Invention Grant
- Patent Title: Predicting safety incidents using machine learning
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Application No.: US15297050Application Date: 2016-10-18
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Publication No.: US10720050B2Publication Date: 2020-07-21
- Inventor: Sangick Jeon
- Applicant: Uber Technologies, Inc.
- Applicant Address: US CA San Francisco
- Assignee: Uber Technologies, Inc.
- Current Assignee: Uber Technologies, Inc.
- Current Assignee Address: US CA San Francisco
- Agency: Fenwick & West LLP
- Main IPC: G08G1/01
- IPC: G08G1/01 ; G08G1/00 ; G06N20/00

Abstract:
A safety system associated with a travel coordination system collects safety data describing safety incidents by providers and generates a plurality of safety incident prediction models using the safety data. The safety incident prediction models predict likelihoods that providers in the computerized travel coordination system will be involved in safety incidents. Two types of safety incidents predicted by the safety system include dangerous driving incidents and interpersonal conflict incidents. The safety system uses the plurality of safety incident prediction models to generate a set of predictions indicating probabilities that a given provider in the travel coordination system will be involved in a safety incident in the future. The safety system selects a safety intervention for the given provider responsive to the set of predictions and performs the selected safety intervention on the given provider.
Public/Granted literature
- US20180107935A1 PREDICTING SAFETY INCIDENTS USING MACHINE LEARNING Public/Granted day:2018-04-19
Information query
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