JPH04314199A - Vehicle dynamics measurement method - Google Patents

Abstract

(57) [Summary] This bulletin contains application data before electronic filing, so abstract data is not recorded.

Description

[Detailed description of the invention]

0001

[Field of Industrial Application] The present invention relates to a measurement method in a vehicle dynamic measuring device installed on a road to measure and collect necessary traffic information such as vehicle speed, number of passing vehicles, vehicle type (regular vehicle/large vehicle), etc. .

0002

[Prior Art] Conventionally, this type of vehicle dynamic measuring device uses a video camera to image-process original image data and background data photographed to give an overview of the movement of vehicles on the road. It is configured to measure and output information such as speed, number of vehicles passing, and vehicle type (regular/large vehicle).

0003

[Problems to be Solved by the Invention] However, the conventional vehicle dynamic measurement device described above detects a pair of headlights at night to track and measure the vehicle, but it is difficult to track and measure the vehicle by detecting pairs of headlights at night. There were cases where it was determined that

Furthermore, because the headlights are located diagonally due to the angle of view, it is difficult to detect headlights in pairs if processing is performed for each scanning line, especially for small lamps that are lit in place of or at the same time as the headlights. This was difficult for lamps with low brightness and a small number of pixels, such as .

[0005] The present invention solves these conventional problems and allows accurate vehicle speed, number of passing vehicles, and vehicle types (regular vehicles, regular vehicles, The purpose of this project is to provide a method for measuring vehicle dynamics that can measure and collect necessary traffic information such as large vehicles.

[0006]

[Means for Solving the Problems] In order to achieve the above object, the present invention eliminates the influence of road surface reflection of headlights during nighttime rainy weather using a threshold value based on the average brightness of each scanning line. This is how it was done.

The present invention also makes it possible to detect small lamps and the like by performing simple coordinate transformation that corrects only the vertical deviation due to the angle of view.

[0008]

[Function] With the above-described configuration, the present invention has the advantage that, first, accurate vehicle measurements can be made without being affected by road surface reflections of headlights during nighttime and rainy weather.

Second, it is possible to detect not only headlights but also small lamps with low brightness and a small number of pixels, which has the effect of allowing accurate vehicle measurements.

0010

【Example】

First Embodiment FIG. 1 shows the configuration of a first embodiment of the present invention. In FIG. 1, 1 is a video camera, 2 is a main body of the vehicle dynamic measurement device, 3 is an image memory for a first input image, 4 is an image memory for a second input image, and 5 is a third input image. 6 is an image memory for the fourth input image, 7 is a video data A/D conversion section, 8 is an image data processing section, and 9 is a data output section.

Next, the operation of the above embodiment will be explained. In the embodiment described above, video information captured using the video camera 1 is transmitted to the vehicle dynamic measurement device main body 2. In the vehicle dynamic measurement device main body 2, this information is converted into digital data using the video data A/D converter 7. Then, digital data for two screens captured at a certain interval is stored in the image memories 3 and 4. Further, the image memory 5 stores information (background data) regarding a state in which a vehicle is not present. Then, using the data in these image memories 3, 4, and 5, an image data processing unit 8 performs image processing using a threshold value based on the average brightness of each scanning line in the case of nighttime, and stores the data in the image memory 6. Write the processing results. Then, by extracting the vehicle from this image data and continuously performing this processing, the tracking of the vehicle, the running speed, etc. are outputted from the data output unit 9, and the current road condition is determined, and this information Update the background data based on.

[0012] Next, a method of measuring by removing the road surface reflection of headlights during nighttime rainy weather will be explained. Figure 2 shows the road surface reflection of headlights during nighttime and rainy weather. As can be seen from this figure, the road surface reflection 22 of the headlight of a vehicle 21 such as an automobile extends long on the road surface at an imaging position far from the video camera 1, and the brightness of the road surface reflection 22 is relatively low. As the vehicle 21 gradually approaches the video camera 1, the road reflection 22 becomes shorter and the brightness of the road reflection becomes higher. When the vehicle 21 reaches the second imaging position, the road surface reflection 22' of the headlight of the vehicle 21' at that position becomes a spot, and its brightness becomes as high as that of the headlight.

[0013] For road reflections such as 22, by changing the brightness threshold of image data using the average value for each scanning line, it is possible to distinguish between headlight light and road reflection light. , it is possible to remove that influence. In addition, for road surface reflections such as 22', the leading edge candidates are measured backward by the average vehicle length from the position determined to be the leading edge candidate of the vehicle, and the leading edge candidates of the vehicle are measured at the position behind that position. If there is, it can be determined that the leading edge candidate at the front is a road surface reflection, and the leading edge candidate at the rear is determined to be a vehicle.

Next, a basic algorithm of a method for removing the road surface reflection of headlights during night and rainy weather will be explained with reference to FIG. First, the average value of luminance for each scanning line is determined (steps 31 and 32). Next, a threshold value for each scanning line is created based on this brightness average value, and a processing screen is created (step 33). This is performed for each measurement scanning line (steps 34, 35, 36). Next, the leading edge (headlight portion) of the vehicle is extracted for each scanning line (step 37). Then, it is determined whether a leading edge candidate exists on the scanning line (step 38). If it is determined that it exists, the leading edge of the vehicle (
headlight section) (step 39), and determines whether a leading edge candidate exists (step 4).
0), if there is no leading edge candidate behind the average vehicle length, the detected leading edge candidate is determined to be the leading edge of the vehicle. Then, vehicle tracking processing is performed for what is determined to be the leading edge of the vehicle (step 41), and this is performed for each measurement scanning line (steps 42, 43).

As described above, according to the above embodiment, the influence of the road surface reflection of the headlights can be removed during nighttime rainy weather, so the accurate leading position of the vehicle can be extracted regardless of the weather. This has the advantage of increasing the accuracy of vehicle speed measurements.

Second Embodiment FIG. 4 shows the concept of simple coordinate transformation in a second embodiment of the present invention. In general, image data from vehicle dynamic measurement devices can rarely be captured from the front of the lane;
As shown in (a), there are many images taken from an oblique angle. Conventionally, the headlights of a pair of vehicles are tracked at night, but since image processing is performed in units of scanning lines, the processed screen is coordinate transformed to place both headlights on the same scanning line. That's what I do. If the coordinates before coordinate transformation are (X, Y), the coordinates after coordinate transformation are (X', Y'), and the rotation angle is θ, coordinate transformation is usually performed using the following equation (1). .

X'=Xcosθ+Ysinθ Y'=Xsinθ+Ycosθ
...(1)

However, converting using such a formula requires a lot of processing time, and is not suitable for this apparatus which performs processing in real time. Therefore, in the present invention, as shown in (b), a method is used in which only the vertical coordinates are moved with the center of the lane as a reference so that they are placed on the same scanning line. This is called simple coordinate transformation. This simple coordinate transformation can be performed using the following formula (2
) can be expressed as:

X'=X Y'=Y+m*(X-c)
...(2)

[0020]
Next, a basic algorithm for detecting small lamps and the like using such simple coordinate transformation will be described with reference to FIG. 5. First, using the method shown in the first embodiment, the front part of the vehicle is extracted by performing differential processing, background difference, frame difference, etc., and extraction data is created (step 51). Next, the vehicle extraction data is compared with the threshold value in units of pixels (steps 52, 53, and 54). Next, if it is larger than the threshold value, "0" is written at the coordinate position where simple coordinate transformation was performed using Equation 2 (step 55
, 56). This is done for all vehicle extraction data to create a processing screen (steps 57, 58, 59, 60)
.

As described above, according to the above embodiment, it is possible to detect not only headlights but also small lamps with low brightness and a small number of pixels, and it is possible to improve the accuracy of measuring vehicle speed at night. It has the advantage of

[0022]

Effects of the Invention As is clear from the above embodiments, the present invention has the following effects. First, it is possible to remove the influence of road reflections from headlights during rainy nights, making it possible to accurately determine the leading position of a vehicle regardless of the weather, thereby increasing the accuracy of vehicle speed measurements at night. can.

Second, it is now possible to detect not only headlights but also small lamps with low brightness and a small number of pixels, making it possible to accurately measure the vehicle.

[Brief explanation of drawings]

FIG. 1 is a block diagram of a vehicle dynamic measurement device for implementing a first embodiment of the present invention.

[Fig. 2] A schematic diagram showing the road surface reflection of headlights during rainy weather at night in the first embodiment.

[Figure 3] Operation flowchart in the first embodiment

[
FIG. 4: Schematic diagram showing the concept of simple coordinate transformation in the second embodiment of the present invention (a) is an original image (b) is a diagram after simple coordinate transformation

Claims (3)

[Claims] Claim 1: When measuring and collecting vehicle dynamics by processing image data taken using a video camera to provide a bird's-eye view of vehicle movements on the road, at night and in rainy weather, each scanning line is A vehicle dynamic measurement method that uses a threshold value based on the average brightness of the vehicle to determine whether the light is from headlights or reflected from the road surface. [Claim 2] When it is determined that the light from the headlights is the leading edge candidate of the vehicle, the leading edge candidate is measured backward from that position by the average vehicle length, and the leading edge of the vehicle is located at the position behind that position. 2. The vehicle dynamics measuring method according to claim 1, wherein when a candidate exists, the light from a headlight determined to be a leading edge candidate at a position ahead is determined to be light reflected from a road surface. [Claim 3] When measuring and collecting vehicle dynamics by processing image data taken using a video camera to provide an overview of the movements of vehicles on the road, at night and in rainy weather, the data is processed for each scanning line. By using the method according to claim 1, which uses a threshold value based on the average luminance of Vehicle dynamics measurement method.