PATENT CLAIM ANALYSIS

Application Number: 15867946
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-05
Patent Classification: ["701", "023000"]

Abstract:
Methods are introduced for customizing and legalizing a self-driving motor vehicle by personalizing and/or disciplining before and during a self-driving motor vehicle is practically used, with human knowledge, preferences and experiences, to provide a more personal service and overcome some hurdles in legalization of self-driving motor vehicles, serving as a bridge in the transition from a human driving world to a personized autonomous freeway.

Claim (Index 17):
The method of  claim 12 , wherein the designing a training collection comprises an embodiment of:\n selecting scenarios after a statistical analysis of conventional motor vehicle scenario data and/or scenario data from simulations and road tests of self-driving motor vehicles; categorizing and/or quantizing the data; assigning a weight to scenarios respectively to their appearance probability, level of abruptness or uncertainty, and level of risks involving a user in handling conflicts of interests between traffic rules and laws, safety of a self-driving motor vehicle and/or the user, and/or other parties sharing roadways; finding a combined weight by a weighted average of individual weights or by a different weighting scheme; sorting the scenarios descending order according to the combined weight of the scenarios; selecting into the training collection the scenarios prioritized according to a top-down order of the value of the combined weight of the scenarios, until to an adjustable threshold value of the combined weight; conducting a statistical analysis of a set of operational behaviors in a scenario from conventional vehicle driving records and/or data from self-driving motor vehicle simulations and/or road tests; removing unlawful operational behaviors from the set; finding a probability of appearance of an operational behavior in the scenario; establishing a psychological behavior model based on the driving style and/or moral and/or ethics traits of the users; forming a probability density distribution between extreme selfish at one side and altruism at the other side; or forming a multiple dimensional user psychological behavior probability density distribution; dividing the range of the probability density distribution into a plurality of segments or regions and the probability of each segment or region corresponding to a group of users with similar psychological behavior pattern of driving styles and/or moral and/or ethics traits; finding for each group of users a match in the set of operational behaviors of the self-driving motor vehicle in a scenario, wherein if the probability of appearance of the matched operational behavior is higher than a threshold, the matched operational behavior is qualified to be a candidate as a selective operational behavior in the scenario of a training collection for a user to choose from to form a scenario-user-choice pair; achieving a compromise between efficiencies of the self-driving vehicle operation, the granularities of user groups and coverage of the psychological behaviors.

Metadata:
- Claim Count in Document: 5.0
- Percentile: 86.0
- Lexical Diversity: 1.38
- Patent Class: 701.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['15662282', '11221027', '15251104', '14563182', '15720775']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3814171410914949
- 35 USC 102 Novelty (BERT): 0.5150201543603563
- Combined Prediction Score: 0.3947774424183811
- Mean Citation Score: 155.855704
- Max Citation Score: 275.33047
- Similarity Product: 184.99663633449853

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

Dataset: test