PATENT CLAIM ANALYSIS

Application Number: 15939192
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-10
Patent Classification: ["701", "027000"]

Abstract:
A temporal prediction model for semantic intent understanding is described. An agent (e.g., a moving object) in an environment can be detected in sensor data collected from sensors on a vehicle. Computing device(s) associated with the vehicle can determine, based partly on the sensor data, attribute(s) of the agent (e.g., classification, position, velocity, etc.), and can generate, based partly on the attribute(s) and a temporal prediction model, semantic intent(s) of the agent (e.g., crossing a road, staying straight, etc.), which can correspond to candidate trajectory(s) of the agent. The candidate trajectory(s) can be associated with weight(s) representing likelihood(s) that the agent will perform respective intent(s). The computing device(s) can use one (or more) of the candidate trajectory(s) to determine a vehicle trajectory along which a vehicle is to drive.

Claim (Index 4):
The system as  claim 1  recites, wherein the classification distribution comprises a vehicle class, a pedestrian class, or a bicycle class.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 90.0
- Lexical Diversity: 2.58108
- Patent Class: 701.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14933602', '13972911', '15632147', '14756992', '15078143']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4279914480462736
- 35 USC 102 Novelty (BERT): 0.4772022482129872
- Combined Prediction Score: 0.4329125280629449
- Mean Citation Score: 138.83069
- Max Citation Score: 145.142
- Similarity Product: 95.98179953253268

Labels:
- Claim Label 101: 1
- Claim Label 102: 0
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 1

Dataset: test