Raleigh’s Population Growth Spurs Need for Smarter Traffic Solutions
As Raleigh’s population surpasses 500,000, the city is turning to artificial intelligence (AI) to better manage its increasingly congested roads. City officials have launched a pilot program that integrates AI-powered traffic cameras with mapping software to analyze real-time traffic patterns and optimize signal timing across busy intersections.
Jed Niffenegger, Raleigh’s city transportation manager, emphasized the city’s goal: not to eliminate traffic entirely, but to enhance the efficiency and safety of intersections, especially in pedestrian-heavy zones. “We can’t change the fact that an intersection is busy,” he said. “What we can do is make sure it’s operating as efficiently as possible.”
AI and Computer Vision Streamline Data Collection
The new system employs computer vision technology to transform live video feeds into actionable data. The cameras can automatically track vehicle turns, traffic volume, and travel modes—tasks that previously required staff to manually count and record traffic flow at intersections.
“The cameras allow us to make changes much more quickly,” Niffenegger explained. “With analytics, the amount of work it takes has been reduced to a fraction of what it used to be.”
Currently, Raleigh operates around 250 closed-circuit traffic cameras. However, due to computing constraints, only 10 to 12 cameras can be analyzed simultaneously. These cameras are rotated within the program depending on where signal timing studies or corridor reviews are ongoing, such as along Glenwood Avenue and downtown corridors.
Fine-Tuning Traffic Signals in Real Time
Using the AI-driven insights, transportation engineers can adjust signal timings during peak traffic hours. Even adjustments as small as a few seconds can make a noticeable difference in easing congestion. “We’ll look at the evening rush and see whether a signal is running too long or needs to start a little later,” said Niffenegger. “It’s about fine-tuning what we’re already doing.”
City officials note that improving intersections is often more impactful than expanding roadways. “If we can maximize efficiency at intersections, we can delay costly road-widening projects,” Niffenegger added. “That saves money and allows us to invest in other places where it can have a bigger impact.”
Digital Twin Technology Enhances Traffic Analysis
James Alberque, Raleigh’s emerging technology manager, highlighted the use of a high-resolution 3D model—commonly referred to as a “digital twin”—to visualize traffic conditions citywide. This tool allows staff to compare traffic patterns before and after adjusting signal timings and evaluate the effectiveness of those changes.
Initially focused on vehicle traffic, the pilot program has since expanded to include pedestrian and bicycle movement, particularly in downtown areas with high foot traffic and scooter use. “We wanted to understand all modes of transportation,” Alberque noted. “GIS allows us to integrate traffic data with other information and analyze it in one place.”
Privacy and Human Oversight Remain Priorities
Despite the technological advancements, Raleigh officials stress that privacy and human oversight remain central to the project. The system does not record or store video footage, nor does it collect personally identifiable information. All data is anonymized and categorized in 15-minute intervals based on object type—vehicle, pedestrian, or bicycle.
“There’s no identifying information at all,” Alberque said. “We’re not recording video.”
Importantly, the AI system does not autonomously adjust traffic signals. Engineers manually review the generated data and make informed decisions based on the insights. During the testing phase, manual vehicle counts have been conducted alongside AI analysis to validate the system’s accuracy. Alberque reported that over a dozen test cases have been reviewed, building confidence in the technology’s reliability.
Broader Applications and Future Expansion
Beyond traffic management, Raleigh’s camera network already supports other municipal departments. Police, emergency dispatchers, and stormwater crews use the system during emergencies, such as floods, to assess conditions on the ground more accurately.
Scaling the AI system beyond the pilot phase will require additional investments. So far, Raleigh has utilized existing infrastructure and limited resources to test the technology’s potential. “The technology is advancing very quickly,” Alberque said. “We’re trying to be thoughtful about how we invest so we’re making good decisions as this evolves.”
City leaders see this initiative as a forward-thinking strategy to improve safety and efficiency at busy intersections without resorting to costly and disruptive road expansions. As Raleigh continues to grow, leveraging AI and data-driven decision-making will be critical in shaping a smarter, safer, and more sustainable urban environment.
This article is inspired by content from Original Source. It has been rephrased for originality. Images are credited to the original source.