuck at a red light at an empty intersection late at night. This unnecessary waiting made him realize that traditional traffic management systems were outdated and inefficient, relying on set timing plans that didn’t adapt to real-time conditions. This sparked the idea of creating a more modern solution—one that leverages AI to dynamically manage traffic based on actual road usage and conditions.
To address this issue we founded NoTraffic in 2017, with the goal of revolutionizing urban mobility and traffic management. Despite not having a background in traffic management, our fresh perspective allowed us to think creatively and approach the problem with an out-of-the box solution. Fast forward to today, and NoTraffic is at the forefront of redefining urban mobility, future-proofing our cities into smarter and more efficient ecosystems.
How does NoTraffic’s AI-powered platform transform traditional intersections into intelligent hubs?
NoTraffic’s platform transforms traditional intersections into smart, connected hubs by integrating AI-driven sensors and edge computing capabilities seamlessly into existing infrastructure, leveraging a fusion of advanced radar and camera technology to achieve 99% detection accuracy, regardless of weather conditions. These sensors detect and identify all types of road users, from vehicles to micromobility users, in real-time, enabling the platform to dynamically adjust traffic signals, optimizing the flow of traffic and enhancing safety on the roads.
The platform’s real-time communication with a cloud-based system ensures continuous learning and updates, allowing intersections to respond intelligently to real time changing conditions, significantly enhancing the efficiency, safety, and overall flow of traffic across urban areas.
The platform is made up of four core components:
- Mobility OS (Operating system): A cloud-based dashboard that allows for real-time adjustments and optimizations, crucial for managing modern urban mobility.
- AI-driven Edge Devices: These ensure continuous connectivity, detect road users, and link intersections to the cloud, enabling real-time decisions via edge computing and advanced analytics.
- Mobility Store: A first-of-its-kind feature that functions like an app store, allowing operators to remotely add and update mobility applications, ensuring adaptability without costly hardware upgrades.
- 24/7 Support: Continuous and reliable operation is guaranteed, with prompt issue resolution to maintain safety and efficiency.
Can you explain the role of edge computing in your platform and how it enhances real-time traffic management?
Edge computing plays a critical role in NoTraffic’s platform by enabling real-time data processing directly at the intersection, without having to first upload data to the cloud. This allows the system to make instant decisions, making traffic management both faster and more efficient. This ensures that traffic signals and systems can quickly adapt to changing conditions, such as a sudden increase in pedestrian activity or giving priority to emergency vehicles. By localizing data processing, edge computing speeds up decision-making while also lowering operational costs by minimizing the need for cloud-based resources and additional hardware. This is essential for managing dynamic urban traffic environments, where quick reactions are essential for optimizing traffic flow and improving safety.
How does NoTraffic improve safety at intersections, especially for vulnerable road users such as pedestrians and cyclists?
Every year, over 700 deaths are caused by red light runners, including fatalities among pedestrians, cyclists and motorists.
NoTraffic improves safety at intersections by using AI-powered cameras and radar detection to accurately identify and differentiate between all types of road users, including pedestrians, cyclists, and scooters. After identifying them, the platform can adjust traffic signals to prioritize the safety of these vulnerable groups. For example, it can extend green light times or activate pedestrian crossings only when people are actually waiting. The system also proactively prevents potential accidents, such as vehicles running red lights, by adjusting signal phases in real-time. These measures not only reduce accidents but also create safer intersections, easing congestion on roads, sidewalks, and bike paths.
NoTraffic’s Intersection Safety Insights (ISI) is a safety-oriented AI software application, designed to enhance safety by correlating traffic signal phases with vehicle movements across the stop line, enabling precise tracking of red light runners. The technology was deployed at 55 intersections across three major urban traffic corridors in Tucson, Arizona, and was able to significantly reduce red light running infractions. Over a 3-month period, ISI enabled the city of Tucson to reduce red light runners by 42% across these corridors, equating to 294 lives saved annually.
In what ways does your platform reduce CO2 emissions and mitigate traffic congestion in urban areas?
As our roads become increasingly crowded with a mix of cars, bikes, and pedestrians, congestion is on the rise—growing by 12% each year. The resulting gridlock leads to harmful CO2 emissions and a 10.5% increase in traffic accidents, making our roads less safe.
NoTraffic addresses these challenges by optimizing traffic flow at intersections by pairing AI-driven real-time traffic analysis with edge-compute-enabled on-premise sensors that make instant decisions. This easy-to-install software-defined SaaS platform adjusts traffic light patterns based on real-time conditions, minimizing idle times and reducing unnecessary stops and starts. By improving the efficiency of traffic signals, NoTraffic decreases the time vehicles spend idling at red lights, which reduces fuel consumption and lowers emissions. NoTraffic empowers Departments of Transportation and other stakeholders to efficiently manage increasing traffic volume and reduce congestion and CO2 emissions, contributing to a more efficient and environmentally friendly urban mobility system.
One of NoTraffic’s key features available on its Mobility Store is Optimization Mode, which leverages predictions to evaluate thousands of potential traffic scenarios in real time to optimize traffic flow, reduce congestions, and improve overall safety. When deployed at the University of British Columbia, the solution eased campus traffic and improved flow at intersections, leading to a reduction in greenhouse gas emissions. By using edge based computing, NoTraffic was able to optimize traffic flow by calculating thousands of possible scenarios for every roadway user, and determining the most appropriate one in real-time. Implementation of the solution enabled NoTraffic to reduce carbon emissions by 75 tons per year.
How does NoTraffic integrate with connected and autonomous vehicles through V2X technology?
NoTraffic’s platform is designed to fully support V2X (Vehicle-to-Everything) communication, enabling seamless integration with connected and autonomous vehicles. Through V2X, NoTraffic-equipped intersections can exchange real-time data with vehicles, enabling more efficient and safer traffic management.
NoTraffic has commercialized V2X technology with two specialized packages for connected and autonomous vehicles: a Safety Package and an Efficiency Package. These packages provide sets of messages to vehicles using C-V2X or DSRC protocols, supplementing V2X capabilities with data from NoTraffic sensors and providing external blind spot information, Signal Phase and Timing (SPaT) enhanced driver decisions, Red Light Runner (RLR) detection, and other safety features.
By integrating V2X communication, NoTraffic’s platform fuses and shares data generated by their proprietary intelligent edge sensors together with connected and autonomous vehicles data and other data sources to manage traffic flows in real time and prevent potential collisions. The system provides vehicles with critical information such as SPaT, collision warnings, and optimal speed recommendations. This real-time connectivity ensures smoother traffic flow, reduces conflicts, and enhances the safe and efficient operation of autonomous vehicles.
What measures are in place to ensure the platform also accommodates non-connected vehicles and road users?
NoTraffic’s platform is built to accommodate all road users, from cars and bikes to pedestrians and emergency vehicles, even in challenging weather conditions. Its advanced sensors enable municipalities to optimize traffic flow for all commuters while reducing congestion on roads, sidewalks, and bike paths.
The platform’s advanced AI sensors can detect and analyse the behaviour of every road user, regardless of their connectivity status. This ensures that non-connected vehicles and pedestrians are always considered in real-time traffic decisions.
What challenges have you faced in scaling the deployment of your platform across different regions?
Scaling the NoTraffic platform across different regions presented significant challenges, particularly due to the complexity of integrating a cloud based interface, known as our Mobility OS (Operating system), with edge devices at every intersection.
One of the main challenges was adapting the cloud-based Mobility OS (Operating System) and edge devices to meet the various technical standards and infrastructure capabilities across different regions. Each region had its own set of rules, regulations, and requirements, and so the platform had to be personalized and adapted to meet the needs of each region, and ensure seamless integration with existing traffic systems. Additionally, managing the high bandwidth requirements needed for real-time communication between the cloud and the edge devices. To address this, NoTraffic implemented edge computing within their hardware, allowing a significant portion of analytics to be processed locally before sending the results to the cloud for further analysis. This reduced bandwidth usage while also making the solution more cost-effective for both NoTraffic and their customers.
Another challenge was the need to update, upgrade, and maintain software for hundreds of thousands of devices across various locations. To combat this, NoTraffic developed robust over the air mechanisms to enable rapid deployment of updates, regardless of location. These mechanisms ensure that updates are seamlessly distributed and installed across all devices, minimizing downtime and maintaining consistency in performance and reliability.
Security was also a critical concern, especially when dealing with infrastructure as critical as traffic management. NoTraffic implemented strict security protocols tailored to each region, ensuring that their data remained isolated and protected, preventing any potential overlap or interference. By leveraging advanced cloud security measures, the company ensured that they were able to maintain the integrity and confidentiality of data, while complying with local regulations.
Through these strategies, NoTraffic successfully navigated the complexities of developing and scaling a platform that combines hardware and software, ultimately delivering a reliable, secure, and cost-effective mobility solution across different regions.
How do you envision the future of traffic management and urban infrastructure evolving in the next decade?
The future of traffic management and urban infrastructure will be driven by the widespread adoption of software-enabled devices that enhance the sustainability and efficiency of cities. Similar to how Tesla reinvented cars, these devices are set to reinvent the rest of the mobility ecosystem. Advanced sensors with built-in communication capabilities, powerful computing, and the capacity to analyse vast amounts of data will become standard. These sensors will offer a wide range of services that can be updated, adjusted, and repaired remotely, ensuring continuous improvement and minimizing the need for physical intervention. The shift towards these smart, software-driven devices will simplify the modernization of infrastructure, reduce waste, and cut down on the need for extensive hardware. Traffic devices and systems will function more like smartphones, where features can be personalized, activated, updated, or repaired remotely, making infrastructure upgrades smoother, more affordable, and less intimidating for municipalities.
One of the key advantages of this technology is the ability to aggregate data and quantify various parameters like traffic improvements, safety enhancements, and emissions reductions. It can also enable the identification of trends and support predictive analytics, offering insights into potential outcomes of specific policies before they are implemented. For example, the economic impact of traffic delays could be measured, or before-and-after studies could assess the effectiveness of traffic management strategies – something that is impossible with current systems.
By reimagining transportation systems with these strategies, future urban areas can achieve enhanced safety and improved mobility while significantly reducing their environmental footprint, leading to more sustainable and livable cities.
What role do you see AI playing in the future of smart cities and mobility solutions?
AI will play a major role in the future of smart cities and mobility solutions through data aggregation and decision-making. Thanks to AI-powered technologies being used in traffic management, cities can now use data to quantify various parameters, such as traffic improvements, safety enhancements, and emission reductions. This data provides a clear picture of the effectiveness of different traffic management strategies, enabling cities to make the most impactful and beneficial decisions, tailored to the specific needs of each area.
AI also enables the identification of trends and supports predictive analytics, offering insights into potential outcomes if specific policies are implemented. For example, using AI cities can now measure the economic impact of traffic delays, or carry out before and after studies to measure the effectiveness and success of new initiatives. By being able to back up decisions with concrete data, cities are able to pinpoint problems and implement targeted solutions, something that would previously have been impossible to achieve.