Predictive cruise control method and system based on multi-source road information dynamic optimization

Abstract

The invention belongs to the technical field of vehicle control, and particularly relates to a predictive cruise control method and system based on multi-source road information dynamic optimization. Comprising the steps of obtaining multi-source heterogeneous data of a planned driving road of a vehicle; taking the minimum value of the road speed limit, the turning speed limit and the traffic light signal speed limit of the planned driving road of the vehicle as a current basic speed limit control value; the basic speed limit control value is retrieved, the driving working condition position of acceleration and then deceleration is recognized, and the maximum constant driving speed within the distance of the driving working condition of acceleration and then deceleration is solved; and optimizing the basic speed limit control value of the corresponding road section by using the maximum constant driving speed of each road section to obtain the optimized vehicle speed of each road section. According to the method, the dynamic traffic information and the static road characteristic parameters are fused, and the processing of road short-distance acceleration and deceleration working conditions is considered, so that the optimal vehicle speed planning strategy is realized, and the driving safety and the energy utilization efficiency are improved.

Description

Technical Field

[0001] This invention belongs to the field of vehicle control technology, and particularly relates to a predictive cruise control method and system based on dynamic optimization of multi-source road information. Background Technology

[0002] Traditional cruise control systems mainly include two types: constant speed cruise (CC) and adaptive cruise (ACC). Constant speed cruise control can only maintain a preset, constant speed and cannot adjust according to changes in road conditions; while adaptive cruise control can adjust its own speed based on the speed of the vehicle in front, it still has the following limitations: 1) It only considers the relative motion information of the vehicle in front, lacking utilization of the overall road conditions. For example, it cannot know in advance the curvature of the curve ahead, changes in road speed limits, etc., causing the vehicle to react only when approaching these special road sections, increasing driving risks; 2) Adopting a reactive control strategy, which adjusts the vehicle's speed in real time based on changes in the speed of the vehicle in front, can easily lead to frequent acceleration and deceleration. Frequent acceleration and deceleration not only affect ride comfort but also increase fuel consumption or energy loss. 3) It cannot predict changes in road conditions ahead, such as traffic lights and curves. This makes it impossible for the vehicle to plan its speed in advance, hindering more intelligent and efficient cruise control. Summary of the Invention

[0003] To overcome the shortcomings of the prior art, this invention provides a predictive cruise control method and system based on dynamic optimization of multi-source road information. By integrating dynamic traffic information and static road characteristic parameters, and considering the processing of short-distance acceleration and deceleration conditions, it achieves an optimized vehicle speed planning strategy, thereby improving driving safety and energy efficiency.

[0004] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions: The first aspect of this invention provides a predictive cruise control method based on dynamic optimization of multi-source road information.

[0005] The predictive cruise control method based on dynamic optimization of multi-source road information includes the following steps: Acquire multi-source heterogeneous data of the vehicle's planned driving route, preprocess it, and calculate the turning speed limit; The minimum value among the road speed limit, turning speed limit and traffic light signal speed limit of the planned route for the vehicle is used as the current base speed limit control value; Based on whether the basic speed limit control value has changed, the planned driving route for vehicles is divided into several road segments; The basic speed limit control value is retrieved to identify the driving conditions where acceleration precedes deceleration, and the maximum constant driving speed within the corresponding acceleration-deceleration driving condition distance is calculated. The maximum constant driving speed of each road segment is used to optimize the basic speed limit control value of the corresponding road segment, thereby obtaining the optimized speed of each road segment and generating the final road speed planning curve.

[0006] A second aspect of the present invention provides a predictive cruise control system based on dynamic optimization of multi-source road information.

[0007] A predictive cruise control system based on dynamic optimization of multi-source road information includes: The data acquisition and preprocessing module is configured to: acquire multi-source heterogeneous data of the vehicle's planned driving route, perform preprocessing, and calculate the turning speed limit; The basic speed limit control value calculation module is configured to use the minimum value among the road speed limit, turning speed limit and traffic light signal speed limit of the planned driving route of the vehicle as the current basic speed limit control value; The road segment division module is configured to divide the planned driving route of the vehicle into several road segments based on whether the basic speed limit control value has changed; The maximum constant driving speed solution module is configured to: retrieve the basic speed limit control value, identify the driving condition position where acceleration precedes deceleration, and solve for the maximum constant driving speed within the corresponding acceleration precedes deceleration driving condition distance; The optimization module is configured to: use the maximum constant driving speed of each road segment to optimize the basic speed limit control value of the corresponding road segment, obtain the optimized speed of each road segment, and generate the final road speed planning curve. A third aspect of the present invention provides a computer-readable storage medium having a program stored thereon that, when executed by a processor, implements the steps of the predictive cruise control method based on dynamic optimization of multi-source road information as described in the first aspect of the present invention.

[0008] A fourth aspect of the present invention provides an electronic device including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the predictive cruise control method based on dynamic optimization of multi-source road information as described in the first aspect of the present invention.

[0009] The above one or more technical solutions have the following beneficial effects: This invention, on the one hand, fuses multi-source data, comprehensively integrating dynamic traffic information and static road characteristic parameters to determine a basic speed limit control value. On the other hand, it also considers the handling of short-distance acceleration and deceleration conditions on the road. By combining acceleration and deceleration obtained from road slope signals, the distance between the start of acceleration and the completion of deceleration, the speed limit before acceleration, and the speed limit after deceleration, a maximum constant driving speed within the acceleration-deceleration driving condition is calculated. The determined basic speed limit control value is then optimized to obtain the final optimized speed. This achieves an optimized speed planning strategy, thereby improving driving safety and energy efficiency.

[0010] When calculating the turning speed limit, this invention takes the minimum value R of all turning radii, including road curves and roundabout curves, and then calculates the upper limit of the physical safe speed of the vehicle under the minimum turning radius R, which is used as the turning speed limit of the current road section, thus maximizing safety.

[0011] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0012] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0013] Figure 1 This is a flowchart of the method in Example 1. Detailed Implementation

[0014] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0015] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0016] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0017] Example 1 This embodiment discloses a predictive cruise control method based on dynamic optimization of multi-source road information. By fusing dynamic traffic information and static road characteristic parameters, it achieves an optimal vehicle speed planning strategy, thereby improving driving safety and energy efficiency.

[0018] like Figure 1As shown, the predictive cruise control method based on dynamic optimization of multi-source road information includes the following steps: Acquire multi-source heterogeneous data of the vehicle's planned driving route, preprocess it, and calculate the turning speed limit; The minimum value among the road speed limit, turning speed limit and traffic light signal speed limit of the planned route for the vehicle is used as the current base speed limit control value; Based on whether the basic speed limit control value has changed, the planned driving route for vehicles is divided into several road segments; The basic speed limit control value is retrieved to identify the driving conditions where acceleration precedes deceleration, and the maximum constant driving speed within the corresponding acceleration-deceleration driving condition distance is calculated. The maximum constant driving speed of each road segment is used to optimize the basic speed limit control value of the corresponding road segment, thereby obtaining the optimized speed of each road segment and generating the final road speed planning curve.

[0019] The technical solution of this embodiment will be explained in detail below.

[0020] 1. Information collection and reconstruction.

[0021] Acquires and processes multiple input signals from the ADAS system, including: Static road signals include road speed limits, turning radii, roundabouts, highway exit locations, and gradients; Dynamic traffic signals include traffic light signals and red light waiting times.

[0022] Synchronizing and unifying the format of this multi-source heterogeneous information provides standardized data for subsequent processing.

[0023] 2. Information preprocessing module.

[0024] Standardized data is used to preset and calculate parameters, providing basic data for subsequent vehicle speed planning.

[0025] 1) Calculation of turning speed limit: Take the minimum value R of all turning radius signals (including road curves and roundabout turning signals, etc.), and based on the friction circle theory, use the formula... Calculate the minimum turning radius signal R and the road adhesion coefficient of the vehicle. The physical safe speed limit is set as the turning speed limit for the current road section.

[0026] The available road information is the turning radius (using high-precision maps, etc.), which needs to be calculated (by introducing a dynamic model or using the friction circle theory for simple calculation) to obtain a safe speed.

[0027] 2) Acceleration / deceleration presets: The acceleration and deceleration are preset based on the slope signal (uphill / downhill / flat ground).

[0028] 3) Road segment initialization: The maximum initial speed limit for the entire road segment is preset (assumed to be 120 km / h), and the speed limit at red light locations is set to 0 km / h.

[0029] 3. Control interface.

[0030] Provides an enable interface for PCC functionality, allowing the driver to manually turn predictive cruise mode on / off.

[0031] 4. Arbitration based on multiple factors affecting vehicle speed limits.

[0032] Taking into account multiple factors such as turning, road speed limits, parking, and short-distance acceleration, the safe limit value for controlling road speed is determined. Specifically, this includes: 1) Integration of road conditions and vehicle speed limits.

[0033] Take the minimum value of the multiple speed limit signals as the basic speed limit control value. The formula is as follows:

[0034] in, Speed ​​limits for roads, Speed ​​limits for turns Speed ​​limit for traffic light signals (vehicle speed = 0 km / h).

[0035] 2) Road segment division.

[0036] Based on whether the speed limit of the basic speed control value changes, the planned road is divided into several road segments.

[0037] 3) Speed ​​limit arbitration.

[0038] The core of this step is handling short-distance acceleration and deceleration conditions on urban roads. When a vehicle is about to enter a continuous change from acceleration to deceleration, if the distance between two consecutive speed limits is too short, sudden speed changes can easily occur, which is detrimental to safe driving and energy consumption.

[0039] To address this issue, the following measures are taken in this embodiment: First, the basic speed limit curve is retrieved to identify the driving conditions where the vehicle accelerates first and then decelerates. The distance between the vehicle's acceleration and deceleration to a certain value (e.g., 0 km / h at the parking position and the turning speed limit at the turning position) and the two speed limits before and after the vehicle accelerates and decelerates are extracted.

[0040] The basic speed limit curve is a curve formed by the basic speed limit control value.

[0041] Then, a parameter rVehSpdCon_C is preset, which represents the percentage of the distance traveled at a constant speed within the first-addition-then-subtraction working condition, and can be set to 0-90%.

[0042] The formula for determining the maximum constant driving speed vVehSpdMax under the condition of acceleration followed by deceleration is as follows:

[0043] Wherein, aVehAcceCon_C / aVehDeceCon_C are the acceleration and deceleration obtained by the information preprocessing module based on the slope signal, dstSpdLimIncr is the working interval from the start of acceleration to the completion of deceleration, and vVehSpdLim1 / vVehSpdLim2 are the vehicle speed limits before acceleration and after deceleration.

[0044] By comparing the vVehSpdMax obtained for each road segment with the basic speed limit control value given based on the current road multi-source dynamic and static signals, the smaller value of the two is taken as the optimized vehicle speed for each road segment, and the final road speed planning curve is generated.

[0045] This embodiment integrates multi-source data, combining static and dynamic road signal data to determine a basic speed limit control value. It also considers the handling of short-distance acceleration and deceleration conditions. When a vehicle is about to enter a continuous change from acceleration to deceleration, if the distance between two consecutive speed limits is too short, sudden speed changes can easily occur, which is detrimental to safe driving and energy consumption. This embodiment considers this scenario and optimizes the determined basic speed limit control value to obtain the final optimized vehicle speed.

[0046] Comparison process Figure 1 The specific embodiments of the present invention will be described in further detail below.

[0047] Step 1: Collect and process multiple input signals from the ADAS system into standardized data, including road slope, traffic light signals, etc.

[0048] Among these methods, information such as road curvature and slope is obtained through high-precision maps; It receives traffic light and speed limit data via V2X.

[0049] Step 2: Information preprocessing, including vehicle acceleration and deceleration presets, turning speed limit calculations, and overall road segment speed initialization control.

[0050] Step 3: Taking into account multiple factors such as turning, road speed limits, and parking, the minimum value of the speed limit information from multiple signals is taken as the basic speed limit control.

[0051] Step 4: Handle short-distance acceleration and deceleration conditions on urban roads.

[0052] The parameter rVehSpdCon_C for the short-distance acceleration and deceleration condition is preset, and the speed limit vVehSpdMax for the short-distance acceleration and deceleration condition is calculated.

[0053] Step 5: Arbitration optimization process.

[0054] If vVehSpdMax is greater than the basic speed limit for this road segment, then vVehSpdMax is used to replace the basic speed limit as the speed limit control value for this road segment. The basic speed limit control value is then optimized to generate the final road speed planning curve.

[0055] Example 2 This embodiment discloses a predictive cruise control system based on dynamic optimization of multi-source road information.

[0056] A predictive cruise control system based on dynamic optimization of multi-source road information includes: The data acquisition and preprocessing module is configured to: acquire multi-source heterogeneous data of the vehicle's planned driving route, perform preprocessing, and calculate the turning speed limit; The basic speed limit control value calculation module is configured to use the minimum value among the road speed limit, turning speed limit and traffic light signal speed limit of the planned driving route of the vehicle as the current basic speed limit control value; The road segment division module is configured to divide the planned driving route of the vehicle into several road segments based on whether the basic speed limit control value has changed; The maximum constant driving speed solution module is configured to: retrieve the basic speed limit control value, identify the driving condition position where acceleration precedes deceleration, and solve for the maximum constant driving speed within the corresponding acceleration precedes deceleration driving condition distance; The optimization module is configured to: use the maximum constant driving speed of each road segment to optimize the basic speed limit control value of the corresponding road segment, obtain the optimized speed of each road segment, and generate the final road speed planning curve.

[0057] More specifically, in this embodiment, the data acquisition and preprocessing module includes two parts: an information acquisition and reconstruction module and an information preprocessing module. Specifically: (1) Information Acquisition and Reconstruction Module: This module is responsible for collecting and processing multiple input signals from the ADAS system. Static road signals include speed limits, turning radii, roundabout turns, highway exit locations, and gradients; dynamic traffic signals include traffic light signals and red light waiting times. This module synchronizes and standardizes the format of this multi-source, heterogeneous information, providing standardized data for subsequent processing.

[0058] (2) Information preprocessing module: Standardized data is used to preset and calculate parameters, providing basic data for subsequent vehicle speed planning.

[0059] 1) Turning speed limit calculation: The minimum value of all turning signals (including road curves and roundabout turning signals, etc.) is taken as the turning speed limit for the current road segment. Based on the vehicle dynamics model, combined with the curve radius and road surface adhesion coefficient, the maximum safe speed for the current curve is calculated.

[0060] 2) Preset acceleration / deceleration: Preset acceleration / deceleration and deceleration based on the slope signal (uphill / downhill / flat ground).

[0061] 3) Road segment initialization: Preset the maximum initial value of the speed limit for the entire road segment (assuming it is 120km / h), and set the speed limit at red light locations to 0km / h.

[0062] This embodiment also includes: (3) Control interface module: Provides an enable interface for PCC function, supporting the driver to manually turn on / off predictive cruise mode.

[0063] (4) In the basic speed limit control value calculation module, multiple factors are used for vehicle speed limit arbitration, taking into account multiple factors such as turning, road speed limit, parking, and short-distance acceleration, to control the safe limit value of road vehicle speed.

[0064] This module consists of the following three parts: 1) Road condition speed limit integration: Take the minimum value of multiple signal speed limit information as the basic speed limit control. The formula is as follows:

[0065] in, Speed ​​limits for roads, Speed ​​limits for turns Speed ​​limit for traffic light signals (vehicle speed = 0 km / h).

[0066] 2) Road segment division: Based on whether the speed limit changes, the planned road is divided into several road segments.

[0067] 3) Speed ​​Limit Arbitration: The core of this module is the handling of short-distance acceleration and deceleration conditions on urban roads. When a vehicle is about to enter a continuous change from acceleration to deceleration, if the distance between two consecutive speed limits is too short, sudden speed changes can easily occur, which is detrimental to safe driving and energy consumption.

[0068] The following measures were taken to address this issue: First, the basic speed limit curve is retrieved to identify the driving conditions where the vehicle accelerates first and then decelerates. The distance between the vehicle's acceleration and deceleration to a certain value (e.g., 0 km / h at the parking position and the turning speed limit at the turning position) and the two speed limits before and after the vehicle accelerates and decelerates are extracted.

[0069] A preset parameter rVehSpdCon_C is used, which represents the percentage of the distance traveled at a constant speed within the first-addition-then-subtraction working condition. The range can be 0-90%.

[0070] The formula for determining the maximum constant driving speed vVehSpdMax under the condition of acceleration followed by deceleration is as follows:

[0071] Where aVehAcceCon_C / aVehDeceCon_C are the acceleration and deceleration obtained by the information preprocessing module based on the slope signal, dstSpdLimIncr is the working interval from the start of acceleration to the completion of deceleration, and vVehSpdLim1 / vVehSpdLim2 are the vehicle speed limits before acceleration and after deceleration.

[0072] By comparing the vVehSpdMax obtained for each road segment with the road speed limit value given based on the current road multi-source dynamic and static signals, the smaller value of the two is taken as the optimized vehicle speed for each road segment, and the final road speed planning curve is generated. Example 3 The purpose of this embodiment is to provide a computer-readable storage medium.

[0073] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the predictive cruise control method based on dynamic optimization of multi-source road information as described in Embodiment 1 of this disclosure.

[0074] Example 4 The purpose of this embodiment is to provide an electronic device.

[0075] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the predictive cruise control method based on dynamic optimization of multi-source road information as described in Embodiment 1 of this disclosure.

[0076] The steps and methods involved in the apparatuses of Embodiments 2, 3, and 4 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0077] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0078] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A predictive cruise control method based on dynamic optimization of multi-source road information, characterized in that, Includes the following steps: Acquire multi-source heterogeneous data of the vehicle's planned driving route, preprocess it, and calculate the turning speed limit; The minimum value among the road speed limit, turning speed limit and traffic light signal speed limit of the planned route for the vehicle is used as the current base speed limit control value; Based on whether the basic speed limit control value has changed, the planned driving route for vehicles is divided into several road segments; The basic speed limit control value is retrieved to identify the driving conditions where acceleration precedes deceleration, and the maximum constant driving speed within the corresponding acceleration-deceleration driving condition distance is calculated. The maximum constant driving speed of each road segment is used to optimize the basic speed limit control value of the corresponding road segment, thereby obtaining the optimized speed of each road segment and generating the final road speed planning curve.

2. The predictive cruise control method based on dynamic optimization of multi-source road information as described in claim 1, characterized in that, The multi-source heterogeneous data for vehicle planning and driving routes includes static road signal data and dynamic road signal data, among which: Static road signal data includes road speed limits, turning radii, roundabout turns, highway exit locations, and road gradients; Dynamic road signal data includes traffic light signals and red light waiting time.

3. The predictive cruise control method based on dynamic optimization of multi-source road information as described in claim 2, characterized in that, The specific process for calculating the speed limit for turning includes: Take the minimum value R of all turning radii, including road curves and roundabout curves, and then calculate the physical safe speed limit of the vehicle under the minimum turning radius R, which is used as the turning speed limit for the current road section.

4. The predictive cruise control method based on dynamic optimization of multi-source road information as described in claim 2, characterized in that, The preprocessing also includes: Acceleration / deceleration presets: Preset acceleration / deceleration and deceleration based on road gradient signals; Road segment initialization: Preset the maximum initial speed limit for the entire planned road for vehicles, and limit the speed at red light locations to 0 km / h.

5. The predictive cruise control method based on dynamic optimization of multi-source road information as described in claim 1, characterized in that, Solving for the maximum constant driving speed under the corresponding acceleration-then-deceleration driving condition, specifically including: Extract the distance of the vehicle from acceleration to deceleration to a certain value, as well as the two speed limits before acceleration and after deceleration; A preset parameter rVehSpdCon_C is used, which represents the proportion of the distance traveled at a constant speed within the driving conditions of the vehicle accelerating first and then decelerating. The formula for determining the maximum constant speed vVehSpdMax over a distance under the condition of vehicle acceleration followed by deceleration is as follows: ； Where aVehAcceCon_C and aVehDeceCon_C are the acceleration and deceleration obtained from the road slope signal; dstSpdLimIncr is the working interval from the start of acceleration to the completion of deceleration; vVehSpdLim1 and vVehSpdLim2 are the vehicle speed limit before acceleration and the vehicle speed limit after deceleration; sqrt is the square root.

6. The predictive cruise control method based on dynamic optimization of multi-source road information as described in claim 5, characterized in that, The maximum constant driving speed of each road segment is used to optimize the basic speed limit control value of the corresponding road segment, resulting in the optimized speed for each road segment. Specifically, this includes: The smaller of the basic speed limit and the maximum constant speed in each road segment is taken as the optimal speed for each road segment.

7. The predictive cruise control method based on dynamic optimization of multi-source road information as described in claim 6, characterized in that, If there is no driving condition position in a certain road segment where acceleration is followed by deceleration, then the optimized speed for this road segment is the basic speed limit control value for the current road segment.

8. A predictive cruise control system based on dynamic optimization of multi-source road information, characterized in that, include: The data acquisition and preprocessing module is configured to: acquire multi-source heterogeneous data of the vehicle's planned driving route, perform preprocessing, and calculate the turning speed limit; The basic speed limit control value calculation module is configured to use the minimum value among the road speed limit, turning speed limit and traffic light signal speed limit of the planned driving route of the vehicle as the current basic speed limit control value; The road segment division module is configured to divide the planned driving route of the vehicle into several road segments based on whether the basic speed limit control value has changed; The maximum constant driving speed solution module is configured to: retrieve the basic speed limit control value, identify the driving condition position where acceleration precedes deceleration, and solve for the maximum constant driving speed within the corresponding acceleration precedes deceleration driving condition distance; The optimization module is configured to: use the maximum constant driving speed of each road segment to optimize the basic speed limit control value of the corresponding road segment, obtain the optimized speed of each road segment, and generate the final road speed planning curve.

9. A computer-readable storage medium having a program stored thereon, characterized in that, When executed by the processor, the program implements the steps of the predictive cruise control method based on dynamic optimization of multi-source road information as described in any one of claims 1-7.

10. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the predictive cruise control method based on dynamic optimization of multi-source road information as described in any one of claims 1-7.

Images