Method for controlling a navigational travel of a vehicle, assistance system and vehicle

Abstract

This application relates to a method for controlling the navigation of a vehicle (1), the method comprising: generating shadow prediction information on each candidate navigation route from the current position of the vehicle (1) to the destination based at least on weather forecast information, trip departure time, sun position information and map information; determining the final navigation route from the current position of the vehicle (1) to the destination based on the shadow prediction information of each candidate navigation route and the trip duration; and, while controlling the vehicle to travel along the determined final navigation route, detecting actual shadow information of the road ahead of the vehicle, and adjusting the vehicle's assisted driving control parameters based at least on the shadow prediction information and the detected actual shadow information. According to this application, while ensuring the vehicle's travel efficiency, the energy consumption of the vehicle's air conditioning is reduced as much as possible, effectively improving the vehicle's driving range, and improving the vehicle's cabin temperature comfort and driving experience.

Description

Technical Field

[0001] This application relates to the field of driver assistance, and more particularly to a method for controlling the navigation of a vehicle, a driver assistance system, a vehicle including the driver assistance system according to this application, and a computer program product. Background Technology

[0002] Most vehicles are now equipped with in-vehicle air conditioning, and especially in hot weather, the usage time and load of these air conditioners increase significantly. This not only increases the vehicle's energy consumption and carbon emissions but also shortens its driving range. Therefore, reducing the energy consumption of in-vehicle air conditioning in hot weather has become a pressing technical challenge. Summary of the Invention

[0003] The purpose of this application is to provide a method for controlling the navigation of a vehicle, a driver assistance system, a vehicle including the driver assistance system according to this application, and a computer program product, to at least partially solve the problems in the prior art.

[0004] According to a first aspect of this application, a method for controlling the navigation and driving of a vehicle is provided, the method comprising: - It can generate shadow prediction information on various candidate navigation routes from the vehicle's current location to the destination based on weather forecast information, trip departure time, sun position information and map information; - Determine the final navigation route from the vehicle's current location to the destination based on the shadow prediction information and trip duration of each candidate navigation route; - While controlling the vehicle to travel along the determined final navigation route, detect the actual information of shadows on the road ahead of the vehicle, and adjust the vehicle's assisted driving control parameters based at least on the shadow prediction information and the detected actual shadow information.

[0005] The core concept of this application is to fully consider the shadow prediction information of each candidate navigation route when planning the final navigation route of the vehicle, maximize the shadow occlusion effect of the navigation route while taking into account the travel time of the navigation route, and incorporate the shadow prediction information and the detected actual shadow information into the decision factors of the vehicle's assisted driving control during the process of controlling the vehicle to drive along the determined final navigation route. In this way, while ensuring the vehicle's travel efficiency, the energy consumption of the vehicle's air conditioning is reduced as much as possible, effectively improving the vehicle's driving range, and improving the vehicle's cabin temperature comfort and driving experience.

[0006] According to an optional embodiment of this application, the final navigation route of a vehicle can be determined based on the shadow prediction information and travel duration of each candidate navigation route in such a way that the sum of the product of the shadow occlusion effect parameter evaluated based on the shadow prediction information of the final navigation route and a first weighting factor and the product of the travel duration of the final navigation route and a second weighting factor is minimized, wherein the first weighting factor and the second weighting factor are particularly adjustable.

[0007] According to another optional embodiment of this application, the shadow prediction information includes one or more of the following information of the predicted shadow area: location information, geometric information, shadow intensity information, and confidence information, etc.

[0008] According to another optional embodiment of this application, the actual shadow information includes one or more of the following information of the detected shadow area: location information, geometric information, and shadow intensity information, etc.

[0009] According to another optional embodiment of this application, the map information may include one or more of the following: building information, vegetation information, and tunnel information for each location area in the map.

[0010] According to another optional embodiment of this application, the vehicle's assisted driving control parameters may include one or more of the following parameters: target driving lane, lane change position, parking position, driving speed, and vehicle air conditioning power, etc.

[0011] According to another optional embodiment of this application, when a traffic light turns red within a predetermined distance range in front of the vehicle, the vehicle's speed can be adjusted to extend the duration of the vehicle's stay within the predicted or detected shadow area.

[0012] According to another optional embodiment of this application, when the vehicle is parked, the safe distance between the vehicle and the vehicle in front can be reduced, so that the vehicle body area within the predicted shadow area or the detected shadow area is maximized.

[0013] According to another optional embodiment of this application, the target lane and lane-changing position of the vehicle can be adjusted based on the shadow prediction information, the actual shadow information detected, and the detected road traffic flow information, so as to extend the dwell time of the vehicle in the predicted shadow area or the detected shadow area, and to perform the lane change of the vehicle when the road traffic flow is less than a pre-given flow threshold.

[0014] According to another optional embodiment of this application, when the vehicle is parked in a predicted or detected shaded area, the vehicle's onboard air conditioning power can be reduced, and when the vehicle starts up in the shaded area and drives away from the shaded area, the vehicle's onboard air conditioning power can be increased.

[0015] According to another optional embodiment of this application, the vehicle's air conditioning power can be reduced when the vehicle is approaching a shaded area with a length greater than a predetermined length threshold, and the vehicle's air conditioning power can be increased when the vehicle is leaving a shaded area with a length greater than a predetermined length threshold.

[0016] According to a second aspect of this application, a driving assistance system is provided, which may include the following components: - An environmental perception unit, which is configured to detect actual information about shadows on the road ahead of the vehicle; - A control unit for performing the method according to this application.

[0017] According to another optional embodiment of this application, the control unit may be integrated into the environment perception unit, and an end-to-end model may be deployed in the control unit to at least assist in the execution of the method according to this application through the end-to-end model, wherein the end-to-end model includes, for example, a vision-language-action model, and wherein the environment perception unit includes, for example, one or more of the following devices: vehicle camera, millimeter-wave radar, and lidar.

[0018] According to a third aspect of this application, a vehicle is provided that may include a driver assistance system according to this application.

[0019] According to a fourth aspect of this application, a computer program product, such as a computer-readable program carrier, is provided, comprising or storing computer program instructions that, when executed by a processor, at least assist in implementing the steps of the method described in this application. Attached Figure Description

[0020] The principles, features, and advantages of this application can be better understood by describing it in more detail below with reference to the accompanying drawings. The drawings show: Figure 1 A flowchart illustrating a method for controlling the navigation of a vehicle according to an exemplary embodiment of this application is shown. Figure 2 A schematic diagram of a driving scenario according to an exemplary embodiment of this application is shown; Figure 3 A schematic diagram of a driving scenario according to another exemplary embodiment of this application is shown; Figure 4A schematic diagram of a driving scenario according to another exemplary embodiment of this application is shown; Figure 5 A schematic diagram of a vehicle according to an exemplary embodiment of this application is shown. Detailed Implementation

[0021] To make the technical problems to be solved, the technical solutions, and the beneficial technical effects of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and several exemplary embodiments. It should be understood that the specific embodiments described herein are only for explaining this application and are not intended to limit the scope of protection of this application.

[0022] Figure 1 A flowchart illustrating a method for controlling the navigation and driving of a vehicle according to an exemplary embodiment of this application is shown. The following exemplary embodiments describe the method according to this application in more detail.

[0023] The method can be implemented by the driver assistance system 10 equipped in vehicle 1. Embodiments of this application propose that the cabin temperature of vehicle 1 can be reduced by controlling vehicle 1 to drive as far as possible in the shaded areas formed by roadside buildings or vegetation. This reduces the energy consumption of vehicle 1's air conditioning in hot weather without increasing vehicle hardware costs. Therefore, the shaded areas on vehicle 1's navigation route can be predicted, and the predicted shaded areas can be fully considered when planning vehicle 1's navigation route.

[0024] like Figure 1As shown, the method may include steps S1 to S3. In step S1, shadow prediction information can be generated on each candidate navigation route from the current location of vehicle 1 to the destination based on weather forecast information, trip departure time, solar position information, and map information. When planning a navigation route from the current location of vehicle 1 to the destination, the vehicle navigation system can typically plan multiple candidate navigation routes. Weather information along each segment of the candidate navigation route from the trip departure time can be extracted from the weather forecast information. This change information includes changes in weather type (e.g., sunny or cloudy) over time, temperature changes over time, etc. The map information may include one or more of the following: building information (including building location and size information), vegetation information (including vegetation location and type information), tunnel information (including tunnel location and length information), overpass information (including overpass location, height, and length information), etc. The solar position information includes, for example, information on changes in the solar altitude angle over time. For example, under clear weather conditions, based on the sun's position information and map information, it is possible to predict the shadow prediction information of the shadow area of ​​each road segment at the estimated time when the vehicle travels to each road segment of the planned candidate navigation route.

[0025] In this application, the shaded area refers to a road surface area receiving less light intensity than the surrounding surface area, such as a road surface area covered by the shadow of adjacent buildings, a road surface area covered by light spots from tree leaves, or a tunnel area. The shadow prediction information may include one or more of the following information about the predicted shadow area: location information, geometric information, shadow intensity information, and confidence information. Here, the location information indicates the relative position of the predicted shadow area within the road area at the estimated time when vehicle 1 arrives at the predicted shadow area; the geometric information indicates the shape or size of the predicted shadow area at the estimated time when vehicle 1 arrives at the predicted shadow area; the shadow intensity information indicates the light intensity or brightness of the predicted shadow area at the estimated time when vehicle 1 arrives at the predicted shadow area; and the confidence information indicates the degree of confidence in the predicted shadow area. For example, based on the location and height information of buildings in the map, combined with the change of the local sun's altitude angle over time, the location, geometric information, shadow intensity, and confidence level of the shadow area formed by the building when a vehicle travels to a road segment near the building can be predicted; based on the location and type information of vegetation in each segment of the candidate navigation route, combined with the change of the local sun's altitude angle over time, the location, geometric information, shadow intensity, and confidence level of the shadow area formed by the vegetation when a vehicle travels to the corresponding road segment can be predicted; based on the location, height, and length information of overpasses in each segment of the candidate navigation route, combined with the change of the local sun's altitude angle over time, the location, geometric information, shadow intensity, and confidence level of the shadow area formed by the overpass when a vehicle travels to the corresponding road segment can be predicted; based on the location and length information of tunnels, combined with the change of the local sun's altitude angle over time, the shadow intensity and confidence level of the shadow area in the tunnel in each segment of the candidate navigation route can be predicted, and so on.

[0026] In step S2, the final navigation route from the current location of vehicle 1 to its destination can be determined based on the shadow prediction information and travel duration of each candidate navigation route. When selecting the final navigation route for vehicle navigation from the candidate routes, it is necessary to consider not only the travel duration of each candidate route but also the shadow occlusion effect of each candidate route. The shadow occlusion effect parameter of each candidate route can be evaluated based on the shadow prediction information. In this application, the shadow occlusion effect parameter is a quantitative parameter used to represent the occlusion effect of the shadow area of ​​the candidate navigation route on the vehicle. It can be comprehensively evaluated based on the location information, geometric information, shadow intensity information, and confidence information of the shadow areas formed by buildings, vegetation, tunnels, overpasses, etc., in each candidate navigation route. The larger the shadow occlusion effect parameter, the better the occlusion effect of the shadow area of ​​the candidate navigation route on the vehicle. Here, the final navigation route for vehicle 1 can be determined based on the shadow prediction information and travel duration of each candidate navigation route in the following manner, such that the sum of the product of the shadow occlusion effect parameter evaluated based on the shadow prediction information of the final navigation route and the first weighting factor, and the product of the travel duration of the final navigation route and the second weighting factor, is minimized. The first weighting factor and the second weighting factor can be adjusted according to the user's actual needs to avoid affecting the driving experience due to frequent lane changes or late lane change positions. Specifically, when the user considers the shadow occlusion effect of the navigation route to be more important, the first weighting factor can be increased; when the user considers the travel duration of the navigation route to be more important, the second weighting factor can be increased.

[0027] In step S3, during the process of controlling the vehicle 1 to travel along the determined final navigation route, the actual shadow information of the road ahead of the vehicle 1 can be detected, and the assisted driving control parameters of the vehicle 1 can be adjusted at least based on the shadow prediction information and the detected actual shadow information. After determining the final navigation route, the vehicle 1 can be controlled to travel along the determined final navigation route, and during the travel, the actual shadow information of the road ahead of the vehicle 1 can be detected by the environmental perception unit 11 of the vehicle 1. The actual shadow information may include one or more of the following information of the detected shadow area: position information, geometric information, and shadow intensity information, etc. Here, the position information is used to indicate the relative position of the shadow area detected at the current moment in the road area; the geometric information is used to indicate the shape or size of the shadow area detected at the current moment; and the shadow intensity information is used to indicate the light intensity or brightness of the shadow area detected at the current moment.

[0028] During the process of controlling the vehicle 1 to travel along the determined final navigation route, the vehicle 1's assisted driving control parameters can be adjusted by the vehicle 1's control unit 12 based at least on the shadow prediction information and the detected actual shadow information. The vehicle 1's assisted driving control parameters may include one or more of the following parameters: target driving lane, lane change position, parking position, driving speed, and vehicle air conditioning power, etc.

[0029] For example, the environment perception unit 11 may include one or more of the following devices: an in-vehicle camera, millimeter-wave radar, and lidar, etc. Optionally, the control unit 12 of the vehicle 1 may be integrated into the environment perception unit 11, particularly into the in-vehicle camera, and an end-to-end model may be deployed in the control unit 12. This end-to-end model can at least assist in executing the various steps of the method according to this application. The end-to-end model may include, for example, a Vision-Language-Action Model (VLA model), which can take images / videos and natural language commands as input and directly output action commands executable by actuators or intelligent agents. This reduces the accumulation of errors in the intermediate links from environment perception and route planning to actuator control, significantly improving the scene adaptability of vehicle assisted driving control.

[0030] Next, combined Figures 2 to 4 The diagrams shown in the figure illustrate the various driving scenarios during the journey along the determined final navigation route, and provide a detailed explanation of the adjustment process of the driver assistance control parameters of vehicle 1.

[0031] like Figure 2 This diagram illustrates a driving scenario according to an exemplary embodiment of the present application. Vehicle 1, while driving on a road, detects a traffic light 22 within a predetermined distance ahead, and the traffic light 22 is red. A building 21 is located on the right side of the road, forming a shadow area 211 schematically marked with a dashed box under the current sunlight. When there are no other vehicles nearby, the speed of vehicle 1 can be adjusted, particularly by reducing the speed as vehicle 1 approaches and enters the predicted or detected shadow area 211, thereby maximizing the duration of vehicle 1's stay within the shadow area 211. When road traffic is light, the vehicle 1's position within the shadow area 211 can also be controlled. Figure 2The vehicle 1 stops at the marked position 1' while waiting at a red light, thus avoiding the need for the vehicle 1 to wait in direct sunlight before the stop line, effectively reducing the cabin temperature of the vehicle 1 while waiting at a red light. When the vehicle 1 is stopped within the predicted or detected shaded area 211, the power of the vehicle 1's air conditioning can be reduced to decrease energy consumption during the waiting period in the shaded area 211 and prevent the cabin temperature of the vehicle 1 from dropping too low. When the red light ends, as the vehicle starts and leaves the shaded area, the power of the vehicle 1's air conditioning can be increased to automatically restore the cooling capacity of the air conditioning to normal levels.

[0032] Furthermore, when vehicle 1 is parked, the safe distance between vehicle 1 and the vehicle in front can be reduced, thereby maximizing the vehicle body area of ​​vehicle 1 within the predicted or detected shadow area. For example... Figure 3 This illustration shows a driving scenario according to another exemplary embodiment of the present application. During the process of controlling vehicle 1 to approach and enter the shaded area 211 formed by building 21 under the current sunlight, it is detected that a first vehicle 31 and a second vehicle 32 are stopped at the stop line waiting for a red light, and the second vehicle 32 is stopped within the shaded area 211. When vehicle 1 is stopped waiting for the red light, the safe distance between vehicle 1 and the second vehicle 32 can be reduced if necessary—the stopping position of the vehicle within the shaded area 211 is marked as 1', maximizing the vehicle body area of ​​vehicle 1' within the shaded area 211 to minimize the area of ​​vehicle 1' exposed to sunlight.

[0033] like Figure 4 This diagram illustrates a driving scenario according to another exemplary embodiment of the present application. Vehicle 1 is traveling on a two-lane road, with the road curving to the right at a certain distance in front of vehicle 1. A building 22 is located on the right side of the road, forming a shadow area 221 schematically marked with a dashed box under the current sunlight. While traveling on a straight road, vehicle 1 can detect road traffic flow information ahead via an environmental perception unit 11, and adjust its target lane and lane-changing position based on the predicted shadow information, the actual detected shadow information, and the detected road traffic flow information. This extends the duration of vehicle 1's stay within the predicted or detected shadow area, and executes a lane change when the road traffic flow is less than a pre-defined flow threshold. Figure 4In driving scenarios, on straight roads, vehicle 1 can be controlled to approach and enter the shaded area 221 from the right lane, thereby maximizing the duration of vehicle 1's stay within the shaded area 221. If the length of the shaded area 221 exceeds a predetermined length threshold, the vehicle's air conditioning power can be reduced as vehicle 1 approaches the shaded area 221 to minimize energy consumption and prevent the vehicle's cabin temperature from dropping too low. Conversely, as vehicle 1 leaves the shaded area 221, the vehicle's air conditioning power can be increased to automatically restore its cooling capacity to normal levels. After vehicle 1 leaves the shaded area 221, when the environmental perception unit 11 detects that there is only a third vehicle 33 traveling at a relatively far distance in the left lane, it can be determined that the road traffic flow is less than a pre-given flow threshold, and vehicle 1 is controlled to change lanes and enter the left lane after leaving the shaded area 221. The position of the vehicle in the left lane is marked as 1', and vehicle 1' continues to be controlled to complete the right turn process along the left lane.

[0034] According to embodiments of this application, when planning the final navigation route of a vehicle, the shadow prediction information of each candidate navigation route is fully considered. While taking into account the travel time of the navigation route, the shadow occlusion effect of the navigation route is maximized. In the process of controlling the vehicle to drive along the determined final navigation route, the shadow prediction information and the detected actual shadow information are incorporated into the decision factors of the vehicle's assisted driving control. This ensures the vehicle's travel efficiency while minimizing the energy consumption of the vehicle's air conditioning, effectively improving the vehicle's range, and enhancing the vehicle's cabin temperature comfort and driving experience.

[0035] In addition, it should be noted that the step numbers described herein do not necessarily represent the order of steps, but are merely a reference numeral. The order may be changed depending on the specific circumstances, as long as the technical objective of this application can be achieved.

[0036] Figure 5 A schematic diagram of a vehicle according to an exemplary embodiment of this application is shown. Figure 5 As shown, vehicle 1 is equipped with a driver assistance system 10, which may include the following components: - An environmental perception unit 11 is configured to detect actual information about shadows on the road ahead of the vehicle 1, wherein the environmental perception unit 11 includes, for example, one or more of the following devices: an onboard camera, a millimeter-wave radar, and a lidar, etc. - Control unit 12, which is used to perform the method according to this application.

[0037] Optionally, the control unit 12 may be integrated into the environment sensing unit 11, and an end-to-end model may be deployed in the control unit 12 to at least assist in the execution of the method according to this application, wherein the end-to-end model includes, for example, a vision-language-action model.

[0038] It should be understood that the terms “first,” “second,” “third,” etc., used in this document are for descriptive purposes only and should not be construed as indicating or implying relative importance, nor should they be construed as implicitly specifying the number of technical features indicated.

[0039] If an embodiment includes an "and / or" association between a first feature and a second feature, it should be interpreted as follows: according to one implementation, the embodiment has not only the first feature but also the second feature; according to another implementation, the embodiment has either only the first feature or only the second feature.

[0040] Although specific embodiments have been described above, these embodiments are not intended to limit the scope of this application, even when only a single embodiment is described with respect to a particular feature. The feature examples provided in this application are intended for illustrative purposes and not for limitation, unless otherwise stated. In practice, multiple features may be combined with each other as needed and where technically feasible. Various substitutions, modifications, and alterations are also conceived without departing from the spirit and scope of this application.

Claims

1. A method for controlling the navigation of a vehicle (1), the method comprising: Based on weather forecast information, trip departure time, sun position information and map information, shadow prediction information is generated on each candidate navigation route from the current position of the vehicle (1) to the trip destination; The final navigation route from the current position of the vehicle (1) to the destination is determined based on the shadow prediction information and travel duration of each candidate navigation route; During the process of controlling the vehicle (1) to travel along the determined final navigation route, the actual information of the shadow of the road ahead of the vehicle (1) is detected, and the assisted driving control parameters of the vehicle (1) are adjusted based at least on the shadow prediction information and the detected actual shadow information.

2. The method of claim 1, wherein, The final navigation route of the vehicle (1) is determined based on the shadow prediction information and travel duration of each candidate navigation route in such a way that the sum of the product of the shadow occlusion effect parameter evaluated based on the shadow prediction information of the final navigation route and the first weight factor and the product of the travel duration of the final navigation route and the second weight factor is minimized, wherein the first weight factor and the second weight factor are particularly adjustable.

3. The method according to any of the preceding claims, wherein, The shadow prediction information includes one or more of the following information about the predicted shadow area: location information, geometric information, shadow intensity information, and confidence information; and / or The actual shadow information includes one or more of the following information about the detected shadow area: location information, geometric information, and shadow intensity information.

4. The method according to any one of the preceding claims, wherein, The map information includes one or more of the following: building information, vegetation information, tunnel information for each location area on the map; and / or The assisted driving control parameters of the vehicle (1) include one or more of the following parameters: target driving lane, lane change position, parking position, driving speed and vehicle air conditioning power.

5. The method according to any one of the preceding claims, wherein, When a traffic light turns red within a predetermined distance in front of the vehicle (1), the speed of the vehicle (1) is adjusted to extend the duration of the vehicle (1) in the predicted or detected shadow area. and / or When the vehicle (1) is parked, the safe distance between the vehicle (1) and the vehicle in front is reduced so that the vehicle body area of ​​the vehicle (1) is maximized within the predicted or detected shadow area.

6. The method according to any one of the preceding claims, wherein, Based on the shadow prediction information, the detected shadow actual information and the detected road traffic flow information, the target driving lane and lane change position of the vehicle (1) are adjusted so as to extend the dwell time of the vehicle (1) in the predicted shadow area or the detected shadow area, and the lane change of the vehicle (1) is performed when the road traffic flow is less than a pre-given flow threshold. and / or When the vehicle (1) is parked in the predicted or detected shaded area, the onboard air conditioning power of the vehicle (1) is reduced, and when the vehicle starts up and leaves the shaded area, the onboard air conditioning power of the vehicle (1) is increased, or As the vehicle (1) approaches a shaded area with a length greater than a predetermined length threshold, the vehicle's air conditioning power is reduced, and as the vehicle (1) leaves a shaded area with a length greater than a predetermined length threshold, the vehicle's air conditioning power is increased.

7. A driver assistance system (10), the driver assistance system (10) comprising the following components: An environmental perception unit (11) is configured to detect actual information about the shadow of the road ahead of the vehicle (1); Control unit (12) for performing the method according to any one of the preceding claims.

8. The driver assistance system (10) according to claim 7, wherein, The control unit (12) is integrated in the environment sensing unit (11), and an end-to-end model is deployed in the control unit (12) to at least assist in performing the method according to any one of the preceding claims, wherein the end-to-end model includes, for example, a vision-language-action model, and wherein the environment sensing unit (11) includes, for example, one or more of the following devices: an in-vehicle camera, a millimeter-wave radar, and a lidar.

9. A vehicle (1) comprising a driver assistance system (10) according to claim 7 or 8.

10. A computer program product, such as a computer-readable program carrier, comprising or storing computer program instructions that, when executed by a processor, at least auxiliaryly implement the steps of the method according to any one of claims 1 to 6.

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