PATENT CLAIM ANALYSIS

Application Number: 16080886
Application Type: Utility
Filing Date: 2018-08
Publication Date: 2019-01
Patent Classification: ["340", "903000"]

Abstract:
The present disclosure relates to an information processing apparatus, an information processing method, a program, and a vehicle capable of predicting occurrence of a car traffic accident by detecting information regarding the other vehicle traveling around the vehicle and the other person who is a driver. An information processing apparatus according to a first aspect of the present disclosure includes a sensing unit that senses surrounding environment, a reception unit that receives information to prevent an accident regarding a predetermined area according to a current position, and a control unit that changes a parameter with which the sensing unit senses the surrounding environment on the basis of the information to prevent an accident received from the reception unit and a performance of the sensing unit. The present disclosure is capable of being applied to, for example, a car navigation system.

Claim (Index 10):
The information processing apparatus according to  claim 6 , wherein\n the determination unit determines a stepwise warning level regarding the traffic accident in which the first vehicle may be involved on the basis of the number of key factors of which collected value exceeds the threshold value.

Metadata:
- Claim Count in Document: 2.0
- Percentile: 96.0
- Lexical Diversity: 2.20588
- Patent Class: 340.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['13323218', '14192474', '15750384', '16109335', '11681817']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.69410195866293
- 35 USC 102 Novelty (BERT): 0.5090895620910392
- Combined Prediction Score: 0.675600719005741
- Mean Citation Score: 186.596258
- Max Citation Score: 197.1413
- Similarity Product: 119.3083622414291

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

Dataset: test