APPARATUS FOR AUTOMATICALLY CONTROLLING VEHICLE SPEED AND METHOD OF USING THE SAME

• US 20150224990A1
• Filed: 10/07/2014
• Published: 08/13/2015
• Est. Priority Date: 02/11/2014
• Status: Active Grant

• Current Assignee: Hyundai Motor Company (Hyundai Motor Group)
• Original Assignee: Hyundai Motor Company (Hyundai Motor Group)
• Inventors: KIM, Dae Sik
• Granted Patent: US 9,399,471 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60W 2050/0075 Automatic parameter input, automatic initialising or calibrating means
• CPC Class Codes: B60W 2050/146 Display means
• CPC Class Codes: B60W 2540/043 Identity of occupants
• CPC Class Codes: B60W 2552/20 Road profile, i.e. the change in elevation or curvature of a plurality of continuous road segments
• CPC Class Codes: B60W 2554/00 Input parameters relating to objects
• CPC Class Codes: B60W 2556/10 Historical data
• CPC Class Codes: B60W 2556/50 of positioning data, e.g. GPS [Global Positioning System] data
• CPC Class Codes: B60W 2720/103 Speed profile
• CPC Class Codes: B60W 30/143 Speed control B60W30/16 takes precedence
• CPC Class Codes: B60W 50/0097 Predicting future conditions
• CPC Class Codes: B60W 50/14 Means for informing the driver, warning the driver or prompting a driver intervention
• CPC Class Codes: Y02T 10/84 Data processing systems or methods, management, administration

Abstract

An apparatus for automatically controlling a vehicle speed includes a first unit configured to drive data of a vehicle from electric control units (ECUs) to determine driver'"'"'s habits, a second unit configured to receive the drive data from the ECUs and receive a driver'"'"'s habit value from the first unit to control a speed of a smart cruise control apparatus, a third unit configured to guide the driver visually or audibly by using information about a result of controlling the smart cruise control apparatus by the second unit, the drive data and driver'"'"'s habit information, and a fourth unit configured to monitor the result of controlling the smart cruise control apparatus or drive data generated while the smart cruise control apparatus is operated to transmit the controlling result or the generated drive data to the first unit.

Claims

1. An apparatus for automatically controlling a vehicle speed, the apparatus comprising:

a driver'"'"'s habit determining unit configured to receive drive data of a vehicle from Electric Control Units (ECUs) provided in the vehicle to determine driver'"'"'s habits;

a speed control time point generation control unit configured to receive the drive data of the vehicle from the ECUs and receive a driver'"'"'s habit value from the driver'"'"'s habit determining unit to control a speed of a smart cruise control apparatus;

a display/audio control unit configured to guide the driver visually or audibly by using information about a result of controlling the smart cruise control apparatus by the speed control time point generation control unit, the drive data and driver'"'"'s habit information; and

a control result transmitting/monitoring unit configured to monitor the result of controlling the smart cruise control apparatus or drive data generated while the smart cruise control apparatus is operated in order to transmit the controlling result or the generated drive data to the driver'"'"'s habit determining unit.

2. The apparatus of claim 1, wherein the driver'"'"'s habit determining unit includes:

an input unit configured to receive the drive data from the ECUs, the controlling result from the control result transmitting/monitoring unit, and the drive data generated while the smart cruise control apparatus is operated;

a rule database including a normalized table by removing an outlier from values received through the input unit, wherein the outlier is a value greater than a preset acceleration or deceleration value;

a learning factor calculating part configured to calculate a learning factor from the rule database;

a driver'"'"'s habit calculating unit to calculate a driver'"'"'s habit value by weighting a learning factor of a road type among learning factors calculated by the learning factor calculating part, wherein the weighted learning factor has a selection frequency value greater than a preset selection frequency value;

a driver'"'"'s habit database storing the driver'"'"'s habit value calculated by the driver'"'"'s habit calculating unit.

3. The apparatus of claim 2, wherein the learning factor calculating unit is configured to extract a representative value from values stored in the rule database and apply an adaptive fuzzy logic to the representative value to calculate the learning factor.

4. The apparatus of claim 1, wherein the speed control time point generation control unit includes:

a vehicle monitoring unit configured to receive the drive data from the ECUs of the vehicle to produce valid drive data;

a traveling route information generating unit configured to receive map data stored in the vehicle, and real time traffic information and road traffic message (RTM) information received from an outside to produce traveling route information including a cost of a predicted traveling route of the vehicle;

a speed control profiling unit configured to receive the valid drive data from the vehicle monitoring unit and the driver'"'"'s habit from the driver′

habit determining unit to calculate speed control information; and

a speed control value/time point determining unit configured to control the smart cruise control apparatus according to the speed control information calculated by the speed control profiling unit.

5. The apparatus of claim 4, wherein the vehicle monitoring unit is configured to receive the drive data periodically transmitted from the ECUs of the vehicle, classify the drive data into acceleration/deceleration information, speed information, brake operation information, gear shift information, real-time fuel efficiency information, air-conditioner control information, or average fuel efficiency information, and remove an outlier from the classified information to produce the valid drive data, wherein the outlier is a value greater than a preset reference value.

6. The apparatus of claim 4, wherein the driving route information generating unit is configured to apply the road traffic message (RTM) information to the map data stored in the vehicle, and calculate a total energy consumption cost according to nodes and links in a predicted route of the vehicle based on the map data stored in the vehicle to produce driving route information.

7. The apparatus of claim 4, wherein the speed control profiling unit is configured to apply the driver'"'"'s habit value to the traveling route information received from the traveling route information generating unit in order to generate the traveling route information on which the driver'"'"'s habit is reflected, and produce the speed control information including a value for controlling a speed of the smart cruise control apparatus according to the traveling route information on which the driver'"'"'s habit is reflected.

8. The apparatus of claim 1, wherein the drive data includes acceleration/deceleration information, speed information, brake operation information, gear shift information, real-time fuel efficiency information, air-conditioner control information, or an average fuel efficiency information of the vehicle.

9. The apparatus of claim 1, wherein the information about the result of controlling the smart cruise control apparatus includes set speed information, ON/OFF information, operation change information and maintaining time information.

14. The apparatus of claim 4, wherein an energy minimizing position is calculated by determining whether the predicted traveling route exists or not.

15. The apparatus of claim 14, wherein:

when it is determined that the predicted traveling route exists, the cost of the predicted traveling route is calculated according to the predicted traveling route, and

when it is determined that no predicted traveling route exists, the cost of the predicted traveling route is calculated a link combination that minimizes the energy of link/sections in a radius.

10. The method of automatically controlling a vehicle speed, comprising:

receiving drive data of a vehicle from Electric Control Units (ECUs) provided in the vehicle to store the drive data;

determining a driver'"'"'s habit of the vehicle based on the drive data;

applying the drive data and the driver'"'"'s habit of the vehicle to control a speed of the vehicle; and

monitoring a speed control of the vehicle to store the speed control as the drive data.

11. The method of claim 10, wherein the determining of the driver'"'"'s habit comprises:

removing an outlier from the drive data, wherein the outlier is a value greater than a preset acceleration or deceleration value;

applying an adaptive fuzzy logic to the drive data from which the outlier is removed to calculate a learning factor; and

weighting a learning factor of a road type among learning factors to determine the driver'"'"'s habit, wherein the weighted learning factor has a selection frequency value greater than a preset selection frequency value.

12. The method of claim 10, wherein the applying of the drive data and the driver'"'"'s habit comprises:

producing a speed control profile according to a predicted traveling route of the vehicle based on map data, drive data and a driver'"'"'s habit value stored in the vehicle; and

controlling a speed of the vehicle according to the speed control profile.

13. The method of claim 10, wherein the drive data comprises acceleration/deceleration information, speed information, brake operation information, gear shift information, real-time fuel efficiency information, air-conditioner control information, or average fuel efficiency information.

16. The method of claim 12, further comprising:

calculating an energy minimizing position by determining whether the predicted traveling route exists or not.

17. The method of claim 16, wherein:

when it is determined that the predicted traveling route exists, a cost of the predicted traveling route is calculated according to the predicted traveling route, and

when it is determined that no predicted traveling route exists, the cost of the predicted traveling route is calculated a link combination that minimizes the energy of link/sections in a radius.