Transcality creates digital twins of transportation systems to simulate current traffic conditions and evaluate future planning scenarios. Their web‑based platform combines traffic flow modeling with automated data pipelines, delivering accurate, standards‑compliant models without requiring expert training. The solution enables transport planners and engineers to conduct cost‑efficient, model‑based analysis for sustainable mobility decisions.
Funding
$160K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Current traffic planning and operations often rely on outdated methods, leading to inefficiencies in managing congestion and emissions in urban and interurban environments. Traditional approaches lack the real-time adaptability and predictive capabilities needed to optimize traffic flow effectively.
Solution
Transcality offers a digital twin platform that leverages big data, machine learning, and simulation to create real-time traffic models. This platform provides an all-in-one solution spanning from traffic monitoring to advanced analytical and predictive services, enabling users to evaluate current conditions and plan for the future. The platform's modular architecture allows for flexible integration of various data sources and existing tools. By automating model generation and calibration, Transcality minimizes the need for human resources, reducing costs and time requirements for model-based traffic planning and operations. The platform also uses open standards-based methods and a digital thread to ensure efficient, transparent maintenance and end-to-end traceability.
Target Audience
The primary audience includes urban planners, traffic engineers, and government agencies responsible for managing and optimizing traffic flow in urban and interurban areas.
Features
- Web-based interface for transport system planning
- AI-based traffic monitoring and prediction for urban and interurban roads
- Modular architecture for flexible data integration
- Automated model generation and calibration
- Open standards-based methods for efficient maintenance
- Digital thread for full transparency and traceability
- Real-time display and analysis of traffic flow and emissions indicators