PATENT CLAIM ANALYSIS

Application Number: 16318691
Application Type: Utility
Filing Date: 2019-01
Publication Date: 2019-06
Patent Classification: ["701", "117000"]

Abstract:
The present invention provides a method for judging a highway abnormal event, which can determine the traffic jam phenomenon in the target road segment based on the trajectory data of each sample vehicle of the target road segment. The solution of the present invention has the following beneficial effects of 1. comprehensively considering the vehicle speed information of the sample vehicles to judge the traffic jam event; 2. determining the overall traffic jam event of the target road segment; 3. more accurately judging the traffic jam event of the target road segment.

Claim (Index 7):
The method according to  claim 6 , wherein the step of calculating the total number of sample vehicles at the spatio-temporal points in the discretized trajectories in the step 4 further includes:\n merging the trajectory matrixes U of all sample vehicles into a three-dimensional matrix D=[U 1 , U 2 , . . . , U u ], wherein u represents the number of the sample vehicles, D x ,D y ,D z  respectively represent three dimensions of the three-dimensional matrix D, namely, the road segment, the time and the user, any element D(i,j,k) in the matrix represents the number of users at the ith road segment and the jth time point; and expressing the total number of the sample vehicles at the spatio-temporal points in the discretized trajectories by using a two-dimensional matrix E, wherein E(i,j) represents the number of users at the ith road segment and the jth time point; and traversing the two dimensions of D x  and D y  of the three-dimensional matrix D to find a non-empty element set D ij \u2032, E(i,j)=|D ij \u2032| in the D(i,j,:) for all i and j.

Metadata:
- Claim Count in Document: 20.0
- Percentile: 99.0
- Lexical Diversity: 1.86538
- Patent Class: 701.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['14694984', '13111110', '11655047', '14341435', '16322095']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4244263940943745
- 35 USC 102 Novelty (BERT): 0.5139978047519392
- Combined Prediction Score: 0.433383535160131
- Mean Citation Score: 234.76678
- Max Citation Score: 272.65323
- Similarity Product: 179.52393842717888

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

Dataset: test