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 5):
The method according to  claim 4 , wherein the step of obtaining the road segment H i  corresponding to the T i  based on the l k  and the l k+1  in the step 2 further includes:\n when the l k  and the l k+1  are on the same segment of trajectory H i , indicating that the road segment corresponding to the sample vehicle at the moment T i  is H i ; when the l k  and the l k+1  are respectively located on two different road segments Hj and Hj+r, assuming that the sample vehicle performs uniform linear motion between the l k  and the l k+1 ; calculating the speed v = \uf605 l k + 1 - l k \uf606 t k + 1 - t k between the l k  and the l k+1 , obtaining that the sample vehicle is located between the l k  and the l k+1  at the moment T i , and indicating that the distance from the l k  is v\u00b7(t k+1 \u2212t k ), that is, the geographical location of the target vehicle is W=l k +v\u00b7(t k+1 \u2212t k ); and finding the road segment where the W is located from the H ab , that is, the road segment H i  corresponding to the sample vehicle at the moment T i .

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): 0.4246715498059039
- 35 USC 102 Novelty (BERT): 0.5127261516038976
- Combined Prediction Score: 0.4334770099857032
- Mean Citation Score: 234.76678
- Max Citation Score: 272.65323
- Similarity Product: 184.02326822965264

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