GM Files Patent for Vehicle System to Predict Road Deterioration

According to foreign media reports, General Motors has submitted a patent application for a vehicle system capable of predicting road deterioration. The application was filed with the United States Patent and Trademark Office (USPTO) under patent number US 2025/0200526 A1 on December 15, 2023. The application documents were published on June 19, 2025, listing several American engineers as inventors, including Matthew Edward Gilbert-Eyres, Craig Thomas Douglas, Alec M. Wuorinen, and Donald K. Grimm. The patent describes a system that predicts road deterioration using a network of vehicles equipped with various sensors. These sensors collect data during vehicle operation, such as vibrations, suspension displacement, wheel rotation, and visual images captured by cameras. The data is then transmitted in real-time from each vehicle to a cloud computer via telematics and GPS. This central system aggregates the information and calculates a Road Maintenance Score (RMS) that reflects the current road conditions. The system can also track changes over time, effectively predicting future road maintenance needs. If the RMS exceeds a certain threshold, the system sends alerts about potential or urgent maintenance needs to specific groups. These alerts can be classified based on the severity of damage and may include route change suggestions to avoid affected areas. If the vehicle is equipped with navigation software, the system can also provide real-time route updates to warn drivers and even automatically guide autonomous vehicles around rough or hazardous sections. One of the key features of this system is its ability to crowdsource data from multiple vehicles, making it scalable and adaptable to different regions without requiring specific road infrastructure. As the number of vehicles on the road increases, the volume of collected data also rises, allowing the system to become more intelligent and accurate over time. The system can also create feature maps to identify specific road issues, such as potholes, water accumulation, or uneven surfaces, and associate this data with the visual maps used by onboard navigation systems.