NEC Optical Fibre Technology Enhances Real-Time Traffic Congestion Prediction
NEC Corporation has unveiled a ground-breaking optical fibre sensing technology capable of predicting sudden traffic congestion in real time with unprecedented accuracy.
By tapping into existing roadside optical fibre communication cables, this innovation uses a proprietary AI model to analyse live traffic flow, achieving an 80% reduction in prediction errors compared to traditional methods.
This leap in predictive capability promises far-reaching benefits for traffic management, logistics, and environmental sustainability. By enabling road operators to make swift, data-driven decisions—such as rerouting vehicles and preventing bottlenecks—it offers a powerful tool to tackle congestion-related economic losses and reduce CO2 emissions.
The Cost of Congestion
Traffic congestion remains one of the most pressing challenges for modern transport networks, particularly on expressways that underpin national logistics. Delays not only disrupt supply chains but also inflate operational costs, strain driver welfare, and increase fuel consumption.
As NEC notes, solving this problem demands more than reactive measures. It requires a proactive approach: monitoring road conditions in real time, identifying emerging hotspots before they escalate, and deploying responsive strategies at speed.
Limitations of Current Monitoring Methods
Until now, congestion monitoring has largely relied on:
- Point-based sensors: Cameras and loop detectors installed at fixed intervals.
- Probe vehicle data: Information collected from vehicles equipped with onboard units when they pass designated receiver points.
While useful, these systems have drawbacks. Point sensors are expensive to deploy and maintain across entire road networks. Probe data, meanwhile, is limited by the number of equipped vehicles and the spacing of receiver stations, resulting in gaps in continuous coverage.
Worse still, conventional congestion prediction models often depend on historical data, leaving them ill-prepared for sudden, unpredictable events.
A Smarter, More Comprehensive Approach
NEC’s solution transforms existing optical fibre cables—originally laid for communication—into continuous, distributed traffic sensors. These fibres run alongside major roads, making them a cost-effective and expansive data collection platform.
The system feeds this wealth of information into NEC’s AI-powered prediction model, which doesn’t just flag congestion; it forecasts its development and clearance in real time. This means road operators can act decisively before gridlock takes hold.
Technical Innovations
The technology hinges on two key AI-driven algorithms that work hand in hand to ensure accuracy:
- Model Parameter Optimisation: NEC has developed an algorithm that fine-tunes theoretical traffic models—accounting for factors like driver behaviour and inter-vehicle distances—so that simulations closely mirror real-world conditions along entire road segments.
- Data Adaptation: An advanced adaptation algorithm converts varied traffic data, such as average speeds and individual vehicle positions, into a uniform format compatible with simulation models. This ensures that simulations start with accurate, up-to-the-minute initial conditions, significantly boosting reliability.
Proven Results in Real-World Tests
Trials using actual road data have confirmed the system’s impressive accuracy. Travel time prediction errors—a key benchmark for congestion forecasting—were reduced by around 80% compared to current point-sensor-based methods.
This level of precision opens the door to dynamic traffic control strategies that can evolve in sync with live conditions, from adjusting speed limits to managing lane closures and diversions.
Towards a Digital Twin of the Road Network
NEC envisions the creation of a dynamic road digital twin—a virtual model of the transport network that updates in real time. This would allow continuous monitoring, predictive modelling, and rapid deployment of countermeasures, ultimately delivering smoother traffic flow and safer journeys.
The company is working closely with road authorities to refine and test the system, with full-scale deployment targeted for fiscal 2026.
Industry Recognition and Global Collaboration
This innovation has already gained international attention. It was presented at the Transportation Research Board’s 104th Annual Meeting under the title “A Novel Approach to Real-Time Short-Term Traffic Prediction based on Distributed Fiber-Optic Sensing and Data Assimilation with a Stochastic Cell-Automata Model.” NEC will also showcase related findings at the 31st ITS World Congress in Atlanta, focusing on enhancing expressway traffic monitoring.
The development benefitted from data provided by Central Nippon Expressway Company Limited, highlighting the value of industry collaboration in tackling global mobility challenges.
NEC’s Commitment to Sustainable Mobility
Founded in 1899, NEC Group now employs around 110,000 people worldwide, applying cutting-edge AI, security, and communications technologies to address urgent societal needs.
This latest traffic monitoring advancement reflects NEC’s vision for a more sustainable, efficient, and equitable future in which technology empowers everyone to reach their full potential.
Driving Towards Smarter Roads
By turning optical fibre networks into intelligent, real-time traffic monitors, NEC has taken a decisive step towards a future where congestion is no longer an inevitable cost of road travel.
As trials progress and the technology moves towards commercial deployment, its potential to transform transport efficiency and environmental performance is immense.
If realised at scale, this could redefine how road authorities, logistics operators, and urban planners manage traffic, paving the way for cleaner, safer, and more predictable journeys.
