RU2582317C2 - Adaptive cruise control of vehicle - Google Patents

Abstract

FIELD: vehicles.

SUBSTANCE: system of adaptive cruise control for vehicle, in which settings are applied to card drive. System may include GPS-receiver for generating GPS-data about current location of the vehicle, and radar device that generates data on current distance to vehicle ahead. System may also have an electronic controller operable to generate test data based on current and stored data about distance, and then correlate the received data with GPS-distance data.

EFFECT: achieved increase in comfort and safety of vehicle.

8 cl, 6 dwg

Description

FIELD OF THE INVENTION

The invention relates to electronic systems for vehicles, in particular to adaptive cruise control systems.

State of the art

The prior art adaptive cruise control (ACC) systems for automobile vehicles that control the distance between one vehicle and another vehicle in front of it are known. To determine the speed of the vehicle in front and the distance to it, these systems, as a rule, use a forward-directed radar mounted behind the grille of the vehicle. Based on these data, ACC systems can automatically adjust the vehicle speed, observing a predetermined distance to the vehicle in front. For example, if the vehicle in front is slowing down or if another object is detected in the vehicle’s path, the ACC system can send a signal to the engine or brake system about a decrease in vehicle speed. Then, upon clearing the path, the system can again accelerate the vehicle to a predetermined speed and a predetermined distance to the vehicle in front.

In addition, a typical ACC system may include control switches mounted on the steering wheel and allowing the driver to manually change the preset distance to the vehicle in front. In this case, the driver can change the settings manually in real time, providing a different distance to the vehicle in front and creating comfortable conditions throughout the trip. For example, a driver can drive to work on a section of a high-speed freeway with low traffic and high speed and adjust the ACC system to maintain a distance of 65 m at a speed of 100 km / h. On sections of the motorway with lower speed and lower intensity, where, for example, several freeways are connected, the driver can change the settings of the ACC system by setting a distance of 30 m. Accordingly, the driver can manually select various predetermined distances for certain sections of the road.

Disclosure of invention

A system of correlation with a map of driver behavior characteristics and driving parameters is proposed. In one embodiment, the system may include a GPS receiver generating GPS data about the current location of the vehicle. In addition, the system may include a radar device that generates data on the distance to the vehicle in front. In addition, the system may include an electronic controller configured to generate experimental distance information based on the current distance and stored distance data, and then compare the experimental distance information with GPS data.

Also presented is a method of obtaining and changing a predetermined driver behavior parameter in said vehicle system. In one embodiment, the method may include the step of obtaining GPS data about the current location of the vehicle from the GPS satellite and obtaining current information about the distance to the vehicle in front. In addition, the method may also include generating experimental distance data based on current distance information and stored distance data, as well as comparing the experimental distance data with GPS data.

Brief Description of the Drawings

In FIG. 1 shows a general diagram of the components of a driver behavior mapping system and an exemplary image of a vehicle in which such a system can be applied.

In FIG. 2 is a flowchart illustrating the steps of a procedure for selectively storing location data to construct a route map.

In FIG. 3 is an illustration of the principles of the process shown in FIG. 2.

In FIG. 4 is a process diagram illustrating the steps of a procedure for selectively storing altitude data to refine a route map.

In FIG. 5 is an illustration of the principles of the process depicted in FIG. four.

In FIG. 6 is a process diagram demonstrating the steps of comparing the current route with a previously saved vehicle route, as well as adjusting the set parameters in the ACC system and obtaining new values of speed and distance.

The implementation of the invention

This document describes one of the variants of the system and method for modifying and assigning experimental data on distance and speed to certain places along the current route of the vehicle. In one embodiment, the system can create and use a localized and adaptive route map. In particular, the system can be located in the vehicle itself, periodically obtain vehicle location data from GPS satellites, and selectively store a portion of vehicle location data according to certain criteria. The system can store experimental data on the distance and speed of the vehicle in the course of its movement along the route. Thus, map data and vehicle operation data corresponding to a specific vehicle route can be stored locally, occupying a relatively small amount of electronic storage device memory. Locally stored map data and driver behavior parameters can refer to the vehicle in which the data is recorded, or to selected drivers using the vehicle. Locally stored map data can be used on subsequent trips on the same vehicle to view the estimated vehicle path. Locally stored data on the behavior parameters can be used in subsequent trips together with the ACC system to adjust the operation of the vehicle as data on previous actions associated with this vehicle at the corresponding points on the route. The described method may not depend on pre-recorded cards and does not require a communication channel for receiving data from the outside (although it does not exclude the possible use or interaction with such pre-recorded cards and / or communication channels). Instead, the described system may request location data and vehicle operating data related to specific vehicle routes, as well as use such special data on subsequent trips along that route.

In FIG. 1 shows an example of a vehicle 1, in which system 10 can be used to create localized maps and modify the set parameters of the ACC system for the routes traveled. System 10 may include at least one electronic controller 100 connected to at least one storage device 110, an automobile electronic storage device 120, a GPS receiver 130, a radar device 140 (e.g., a forward-facing radar device) and a speed sensor 150 wheel rotation. The controller 100 may receive GPS data generated by the GPS receiver 130 and indicating the current location of the vehicle. In addition, the controller 100 may be configured to receive current distance data generated by the radar device 140 and indicating the current distance to the vehicle in front. The controller 100 may also be configured to receive current speed data generated by the wheel speed sensor 150 and indicating the current speed of the vehicle. However, the controller may also receive data generated by other sensors of the vehicle. The controller can use GPS data to create an experimental map of the routes along which the vehicle was moving, and then link the experimental data on the distance and speed of the vehicle to the experimental routes using the methods and algorithms described below.

In FIG. 2 is a process diagram illustrating the main functional steps of an algorithm stored in a software storage device and executed by a controller 100 to request location data and efficiently construct in real time a map of a new route along which the vehicle is moving. In FIG. 3 is a general graphical representation of the method of FIG. 2. In FIG. 3 circles represent the subsequent geographical locations on the terrain in the "longitude / latitude" grid (altitude is not shown). Large filled circles 310a-310e and small filled circles 320a-320k correspond to the points at which the vehicle’s geographical location is periodically compared (i.e., GPS satellites request the vehicle’s location data in longitude and latitude). Longitude / latitude data associated with large filled circles 310a-310e may be stored by the system in the storage device 120 for later use when the vehicle travels this route in the future. Data associated with small circles 320a-320k is ignored. Large circles 310a-310e are “coordinate nodes”, which are later used to determine the previously traveled route of combining these coordinate nodes 310a-310e with each other.

Coordinate node 310a represents a first sample of vehicle location data on a new route. In this way, the system can store location data associated with the coordinate node 310 as a “head” or starting point of a route. The system can then periodically query or sample longitude / latitude data associated with the subsequent location of the vehicle and received by the GPS receiver 130 from GPS satellites. The system can determine the need to save the requested location data as coordinate nodes (for example, coordinate nodes 310b-310e) when this data goes beyond the boundaries of the workspace between parallel and perpendicular boundary lines.

The threshold parallel distance 330 may be the distance between two imaginary longitudinal lines located on the sides of the vehicle, while the vehicle is located at the same distance from them. The direction of parallel lines at any given moment can be determined by the current direction of movement of the vehicle. For example, the threshold parallel distance 330 shown in FIG. 3 is oriented vertically, since the direction of the vehicle on the graph corresponds to the vertical direction. The threshold parallel distance 330 (the distance between the dashed lines) may be a predetermined value or a programmable variable value. The threshold parallel distance 330 can be practically any (for example, 1 meter, 2 meters, 3 meters, etc.). The threshold perpendicular distance 340 may be the distance (predetermined or variable) between imaginary transverse lines taken in the direction of travel of the vehicle. For a vehicle moving forward, the threshold perpendicular distance 340 is usually counted from the stored coordinate unit forward in the direction of travel of the vehicle. For a vehicle moving backward, the threshold perpendicular distance 340 may be counted back from the stored coordinate node backward in the direction of travel of the vehicle. The value of the threshold perpendicular distance 340 can be almost any, for example 3 meters, 5 meters, 7 meters, etc. Threshold parallel and perpendicular distances can define the working area around a moving vehicle. The requested location data may be ignored when the vehicle is within the working area (within the parallel and perpendicular threshold distances), as shown in FIG. 3 in small circles 320a-320k. However, when the vehicle extends beyond the work area (extends beyond the parallel and perpendicular threshold distances), the system can save the current location data to the storage device 120 as the coordinate node 310. In this case, the vehicle location data can be stored as the coordinate node 310 every time the vehicle deviates from the current direction by a predetermined distance, which is determined by going beyond the threshold parallel States 330. Vehicle location data is also stored as a coordinate node 310 each time the vehicle continues to move in the same direction (within the threshold parallel distance) at a given distance, which is determined by going beyond the threshold perpendicular distance 340. Saved coordinates nodes 310a-310e can then be used to determine the route previously traveled by this vehicle, which can be displayed to the driver on the display when uyuschey trip on this route. The smaller the work area (i.e., the larger the parallel and / or perpendicular threshold distance), the more coordinate nodes 310 will be saved and the smaller the cell size or the higher the resolution of the constructed map. The larger the work area, the larger the cells or the lower the resolution of the card. Obviously, small cells or high resolution require more memory storage device 120.

In FIG. 2 illustrates steps that may be performed by the controller 100 to request location data and map construction, as described above with reference to FIG. 3. In FIG. 2, at step 210, the size of the work area is determined, i.e. determination of parallel and perpendicular threshold distances. Then, at step 220, the system may request location data from GPS satellites. Then, at step 230, the controller 100 based on the received location data of the vehicle can determine whether it is in the work area or outside. In other words, the controller 100 can determine whether the vehicle is within an area bounded by a threshold parallel distance 330 and a threshold perpendicular distance 340. As mentioned above, the parallel and perpendicular distances can be predetermined or variable. If the vehicle is within the work area, then the algorithm may return to step 220 and periodically again request location data. On the other hand, if the vehicle extends beyond the work area (extends beyond the parallel and perpendicular threshold distances), then at step 240, the system can save the current location data (longitude and latitude) to the storage device 120 as a coordinate node 310. After the coordinate node is stored, the algorithm may return to step 220 and periodically again request location data. The frequency of the data request can be predefined or variable. Thus, the set of coordinate nodes 310 will be saved for later use, and these nodes can be mapped to each other so as to determine and display the saved route traveled by the vehicle.

The method described above with reference to FIG. 2 and FIG. 3 is a method for constructing in real time a map of a route traveled by a vehicle, as well as its local storage on a vehicle. There is no need for pre-recorded cards provided by a special supplier, as well as a communication channel with a data source located outside the vehicle. However, instead, the system can use a pre-compiled map purchased from the developer and associate driving characteristics with this map.

Described above with reference to FIG. 2 and FIG. 3 a two-dimensional map of routes traveled by a vehicle can be supplemented by adding other characteristics of the route traveled. For example, in FIG. 4-5 show a method similar to the method of FIG. 2-3, to store altitude data for the route traveled, which can then be called up by the system to provide the driver and control systems, such as the ACC system, information about the terrain and other changes in the height of the road along the route. In FIG. 5 is a graphical illustration of the principles for recording altitude data corresponding to a route. As in the method described above, the system can periodically request altitude data from GPS satellites for the current location of the vehicle. The requested height data is shown in FIG. 5 in the form of large filled circles 510a-510e and small circles 520a-520w. As before, the working area around the vehicle can be determined by a threshold parallel distance 530 and a threshold perpendicular distance 540, both of which can be predefined or variable values. The threshold perpendicular distance 540 may be taken from a previous selection of vehicle direction data. The threshold distance 530 between the longitudinal lines may be the distance between two imaginary longitudinal lines located above the vehicle and below it along the direction of travel. When the system determines that the vehicle has moved beyond the working area (beyond the threshold distance between the longitudinal or transverse lines), it can store the height data along with the vehicle’s location data as the coordinate unit 510a-510d in the storage device for subsequent use. The stored height coordinates 510a-510d can be compared with each other to build a terrain map to display the driver's altitude changes on a previously covered route.

In FIG. 4 is a process diagram that describes a method performed by the controller 100 to construct a terrain map described with reference to FIG. 5. At step 410, the system can determine the height of the work area formed by a threshold parallel distance 530 in height and a threshold perpendicular distance 540 in height. Parallel and perpendicular threshold height distances can be pre-set or variable values, and can also be almost any. At 420, altitude data may be collected using GPS satellites. At step 430, the controller 100 may determine whether the vehicle is within the working area or not (i.e., within the threshold parallel distance 530 in height and the threshold perpendicular distance 540 in height). If so, then the algorithm may return to step 420 and again periodically request height data. The frequency of requesting height data can be predefined or variable. If the vehicle has gone beyond the work area (i.e., beyond the threshold parallel height 530 and vertical perpendicular threshold 540), then at step 440 the system can query the GPS system for the geographic data associated with the point in which vehicle exceeded the working area in height. Then, at step 450, the system can store the height data along with geographic data on the storage device 120 as a new height coordinate node 510a-510d. The algorithm may then return to step 420 and again periodically request height data. Then, these stored height coordinate nodes can be called up and compared with each other to create and provide the driver with information about changes in the terrain (for example, hills) on the route traveled, when the vehicle will go this route in the future.

A map constructed in accordance with the method of FIG. 2 and FIG. 3 and supplemented or not supplemented by height data in accordance with the method of FIG. 4 and FIG. 5 can also be supplemented with other data by comparing them and storing them while passing the route by a vehicle. For example, driving speed, distance values from vehicles in front and other driving characteristics can be compared and saved for later use to control or configure various on-board systems, including the ACC system, based on accumulated data on a change in driving style when passing through various sections of the previously studied route. Other data related to the route may also be requested. Taken together, the data requested and associated with the card are understood as “data of interest”. Such data can be obtained from various sensors and systems integrated into the vehicle using known methods. Figure 6 presents the process of executing a query, storing and matching with a map of data of interest.

FIG. 6 is a flowchart showing a method of using stored data associated with a previously learned route to modify various set parameters for operating the ACC system on the studied routes.

At step 610, the system determines a work area for mapping locations. As mentioned earlier, the work area is defined by a threshold parallel distance and a threshold perpendicular distance, which can be pre-set or variable. The dimensions of the corresponding work area for comparing the location may not depend on the size of the previously described work area used to study the route (as described with reference to Figs. 2 and 3). In this method, a work area is used to determine whether the current location of the vehicle is close enough to an existing stored location node. In other words, if the width and longitude data for a given vehicle location are within the threshold distance between the longitudinal and transverse lines (i.e., the working area) of the location node studied previously, the system correlates the current location with the location node previously studied. To this end, at step 620, the system may request vehicle position data from GPS satellites. At step 630, the controller 100 may determine whether the obtained current vehicle location is within the work area, i.e. within the threshold latitude and longitude studied previously by the location node. If not, the method proceeds to step 640. If so, the method proceeds to step 650.

At 640, the system 10 may save the location of the vehicle as a new location node. The system can also save the new distance reference associated with this new node. However, instead, the system can use the speed and distance setpoints associated with the immediately preceding location node.

At step 650, system 10 can update distance data associated with nodes located on a previously covered route. In particular, this process can be started if it has been determined that a predetermined threshold distance has been observed. In particular, the controller may receive GPS data from the GPS receiver indicating that the vehicle is in close proximity to the node, for example, less than 1% of the distance between nodes 310a and 310b. After that, the controller 100 can receive data from the radar device about the current distance, and from the storage device, stored data about the distance. The controller 100 may calculate the experimental distance data based on the current distance data and the stored distance data, thereby updating the set distance value. Then, the controller 100 can correlate these experimental distance data with the corresponding GPS data. For example, the controller 100 can calculate the distance test data for node 310a as a sum of 10% of the current distance of 70 m and 90% of the distance saved or studied previously equal to 50 m, as a result of which the set value for the distance in node 310a will be changed to 52 m. The experimental distance data can be stored in a storage device and used in conjunction with the ACC system, as described below, for steps 670 and further on a subsequent trip along this route.

At step 660, the controller 100 may update the speed data associated with nodes along the entire previously learned route. In particular, the controller can receive data on the current speed from the wheel speed sensor, and stored speed data from the storage device. After that, the controller can calculate the experimental data on the vehicle speed based on the current speed and stored speed. Then, the controller 100 may correlate the obtained speed data with the corresponding GPS navigation data. For example, the controller 100 can calculate the speed test data for the node 310a as a sum of 10% of the current speed of 95 km / h and 90% of the speed saved or studied previously of 110 km / h, resulting in a set value for the speed at node 310a will be changed to 108.5 km / h. The experimental speed data can be stored in a storage device and used together with the ACC system, as described below, for steps 670 and further on the subsequent trip along this route.

At step 670, the controller 100 may in real time interpolate a predetermined speed value between two consecutive nodes on a previously traversed route. In particular, the controller can calculate a predetermined speed value based on previously studied speed values at nodes 310a, 310b, and also based on the distance from the vehicle to these nodes. According to the previous example, the vehicle may be located less than 1% of the distance between nodes 310a and 310b. The previously studied speed values at nodes 310a, 310b may be 110 km / h and 80 km / h, respectively. The controller can calculate the speed setpoint as the sum of 1% of 110 km / h and 99% of 80 km / h, obtaining an interpolated speed setpoint of 109.7 km / h.

Similarly, at step 680, the controller 100 can interpolate in real time the set value for the distance to the vehicle in front between two consecutive nodes on a previously traversed route. According to the previous example, the vehicle may be located less than 1% of the distance between nodes 310a and 310b. Previously studied distances at nodes 310a, 310b may be 50 m and 70 m, respectively. The controller can calculate the setpoint for the distance as the sum of 1% of 50 m and 99% of 70 m, obtaining an interpolated setpoint of the distance equal to 50.2 m.This interpolation can allow the ACC system to control the vehicle smoothly, without sudden accelerations and braking.

At step 690, the controller 100 may determine whether the driver has activated the ACC system 10 to provide automatic control of speed and distance to the vehicle in front. If not, the method returns to step 620. If so, the method proceeds to step 700.

At step 700, the controller can check whether the ACC system is on in standby mode. If not, the method immediately proceeds to step 720. If the ACC system is turned on in standby mode, the method proceeds to step 710.

At step 710, the controller 100 can check whether the automatic activation of the ACC system is activated. If not, the method may return back to step 620. If the automatic turn-on function has been activated, the method may go to step 720.

At step 720, the controller 100 can provide the ACC system with current setpoints for vehicle speed and the distance to the vehicle in front, thereby allowing the ACC system to control vehicle mechanisms and devices, such as throttle and / or brake mechanisms. Continuing the example above, the ACC system can use the current distance value of 50.2 m for the next trip on this route. However, if the controller 100 determines that the vehicle is heading to a new work area and, therefore, is driving a route that has not been traveled before, the controller can bind the previously learned distance value to a new node. Similarly, if the controller 100 determines that the vehicle is heading to a new work area, the controller can bind the previously learned speed setpoint to the new node.

In relation to the processes, systems, methods, heuristic algorithms described in this document, etc. it should be understood that, despite the indicated sequence of steps, they can be performed in a different sequence. It should also be understood that some steps may be performed at the same time, and also some steps may be added or omitted. In other words, the process descriptions are presented only as an example of embodiments of the invention and are not considered as limiting the invention.

Therefore, it should be understood that the description is for illustrative purposes and not limitation. Many additional options for implementation and application, other than the examples shown, will become apparent when reading the above description. The scope should not be determined on the basis of the above description, but, on the contrary, should be determined on the basis of the attached claims along with the full scope of equivalents for which this formula is the basis. It is assumed and intended that the described technologies may be developed and improved in the future, and the disclosed systems and methods will be included in similar future implementations. Thus, it should be understood that the application of the invention may be modified and modified.

All terms used in the claims should be understood in their broadest reasonable interpretations and their usual meanings, as is understood by specialists in this field of technology, unless otherwise expressly indicated in the description of the invention. In particular, the use of the words “any”, “given”, “above”, etc. it should be understood as one or more of these elements, unless otherwise specified in the formula.

Claims (8)

1. Adaptive cruise control system for a vehicle, which includes a GPS receiver generating GPS data indicating the current location of the vehicle, a radar device generating data on the current distance to the vehicle in front, and an electronic controller, which is programmed to generate experimental data based on the current and stored distance data, and then correlate the received distance data with GPS data and the stored distance data and apply the experimental data in accordance with the current location of the vehicle, also determine the experimental distance data based on the current distance and distance data stored on the storage device, and also determine the experimental distance data based on the sum of one percent of the current distance and another percentage fractions of the saved distance. 2. The system according to claim 1, which includes an automobile electronic storage device having electronic communication with said controller, the controller being programmed to receive stored distance data from the storage device and store experimental distance data on the storage device. 3. The system of claim 1, wherein the controller is programmed to interpolate a predetermined distance at a point between two stored locations, based on the current location of the vehicle relative to the first and second locations and the received distance data associated with each of these locations. 4. The system of claim 1, wherein the radar device is directed forward and attached to the front of the vehicle. 5. A method for modifying preset values of driving parameters, in which GPS data on the vehicle’s location are received from GPS satellites, current data on the distance to the vehicle in front are received from the radar device and generate experimental distance data based on the current distance data and stored distance data, the experimental distance data being based at least in part on the sum of one percent of the current distance and another percentage of the stored distance then correlate the experimental distance data with the GPS data and apply the experimental data in accordance with the current location of the vehicle. 6. The method according to p. 5, in which generate data about the current speed of the vehicle and experimental data about the speed associated with GPS data, data about the current speed and stored data about the speed. 7. The method according to claim 6, in which the received data about the distance and / or speed is stored on the automobile electronic storage device. 8. The method according to claim 7, in which the experimental speed data is determined based on the current speed data and the stored speed data from the storage device, the obtained experimental distance and / or speed data are linked to stored locations corresponding to points along a previously traveled route .

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