CN205608707U - Car horn volume adaptive control system based on place ahead pedestrian's target identification - Google Patents

Abstract

The utility model discloses an adaptive control system for car horn volume based on front pedestrian target identification, aiming at solving the problem that the current car horn volume cannot be adjusted, and a vehicle speed detection module obtains the real-time driving speed of the vehicle through a Hall wheel speed sensor; The pedestrian recognition module uses the front-view camera on the vehicle to obtain the image of the road ahead, and uses the image processing algorithm to detect the pedestrian information in front of the vehicle, and judges the distance of the pedestrian in front; the vehicle control module designs an adaptive adjustment algorithm for the car volume according to the vehicle speed and the position of the pedestrian, and then Adjust car horn volume.

Description

Adaptive Control System of Car Horn Volume Based on Front Pedestrian Target Recognition

technical field

The utility model relates to the field of auto parts, in particular to an auto horn volume adaptive control system and a control method based on front pedestrian target recognition.

Background technique

With the continuous increase of the number of cars, the noise pollution of car horns is becoming more and more serious. No matter what the situation is, the traditional car horns can only emit a decibel-level beeping sound, which can easily frighten pedestrians and make people feel uncomfortable. The generation of bad emotions such as anxiety and panic does not meet the current development requirements of intelligent and humanized automobiles. Therefore, it is an urgent problem to be solved to design an invention so that it can be adaptively controlled based on the car horn volume of the front pedestrian target recognition, so that the car horn can be pronounced intelligently and humanized.

Contents of the invention

The utility model aims at the problem that the volume of the current automobile horn cannot be adjusted, and proposes an adaptive control system for the volume of the automobile horn based on the recognition of the pedestrian target in front. According to the vehicle speed and pedestrian position, it adaptively adjusts the volume of the car horn through the fitting relationship model between the volume decibel and the distance of the pedestrian in front and the vehicle speed.

The purpose of this utility model is achieved by the following scheme:

A car horn volume adaptive control system based on front pedestrian target recognition, including a vehicle speed detection module, a pedestrian recognition module, a vehicle control module and a car horn; the vehicle speed detection module and the pedestrian recognition module are connected to the vehicle control module through data lines, and the vehicle The control module is electrically connected with the car horn.

Among them, the vehicle speed detection module is used to obtain the real-time driving speed of the vehicle, and send the vehicle speed signal to the vehicle control module; the pedestrian identification module is used to detect the pedestrian information in front of the vehicle, judge the distance of the pedestrian in front, and send the pedestrian distance signal to the vehicle control module; The on-board control module is used to design an adaptive adjustment algorithm for car volume based on the obtained vehicle speed signal and pedestrian distance signal, and then adjust the volume of the car horn through the fitting relationship model between the volume decibel and the distance of the pedestrian in front and the vehicle speed.

Further, the vehicle speed detection module includes a Hall wheel speed sensor.

Further, the pedestrian recognition module includes a vehicle-mounted front-view camera.

The beneficial effects of the utility model are:

The utility model enables the car horn to adaptively emit sounds of different decibels according to the speed of the vehicle and the position of pedestrians, thus effectively solving the problem that it is difficult for the vehicle to whistle in time to remind pedestrians when the speed is too fast, and the whistle is sounded when the distance is relatively short. It is easy to frighten pedestrians, make car horns sound intelligently and humanely, and enrich the functional design of on-board driving assistance systems.

Description of drawings

Fig. 1 is a structural block diagram of the vehicle horn volume adaptive control system based on front pedestrian target recognition of the present invention.

Fig. 2 is a signal flow chart of the self-adaptive control method of the volume of the car horn based on the recognition of the pedestrian in front of the utility model.

detailed description

This patent will be explained below in conjunction with the accompanying drawings. When the speed of the vehicle is slow and the distance between the pedestrians in front is relatively close, the whistle will frighten the pedestrians and cause the pedestrians to produce bad emotions such as panic; When the speed of the car is fast and the pedestrians in front are far away, the whistle cannot remind the pedestrians in time. Therefore, this patent proposes an adaptive control method for car horn volume based on pedestrian target recognition in front.

The auto horn volume self-adaptive control system based on front pedestrian target identification of the present utility model, as shown in Figure 1, comprises:

Vehicle speed detection module 100, pedestrian identification module 200, vehicle-mounted control module 300 and car horn; Wherein, vehicle speed detection module 100 and pedestrian identification module 200 are all connected with vehicle-mounted control module 300 by data line, and vehicle-mounted control module 300 is electrically connected with vehicle horn 400 .

The vehicle speed detection module 100 is used to obtain the real-time driving speed of the vehicle, and sends the vehicle speed signal to the vehicle control module;

The pedestrian recognition module 200 is used to detect the pedestrian information in front of the vehicle, and judge the distance of the pedestrians ahead, and send the pedestrian distance signal to the vehicle control module;

The on-vehicle control module 300 is used to design the adaptive volume of the car through the fitting relationship model between the volume decibel and the distance of the pedestrian in front and the speed of the vehicle according to the vehicle speed signal sent by the vehicle speed detection module 100 and the pedestrian distance signal sent by the pedestrian recognition control module 200. Adjust the algorithm, and then adjust the volume of the car horn 400.

The vehicle speed detection module uses the Hall wheel speed sensor, and then uses the non-driving wheel speed obtained by the Hall wheel speed sensor to multiply the wheel rolling radius to calculate the vehicle speed.

The pedestrian recognition module includes an on-board front-view camera.

The signal flow chart of the self-adaptive control method for the volume of the car horn based on the target identification of the pedestrians in front of the utility model is shown in Figure 2. When the car is running, the real-time driving speed of the vehicle is obtained through the speed detection module, and the speed signal is sent to the vehicle control unit. The pedestrian recognition module uses the front-view camera on the vehicle to obtain the road image ahead, and uses the image processing algorithm to detect the pedestrian information in front of the vehicle, and judges the pedestrian distance, and sends the pedestrian distance signal to the vehicle control unit; the vehicle control module according to the real-time driving speed of the vehicle and the front Pedestrian distance, that is, the vehicle speed signal and pedestrian distance signal obtained by the control unit, through the fitting relationship model between the volume decibel and the distance of the pedestrian in front and the vehicle speed, an adaptive adjustment algorithm for the volume of the car horn is designed, and the sound signal is output to the car horn, and then the car is adjusted. Speaker volume.

The pedestrian recognition module extracts the histogram of gradient (HOG) features of pedestrians and non-pedestrians through sample training of pedestrians and non-pedestrians, and uses the SVM (support vector machine) classifier to filter the required pedestrian HOG features from the road image ahead, so that Detect pedestrians in images.

The front pedestrian information detected by the pedestrian recognition module is based on the nearest pedestrian information, that is, the distance between the vehicle and the pedestrian is judged based on the nearest pedestrian information.

The pedestrian recognition module realizes the calculation of the pedestrian distance in front of the vehicle under the condition of knowing the internal parameters of the camera and the pixel coordinates of the feature points (manually selected in advance and recording the distance from the camera) through the conversion relationship between the coordinate systems. Its coordinate system conversion relationship is as follows:

$\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; w</span>}}\\ {\mathrm{<span\; class="notranslate">\; Y</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; Y</span>}}_{\mathrm{<span\; class="notranslate">\; W</span>}}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; \&alpha;</span>}\\ {\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; c</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; Z</span>}}_{\mathrm{<span\; class="notranslate">\; W</span>}}\end{array}\right.<span\; class="notranslate">\; ,</span>$

Among them, O _c -X _c Y _c Z _c is called the camera coordinate system. O _w -X _w Y _w Z _w is called the world coordinate system, and α is the height of the optical center of the camera from the ground (m).

The on-board control module is embedded with an adaptive adjustment algorithm for volume decibels based on the distance of pedestrians ahead and the speed of the vehicle.

The algorithm embedded in the vehicle control module is as follows:

$\mathrm{<span\; class="notranslate">\; Y</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 80</span>}\mathrm{<span\; class="notranslate">\; d</span>}\mathrm{<span\; class="notranslate">\; B</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 10</span>}<span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; o</span>}\mathrm{<span\; class="notranslate">\; g</span>}<span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; r</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ^</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; w</span>}<span\; class="notranslate">\; /</span>\mathrm{<span\; class="notranslate">\; 5</span>}$

Among them, Y is the volume in decibels of the car horn output volume (dB); l is the distance of pedestrians in front (m); r is the distance between the measured place and the sound source (m) when the decibel size of the measured place is 80dB, which needs to be measured by experiment ; w is the compensation decibel (dB) for the vehicle speed (km/h), and its magnitude is equal to the vehicle speed.

The utility model enables real-time self-adaptive control of the horn, so that the car horn can adaptively emit sounds in different decibels according to the vehicle speed and the position of pedestrians, through the fitting relationship model between the volume decibel and the distance of the pedestrian in front and the speed of the vehicle. This adaptive mode not only enhances the safety of the car in various environments, but also makes the driving behavior more civilized, and enriches the functional design of the on-board driving assistance system.

Claims (3)

1. a sound volume of automobile horn adaptive control system based on front pedestrian target identification, its feature exists In, including Bus-Speed Monitoring module, pedestrian's identification module, vehicle-mounted control module and car horn；Bus-Speed Monitoring Module and pedestrian's identification module are all connected by data wire with vehicle-mounted control module, vehicle-mounted control module and automobile Loudspeaker electrically connect.

A kind of sound volume of automobile horn self adaptation based on front pedestrian target identification Control system, it is characterised in that described Bus-Speed Monitoring module includes Hall wheel speed sensors.

A kind of sound volume of automobile horn self adaptation based on front pedestrian target identification Control system, it is characterised in that described pedestrian's identification module includes vehicle-mounted forward sight photographic head.