CN115273452A

CN115273452A - Road condition determination method and device and computer readable storage medium

Info

Publication number: CN115273452A
Application number: CN202110475233.7A
Authority: CN
Inventors: 梁宝强
Original assignee: Alibaba Singapore Holdings Pte Ltd
Current assignee: Alibaba Innovation Co
Priority date: 2021-04-29
Filing date: 2021-04-29
Publication date: 2022-11-01

Abstract

The embodiment of the disclosure discloses a road condition determining method, a road condition determining device and a computer readable storage medium, wherein the method comprises the following steps: determining a target road section; dividing the target road section into more than two target sub-road sections; acquiring the number of objects passing through the target sub-road section in a set time length before the current time; determining the road condition of the target sub-road section based on the number of the objects; and fusing the road condition of the target sub-road section to obtain the road condition of the target road section, wherein the road condition comprises: severe congestion, sluggish walking, normal clear and extreme clear. The technical scheme can improve the richness of the traffic road condition information, improve the information quantity of the traffic road condition information provided for the user, provide data support for the user to select a more smooth road, and is favorable for realizing the maintenance and guarantee of traffic safety.

Description

Road condition determination method and device and computer readable storage medium

Technical Field

The embodiment of the disclosure relates to the technical field of traffic data processing, in particular to a road condition determining method and device and a computer readable storage medium.

Background

With the development and progress of the society, vehicles on roads are more and more, and a lot of users can check traffic real-time road condition data through map navigation application software before going out so as to decide the running time, the running mode or the running route. However, the current real-time traffic road condition data generally includes only four road conditions, namely smooth road conditions, slow road conditions, congestion road conditions and severe congestion road conditions, which are respectively identified by green, yellow, red and dark red, and the four road conditions basically cover the common traffic states of roads, but the refinement degree is still insufficient, so that the information amount of the traffic road condition information obtained by the user is insufficient, that is, the accuracy of the user's trip decision or driving decision has a further optimization space.

Disclosure of Invention

The embodiment of the disclosure provides a road condition determining method, a road condition determining device, electronic equipment and a readable storage medium.

In a first aspect, a method for determining a road condition is provided in an embodiment of the present disclosure.

Specifically, the road condition determining method includes:

determining a target road section;

dividing the target road section into more than two target sub-road sections;

acquiring the number of objects passing through the target sub-road section in a set time length before the current time;

determining the road condition of the target sub-road section based on the number of the objects;

and fusing the road condition of the target sub-road section to obtain the road condition of the target road section, wherein the road condition comprises: severe congestion, sluggish walking, normal clear and extreme clear.

With reference to the first aspect, in a first implementation manner of the first aspect, after the obtaining the number of objects that pass through the target sub-segment within a set time period before the current time, the embodiment of the present disclosure further includes:

the number of objects is modified based on the permeation parameter.

With reference to the first aspect and the first implementation manner of the first aspect, an embodiment of the present disclosure is implemented in a second implementation manner of the first aspect, where the modifying the number of objects based on the penetration parameter includes:

acquiring a reference permeability and a permeability of the target sub-road section;

dividing the reference permeability by the permeability of the target sub-road section to obtain a permeability parameter;

and multiplying the number of the objects by the penetration parameter to obtain the corrected number of the objects.

With reference to the first aspect and the foregoing implementation manner of the first aspect, in a third implementation manner of the first aspect, the determining a road condition of the target sub-segment based on the number of the objects includes:

comparing the object quantity of the target sub-road section with an object quantity threshold corresponding to the road condition to determine the road condition of the target sub-road section, wherein the object quantity threshold comprises the following steps in the descending order of the threshold: a severe congestion threshold, a crawl threshold, a regular clear threshold, and an extreme clear threshold.

With reference to the first aspect and the foregoing implementation manner of the first aspect, in a fourth implementation manner of the first aspect, the determining the road condition of the target sub-segment based on the number of the objects includes:

and comparing the number of the objects of the target sub-road section with an extreme speed unblocked threshold value, and determining whether the road condition of the target sub-road section is kept normal unblocked or is updated to be the extreme speed unblocked.

With reference to the first aspect, the foregoing implementation manner of the first aspect, the present disclosure provides in a fifth implementation manner of the first aspect, wherein the factor affecting the extreme speed clear threshold or the normal clear threshold of the target sub-segment includes one or more of the following factors: road type, number of lanes, vehicle density and traffic speed.

With reference to the first aspect and the foregoing implementation manner of the first aspect, in a sixth implementation manner of the first aspect, the fusing the road condition of the target sub-segment to obtain the road condition of the target segment includes:

if the proportion between the number of the target sub-road sections with normal smooth road conditions and the total number of the target sub-road sections is greater than or equal to a preset proportion threshold value, keeping the road conditions of the target road sections normal smooth;

and if the proportion between the number of the target sub-road sections with the extremely-fast smooth road condition and the total number of the target sub-road sections is greater than or equal to the preset proportion threshold value, updating the road condition of the target road section to be the extremely-fast smooth road condition.

With reference to the first aspect and the foregoing implementation manner of the first aspect, in a seventh implementation manner of the first aspect, after determining the road condition of the target sub-segment based on the number of objects, the method further includes:

and when the length of the target road section is greater than a first preset length threshold value, combining adjacent target sub-road sections with the same road condition in the target road section into a new target sub-road section.

With reference to the first aspect and the foregoing implementation manner of the first aspect, in an eighth implementation manner of the first aspect, after determining the road condition of the target sub-segment based on the number of the objects, the method further includes:

and determining the road conditions of partial road sections with missing road conditions in the target road section based on the road conditions of the target sub-road sections.

With reference to the first aspect and the foregoing implementation manner of the first aspect, in a ninth implementation manner of the first aspect, the determining, based on the road condition of the target sub-segment, the road condition of a partial segment that lacks the road condition in the target segment includes:

when the part of the road section where the road condition is missing is a tunnel,

acquiring a road condition of a target sub-road section to which a tunnel entrance belongs as an entrance road condition and a road condition of a target sub-road section to which a tunnel exit belongs as an exit road condition;

when the entrance road condition is consistent with the exit road condition, determining the road condition of the tunnel as the entrance road condition or the exit road condition;

alternatively, the first and second electrodes may be,

when the partial road section lacking the road condition is the ramp,

and acquiring the road condition of a target sub-road section to which the ramp exit belongs as the road condition of the ramp.

In a second aspect, a traffic determination device is provided in the embodiments of the present disclosure.

Specifically, the road condition determining apparatus includes:

a first determination module configured to determine a target road segment;

a segmentation module configured to segment the target segment into two or more target sub-segments;

the acquisition module is configured to acquire the number of objects passing through the target sub-road section within a set time length before the current time;

a second determination module configured to determine a road condition of the target sub-section based on the number of objects;

a fusion module configured to fuse the road condition of the target sub-road segment to obtain the road condition of the target road segment, where the road condition includes: severe congestion, slow traffic, regular traffic and extreme traffic.

In a third aspect, an embodiment of the present disclosure provides an electronic device, including a memory and a processor, where the memory is configured to store one or more computer instructions for supporting a road condition determining device to execute the above road condition determining method, and the processor is configured to execute the computer instructions stored in the memory. The traffic condition determining apparatus may further include a communication interface for the traffic condition determining apparatus to communicate with other devices or a communication network.

In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium for storing computer instructions for a traffic condition determining apparatus, where the computer instructions are used to execute the traffic condition determining method as a traffic condition determining apparatus.

In a fifth aspect, an embodiment of the present disclosure provides a navigation method, where a navigation route calculated at least based on a starting point, an ending point, and a road condition is obtained, and navigation guidance is performed based on the navigation route, where the road condition is implemented based on any one of the above methods.

With reference to the fifth aspect, in a first implementation manner of the fifth aspect, the disclosed embodiments display the road condition on the navigation route based on rendering and dyeing respectively for severe congestion, slow traveling, normal unblocked and extreme unblocked, wherein a visual effect of extreme unblocked expresses a state that the road is easier or safer to travel than the normal unblocked road.

The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:

the technical scheme is based on the determination and fusion of the road conditions of the target sub-road sections, and the smooth road conditions are further distinguished. The technical scheme can improve the richness and the hierarchy of the traffic road condition information, improve the information quantity of the traffic road condition information provided for the user, provide data support for the user to select a more smooth road, and is favorable for realizing the maintenance and the guarantee of traffic safety.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of embodiments of the disclosure.

Drawings

Other features, objects, and advantages of embodiments of the disclosure will become more apparent from the following detailed description of non-limiting embodiments when taken in conjunction with the accompanying drawings. In the drawings:

fig. 1 shows a flow chart of a road condition determination method according to an embodiment of the present disclosure;

2A-2C illustrate three road traffic scenarios in accordance with an embodiment of the present disclosure;

fig. 3 is a block diagram illustrating a structure of a road condition determining apparatus according to an embodiment of the present disclosure;

fig. 4 is a schematic structural diagram of a computer system suitable for implementing the road condition determining method according to an embodiment of the disclosure.

Fig. 5 is a schematic structural diagram of a computer system suitable for implementing the road condition determining method according to an embodiment of the disclosure.

Detailed Description

Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Also, for the sake of clarity, parts not relevant to the description of the exemplary embodiments are omitted in the drawings.

In the disclosed embodiments, it is to be understood that terms such as "including" or "having," etc., are intended to indicate the presence of the disclosed features, numbers, steps, behaviors, components, parts, or combinations thereof, and are not intended to preclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or combinations thereof may be present or added.

It should be further noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

The technical scheme provided by the embodiment of the disclosure further distinguishes smooth road conditions based on the determination and fusion of the road conditions of the target sub-road sections. The technical scheme can improve the richness and the hierarchy of the traffic road condition information, improve the information quantity of the traffic road condition information provided for the user, provide data support for the user to select a more smooth road, and is favorable for realizing the maintenance and the guarantee of traffic safety.

Fig. 1 is a flowchart illustrating a road condition determining method according to an embodiment of the present disclosure, and as shown in fig. 1, the road condition determining method includes the following steps S101 to S105:

in step S101, a target link is determined;

in step S102, the target link is divided into two or more target sub-links;

in step S103, acquiring the number of objects passing through the target sub-road segment within a set time length before the current time;

in step S104, determining the road condition of the target sub-road section based on the number of the objects;

in step S105, the road condition of the target sub-road section is fused to obtain the road condition of the target road section, where the road condition includes: severe congestion, sluggish travel, regular clear, and extreme clear (or, extreme clear).

When severe congestion, slow traffic, normal traffic and extreme-speed traffic are displayed, rendering can be performed on the colors corresponding to the severe congestion, the congestion corresponds to a deep red system, the congestion corresponds to a red system, the slow traffic uses a yellow system, the normal traffic uses a green system, and the extreme-speed traffic uses a deep green system.

As mentioned above, with the development and progress of the society, vehicles on roads are more and more, and many users can check traffic real-time road condition data through map navigation application software before going out, so as to decide a running time, a running mode or a running route. However, in the current real-time traffic road condition data, only four road conditions including smooth road conditions, slow traffic conditions, congestion conditions and severe congestion conditions are usually included, and are respectively identified by green, yellow, red and deep red, and the four road conditions basically cover the common traffic states of roads, but the refinement degree is still insufficient, so that the information amount of traffic road condition information obtained by a user is insufficient, that is, the accuracy of a user's travel decision or driving decision has a further optimization space.

In view of the above problem, in this embodiment, a road condition determining method is provided, which further distinguishes smooth road conditions based on the determination and fusion of the road conditions of the target sub-road segments. According to the technical scheme, the richness and the hierarchy of the traffic road condition information can be improved, the information quantity of the traffic road condition information provided for the user is improved, data support is provided for the user to select a more smooth road, and the maintenance and the guarantee of traffic safety are facilitated.

In an embodiment of the present disclosure, the road condition determining method may be applied to a computer, a computing device, an electronic device, a server, a service cluster, and the like, which may perform road condition determination.

In an embodiment of the present disclosure, the target road segment refers to a road segment whose road condition needs to be determined, and the target road segment may be one road segment in road network data.

In an embodiment of the present disclosure, the target sub-segment refers to a sub-segment obtained by dividing the target segment in order to perform a detailed analysis on a road condition of the target segment, where the number of the target sub-segments is two or more.

In an embodiment of the present disclosure, a specific value of the set time period may be determined according to a requirement of an actual application, for example, the specific value may be set to 10 minutes, 15 minutes, and the like, and the present disclosure does not particularly limit the specific value.

In an embodiment of the present disclosure, the object refers to a sample object used for measuring whether a certain road segment is congested or clear, and the object may be, for example, a vehicle, or, in other application scenarios, a pedestrian, a bicycle, or another observable and statistical object.

In the above embodiment, the target road segment to be processed is first determined, and then the target road segment is divided into two or more shorter target sub-segments; then acquiring the number of objects passing through the target sub-road section within a set time length before the current time; and then determining the road conditions of the target sub-road sections based on the number of the objects, and fusing the road conditions of the target sub-road sections, for example, combining the road conditions of each target sub-road section according to the segmentation sequence of the target sub-road sections to obtain the road conditions of the target road sections. Wherein the road conditions include: the method comprises the steps of severe congestion, slow traffic, normal clear and extreme clear traffic, wherein the normal clear refers to normal clear road conditions, and the extreme clear refers to more clear road conditions. Compared with the road section road condition content in the prior art, the road condition content of the target road section is richer, so that the information content of traffic road condition information provided for a user can be improved, the user can select a more smooth road based on the richer smooth road condition, and meanwhile, the user fatigue caused by the overlong bad driving time of the road condition and the potential safety hazard caused by the user fatigue can be avoided.

In an embodiment of the present disclosure, the step S102 of dividing the target link into two or more target sub-links may include the steps of:

determining a preset segmentation length;

and dividing the target road section into more than two target sub-road sections according to the preset dividing length.

In order to reduce the calculation amount of the road condition and reduce the instantaneous calculation pressure, the target road section can be divided into more than two target sub-sections, and then the target sub-sections are fused after road condition calculation is respectively carried out on the target sub-sections. When the target road segment is divided into more than two target sub-road segments, first determining a preset division length, where the preset division length may be determined according to the needs of practical applications, for example, the preset division length may be determined according to the length of the target road segment and/or the historical road condition information of the target road segment, and in an embodiment of the present disclosure, the preset division length may be set to 50-80 meters, for example; and then dividing the target road segment into more than two target sub-road segments by the preset dividing length, wherein when the target road segment is divided by the preset dividing length, a target sub-road segment with a length less than the preset dividing length is remained since the length of the target road segment may not be divided by the preset dividing length, but it should be noted that even if the length of the target sub-road segment is less than the preset dividing length, the target sub-road segment is still used as a target sub-road segment to participate in subsequent road condition processing.

In an embodiment of the present disclosure, after the step S103 of obtaining the number of objects passing through the target sub-link within a set time length before the current time, the method may further include the following steps:

the number of objects is modified based on the permeation parameter.

In this embodiment, the number of objects is also corrected based on the penetration parameter, considering that the penetration rate may be different for different road sections, which may cause a difference in comparison criteria for the number of objects. Wherein the permeability refers to a ratio of the number of vehicles acquired based on the trajectory data to the actual number of vehicles on the road per unit time, the permeability parameter is obtained based on the permeability, and the calculation of the permeability parameter will be described in detail below.

In an embodiment of the present disclosure, the step of correcting the number of the objects based on the permeation parameter may include the steps of:

In this embodiment, the number of objects is corrected based on a permeability parameter, specifically, a reference permeability and a permeability of the target sub-road section are firstly obtained, where the reference permeability may be determined based on permeability data of a plurality of road sections and requirements of practical application, for example, the reference permeability may be set to 30%, that is, a reference proportion of the number of vehicles obtained based on trajectory data in a unit time to the actual number of vehicles on the road is 30%; then dividing the reference permeability by the permeability of the target sub-road section to obtain a permeability parameter, wherein if the reference permeability is 30% and the permeability of the target sub-road section is 10%, the permeability parameter is 30%/10% =3; and finally, multiplying the number of the objects by the penetration parameter to realize the standardized correction of the number of the objects, so that the comparison of the number of the objects is on the same standard level.

In an embodiment of the present disclosure, it may be directly determined whether the road condition of a certain target sub-road section is heavily congested, slow-moving, normally unblocked, or extremely unblocked based on a comparison between the number of objects of the certain target sub-road section and an object number threshold corresponding to the road condition. That is, in this embodiment, the step S104 of determining the road condition of the target sub-section based on the number of the objects may include the steps of:

comparing the object quantity of the target sub-road section with an object quantity threshold corresponding to the road condition to determine the road condition of the target sub-road section, wherein the object quantity threshold comprises the following steps in descending order of the threshold: a severe congestion threshold, a crawl threshold, a regular clear threshold, and an extreme clear threshold.

In this embodiment, the road condition of the target sub-segment is determined by comparing the number of objects in the target sub-segment with the threshold of the number of objects corresponding to the road condition, for example, if the number of objects in the target sub-segment is greater than or equal to the severe congestion threshold, it may be determined that the road condition of the target sub-segment is severe congestion; if the number of the objects of the target sub-road section is less than the serious congestion threshold value and is greater than or equal to the congestion threshold value, determining that the road condition of the target sub-road section is congested; if the number of the objects of the target sub-road section is smaller than the congestion threshold and is larger than or equal to the delay threshold, determining that the road condition of the target sub-road section is delay; if the number of the objects of the target sub-road section is smaller than the slow running threshold value and is larger than or equal to the conventional unblocked threshold value, determining that the road condition of the target sub-road section is unblocked; and if the number of the objects of the target sub-road section is less than the conventional unblocked threshold value or less than the conventional unblocked threshold value and greater than or equal to the speed unblocked threshold value, determining that the road condition of the target sub-road section is the speed unblocked.

Specific values of the severe congestion threshold, the slow traffic threshold, the normal clear threshold and the extreme speed clear threshold can be set according to the requirements of practical application, and the specific values are not particularly limited in the disclosure. The threshold may be a uniform threshold for the road condition, or may be a threshold for determining the corresponding road condition for each sub-road section according to the condition of each sub-road section.

In another embodiment of the present disclosure, after the road conditions of the road sections have been determined according to four situations, namely, severe congestion, slow driving and normal smooth driving, the road sections with the road conditions being normal smooth driving can be selected as the target road sections for further distinguishing, that is:

and then determining whether the conventional smooth road condition of the target road section needs to be maintained or needs to be updated to or partially updated to the extremely-fast smooth road condition.

In this embodiment, the determination of the four road conditions, i.e., heavy congestion, slow driving and normal clear driving, can be implemented by any existing technology grasped by those skilled in the art, and does not affect the implementation of the present disclosure, and should not be considered as a limitation of the present disclosure. Specifically, in another embodiment of the present disclosure, the step S104 of determining the road condition of the target sub-road section based on the number of the objects may include the following steps:

In the prior art, the traffic state of a road is usually determined according to the vehicle speed, for example, when the vehicle speed is high, the traffic state of the road is determined to be clear, when the vehicle speed is low, the traffic state of the road is determined to be slow, and when the vehicle speed is low, the traffic state of the road is determined to be congested or severely congested. However, in an actual scene, the traffic state is also a smooth state, and the traffic conditions of the roads may have a great difference, for example, in the three scenes shown in fig. 2A to 2C, the traffic states of the roads are smooth, but actually, the traffic density and the driving feeling of the user have a great difference, and obviously, in the scene with low traffic density, the driving feeling of the user is relatively easier, and the safety hazard is relatively easier to control. Therefore, in this embodiment, the clear road traffic status is further distinguished based on the vehicle density, so that the clear road traffic is more hierarchical, and a richer information expression is provided for the user, specifically, whether the road status of the target sub-section is kept normal clear or updated to be extremely clear is determined by comparing the number of objects of the target sub-section with the threshold value of the extremely clear traffic. For example, if the number of objects in the target sub-segment is greater than or equal to the speed clear threshold, it may be determined that the road condition of the target sub-segment should be kept as normal clear; if the number of the objects of the target sub-road section is smaller than the speed unimpeded threshold value, it can be determined that the road condition of the target sub-road section should be updated to be speed unimpeded.

In one embodiment of the present disclosure, the factors affecting the speed-of-extreme clear threshold or the conventional clear threshold of the target sub-segment include one or more of the following factors: road type, number of lanes, vehicle density and traffic speed.

Considering that factors such as road types, number of lanes, vehicle density and passing speed of different road sections are different, and the factors can influence the road condition judgment standard of the road sections, for example, because speed limits of two different road types, namely an expressway and an expressway, are different, the number of crossroads is different, traveling purposes of users are different, and road surface interference factors are different, so that the judgment standard of smooth road conditions of different road types and the body feeling of the users are different; for example, for roads with different lanes, the movement spaces of vehicles are different, so that the user experience is more friendly for roads with more lanes under the condition of the same traffic flow; for another example, different traffic speeds have different influences on smooth road conditions, and on one hand, the driving experience of a user is generally not very friendly when the speed is low, and on the other hand, the vehicle densities on roads with different speeds are different under the condition of the same flow. Therefore, in this embodiment, the road type, the number of lanes, the vehicle density and the traffic speed are used as factors affecting the maximum speed clear threshold or the conventional clear threshold of the target sub-road segment, that is, the corresponding object quantity threshold is determined for different road segments, wherein the selection of the object quantity threshold corresponding to different factors can be determined according to the needs of practical application, and the disclosure does not specifically limit the same.

In an embodiment of the present disclosure, the step S105 of fusing the road condition of the target sub-section to obtain the road condition of the target section may include the following steps:

if the proportion between the number of the target sub-road sections with the normal smooth road condition and the total number of the target sub-road sections is greater than or equal to a preset proportion threshold value, keeping the normal smooth road condition of the target road section;

When the road conditions of the target sub-road sections are fused to determine the road conditions of the target road sections, taking the road conditions occupying most of the target road sections as the road conditions of the target road sections, and specifically, when the conventional smoothness occupies most, namely the ratio between the number of the target sub-road sections with the conventional smoothness and the total amount of the target sub-road sections included in the target road sections is greater than or equal to a preset ratio threshold value, determining the road conditions of the target road sections as more conventional smoothness; and when the highest speed is the majority, namely the ratio of the number of the target sub-road sections with the highest speed to the total number of the target sub-road sections is greater than or equal to the preset ratio threshold, determining the road condition of the target road section as more highest speed unblocked.

In an embodiment of the present disclosure, after determining the road condition of the target sub-section based on the number of the objects, the method may further include:

In this embodiment, for a target road segment with a longer length, adjacent target sub-road segments with the same road condition included in the target road segment may be merged, that is, when the length of the target road segment is greater than a first preset length threshold, the target sub-road segments with the same road condition and adjacent to the target road segment may be merged into a new target sub-road segment. For example, assuming that the target road segment with the length greater than the first preset length threshold is divided into 10 target sub-road segments, wherein the 1 st target sub-road segment L1 is unblocked at the highest speed, the 2 nd to 3 rd target sub-road segments L2 to L3 are unblocked at the normal speed, the 4 th to 6 th target sub-road segments L4 to L6 are unblocked at the target speed, the 7 th target sub-road segment L7 is unblocked at the normal speed, the 8 th to 9 th target sub-road segments L8 to L9 are unblocked at the highest speed, and the 10 th target sub-road segment L10 is unblocked at the normal speed, at this time, the adjacent target sub-road segments L2 to L3, L4 to L6, and L8 to L9 with the same road condition can be respectively merged into a new target sub-road segment: l23, L456 and L89, and finally obtaining the target road section consisting of six target sub-sections such as L1, L23, L456, L7, L89 and L10. The first preset length threshold may be set according to a requirement of an actual application, which is not specifically limited by the present disclosure, for example, the value of the first preset length threshold may be 10km.

In an embodiment of the present disclosure, after determining the road condition of the target sub-road section based on the number of the objects, the method may further include the following steps:

The partial road section lacking the road condition refers to a special road section such as a tunnel and/or a ramp.

Considering that due to the precision problem of signal transmission, object data of special road sections such as tunnels and/or ramps usually lack certain accuracy and integrity, the road sections with the special road sections such as tunnels and/or ramps usually lack the part of road condition data, and considering that the road conditions are usually closely related to the road conditions at the entrance and exit of the special road sections, and most of the time, the road conditions of the special road sections such as tunnels and/or ramps are short, at the moment, in order to improve the reliability of the road condition data, the smooth filling of the part of road sections including the missing road conditions can be carried out. However, considering that a certain traffic condition usually has continuity, that is, the traffic condition usually changes slowly, and usually, a transition from congestion or severe congestion to smooth does not occur, or a transition from slow running, congestion or severe congestion to extremely fast smooth does not occur, therefore, when a target road segment to which a part of a road segment lacking the traffic condition belongs includes non-smooth road segments such as slow running, congestion, severe congestion, and the like, the traffic condition of the part of the road segment lacking the traffic condition is not filled, but the traffic condition of the part of the road segment lacking the traffic condition is calculated based on the actually measured object data.

As mentioned above, the partial road section lacking the road condition may include a special road section such as a tunnel and/or a ramp. The step of determining the road conditions of the partial road sections missing the road conditions in the target road section based on the road conditions of the target sub-road sections may include the following steps:

alternatively, the first and second liquid crystal display panels may be,

when the part of the road section lacking the road condition is the ramp,

and acquiring the road condition of a target sub-road section to which the ramp outlet belongs as the road condition of the ramp.

Considering that the road conditions of the tunnel entrance and the tunnel exit are generally closely related to the road conditions of the road section where the tunnel entrance and the tunnel exit are located, when the partial road section lacking the road conditions is the tunnel, the road conditions of the target sub-road section to which the tunnel entrance belongs are obtained and taken as the road conditions of the tunnel entrance, and the road conditions of the target sub-road section to which the tunnel exit belongs are obtained and taken as the road conditions of the tunnel exit. If the entrance road condition is consistent with the exit road condition, the entrance road condition and the exit road condition are proved to have certain authenticity and credibility, and at the moment, the road condition of the tunnel can be determined as the entrance road condition or the exit road condition.

Considering that the road condition of the ramp is usually closely related to the road condition of the road segment corresponding to the exit of the ramp, when the partial road segment lacking the road condition is the ramp, the road condition of the target sub-road segment belonging to the ramp exit can be directly used as the road condition of the ramp.

In an embodiment of the present disclosure, the method may further include the steps of:

and correcting the road condition of the target road section.

Considering that different road conditions which are frequently staggered may cause interference to users, and meanwhile, different road conditions which are frequently staggered may also have certain unreasonable factors, in this embodiment, after the road conditions of the target sub-road section are fused to obtain the road conditions of the target road section, the road conditions of the target road section may be further corrected, so as to improve the accuracy and reliability of the road condition data.

In an embodiment of the present disclosure, the step of correcting the road condition of the target road segment may include the steps of:

and when the length of the road section part with different road conditions in the target road section is greater than a second preset length threshold value, taking the road condition with a larger proportion in the road section part with different road conditions as the road condition of the road section part.

As mentioned above, based on the consideration of accuracy and reliability, the different road conditions that are frequently staggered need to be corrected, and specifically, when the length of the section having different road conditions in the target road section is greater than the second preset length threshold, the road condition that is greater in the section having different road conditions may be used as the road condition of the section. For example, suppose a certain target road segment is divided into 10 target sub-road segments, wherein the 1 st to 2 nd target sub-road segments L1 to L2 are all conventional unblocked, the 3 rd target sub-road segment L3 is extremely fast unblocked, the 4 th target sub-road segment L4 is conventional unblocked, the 5 th target sub-road segment L5 is extremely fast unblocked, the 6 th target sub-road segment L6 is conventional unblocked, the 7 th target sub-road segment L7 is also extremely fast unblocked, the 8 th to 9 th target sub-road segments L8 to L9 are all conventional unblocked, and the 10 th target sub-road segment L10 is extremely fast unblocked, that is, the target sub-road segments L2 to L8 have the condition that different road conditions are frequently staggered, at this time, the proportion of conventional unblocked in the 7 target sub-road segments L2 to L8 can be counted as 4/7, and the proportion of extremely fast unblocked as 3/7, so that the road conditions of the target sub-road segments L2 to L8 can be determined as large road conditions, that is conventional unblocked. The second preset length threshold may be set according to the actual application requirement and the road type of the road segment, which is not specifically limited by the present disclosure, for example, for an expressway, the second preset length threshold may be set to 2km, and for an expressway, the second preset length threshold may be set to be longer, for example, 5km.

The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods.

Fig. 3 is a block diagram illustrating a structure of a road condition determining apparatus according to an embodiment of the present disclosure, which may be implemented as part or all of an electronic device through software, hardware, or a combination of the two. As shown in fig. 3, the road condition determining apparatus includes:

a first determination module 301 configured to determine a target road segment;

a segmentation module 302 configured to segment the target segment into two or more target sub-segments;

an obtaining module 303, configured to obtain the number of objects passing through the target sub-road segment within a set duration before the current time;

a second determining module 304 configured to determine the road condition of the target sub-section based on the number of the objects;

a fusion module 305 configured to fuse the road conditions of the target sub-segment to obtain the road conditions of the target segment, where the road conditions include: severe congestion, sluggish, regular clear, and extreme clear (or, extreme clear).

When severe congestion, slow running, normal running and extreme speed running are displayed, rendering can be carried out on the colors corresponding to the severe congestion, the congestion corresponds to a deep red system, the congestion corresponds to a red system, the slow running uses a yellow system, the normal running uses a green system, and the extreme speed running uses a deep green system.

As mentioned above, with the development and progress of society, vehicles on roads are increasing, and many users can check traffic real-time road condition data through map navigation application software before going out, so as to determine a traveling time, a traveling mode or a traveling route. However, the current real-time traffic road condition data generally includes only four road conditions, namely smooth road conditions, slow road conditions, congestion road conditions and severe congestion road conditions, which are respectively identified by green, yellow, red and dark red, and the four road conditions basically cover the common actual traffic state of the road, but the refinement degree is still insufficient, so that the information amount of the traffic road condition information obtained by the user is insufficient, that is, the accuracy of the trip decision or the driving decision of the user has a further optimization space.

In view of the above problem, in this embodiment, a road condition determining device is provided, which further distinguishes smooth road conditions based on the determination and fusion of the road conditions of the target sub-road segments. The technical scheme can improve the richness and the hierarchy of the traffic road condition information, improve the information quantity of the traffic road condition information provided for the user, provide data support for the user to select a more smooth road, and is favorable for realizing the maintenance and the guarantee of traffic safety.

In an embodiment of the present disclosure, the traffic determination device may be implemented as a computer, a computing device, an electronic device, a server, a service cluster, and the like, which can perform traffic determination.

In an embodiment of the present disclosure, the target sub-segment refers to a sub-segment obtained by dividing the target segment for performing a detailed analysis on a road condition of the target segment, where the number of the target sub-segments is two or more.

In the above embodiment, the target road segment to be processed is first determined, and then the target road segment is divided into two or more shorter target sub-segments; then acquiring the number of objects passing through the target sub-road section within a set time length before the current time; and then determining the road condition of the target sub-road section based on the number of the objects, and fusing the road condition of the target sub-road section, for example, combining the road condition of each target sub-road section according to the division sequence of the target sub-road section to obtain the road condition of the target road section. Wherein the road conditions include: the method comprises the steps of severe congestion, slow traffic, normal clear and extreme clear traffic, wherein the normal clear refers to normal clear road conditions, and the extreme clear refers to more clear road conditions. Compared with the road section road condition content in the prior art, the road condition content of the target road section is richer, so that the information content of traffic road condition information provided for a user can be improved, the user can select a more smooth road based on the richer smooth road condition, and meanwhile, the user fatigue caused by the overlong bad driving time of the road condition and the potential safety hazard caused by the user fatigue can be avoided.

In an embodiment of the present disclosure, the segmentation module 302 may be configured to:

determining a preset segmentation length;

In order to reduce the calculation amount of the road condition and reduce the instantaneous calculation pressure, the target road section can be divided into more than two target sub-road sections, and then the target sub-road sections are respectively subjected to road condition calculation and then are fused. When the target road segment is divided into more than two target sub-road segments, first determining a preset division length, where the preset division length may be determined according to a requirement of an actual application, for example, determining the preset division length according to a length of the target road segment and/or historical road condition information of the target road segment, and in an embodiment of the present disclosure, the preset division length may be set to 50-80 meters, for example; and then dividing the target road segment into more than two target sub-road segments by the preset dividing length, wherein when the target road segment is divided by the preset dividing length, a target sub-road segment with a length less than the preset dividing length is remained since the length of the target road segment may not be divided by the preset dividing length, but it should be noted that even if the length of the target sub-road segment is less than the preset dividing length, the target sub-road segment is still used as a target sub-road segment to participate in subsequent road condition processing.

In an embodiment of the present disclosure, after the obtaining module 303, the method may further include:

a first correction module configured to correct the number of objects based on a penetration parameter.

In this embodiment, the number of objects is also corrected based on the permeability parameter, considering that the permeability may be different for different road sections, which may cause a difference in comparison criteria for the number of objects. The permeability refers to a ratio of the number of vehicles acquired based on the trajectory data to the actual number of vehicles on the road in a unit time, the permeability parameter is obtained based on the permeability, and the calculation of the permeability parameter will be described in detail below.

In an embodiment of the present disclosure, the part for correcting the number of objects based on the infiltration parameter may be configured to:

In this embodiment, the number of objects is corrected based on a permeability parameter, specifically, a reference permeability and a permeability of the target sub-road section are firstly obtained, where the reference permeability may be determined based on permeability data of a plurality of road sections and requirements of practical application, for example, the reference permeability may be set to 30%, that is, a reference proportion of the number of vehicles obtained based on trajectory data in a unit time to the actual number of vehicles on the road is 30%; then dividing the reference permeability by the permeability of the target sub-road section to obtain a permeability parameter, wherein if the reference permeability is 30% and the permeability of the target sub-road section is 10%, the permeability parameter is 30%/10% =3; and finally, multiplying the number of the objects by the penetration parameter to realize the benchmarking correction of the number of the objects, so that the comparison of the number of the objects is on the same benchmark level.

In an embodiment of the present disclosure, it may be directly determined whether the road condition of a certain target sub-road section is heavily congested, slow-moving, normally unblocked, or extremely unblocked based on a comparison between the number of objects of the certain target sub-road section and an object number threshold corresponding to the road condition. That is, in this embodiment, the second determination module 304 may be configured to:

In this embodiment, the road condition of the target sub-segment is determined by comparing the number of objects in the target sub-segment with the threshold of the number of objects corresponding to the road condition, for example, if the number of objects in the target sub-segment is greater than or equal to the severe congestion threshold, it may be determined that the road condition of the target sub-segment is severe congestion; if the number of the objects of the target sub-road section is less than the serious congestion threshold and is more than or equal to the congestion threshold, determining that the road condition of the target sub-road section is congested; if the number of the objects of the target sub-road section is less than the congestion threshold and is greater than or equal to the delay threshold, determining that the road condition of the target sub-road section is delay; if the number of the objects of the target sub-road section is smaller than the slow running threshold value and is larger than or equal to the conventional unblocked threshold value, determining that the road condition of the target sub-road section is unblocked; and if the number of the objects of the target sub-road section is less than the conventional unblocked threshold value or less than the conventional unblocked threshold value and greater than or equal to the speed unblocked threshold value, determining that the road condition of the target sub-road section is the speed unblocked.

In another embodiment of the present disclosure, after the road conditions of the road segments have been determined according to four situations, namely, heavy congestion, slow traveling and normal clear, the road segments with the road conditions being normal clear are selected as the target road segments to be further distinguished, that is:

In this embodiment, the determination of the four road conditions, i.e., heavy congestion, slow driving and normal smooth driving, can be implemented by any existing technology grasped by those skilled in the art, and does not affect the implementation of the present disclosure, and should not be considered as a limitation to the present disclosure. Specifically, in another embodiment of the present disclosure, the second determining module 304 may be configured to:

In the prior art, the traffic state of a road is usually determined according to the vehicle speed, for example, when the vehicle speed is high, the traffic state of the road is determined to be clear, when the vehicle speed is low, the traffic state of the road is determined to be slow, and when the vehicle speed is low, the traffic state of the road is determined to be congested or severely congested. However, in an actual scene, the traffic state is also a smooth state, and there may be a great difference in the traffic conditions of the roads, for example, as shown in fig. 2A to fig. 2C, the traffic states of the roads are smooth, but actually, the traffic density and the driving feeling of the user have great difference, and obviously, in a scene with a small traffic density, the driving feeling of the user is relatively easier, and the safety hazard is relatively easier to control. Therefore, in this embodiment, the clear road traffic status is further distinguished based on the vehicle density, so that the clear road traffic is more hierarchical, and a richer information expression is provided for the user, specifically, whether the road status of the target sub-section is kept normal clear or updated to be extremely clear is determined by comparing the number of objects of the target sub-section with the threshold value of the extremely clear traffic. For example, if the number of objects in the target sub-segment is greater than or equal to the speed clear threshold, it may be determined that the road condition of the target sub-segment should be kept as normal clear; if the number of the objects of the target sub-road section is smaller than the threshold value of the speed smoothness, it can be determined that the road condition of the target sub-road section should be updated to be speed smoothness.

Considering that factors such as road types, number of lanes, vehicle density and passing speed of different road sections are different, and the factors can influence the road condition judgment standard of the road sections, for example, because speed limits of two different road types, namely an expressway and an expressway, are different, the number of crossroads is different, traveling purposes of users are different, and road surface interference factors are different, so that the judgment standard of smooth road conditions of different road types and the body feeling of the users are different; for example, for roads with different lanes, the movement spaces of vehicles are different, so that the user experience is more friendly for roads with more lanes under the condition of the same traffic flow; for another example, different traffic speeds have different effects on smooth road conditions, and on one hand, the driving experience of a user is generally not friendly when the speed is low, and on the other hand, the vehicle densities on roads with different vehicle speeds under the same flow rate are also different. Therefore, in this embodiment, the road type, the number of lanes, the vehicle density and the traffic speed are used as factors that affect the maximum speed clear threshold or the normal clear threshold of the target sub-road segment, that is, the corresponding object quantity threshold is determined for different road segments, where the selection of the object quantity threshold corresponding to different factors may be determined according to the needs of practical application, and this disclosure does not specifically limit this.

In an embodiment of the present disclosure, the fusion module 305 may be configured to:

and if the proportion between the number of the target sub-road sections with the road condition being extremely fast unblocked and the total number of the target sub-road sections is greater than or equal to the preset proportion threshold value, updating the road condition of the target road sections into the extremely fast unblocked road condition.

When the road conditions of the target sub-road sections are fused to determine the road conditions of the target road sections, taking the road conditions occupying most of the target road sections as the road conditions of the target road sections, and specifically, when the conventional smoothness occupies most, namely the ratio between the number of the target sub-road sections with the conventional smoothness and the total amount of the target sub-road sections included in the target road sections is greater than or equal to a preset ratio threshold value, determining the road conditions of the target road sections as more conventional smoothness; and when the extremely-fast unblocked road section accounts for most parts, namely the proportion between the number of the target sub-road sections with the extremely-fast unblocked road condition and the total number of the target sub-road sections is greater than or equal to the preset proportion threshold value, determining the road condition of the target road section as more extremely-fast unblocked road sections.

In an embodiment of the present disclosure, after the second determining module 304, the method may further include:

and the merging module is configured to merge adjacent target sub-road sections with the same road condition in the target road section into a new target sub-road section when the length of the target road section is greater than a first preset length threshold.

and the third determining module is configured to determine the road conditions of the partial road sections missing the road conditions in the target road section based on the road conditions of the target sub-road sections.

Considering that due to the accuracy problem of signal transmission, object data of special road sections such as tunnels and/or ramps usually lacks certain accuracy and integrity, road sections with special road sections such as tunnels and/or ramps usually lack the part of road condition data, and considering that the road conditions are usually closely related to road conditions at the entrances and exits of the roads, and most of the time, the road conditions of the special road sections such as tunnels and/or ramps are short-time, in order to improve the reliability of the road condition data, the parts of road sections including the missing road conditions can be filled smoothly. However, considering that a certain traffic condition usually has continuity, that is, the traffic condition usually changes slowly, and a transition from congestion or severe congestion to clear or a transition from slow running, congestion or severe congestion to extremely fast clear does not occur, therefore, when a target road segment to which a part of road segments lacking the traffic condition belong includes non-clear road segments such as slow running, congestion, severe congestion, etc., the road condition of the part of road segments lacking the traffic condition is not filled, but the road condition of the part of road segments lacking the traffic condition is calculated based on the actually measured object data.

As mentioned above, the partial road section lacking the road condition may include a special road section such as a tunnel and/or a ramp. The third determination module may be configured to:

when the part of the road section lacking the road condition is the tunnel,

alternatively, the first and second electrodes may be,

when the partial road section lacking the road condition is the ramp,

Considering that the road conditions of the ramp are usually closely related to the road conditions of the corresponding road sections at the exit of the ramp, when the partial road sections lacking the road conditions are the ramps, the road conditions of the target sub-road sections at the exit of the ramp can be directly used as the road conditions of the ramp.

In an embodiment of the present disclosure, the apparatus may further include:

a second correction module configured to correct the road condition of the target road segment.

In an embodiment of the present disclosure, the second modification module may be configured to:

The embodiment of the disclosure also discloses a navigation service, wherein a road condition determination result of a navigated object is obtained based on the road condition determination method, and a navigation guidance service of a corresponding scene is provided for the navigated object based on the road condition determination result. Wherein, the corresponding scene is one or a combination of more of AR navigation, overhead navigation or main and auxiliary road navigation.

The embodiment of the disclosure also discloses a navigation method, wherein a navigation route calculated at least based on the starting point, the end point and the road condition is obtained, and navigation guidance is performed based on the navigation route, and the road condition is realized based on any one of the methods.

In one embodiment of the disclosure, the road condition is displayed on the navigation route based on rendering and dyeing respectively corresponding to severe congestion, slow running, normal unblocked and extreme unblocked, wherein the visual effect of extreme unblocked expresses a state that the road is easier or safer to run than the normal unblocked road.

The present disclosure also discloses an electronic device, fig. 4 shows a block diagram of an electronic device according to an embodiment of the present disclosure, and as shown in fig. 4, the electronic device 400 includes a memory 401 and a processor 402; wherein the content of the first and second substances,

the memory 401 is used to store one or more computer instructions that are executed by the processor 402 to implement the above-described method steps.

Fig. 5 is a schematic structural diagram of a computer system suitable for implementing a road condition determining method according to an embodiment of the present disclosure.

As shown in fig. 5, the computer system 500 includes a processing unit 501 that can execute various processes in the above-described embodiments according to a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. In the RAM503, various programs and data necessary for the operation of the system 500 are also stored. The processing unit 501, the ROM502, and the RAM503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.

The following components are connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output portion 507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary. The processing unit 501 may be implemented as a CPU, a GPU, a TPU, an FPGA, an NPU, or other processing units.

In particular, the above described methods may be implemented as computer software programs, according to embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a medium readable thereby, the computer program comprising program code for performing the road condition determining method. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, a program segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units or modules described in the embodiments of the present disclosure may be implemented by software or hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.

As another aspect, the disclosed embodiment also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus in the foregoing embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the embodiments of the present disclosure.

The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combinations of the above-mentioned features, and that other embodiments can be made by any combination of the above-mentioned features or their equivalents without departing from the spirit of the invention. For example, the above features and (but not limited to) the features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.

Claims

1. A road condition determining method comprises the following steps:

determining a target road section;

dividing the target road section into more than two target sub-road sections;

and fusing the road condition of the target sub-road section to obtain the road condition of the target road section, wherein the road condition comprises: severe congestion, slow traffic, regular traffic and extreme traffic.

2. The method of claim 1, wherein after obtaining the number of objects passing through the target sub-segment within a set duration before the current time, further comprising:

the number of objects is modified based on a permeability parameter.

3. The method of claim 2, wherein the modifying the number of objects based on the permeation parameter comprises:

4. The method according to any one of claims 1-3, wherein the determining the road condition of the target sub-segment based on the number of objects comprises:

5. The method according to any one of claims 1-4, wherein the target road segment is a road segment for which a predetermined road condition is normally clear, and determining the road condition of the target sub-segment based on the number of objects comprises:

and comparing the number of the objects of the target sub-road section with an extreme speed unblocked threshold value, and determining whether the road condition of the target sub-road section is kept normally unblocked or updated to be extreme speed unblocked.

6. The method of claim 5, wherein factors affecting an extreme speed clear threshold or a conventional clear threshold of the target sub-segment include one or more of: road type, number of lanes, vehicle density and traffic speed.

7. The method according to claim 5, wherein the fusing the road conditions of the target sub-segment to obtain the road conditions of the target segment comprises:

8. The method of claim 5, wherein after determining the road condition for the target sub-segment based on the number of objects, further comprising:

9. The method of claim 5, wherein the determining the road condition of the target sub-segment based on the number of objects further comprises:

10. The method of claim 9, wherein the determining the road conditions of the partial road segments of the target road segment lacking the road conditions based on the road conditions of the target sub-road segments comprises:

when the part of the road section lacking the road condition is the tunnel,

alternatively, the first and second electrodes may be,

when the partial road section lacking the road condition is the ramp,

11. A road condition determining apparatus comprising:

a first determination module configured to determine a target road segment;

12. A computer readable storage medium having computer instructions stored thereon, wherein the computer instructions, when executed by a processor, implement the method steps of any of claims 1-10.

13. A navigation method, wherein a navigation route calculated at least based on a starting point, an end point and a road condition is obtained, and navigation guidance is performed based on the navigation route, wherein the road condition is realized based on any one of the methods of claims 1 to 10.

14. The method of claim 13, wherein the road conditions are displayed on the navigation route based on respective corresponding rendering dyeings of severe congestion, slow driving, normal clear, and extreme clear, wherein the visual effect of extreme clear expresses a condition that the road is easier or safer to drive than a normal clear road.