PATENT CLAIM ANALYSIS

Application Number: 16010295
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-10
Patent Classification: ["701", "027000"]

Abstract:
A method for near-collision detection, including determining a risk map for a vehicle and automatically detecting a near-collision event with an object based on vehicle behavior relative to the risk map.

Claim (Index 6):
A method for near-collision analysis, comprising:\n sampling an external image with an external-facing camera mounted to a vehicle; determining obstacle parameters for an obstacle detected from the external image; generating a spatial risk map for the vehicle based on the obstacle parameters, the spatial risk map comprising a risk score for each of a set of spatial positions relative to the vehicle, wherein the risk score is determined using:\n a parametric model comprising a set of Gaussian models; \n the obstacle parameters; and \n driver parameters associated with a driver of the vehicle; \n detecting a near-collision event when a risk score within the spatial risk map exceeds a risk threshold; labeling the near-collision event with a label determined based on the driver parameters; transmitting the label to a remote computing system; and determining a cause of the near-collision event, comprising identifying an independent parameter of the parametric model with a highest weighted value.

Metadata:
- Claim Count in Document: 10.0
- Percentile: 94.0
- Lexical Diversity: 1.26923
- Patent Class: 701.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15892899', '15705043', '14881398', '14702150', '15331243']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4360078146329048
- 35 USC 102 Novelty (BERT): 0.5111618707738482
- Combined Prediction Score: 0.4435232202469992
- Mean Citation Score: 191.1877512
- Max Citation Score: 330.02994
- Similarity Product: 327.0927172515356

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

Dataset: test