Lyft has patented a system that uses machine learning to determine whether to assess a cancellation penalty for transportation requests. The system generates conversion probabilities based on historical data and provides customized cancellation notices to requestors. This aims to improve transportation efficiency and user experience. GlobalData’s report on Lyft gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Lyft, Autonomous delivery vehicle navigation system was a key innovation area identified from patents. Lyft's grant share as of May 2024 was 25%. Grant share is based on the ratio of number of grants to total number of patents.
Customized cancellation notices for transportation requests
A recently granted patent (Publication Number: US11989669B2) discloses a system and method for training a conversion-machine-learning model using ground-truth-conversions and historical transportation features, including historical cancellation penalties. The system, comprising at least one processor and a non-transitory computer-readable storage medium, is designed to generate predicted conversion probabilities, compare them with ground-truth-conversion probabilities, and modify model parameters based on the measure of loss. Upon receiving a transportation request, the system extracts transportation features, generates conversion probabilities based on cancellation penalties, and provides a customized cancellation notice to the requestor device based on these probabilities.
Furthermore, the patented system includes instructions to generate feedback probabilities based on transportation features, utilize a requestor-feedback-machine-learning model, apply a transportation-value metric for the requestor, and provide customized cancellation notices accordingly. The system also offers notifications regarding cancellation penalties or the absence of penalties to the requestor device. The transportation features used in the system include estimated time of arrival, time between request acceptance and cancellation, and distance between the requestor device and pickup location. The system aims to enhance user experience by providing tailored cancellation notices based on various factors, ultimately improving the efficiency and effectiveness of transportation services.
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