Road quality evaluation method and system based on driving data

Abstract

The invention discloses a road quality evaluation method based on driving data, and the method comprises the steps: carrying out the standardization processing of the driving data Xi (t) of a vehicle at least according to the dead weight of the vehicle, the characteristics of a suspension system, the center of gravity of the vehicle, and the contact condition of wheels and a road surface, and obtaining the standardized driving data Yi (t), t represents an index of a temporal or spatial position (step S1); and evaluating the road quality according to the driving standardized data Yi (t) (step S2). According to certain exemplary embodiments of the invention, real-time and accurate monitoring of road quality can be realized.

Description

Technical Field

[0001] The present invention relates to the field of vehicles, and in particular to a road quality assessment method and system based on driving data. Background Art

[0002] In modern transportation systems, road quality is crucial to the safety and comfort of vehicle driving. However, it is currently difficult to use vehicle driving data to evaluate road quality. The main reason is that different types of vehicles have different inherent characteristics, and these differences will make it difficult to directly use the feedback driving data to accurately evaluate road quality.

[0003] Traditional road quality detection methods usually rely on professional detection equipment, such as laser instruments, which are expensive and complex to operate, and cannot achieve large-scale real-time monitoring. In addition, some existing analysis methods based on driving data also have limitations and cannot effectively eliminate the impact of differences in vehicle characteristics on the data, making it difficult to accurately reflect the actual quality of the road.

[0004] Therefore, the present invention aims to provide a road quality assessment method and system based on driving data, which can effectively eliminate the differences in characteristics of different vehicles, realize real-time and accurate monitoring of road quality, and promptly notify relevant departments to carry out road maintenance. Summary of the invention

[0005] In order to overcome one of the above-mentioned shortcomings and / or other possible shortcomings in the prior art not mentioned herein, an object of the present invention is to provide a road quality assessment method and system based on driving data.

[0006] The present invention particularly includes the following technical concepts: standardizing the driving data of vehicles, and implementing the standardization according to the inherent characteristics of the vehicles, thereby eliminating the differences in driving data of different types of vehicles, so as to accurately reflect the actual quality of the road, and further, in order to construct a big data model, introduce the driving data of all vehicles passing on the road to evaluate the road quality.

[0007] According to one aspect of the present invention, a road quality assessment method based on driving data is provided, the road quality assessment method comprising: step S1: evaluating the driving data X of the vehicle based on at least the vehicle's own weight, suspension system characteristics, vehicle center of gravity, and wheel-road contact conditions. i (t) Perform standardization processing to obtain driving standardized data Y i (t), wherein i represents different vehicles and t represents the index of time or spatial position; and step S2: according to the driving standardized data Y i (t) Evaluate road quality.

[0008] According to an optional embodiment of the present invention, Among them, the normalization factor m i is the vehicle's own weight, k i is the stiffness of the suspension system, A i is the contact area between the wheel and the road, h i is the height of the vehicle's center of gravity.

[0009] According to an optional embodiment of the present invention, the driving data X i (t) includes driving data of a plurality of vehicles, wherein the plurality of vehicles includes vehicles of different types.

[0010] According to an optional embodiment of the present invention, the driving data X i (t) is the vehicle's speed, acceleration, suspension system response data or any combination of the above data; wherein the vehicle's acceleration includes the vehicle's longitudinal acceleration and lateral acceleration; and / or the vehicle's suspension system response data includes the vibration frequency and amplitude of the suspension system.

[0011] According to an optional embodiment of the present invention, the road quality includes the flatness of the road.

[0012] According to an optional embodiment of the present invention, based on the standardized driving data Y of all vehicles passing through the road to be evaluated within a predetermined time i (t) constructing a big data model, and using the big data model to evaluate the road quality of each road section according to time or spatial location.

[0013] According to an optional embodiment of the present invention, the road quality of each road section is evaluated according to time or spatial position with the help of the big data model, specifically: the driving fusion data Y for evaluating the road quality is obtained with the help of the big data model, and when the driving fusion data Y of adjacent road sections are different, a road maintenance notice is generated.

[0014] According to an optional embodiment of the present invention, the road quality of each road section is evaluated according to time or spatial position with the help of the big data model, specifically: the driving fusion data Y for evaluating the road quality is obtained with the help of the big data model, and when the driving fusion data Y of the same road section at different times changes at a rate greater than a preset change rate over time, a road maintenance notification is generated.

[0015] According to a second aspect of the present invention, a road quality assessment system based on driving data is provided, the road quality assessment system comprising: a standardization module 10, which is configured to be able to standardize the driving data X of the vehicle based on at least the vehicle's own weight, suspension system characteristics, vehicle center of gravity, and contact conditions between the wheels and the road surface. i (t) Perform standardization processing to obtain driving standardized data Y i(t), where i represents different types of vehicles, and t represents an index of a time or spatial position; and an evaluation module 20, which is configured to be able to evaluate the vehicle according to the driving standardized data Y i (t) Evaluate road quality.

[0016] According to a third aspect of the present invention, there is provided a computer program product, such as a machine-readable storage medium, comprising or storing computer program instructions, the computer program being adapted to perform a road quality assessment method when run on a computer.

[0017] According to some exemplary embodiments of the present invention, real-time and accurate monitoring of road quality can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention will be described in more detail below with reference to the accompanying drawings, so that the principles, features and advantages of the present invention can be better understood. The accompanying drawings include:

[0019] Figure 1 A schematic diagram showing a vehicle traveling on a flat road according to an exemplary embodiment of the present invention is shown.

[0020] Figure 2 A schematic diagram showing a vehicle traveling on an uneven road according to an exemplary embodiment of the present invention is shown.

[0021] Figure 3 A flow chart of a road quality assessment method based on driving data according to an exemplary embodiment of the present invention is shown.

[0022] Figure 4 A schematic block diagram of a road quality assessment system based on driving data according to an exemplary embodiment of the present invention is shown. DETAILED DESCRIPTION

[0023] In order to make the technical problems, technical solutions and beneficial technical effects to be solved by the present invention more clearly understood, the present invention will be further described in detail below in conjunction with the accompanying drawings and multiple exemplary embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the scope of protection of the present invention.

[0024] Figure 1 A schematic diagram showing a vehicle traveling on a flat road according to an exemplary embodiment of the present invention is shown. Figure 2 A schematic diagram showing a vehicle driving on an uneven road according to an exemplary embodiment of the present invention is shown. Figure 1 , Figure 2 By comparison, it can be seen that the road quality of the road where the vehicle is located will have a multi-faceted impact on the vehicle's movement pattern.

[0025] Road quality refers to the road surface quality that can effectively ensure driving safety and driving comfort. When the road quality decreases, it is easy to cause unstable driving and potential safety hazards during driving. In particular, the flatness of the road is an important parameter that can reflect the quality of the road. The flatness of the road can be the roughness of the road surface. When the road surface has pits, cracks, bulges, etc., it will cause the road flatness to change, which is generally caused by improper maintenance. The accumulation of ice and snow or spilled objects on the road surface will also cause the road flatness to change, which is generally caused by weather and accidents. However, no matter what the circumstances are that cause the change in road flatness, when the road flatness deviates from the predetermined flatness, the road should be maintained in a timely manner. The predetermined flatness can be set according to the International Roughness Index (IRI) or local laws and regulations to ensure driving safety.

[0026] Figure 3 A flow chart of a road quality assessment method based on driving data according to an exemplary embodiment of the present invention is shown, the method at least comprising steps S1 and S2. Through the method of the present invention, road quality can be assessed accurately in real time, and timely road maintenance suggestions can be provided.

[0027] In step S1 of the exemplary embodiment, the vehicle driving data X is analyzed based on at least the vehicle's own weight, the suspension system characteristics, the vehicle's center of gravity, and the contact condition between the wheels and the road surface. i (t) Perform standardization processing to obtain driving standardized data Y i (t), where i represents different vehicles and t represents the index of time or spatial position. i (t) can represent the driving data of different vehicles. Depending on the application, it can include the driving data of only one vehicle, or multiple vehicles, or even all vehicles, especially the driving data of all vehicles passing within the road range to be evaluated at a predetermined time. i (t) can be the driving data of the vehicle changing with time, or the vehicle changing with the spatial position CNDAI216032-indicates the traffic bureau, the data has been confirmed X i (t), it is also difficult to directly use the driving data X from different vehicles i (t) To accurately assess road quality, it is necessary to analyze the driving data X i (t) Standardization processing is performed. The present invention processes the driving data X according to the inherent characteristics of the vehicle. i (t) Standardize the vehicle's driving data X by selecting the vehicle's own weight, suspension system characteristics, vehicle center of gravity height, and wheel-road contact conditions that can highlight the inherent characteristics of the vehicle. i (t) Standardization processing is performed. The standardized data Yi (t) It can better reflect the actual situation of road surface smoothness without being disturbed by the inherent characteristics of the vehicle.

[0028] Preferably, C i is a normalization factor, the normalization factor m i is the weight of the vehicle, k i is the stiffness of the suspension system, A i is the contact area between the wheel and the road, h i is the height of the vehicle's center of gravity.

[0029] Optionally, the driving data X i (t) may be the vehicle's speed, acceleration, suspension system response data, or any combination of the above data. When the quality of the road on which the vehicle is located is not high, especially when the road flatness is poor, the longitudinal or lateral displacement of the vehicle will change, and the rate of change of the displacement will also be more significant. The change of the displacement can be reflected by the vehicle's speed, acceleration, and suspension system response data. Therefore, the vehicle's speed, acceleration, and suspension system response data can indirectly reflect the road flatness. In particular, the longitudinal acceleration and lateral acceleration of the vehicle will change significantly with the change of time and driving position. Therefore, the acceleration of the vehicle can be the longitudinal acceleration or lateral acceleration of the vehicle; the suspension system response data of the vehicle mainly includes the change of the suspension system damping parameters, and the vibration frequency and amplitude of the suspension system. Additionally, the driving data X i (t) may be a combination of the vehicle's speed, acceleration, and suspension system response data, or a combination of any two of the three. Here, the combination may be an operational combination of the above-mentioned multiple parameters.

[0030] In step S2 of this exemplary embodiment, according to the driving standardization data Y i (t) evaluating the road quality. Preferably, according to the standardized driving data Y i (t) Evaluate the smoothness of the road. When the road quality is poor and lower than the pre-set road quality level, the relevant department responsible for road maintenance needs to be notified so that the relevant department can make maintenance decisions. The road quality level can be calculated based on the standardized driving data Y i(t). In particular, when the flatness of the road deteriorates and does not meet the International Roughness Index (IRI) or the prescribed range of local laws and regulations, it means that the road quality is poor and is lower than the preset road quality level. Additionally, when the road quality is poor and lower than the preset road quality level, the image of the road where the vehicle is located can be retrieved to further analyze the reasons for the deterioration of the road quality, which is conducive to deciding the priority of road maintenance. The image of the road can be collected by a roadside unit or by on-board equipment of the vehicle and other vehicles.

[0031] Optionally, the driving standardized data Y i (t), evaluate the road quality of each road section according to time or spatial position. Here, all vehicles passing through the road to be evaluated within a predetermined time can be introduced. All passing vehicles can include vehicles of different types and with different components. The driving data of all passing vehicles can also be obtained in real time. i (t), and the driving data X of all passing vehicles i (t) After standardization, the standardized driving data Y of all vehicles passing through is obtained i (t), and then the driving standard data Y of all passing vehicles i (t) The fusion data Y is obtained by fusion. Since the fusion data Y is derived from the data fed back by multiple different vehicles, rather than relying solely on the driving data of a single vehicle, the fusion data Y is conducive to improving the reliability of the road quality assessment method and can also effectively eliminate the assessment error. In addition, in order to standardize the driving data Y of all vehicles passing through i (t) can be used for efficient data fusion. A big data model can also be constructed based on the standardized driving data Yi(t) of all vehicles on the road, and the driving fusion data Y can be obtained with the help of the big data model.

[0032] Optionally, according to the standardized driving data Y of all vehicles passing through the road to be evaluated within a predetermined time i (t) With the help of the big data model, the driving fusion data Y for evaluating road quality is obtained. When the driving fusion data Y of adjacent road sections are different, or when the driving fusion data Y of the same road section at different times changes over time at a rate greater than a preset change rate, a road maintenance notice is generated to facilitate relevant departments to make maintenance decisions.

[0033] Figure 4 A schematic block diagram of a road quality assessment system based on driving data according to an exemplary embodiment of the present invention is shown.

[0034] The road quality assessment system has the following components: a standardization module 10, which is configured to be able to analyze the vehicle driving data X according to the vehicle's own weight, suspension system characteristics, vehicle center of gravity, and the contact condition between the wheel and the road surface; i (t) Perform standardization processing to obtain driving standardized data Y i (t), where i represents different types of vehicles and t represents the index of time or spatial position;

[0035] The evaluation module 20 is configured to be able to i (t) Evaluate road quality.

[0036] Optionally, the road quality assessment system further comprises a notification module, which is configured to be able to feed back road assessment information to relevant departments responsible for road maintenance.

[0037] Optionally, the driving normalized data Y i (t) includes standardized driving data from different vehicles, and the evaluation module 20 can evaluate the driving standardized data Y according to the standardized driving data Y. i (t) A big data model is established, and with the help of the big data model, driving fusion data Y for evaluating road quality is obtained. The driving fusion data Y is conducive to improving the reliability of the road quality evaluation method and can also effectively eliminate evaluation errors.

[0038] Obviously, those skilled in the art can understand that the above technical features can also be applied here, and no further details will be given.

[0039] Although specific embodiments have been described above, these embodiments are not intended to limit the scope of the present disclosure, even when only a single embodiment is described with respect to specific features. The feature examples provided in the present disclosure are intended to be illustrative, not limiting, unless otherwise expressly stated. In specific implementations, multiple features can be combined with each other where technically feasible, depending on actual needs. Various substitutions, changes, and modifications may also be conceived without departing from the spirit and scope of the present invention.

Claims

1. A road quality assessment method based on driving data, the road quality assessment method comprising: Step S1: Analyze the vehicle driving data X based on at least the vehicle's own weight, suspension system characteristics, vehicle center of gravity, and contact conditions between the wheels and the road surface. i (t) Perform standardization processing to obtain driving standardized data Y i (t), where i represents a different vehicle and t represents an index of a time or spatial position; and Step S2: Based on the driving standardization data Y i (t) Evaluate road quality.

2. The road quality assessment method according to claim 1, characterized in that: Among them, the normalization factor m i is the vehicle's own weight, k i is the stiffness of the suspension system, A i is the contact area between the wheel and the road, h i is the height of the vehicle's center of gravity.

3. The road quality assessment method according to claim 1, characterized in that: The driving data X i (t) includes driving data of a plurality of vehicles, wherein the plurality of vehicles includes vehicles of different types.

4. The road quality assessment method according to claim 1, characterized in that: The driving data X i (t) is the vehicle's speed, acceleration, suspension system response data, or any combination of the above data; The acceleration of the vehicle includes the longitudinal acceleration and the lateral acceleration of the vehicle; and / or The vehicle suspension system response data includes the vibration frequency and amplitude of the suspension system.

5. The road quality assessment method according to claim 1, characterized in that: The road quality includes the flatness of the road.

6. The road quality assessment method according to claim 1, characterized in that: Based on the standardized driving data Y of all vehicles passing through the road to be evaluated within a predetermined time i (t) constructing a big data model, and using the big data model to evaluate the road quality of each road section according to time or spatial location.

7. The road quality assessment method according to claim 6, characterized in that: The road quality of each road section is evaluated according to time or spatial position by using the big data model, specifically: The big data model is used to obtain driving fusion data Y for evaluating road quality. When the driving fusion data Y of adjacent road sections are different, a road maintenance notice is generated.

8. The road quality assessment method according to claim 6, characterized in that: The road quality of each road section is evaluated according to time or spatial position by using the big data model, specifically: The big data model is used to obtain the driving fusion data Y for evaluating road quality. When the driving fusion data Y of the same road section at different times changes over time at a rate greater than a preset change rate, a road maintenance notice is generated.

9. A road quality assessment system based on driving data, the road quality assessment system comprising: The standardization module (10) is configured to be able to adjust the vehicle driving data X based on at least the vehicle's own weight, the suspension system characteristics, the vehicle's center of gravity and the contact condition between the wheels and the road surface. i (t) Perform standardization processing to obtain driving standardized data Y i (t), where i represents different types of vehicles and t represents the index of time or spatial position; and An evaluation module (20) is configured to evaluate the vehicle driving standardization data Y i (t) Evaluate road quality.

10. A computer program product, such as a machine-readable storage medium, comprising or storing computer program instructions, wherein the computer program is adapted to perform the road quality assessment method according to any one of claims 1 to 8 when executed on a computer.

Images