# US 10,872,525 B2 · Speed prediction method and apparatus

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- Number: US 10,872,525 B2
- Document ID: US10872525B2
- Status: Granted
- Kind: B2
- Application number: 16/099,785
- Filed: 2016-11-04
- Published: 2019-05-09
- Granted: 2020-12-22
- Earliest claimed: 2016-05-11
- Assignees: Hangzhou Hikvision Digital Technology Co., Ltd.
- Applicants: Hangzhou Hikvision Digital Technology Co., Ltd.
- Inventors: Yuyao Xu; Shifan Zhao; Long Wang
- Web page: https://patentgrep.com/patent/US10872525B2

## CPC

- G08G 1/0129: {for creating historical data or processing based on historical data}
- G01C 21/3691: {Retrieval, searching and output of information related to real-time traffic, weather, or environmental conditions (arrangements for giving variable traffic instructions G08G1/09)}
- G06Q 10/04: Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202)
- G08G 1/01: Detecting movement of traffic to be counted or controlled (G08G1/07 - G08G1/14 take precedence)
- G08G 1/052: with provision for determining speed or overspeed {(speed measuring in general G01P)}
- G08G 1/0133: {for classifying traffic situation}
- G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93})
- G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S)
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

A speed prediction method and apparatus are disclosed. The method includes: obtaining traffic-effecting parameter information of a first road segment in a current time period (S101), wherein the traffic-effecting parameter information comprises at least one of a parameter of the effect of the current weather on the traffic, a parameter of the effect of an attribute of the current date on the traffic and a parameter of the effect of a special event on the traffic; determining a similarity between the traffic-effecting parameter information and historical traffic-effecting parameter information of the first road segment stored in a historical traffic database (S102), and determining target historical traffic-effecting parameter information according to the determined similarity (S103); and predicting a first speed of a vehicle on the first road segment in the next time period, according to a speed of a vehicle in a next time period of a time period corresponding to the target historical traffic-effecting parameter information, stored in the historical traffic database (S104).

## Claims

### Claim 1

A speed prediction method, comprising:
obtaining traffic-effecting parameter information of a first road segment in a current time period, wherein the traffic-effecting parameter information comprises at least one of a parameter of the effect of the current weather on the traffic, a parameter of the effect of an attribute of the current date on the traffic and a parameter of the effect of a special event on the traffic;
determining a similarity between the traffic-effecting parameter information and historical traffic-effecting parameter information of the first road segment stored in a historical traffic database, and determining target historical traffic-effecting parameter information according to the determined similarity;
predicting a first speed of a vehicle on the first road segment in a next time period, according to a speed of a vehicle in a next time period of a time period corresponding to the target historical traffic-effecting parameter information stored in the historical traffic database;
identifying at least one second road segment with a distance to the first road segment less than a second preset threshold, and obtaining a second speed of a vehicle on each second road segment in the current time period; and
predicting a third speed of the vehicle on the first road segment in the next time period according to the first speed and the second speed.

### Claim 2 (depends on 1)

The method of claim 1, further comprising:
predicting a congestion level for the vehicle on the first road segment in the next time period, according to the predicted speed of the vehicle on the first road segment in the next time period and a preset correspondence between each speed and a congestion level.

### Claim 3 (depends on 1)

The method claim 1, wherein obtaining a second speed of a vehicle on each second road segment in the current time period comprises:
obtaining a distance between a first base station and a second base station located in the second road segment, a first instant that a mobile device on a vehicle passes by the first base station in the current time period and a second instant that the mobile device on the vehicle passes by the second base station;
calculating a speed of the mobile device on the vehicle between the first base station and the second base station according to the distance, the first instant and the second instant; and
determining an average value of speeds of mobile devices on a plurality of vehicles between the first base station and the second base station as the second speed of the vehicle on the second road segment in the current time period.

### Claim 4 (depends on 1)

The method of claim 1, wherein determining a similarity between the traffic-effecting parameter information and historical traffic-effecting parameter information of the first road segment stored in a historical traffic database comprises:
determining a target time period corresponding to the current time period in the historical traffic database; and
determining a similarity between the traffic-effecting parameter information and historical traffic-effecting parameter information of the first road segment in the target time period stored in the historical traffic database.

### Claim 5 (depends on 1)

The method of claim 1, wherein in the case that the traffic-effecting parameter information comprises the parameter of the effect of the current weather on the traffic, the parameter of the effect of an attribute of the current date on the traffic and the parameter of the effect of a special event on the traffic, determining a similarity between the traffic-effecting parameter information and historical traffic-effecting parameter information of the first road segment stored in a historical traffic database comprises:
obtaining the similarity between the traffic-effecting parameter information and the historical traffic-effecting parameter information of the first road segment stored in the historical traffic database according to the following formula:
sim
⁡
(
Q
,
Q
h
)
=
WW
h
+
HH
h
+
EE
h
W
2
+
H
2
+
E
2
*
W
h
2
+
H
h
2
+
E
h
2
where W, H and E respectively represent the parameter of the effect of the current weather on the traffic, the parameter of the effect of an attribute of the current date on the traffic and the parameter of the effect of a special event on the traffic included in the traffic-effecting parameter information, and Wh, Hh and Eh respectively represent a parameter of the effect of a historical weather on the traffic, a parameter of the effect of an attribute of a historical date on the traffic and a parameter of the effect of a special event on the traffic included in the historical traffic-effecting parameter information.

### Claim 6 (depends on 1)

The method of claim 1, wherein determining target historical traffic-effecting parameter information according to the determined similarity comprises:
determining historical traffic-effecting parameter information most similar to the traffic-effecting parameter information as the target historical traffic-effecting parameter information,
or
wherein determining target historical traffic-effecting parameter information according to the determined similarity comprises:
determining at least two items of historical traffic-effecting parameter information, having a similarity to the traffic-effecting parameter information greater than a first preset threshold, as the target historical traffic-effecting parameter information.

### Claim 7 (depends on 6)

The method of claim 6, wherein predicting a first speed of a vehicle on the first road segment in a next time period, according to a speed of a vehicle in a next time period of a time period corresponding to the target historical traffic-effecting parameter information stored in the historical traffic database comprises:
determining a weight for each item of target historical traffic-effecting parameter information, according to a distance between the traffic-effecting parameter information and the target historical traffic-effecting parameter information; and
predicting the first speed of the vehicle on the first road segment in the next time period, according to the weight for each item of target historical traffic-effecting parameter information and the speed of the vehicle in the next time period of a time period corresponding to each item of target historical traffic-effecting parameter information, stored in the historical traffic database.

### Claim 8 (depends on 7)

The method of claim 7, wherein determining a weight for each item of target historical traffic-effecting parameter information, according to a distance between the traffic-effecting parameter information and the target historical traffic-effecting parameter information comprises:
determining the weight for each item of target historical traffic-effecting parameter information through the following formula:
β
i
=
d
i
-
1
∑
i
=
1
K
⁢
d
i
-
1
,
(
i
=
1
,
2
,
…
⁢
,
K
)
,
where K represents the number of items of the target historical traffic-effecting parameter information, and di is a distance between the ith item of target historical traffic-effecting parameter information and the traffic-effecting parameter information.

### Claim 9

A speed prediction apparatus, comprising:
a first obtaining module configured to obtain traffic-effecting parameter information of a first road segment in a current time period, wherein the traffic-effecting parameter information comprises at least one of a parameter of the effect of the current weather on the traffic, a parameter of the effect of an attribute of the current date on the traffic and a parameter of the effect of a special event on the traffic;
a first determining module configured to determine a similarity between the traffic-effecting parameter information and historical traffic-effecting parameter information of the first road segment stored in a historical traffic database;
a second determining module configured to determine target historical traffic-effecting parameter information according to the similarity determined by the first determining module;
a first predicting module configured to predict a first speed of a vehicle on the first road segment in a next time period, according to a speed of a vehicle in a next time period of a time period corresponding to the target historical traffic-effecting parameter information stored in the historical traffic database;
an identifying module configured to identify at least one second road segment with a distance to the first road segment less than a second preset threshold;
a second obtaining module configured to obtain a second speed of a vehicle on each second road segment in the current time period; and
a second predicting module is configured to predict a third speed of the vehicle on the first road segment in the next time period according to the first speed and the second speed.

### Claim 10 (depends on 9)

The apparatus of claim 9, further comprising:
a third determining module configured to predict a congestion level for the vehicle on the first road segment in the next time period, according to the predicted speed of the vehicle on the first road segment in the next time period and a preset correspondence between each speed and a congestion level.

### Claim 11 (depends on 9)

The apparatus of claim 9, wherein the second obtaining module comprises:
an obtaining submodule configured to obtain a distance between a first base station and a second base station located in the second road segment, a first instant that a mobile device on a vehicle passes by the first base station in the current time period and a second instant that the mobile device on the vehicle passes by the second base station;
a calculating submodule configured to calculate a speed of the mobile device on the vehicle between the first base station and the second base station according to the distance, the first instant and the second instant obtained by the obtaining submodule; determine an average value of speeds of mobile devices on a plurality of vehicles between the first base station and the second base station as the second speed of the vehicle on the second road segment in the current time period.

### Claim 12 (depends on 9)

The apparatus of claim 9, wherein the first determining module comprises:
a first determining submodule configured to determine a target time period corresponding to the current time period in the historical traffic database; and
a second determining submodule configured to determine a similarity between the traffic-effecting parameter information and historical traffic-effecting parameter information of the first road segment in the target time period stored in the historical traffic database.

### Claim 13 (depends on 9)

The apparatus of claim 9, wherein in the case that the traffic-effecting parameter information comprises the parameter of the effect of the current weather on the traffic, the parameter of the effect of an attribute of the current date on the traffic and the parameter of the effect of a special event on the traffic, the first determining module is specifically configured to:
obtain the similarity between the traffic-effecting parameter information and the historical traffic-effecting parameter information of the first road segment stored in the historical traffic database according to the following formula:
sim
⁡
(
Q
,
Q
h
)
=
WW
h
+
HH
h
+
EE
h
W
2
+
H
2
+
E
2
*
W
h
2
+
H
h
2
+
E
h
2
where W, H and E respectively represent the parameter of the effect of the current weather on the traffic, the parameter of the effect of an attribute of the current date on the traffic and the parameter of the effect of a special event on the traffic included in the traffic-effecting parameter information, and Wh, Hh and Eh respectively represent a parameter of the effect of a historical weather on the traffic, a parameter of the effect of an attribute of a historical date on the traffic and a parameter of the effect of a special event on the traffic included in the historical traffic-effecting parameter information.

### Claim 14 (depends on 9)

The apparatus of claim 9, wherein the second determining module is specifically configured to:
determine historical traffic-effecting parameter information most similar to the traffic-effecting parameter information as the target historical traffic-effecting parameter information,
or
wherein the second determining module is specifically configured to:
determine at least two items of historical traffic-effecting parameter information, having a similarity to the traffic-effecting parameter information greater than a first preset threshold, as the target historical traffic-effecting parameter information.

### Claim 15 (depends on 14)

The apparatus of claim 14, wherein the first predicting module comprises:
a third determining submodule configured to determine a weight for each item of target historical traffic-effecting parameter information, according to a distance between the traffic-effecting parameter information and the target historical traffic-effecting parameter information; and
a predicting submodule configured to predict the first speed of the vehicle on the first road segment in the next time period, according to the weight for each item of target historical traffic-effecting parameter information and the speed of the vehicle in the next time period of a time period corresponding to each item of target historical traffic-effecting parameter information, stored in the historical traffic database.

### Claim 16 (depends on 15)

The apparatus of claim 15, wherein the third determining submodule is specifically configured to:
determine the weight for each item of target historical traffic-effecting parameter information through the following formula:
β
i
=
d
i
-
1
∑
i
=
1
K
⁢
d
i
-
1
,
(
i
=
1
,
2
,
…
⁢
,
K
)
,
where K represents the number of items of the target historical traffic-effecting parameter information, and di is a distance between the ith item of target historical traffic-effecting parameter information and the traffic-effecting parameter information.

### Claim 17 (depends on 1)

An electronic device, comprising: a housing, a processor, a memory, a circuit board and a power supply circuit, wherein the circuit board is arranged in a space surrounded by the housing, and the processor and memory are disposed on the circuit board; the power supply circuit is configured to supply power for circuits and components of the electronic device; the memory is configured to store executable program codes; and the processor is configured to execute a program corresponding to the executable program codes by reading the executable program codes stored in the memory to perform the speed prediction method of claim 1.

### Claim 18 (depends on 1)

A non-transitory storage medium for storing an executable program code that, when being executed, implements the speed prediction method of claim 1.