Tal Kreisler is the CEO and Co-Founding father of NoTraffic, a platform that digitizes road infrastructure management, allowing cities to administer their entire grid on the push of a button.
NoTraffic transforms intersections into intelligent hubs able to 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 greater than 25 U.S. states and in Canada, serving tens of millions of drivers per day.
Are you able to give us a transient 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NoTraffic is a first-of-its-kind AI-powered mobility platform, that transforms outdated intersections into smart, cloud-connected hubs.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 concept behind NoTraffic stemmed from an easy yet frustrating experience experienced by one in every 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 This unnecessary waiting made him realize that traditional traffic management systems were outdated and inefficient, counting on set timing plans that didn’t adapt to real-time conditions. This sparked the concept of making a more modern solution—one which leverages AI to dynamically manage traffic based on actual road usage and conditions.
To handle 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 issue with an out-of-the box solution. Fast forward to today, and NoTraffic is on 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 attain 99% detection accuracy, no matter weather conditions. These sensors detect and discover all sorts 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 reply 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 4 core components:
- Mobility OS (Operating system): A cloud-based dashboard that enables 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 primary-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 take care of safety and efficiency.
Are you able to explain the role of edge computing in your platform and the way it enhances real-time traffic management?
Edge computing plays a critical role in NoTraffic’s platform by enabling real-time data processing directly on the intersection, without having to first upload data to the cloud. This permits the system to make fast decisions, making traffic management each faster and more efficient. This ensures that traffic signals and systems can quickly adapt to changing conditions, resembling a sudden increase in pedestrian activity or giving priority to emergency vehicles. By localizing data processing, edge computing accelerates decision-making while also lowering operational costs by minimizing the necessity for cloud-based resources and extra hardware. This is crucial 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 resembling pedestrians and cyclists?
Yearly, over 700 deaths are brought on by red light runners, including fatalities amongst pedestrians, cyclists and motorists.
NoTraffic improves safety at intersections through the use of AI-powered cameras and radar detection to accurately discover and differentiate between all sorts of road users, including pedestrians, cyclists, and scooters. After identifying them, the platform can adjust traffic signals to prioritize the security of those vulnerable groups. For instance, it might probably extend green light times or activate pedestrian crossings only when persons are actually waiting. The system also proactively prevents potential accidents, resembling vehicles running red lights, by adjusting signal phases in real-time. These measures not only reduce accidents but additionally 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 reinforce 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 capable of significantly reduce red light running infractions. Over a 3-month period, ISI enabled the town of Tucson to cut back 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 develop into increasingly crowded with a mixture of cars, bikes, and pedestrians, congestion is on the rise—growing by 12% every year. The resulting gridlock results in harmful CO2 emissions and a 10.5% increase in traffic accidents, making our roads less protected.
NoTraffic addresses these challenges by optimizing traffic flow at intersections by pairing AI-driven real-time traffic evaluation with edge-compute-enabled on-premise sensors that make fast 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.
Certainly one of NoTraffic’s key features available on its Mobility Store is Optimization Mode, which leverages predictions to guage 1000’s of potential traffic scenarios in real time to optimize traffic flow, reduce congestions, and improve overall safety. When deployed on the University of British Columbia, the answer eased campus traffic and improved flow at intersections, resulting in a discount in greenhouse gas emissions. By utilizing edge based computing, NoTraffic was capable of optimize traffic flow by calculating 1000’s of possible scenarios for each roadway user, and determining probably the most appropriate one in real-time. Implementation of the answer enabled NoTraffic to cut back carbon emissions by 75 tons per yr.
How does NoTraffic integrate with connected and autonomous vehicles through V2X technology?
NoTraffic’s platform is designed to completely support V2X (Vehicle-to-The whole lot) 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 along with connected and autonomous vehicles data and other data sources to administer traffic flows in real time and forestall potential collisions. The system provides vehicles with critical information resembling SPaT, collision warnings, and optimal speed recommendations. This real-time connectivity ensures smoother traffic flow, reduces conflicts, and enhances the protected and efficient operation of autonomous vehicles.
What measures are in place to make sure 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 difficult 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 each road user, no matter their connectivity status. This ensures that non-connected vehicles and pedestrians are all the time considered in real-time traffic decisions.
What challenges have you ever faced in scaling the deployment of your platform across different regions?
Scaling the NoTraffic platform across different regions presented significant challenges, particularly because of the complexity of integrating a cloud based interface, often called our Mobility OS (Operating system), with edge devices at every intersection.
Certainly one of the major challenges was adapting the cloud-based Mobility OS (Operating System) and edge devices to satisfy the assorted technical standards and infrastructure capabilities across different regions. Each region had its own algorithm, regulations, and requirements, and so the platform needed to be personalized and adapted to satisfy the needs of every region, and ensure seamless integration with existing traffic systems. Moreover, managing the high bandwidth requirements needed for real-time communication between the cloud and the sting devices. To handle this, NoTraffic implemented edge computing inside their hardware, allowing a good portion of analytics to be processed locally before sending the outcomes to the cloud for further evaluation. This reduced bandwidth usage while also making the answer cheaper for each NoTraffic and their customers.
One other challenge was the necessity to update, upgrade, and maintain software for a whole bunch of 1000’s of devices across various locations. To combat this, NoTraffic developed robust over the air mechanisms to enable rapid deployment of updates, no matter location. These mechanisms be certain 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 coping with infrastructure as critical as traffic management. NoTraffic implemented strict security protocols tailored to every region, ensuring that their data remained isolated and guarded, stopping any potential overlap or interference. By leveraging advanced cloud security measures, the corporate ensured that they were able to take care of the integrity and confidentiality of knowledge, while complying with local regulations.
Through these strategies, NoTraffic successfully navigated the complexities of developing and scaling a platform that mixes hardware and software, ultimately delivering a reliable, secure, and cost-effective mobility solution across different regions.
How do you envision the long run of traffic management and concrete infrastructure evolving in the following decade?
The longer term of traffic management and concrete infrastructure will likely be driven by the widespread adoption of software-enabled devices that enhance the sustainability and efficiency of cities. Just like how Tesla reinvented cars, these devices are set to reinvent the remaining of the mobility ecosystem. Advanced sensors with built-in communication capabilities, powerful computing, and the capability to analyse vast amounts of knowledge will develop into standard. These sensors will offer a wide selection of services that could be updated, adjusted, and repaired remotely, ensuring continuous improvement and minimizing the necessity for physical intervention. The shift towards these smart, software-driven devices will simplify the modernization of infrastructure, reduce waste, and cut down on the necessity for extensive hardware. Traffic devices and systems will function more like smartphones, where features could be personalized, activated, updated, or repaired remotely, making infrastructure upgrades smoother, more cost-effective, and fewer intimidating for municipalities.
Certainly one of the important thing benefits of this technology is the flexibility to aggregate data and quantify various parameters like traffic improvements, safety enhancements, and emissions reductions. It may possibly also enable the identification of trends and support predictive analytics, offering insights into potential outcomes of specific policies before they’re implemented. For instance, the economic impact of traffic delays could possibly be measured, or before-and-after studies could assess the effectiveness of traffic management strategies – something that’s unattainable 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, resulting in more sustainable and livable cities.
What role do you see AI playing in the long run of smart cities and mobility solutions?
AI will play a serious role in the long run of smart cities and mobility solutions through data aggregation and decision-making. Because of AI-powered technologies getting used in traffic management, cities can now use data to quantify various parameters, resembling traffic improvements, safety enhancements, and emission reductions. This data provides a transparent picture of the effectiveness of various traffic management strategies, enabling cities to make probably the most impactful and helpful decisions, tailored to the precise needs of every area.
AI also enables the identification of trends and supports predictive analytics, offering insights into potential outcomes if specific policies are implemented. For instance, using AI cities can now measure the economic impact of traffic delays, or perform before and after studies to measure the effectiveness and success of recent initiatives. By with the ability to back up decisions with concrete data, cities are capable of pinpoint problems and implement targeted solutions, something that may previously have been unattainable to attain.
