BNSF’s PVM: Rail Innovation for 32,500 Miles

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Introduction

BNSF Railway Co. has developed predictive vegetation management (PVM) technology to optimize vegetation control across its 32,500-mile network, which includes over 15,000 grade crossings.

Predictive Vegetation Management (PVM) Technology

BNSF Railway Co., with support from outside vendors, has developed predictive vegetation management (PVM) technology. This technology utilizes artificial intelligence to predict vegetation growth accurately.

Data Collection and Analysis

Since 2023, BNSF has been using lidar technology to assess vegetation. The company combines lidar-generated data with information on soil conditions and historical weather patterns.

Operational Impact and Inspection Protocols

The goal is to forecast vegetation growth more precisely and enhance crew scheduling. Field crews inspect more than 15,000 crossings on BNSF’s network to ensure compliance with state and federal standards. These inspections confirm that vegetation is trimmed to maintain visibility for train crews and the public.

Network Scope

BNSF’s railway network spans 32,500 miles, encompassing the crossings managed by the PVM system.

Conclusion

BNSF Railway Co. has developed a PVM technology that utilizes artificial intelligence, lidar data, soil data and weather data to predict vegetation growth across its network, optimizing crew scheduling and ensuring compliance with regulations at over 15,000 crossings.

Company Summary

BNSF Railway Co.: Operates a 32,500-mile rail network and is implementing advanced technologies to manage vegetation and maintain safety standards across its grade crossings.

Technology

Predictive Vegetation Management (PVM): A technology that uses artificial intelligence to predict vegetation growth.

Lidar: A technology used to assess vegetation.

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