Device for detecting obstacles, for use in vehicles

• US 6,163,252 A
• Filed: 09/28/1999
• Issued: 12/19/2000
• Est. Priority Date: 04/07/1999
• Status: Expired due to Term

• Current Assignee: Mitsubishi Denki Kabushiki Kaisha (Mitsubishi Electric Corporation)
• Original Assignee: Mitsubishi Denki Kabushiki Kaisha (Mitsubishi Electric Corporation)
• Inventors: Nishiwaki, Takeshi
• Primary Examiner(s): Lefkowitz, Edward
• Application Number:
  US09/406,802
• Time in Patent Office: 448 Days
• Field of Search: 340/435, 340/436, 340/903, 340/904, 342/70
• US Class Current: 340/435
• CPC Class Codes: B60Q 9/006 using a distance sensor
• CPC Class Codes: B60Q 9/008 for anti-collision purposes
• CPC Class Codes: G01S 13/87 Combinations of radar systems, e.g. primary radar and secondary radar
• CPC Class Codes: G01S 13/931 of land vehicles
• CPC Class Codes: G01S 15/87 Combinations of sonar systems
• CPC Class Codes: G01S 15/931 of land vehicles
• CPC Class Codes: G01S 17/87 Combinations of systems using electromagnetic waves other than radio waves
• CPC Class Codes: G01S 17/931 of land vehicles
• CPC Class Codes: G01S 2013/932 using own vehicle data, e.g. ground speed, steering wheel direction
• CPC Class Codes: G01S 2013/93271 in the front of the vehicles
• CPC Class Codes: G01S 2013/93272 in the back of the vehicles
• CPC Class Codes: G01S 2013/93274 on the side of the vehicles

Abstract

A device for detecting obstacles, for use in vehicles, capable of correctly detecting obstacles without driving up the cost. the device includes a signal processing device 3 for detecting an obstacle Z based on reception signals A, B from a plurality of sensor devices 1, 2, wherein the signal processing device includes detection region-setting devices 31, 32 for dividing the region around the vehicle into a plurality of detection regions, probability-of-presence operation devices 33, 34 for operating the in-the-region presence probabilities P, Q of obstacle, a probability distribution operation device 35 for operating the in-the-region presence probabilities for each of the detection regions, and an obstacle detection device 36 for judging the regions S where the obstacles exist based on the in-the-region presence probabilities R in the distribution of presence probabilities, wherein the obstacle detection device judges detection regions exhibiting the in-the-region presence probabilities that are larger than a predetermined threshold value to be the regions where the obstacles exist among the in-the-region presence probabilities in the detection regions in the distribution of presence probabilities.

Claims

1. A device for detecting obstacles, for use in vehicles comprising:

a plurality of sensor means for emitting beams toward the surrounding of the vehicle and for producing reception signals depending upon the intensities of the reflection beams; and

a signal processing means for detecting obstacles around said vehicle based upon changes in the reception signals with the passage of time;

wherein said signal processing means includes;

detection region-setting means for dividing the region around said vehicle into a plurality of matrix-like detection regions;

probability-of-presence operation means for operating the probabilities of presence of said obstacles in said detection regions as in-the-region presence probabilities;

a probability distribution operation means for operating the distribution of presence probabilities by synthesizing said in-the-region presence probabilities for each of the detection regions; and

an obstacle detection means for detecting the positions and sizes of said obstacles from said regions where said obstacles exist by judging the regions where said obstacles exist based on said distribution of presence probabilities;

wherein said obstacle detection means judges detection regions exhibiting the in-the-region presence probabilities that are larger than a predetermined threshold value to be the regions where said obstacles exist among the in-the-region presence probabilities in the detection regions in said distribution of presence probabilities.

2. A device for detecting obstacles, for use in vehicles according to claim 1, wherein said sensor means includes a first sensor means and a second sensor means that use ultrasonic waves as said beams, said first sensor means and said second sensor means being installed at different positions on the vehicle.

3. A device for detecting obstacles, for use in vehicles according to claim 1, wherein said sensor means includes a first sensor means that uses electromagnetic waves as said beam and a second sensor means that uses light as said beam.

4. A device for detecting obstacles, for use in vehicles according to claim 1, wherein said sensor means includes a first sensor means that uses ultrasonic waves as said beam and a second sensor means that uses light as said beam.

5. A device for detecting obstacles, for use in vehicles according to claim 1, wherein said obstacle detection means finds a maximum value in the in-the-region presence probabilities in each of the detection regions in said distribution of presence probabilities, and sets a value obtained by multiplying said maximum value by a correction coefficient as said threshold value.

6. A device for detecting obstacles, for use in vehicles according to claim 1, wherein said obstacle detection means;

includes a filter processing means for effecting the filter processing for said in-the-region presence probabilities with the passage of time; and

sets, as said in-the-region presence probability, a value obtained by adding up together;

a value obtained by multiplying a value Rk of the in-the-region presence probability of this time in each detection region Ek in the distribution of presence probabilities, by a first filter coefficient; and

a value obtained by multiplying a value Rbj of the in-the-region presence probability of the previous time in each detection region Ej in the distribution of presence probabilities, by a second filter coefficient.

7. A device for detecting obstacles, for use in vehicles according to claim 6, further comprising a vehicle speed sensor for detecting the speed of said vehicle, wherein the filter processing means in said obstacle detection means includes a previous value operation means for operating the previous value Rbj of the in-the-region presence probability corresponding to the value Rk of the in-the-region presence probability of this time depending upon the vehicle speed, and effects the filter processing with the passage of time by using said previous value Rbj.

8. A device for detecting obstacles, for use in vehicles according to claim 7, wherein said previous time operation means includes a correlation coefficient operation means for operating the correlation coefficient W (k, j) of the region Ej detected in the previous time corresponding to the region Ek detected this time for each of the detection regions depending upon the vehicle speed, and sets the sum of the values obtained by multiplying the in-the-region presence probabilities of the previous time related to all detection regions by said correlation coefficient W (k, j), as the previous value Rbj corresponding to the value Rk of this time.

9. A device for detecting obstacles, for use in vehicles according to claim 6, further comprising a yaw rate sensor for detecting the yaw rate of the vehicle, wherein the filter processing means in said obstacle detection means includes a previous value operation means for operating the previous value Rbj corresponding to the value Rk of said in-the-region presence probability of this time depending upon said yaw rate, and effects the filter processing with the passage of time by using said previous value Rbj.

10. A device for detecting obstacles, for use in vehicles according to claim 9, wherein said previous value operation means includes a correlation coefficient operation means for operating the correlation coefficient W (k, j) of the region Ej detected in the previous time corresponding to the region Ek detected this time for each of the detection regions depending upon the yaw rate, and sets the sum of the values obtained by multiplying the in-the-region presence probabilities of the previous time related to all detection regions by said correlation coefficient W (k, j), as the previous value Rbj corresponding to the value Rk of this time.