A vehicle driving route planning method, intelligent terminal and storage medium

Abstract

The vehicle driving route planning method disclosed by the present invention reasonably plans the driving route of the current vehicle according to the set travel destination of the vehicle. First, it obtains the number of lanes on the current driving road of the vehicle, and obtains the number of congested vehicles according to the image and server data. Finally, it selects the appropriate driving lane by screening the smallest number of congested vehicles among multiple lanes, which meets the principle of maximizing the utilization of road resources during route planning and can ensure that the obtained congested mileage is more accurate and reasonable. When planning the route, it is also possible to plan the route more reasonably based on the congestion situation on the road network, so that the vehicle driving route is optimal and the time used is the shortest.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle navigation, and particularly to a vehicle driving route planning method, an intelligent terminal, and a storage medium. Background Art

[0002] With the continuous growth of the automobile ownership in large, medium and small cities in China, the contradiction between the limited road resources has been intensifying, and the road traffic congestion coefficient has become increasingly frequent. Urban road traffic managers have to use various channels to relieve traffic congestion. Among them, by obtaining existing traffic parameter resources or adding some detection devices, the road traffic congestion status is obtained, and then the road traffic operation status is purposefully released to drivers to induce drivers to travel, so as to achieve the purpose of relieving road traffic congestion. However, the current congestion coefficient released can only target the overall congestion situation of the area, and it is impossible to accurately understand the congestion situation of each lane on the road, and even impossible to provide a suitable road choice. Therefore, how to select the road with the least driving time to the destination is becoming more and more important. At the same time, based on the detection of the lane congestion coefficient, the overall travel efficiency can be effectively improved and the commuting speed of the road can be increased.

[0003] The prior art mainly calculates the road traffic congestion coefficient through the congestion delay index. By calculating the ratio of the travel time during congestion to the travel time during smooth traffic, the larger the ratio, the more congested the road traffic is. The time taken for the same vehicle to pass through a certain section is obtained through a camera, and the average travel time is calculated by weighted calculation of all vehicles passing through during a period of time, and then the road traffic congestion coefficient is calculated.

[0004] The existing solutions can only obtain the road traffic congestion situation in a certain section, but for actual driving vehicles, it is impossible to be accurate to the specific driving lane. For example, at a certain intersection, the left-turn lane is seriously congested, but the straight or right-turn lanes are unobstructed. However, the existing solutions cannot understand this detailed situation. At the same time, the best driving lane indication cannot be provided for different lanes, resulting in a long queue in a certain lane and no queue in other lanes, resulting in low utilization rate of road resources. Summary of the Invention

[0005] In order to solve the above problems, the present invention proposes a vehicle driving route planning method, an intelligent terminal, and a storage medium.

[0006] The present invention is realized through the following technical solutions:

[0007] A vehicle driving route planning method, comprising:

[0008] Obtaining the driving information, positioning location, and environmental image of the vehicle, and obtaining multiple lanes according to the driving information, the positioning location, and the environmental image;

[0009] Obtain the driving distance and relative speed of the vehicle in a single lane based on the environmental image;

[0010] Obtain the driving time corresponding to a single lane based on the driving distance and relative speed, and select the lane corresponding to the minimum driving time as the driving lane.

[0011] Further, the obtaining of the driving information, positioning location, and environmental image of the vehicle, and the obtaining of multiple lanes based on the driving information, the positioning location, and the environmental image specifically include:

[0012] Obtain the driving route of the vehicle according to the departure location, destination location, and map data of the vehicle;

[0013] Obtain the current driving road of the vehicle according to the driving route and positioning location of the vehicle;

[0014] Obtain the current environmental image and driving information of the vehicle, and judge the number of lanes on the current driving road of the vehicle.

[0015] Further, the obtaining of the driving distance and relative speed of the vehicle in a single lane based on the environmental image specifically includes:

[0016] Obtain the environmental image, driving information, and positioning location;

[0017] Obtain the first distance (D1) between the vehicle and the intersection, and the second distance (D2) between the vehicle and the vehicle in front;

[0018] Collect the environmental image multiple times, and obtain the relative speed (v) of the vehicle according to the collection time interval (t) and the change value (ΔD2) of the second distance in the environmental image: v = ΔD2 / t;

[0019] Obtain the number of vehicles (n) with a vehicle speed less than the preset value in a single lane

[0020] The driving distance (S) is: S = (D1 - D2) + n * 6.

[0021] Further, the second distance specifically is:

[0022] If the vehicle in front of the vehicle and the vehicle are currently in the same lane, then calculate the second distance according to the lens focal length (f), the width (w) of the image of the vehicle in front, and the height (W) of the vehicle in front as:

[0023] D2 = W * f / w

[0024] Further, the second distance specifically is:

[0025] If the leading vehicle of the vehicle is in a different lane from the current vehicle, the second distance is calculated based on the lens focal length (f), the width (w) of the leading vehicle image, the height (W) of the leading vehicle, and the camera tilt angle α as follows:

[0026] D2 = W * f * cosα / w

[0027] An intelligent terminal, comprising: a memory, a processor, and a vehicle driving route planning program stored on the memory and executable on the processor. When the vehicle driving route planning program is executed by the processor, the vehicle driving route planning method as described above is implemented.

[0028] A storage medium stores a vehicle driving route planning program. When the vehicle driving route planning program is executed by a processor, the vehicle driving route planning method as described above is implemented.

[0029] The beneficial effects of the present invention are as follows:

[0030] The vehicle driving route planning method provided by the present invention reasonably plans the driving route of the current vehicle according to the set travel destination of the vehicle. First, the number of lanes on the current driving road of the vehicle is obtained, and the number of congested vehicles is obtained based on images and server data. Finally, the lane with the smallest number of congested vehicles among multiple lanes is selected to choose a suitable driving lane, meeting the principle of maximizing the utilization of road resources during route planning, and ensuring that the obtained congested mileage is more accurate and reasonable. During route planning, the route can also be more reasonably planned based on the congestion situation on the road network, making the vehicle driving route optimal and the travel time shortest. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 is a schematic working flow diagram of the vehicle driving route planning method of the present invention;

[0032] Figure 2 is a schematic diagram of the second distance between the vehicle driving on the road and other leading vehicles in the lane;

[0033] Figure 3 is a schematic diagram of the operating environment of the intelligent terminal of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0034] To make the objectives, technical solutions, and effects of the present invention clearer and more definite, the following further describes the present invention in detail with reference to the accompanying drawings and by way of examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0035] Please refer to Figure 1 and Figure 2 , the present invention discloses a vehicle driving route planning method, including:

[0036] S100, obtain the driving information, positioning location and environmental image of the vehicle, and obtain multiple lanes based on the driving information, the positioning location and the environmental image;

[0037] S200, obtain the driving distance and relative speed of the vehicle within a single lane based on the environmental image;

[0038] S300, obtain the driving time corresponding to a single lane based on the driving distance and relative speed, and select the lane corresponding to the minimum driving time as the driving lane.

[0039] Among them, the driving information of the vehicle is the starting position, destination position and driving route of the vehicle. The driving route in the present invention is planned and calculated based on the starting position and destination position of the vehicle in combination with the server map. In other embodiments of the present invention, an offline map can also be preset in the vehicle to obtain the driving route. The positioning location locates the current driving road of the vehicle through the positioning system in combination with the driving information. The environmental image further verifies and determines the driving road in combination with the positioning location and the driving information. That is:

[0040] S101, obtain the driving route of the vehicle according to the departure position, destination position and map data of the vehicle;

[0041] S102, obtain the current driving road of the vehicle according to the driving route and positioning location of the vehicle;

[0042] S103, obtain the current environmental image and driving information of the vehicle, and judge the number of lanes on the current driving road of the vehicle.

[0043] The environmental image captures an image of the driving road, and multiple drivable lanes are obtained according to the lane lines in the image and the server data. Among them, according to the driving information of the vehicle, for straight-going vehicles, the left-turn lanes in the road are screened out and excluded, and the straight lanes and right-turn lanes are selected as the target lanes. In the subsequent lane data processing, the information within the screened-out lanes is not processed, and only the information within the lanes that have been selected as the target lanes is processed.

[0044] After multiple lanes are obtained, the image acquisition device and data processing device on the vehicle calculate and process the driving parameters of the vehicle.

[0045] Specifically:

[0046] S201, obtain the environmental image, driving information and positioning location;

[0047] S202, obtain the first distance (D1) between the vehicle and the intersection, and the second distance (D2) between the vehicle and the vehicle in front;

[0048] S203. Collect environmental images multiple times, and obtain the relative speed (v) of the vehicle based on the collection time interval (t) and the change value (ΔD2) of the second distance in the environmental images: v = ΔD2 / t;

[0049] S204. Obtain the number (n) of vehicles with a vehicle speed less than a preset value in a single lane

[0050] The driving distance (S) is: S = (D1 - D2) + n * 6.

[0051] If the vehicle speed is less than the preset value, it is determined that the vehicle stops and waits at the current intersection. During the waiting process of the vehicle at the intersection, the vehicle has a short displacement and the speed for adjusting the vehicle position is below the preset value, which does not affect the judgment of the vehicle as a congested vehicle.

[0052] Among them, the specific calculation method of the second distance is as follows:

[0053] If the vehicle in front of the vehicle and the vehicle are currently in the same lane, calculate the second distance according to the lens focal length (f), the width (w) of the image of the vehicle in front, and the height (W) of the vehicle in front:

[0054] D2 = W * f / w

[0055] If the vehicle in front of the vehicle and the vehicle are currently in different lanes, calculate the second distance according to the lens focal length (f), the width (w) of the image of the vehicle in front, the height (W) of the vehicle in front, and the camera tilt angle α:

[0056] D2 = W * f * cosα / w

[0057] Please refer to Figure 3 , based on the above method, the present invention also discloses an intelligent terminal, and the intelligent terminal includes: a memory 10, a processor 20, and a vehicle driving route planning program 11 stored on the memory 10 and executable on the processor 20. When the vehicle driving route planning program 11 is executed by the processor 20, the vehicle driving route planning method as described above is implemented.

[0058] The present invention also provides a storage medium, and the storage medium stores a vehicle driving route planning program. When the vehicle driving route planning program is executed by a processor, the vehicle driving route planning method as described above is implemented.

[0059] The vehicle driving route planning method provided by the present invention reasonably plans the driving route of the current vehicle according to the travel destination set by the vehicle. First, obtain the number of lanes on the current driving road of the vehicle, and obtain the number of congested vehicles according to the image and server data. Finally, select the appropriate driving lane by screening the smallest number of congested vehicles among multiple lanes, which meets the principle of maximizing the utilization of road resources during route planning and can ensure that the obtained congested mileage is more accurate and reasonable. When planning the route, it is also possible to more reasonably plan the route according to the congestion situation on the road network, so that the vehicle driving route is optimal and the travel time is the shortest.

[0060] It should be understood that the application of the present invention is not limited to the above examples. For those of ordinary skill in the art, improvements or transformations can be made according to the above description, and all such improvements and transformations should fall within the protection scope of the appended claims of the present invention.

Claims

1. A vehicle driving route planning method, characterized in that, Including: Obtain the driving information, positioning location, and environmental image of the vehicle, and obtain multiple lanes based on the driving information, the positioning location, and the environmental image; The environmental image captures an image of the driving road. Obtain multiple drivable lanes based on the lane lines in the image and server data. Among them, according to the driving information of the vehicle, for a straight-going vehicle, the left-turn lane in the road is filtered out and excluded, and the straight lane and the right-turn lane are selected as target lanes; in subsequent lane data processing, the information within the filtered-out lanes is not processed, and only the information within the lanes that have been selected as target lanes is processed; Obtain the driving distance and relative speed of the vehicle within a single lane according to the environmental image, specifically including: obtain the environmental image, driving information, and positioning location; obtain the first distance D1 between the vehicle and the intersection, and the second distance D2 between the vehicle and the vehicle in front; collect the environmental image multiple times, and obtain the relative speed v of the vehicle according to the collection time interval t and the change value ΔD2 of the second distance in the environmental image: v = ΔD2 / t; obtain the number n of vehicles within a single lane with a vehicle speed less than a preset value. The driving distance S is: S = (D1 - D2) + n * 6; Obtain the driving time corresponding to a single lane according to the driving distance and relative speed, and select the lane corresponding to the minimum driving time as the driving lane; The obtaining of the driving information, positioning location, and environmental image of the vehicle, and the obtaining of multiple lanes based on the driving information, the positioning location, and the environmental image specifically include: obtain the driving route of the vehicle according to the departure location, destination location, and map data of the vehicle; obtain the current driving road of the vehicle according to the driving route and positioning location of the vehicle; obtain the current environmental image and driving information of the vehicle, and judge the number of lanes of the current driving road of the vehicle; The second distance is specifically: if the vehicle in front of the vehicle is in the same lane as the vehicle currently, then calculate the second distance according to the lens focal length f, the width w of the image of the vehicle in front, and the height W of the vehicle in front: D2 = W * f / w; The second distance is specifically: if the vehicle in front of the vehicle is in a different lane from the vehicle currently, then calculate the second distance according to the lens focal length f, the width w of the image of the vehicle in front, the height W of the vehicle in front, and the camera inclination angle α: D2 = W * f * cosα / w.

2. An intelligent terminal, characterized in that, The intelligent terminal includes: a memory, a processor, and a vehicle driving route planning program stored on the memory and executable on the processor. When the vehicle driving route planning program is executed by the processor, it implements the vehicle driving route planning method as described in claim 1.

3. A storage medium, characterized in that, The storage medium stores a vehicle driving route planning program. When the vehicle driving route planning program is executed by the processor, it implements the vehicle driving route planning method as described in claim 1.

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