Automatic Track Clearance, Gauging & Infringement Surveys
Using Cordel’s platform, it is now possible to automate track clearance, gauging and infringement surveys across entire rail networks, whether metro passenger or nationwide freight. By automating the data processing and using ML to locate, classify, and measure features, we’re able to deliver engineering-grade data within hours instead of months.
How Automatic Transit Space Monitoring Works

1. Survey point clouds
Collected using Cordel sensors or uploaded by customer.

2. Cross-section engine
Point clouds processed into 2D cross sections.

3. Machine Learning
Key features identified, located, measured, and rated.

4. Output Reports
Customer-defined format and delivery: API to existing systems and/or export.
Features

Lidar data processing at scale
The Nextcore LiDAR processing engine was developed in house specifically to work with engineering-grade railroad data, with an emphasis on automation, accuracy, and scalability.

Transit Space Modeling
Apply static and kinematic models across entire networks. Get the most out of your data by running multiple profiles through our cross section engine simultaneously.

Infringement Classification
Identify, measure and classify different types of infringements and exceedances. Classifying by infringement type (e.g. vegetation vs. masonry) enables segmentation of work packages for review by the relevant departments or teams.

Track Clearance Surveys
Identify running rails and adjacent tracks and calculate clearances automatically across entire networks.

Vegetation Surveys
Identify, classify, and rate vegetation encroachments and infringements, design work packages, and push results to your vegetation management teams.

Reporting and API Integrations
Each detected exceedance generates a ticket that can be pushed into customers' legacy software systems via Rest API and/or exported in various formats. See our Partners section for a list of current integrations.
Benefits

Reduce on track working
By using remote condition monitoring and desktop reviews, you reduce the requirement to put people on the track and slow network velocity.

Increase frequency of surveys
By lowering the cost and manual labor required to collect, process, and analyze data, we enable you to survey more track more frequently. Discover defects and leading indicators faster and resolve issues before they require significant maintenance and resulting downtime.

Accelerate scenario planning
The Cordel Machine Learning platform enables you to run scenarios with multiple different envelope profiles, allowing you to test and validate programs quickly and affordably.