Pony.ai has been granted a patent for a system that uses processors and memory to identify and predict changes in entities on a map over time. The system updates the map based on predicted changes and navigates a vehicle accordingly. GlobalData’s report on Pony.ai gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Pony.ai, Autonomous freight management was a key innovation area identified from patents. Pony.ai's grant share as of January 2024 was 50%. Grant share is based on the ratio of number of grants to total number of patents.

Dynamic map updating system for autonomous vehicles

Source: United States Patent and Trademark Office (USPTO). Credit: Pony.ai Inc

A recently granted patent (Publication Number: US11885624B2) discloses a system and method for predicting and managing changes in entities over time. The system includes processors and memory storing instructions to identify entities that change over time on a map, predict the amount of change based on a time scale or relationship over time, obtain updated images of the entities, determine actual change, update predictions, generate updated maps, and navigate based on the updated map. The prediction methods include various relationships like logarithmic, exponential, power, linear, Gompertz, and Lloyd-Lipow, or historical data-based time scales for accurate forecasting.

Furthermore, the system can compare predicted and actual changes, correct identification errors, reclassify static entities as changing based on exceeding threshold change levels, and focus on infrastructure degradation prediction. The entities can change seasonally or cyclically, and identification is based on feature or terrain changes. Additionally, the system can predict changes in other entities due to primary entity changes, updating maps accordingly. The method, implemented by computing systems, follows a similar process, emphasizing the importance of accurate predictions, corrections, and infrastructure management based on degradation rates over time, ensuring efficient navigation and decision-making based on real-time data and historical trends.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.