CN111613049B

CN111613049B - Road state monitoring method and device

Info

Publication number: CN111613049B
Application number: CN201910143419.5A
Authority: CN
Inventors: 吴学新; 孙伟力; 张莉
Original assignee: Beijing Didi Infinity Technology and Development Co Ltd
Current assignee: Beijing Didi Infinity Technology and Development Co Ltd
Priority date: 2019-02-26
Filing date: 2019-02-26
Publication date: 2022-07-12
Anticipated expiration: 2039-02-26
Also published as: CN111613049A

Abstract

The application provides a road state monitoring method and a device, wherein the method comprises the following steps: acquiring target vehicle track data of a vehicle driving through a target road within a preset time period; determining traffic flow change information of the target road in the preset time period according to the target vehicle track data; and determining the traffic state change information of the target road in the preset time period according to the traffic flow change information. The method and the device for obtaining the traffic state change information of the target road in the preset time period are used for determining the traffic state change information of the target road based on the vehicle track data, and compared with a current traffic state change information obtaining mode, the information obtaining is more timely and more efficient.

Description

Road state monitoring method and device

Technical Field

The application relates to the technical field of big data, in particular to a road state monitoring method and device.

Background

With the complication of traffic networks, the problem of low efficiency of traffic becomes one of the hot spots currently concerned by people. In order to improve the traffic efficiency of roads and rationalize the functions of a traffic network, a traffic management department can change the road functions according to the actual use conditions of the roads, such as forbidding the left-turn function of the roads, changing the two-way roads into one-way roads, and the like.

The change information of the road state in the traffic road network has important significance for analyzing whether the road network change measures are reasonable or not, and the problem of low hysteresis and acquisition efficiency exists when the change information of the road state of the road is mainly acquired in a manual acquisition mode at present.

Disclosure of Invention

In view of this, an object of the embodiments of the present application is to provide a road state monitoring method and apparatus, which can automatically generate traffic state change information of a target road in a preset time period based on vehicle trajectory data.

In a first aspect, an embodiment of the present application provides a road condition monitoring method, including:

acquiring target vehicle track data of a vehicle driving through a target road within a preset time period;

determining traffic flow change information of the target road in the preset time period according to the target vehicle track data;

and determining the traffic state change information of the target road in the preset time period according to the traffic flow change information.

In an optional implementation manner, the determining, according to the target vehicle trajectory data, traffic flow change information of the target road in the preset time period includes:

determining the flow of a plurality of acquisition time points in the preset time period according to the target vehicle track data;

and determining traffic flow change information of the target road in the preset time period according to the traffic flow at different acquisition time points.

In an optional implementation manner, before determining the traffic flow change information of the target road in the preset time period according to the traffic flows at different collection time points, the method further includes:

detecting whether the flow at each acquisition time point is abnormal or not;

and if so, correcting the flow at the abnormal acquisition time point.

In an optional embodiment, the detecting whether there is an abnormality in the flow rate at each collection time point includes:

for each acquisition time point, performing:

determining a plurality of acquisition time points of which the time difference with the acquisition time point is within a first preset time difference threshold;

acquiring outlier factors corresponding to the acquisition time points according to the acquisition time points and the determined flow rates of the plurality of acquisition time points;

and determining whether the flow corresponding to the acquisition time point is abnormal or not according to the outlier factor corresponding to the acquisition time point.

In an optional implementation manner, the determining whether there is an abnormality in the flow rate corresponding to the acquisition time point according to the outlier factor corresponding to the acquisition time point includes:

detecting whether the outlier factor corresponding to the acquisition time point is larger than a preset outlier factor threshold value or not; if so, determining that the flow corresponding to the acquisition time point is abnormal.

clustering each acquisition time point according to the flow of each acquisition time point to form a plurality of classifications;

for each classification, dividing each acquisition time point in the classification into a plurality of groups according to the continuous relation of each acquisition time point in the classification;

detecting whether the number of the acquisition time points in any one group exceeds a preset number;

if not, the traffic of the collection time point in the packet is considered to be abnormal.

In an optional embodiment, the correcting the flow rate at the abnormal collection time point includes:

determining a plurality of acquisition time points of which the time difference with the acquisition time point with the abnormality is within a second preset time difference threshold;

and determining the average value of the flow of the plurality of determined acquisition time points as the flow of the acquisition time point with the abnormality.

In an optional embodiment, the traffic flow change information includes: the method comprises the steps that a flow value corresponding to at least one target road continuous state and starting time and ending time corresponding to each target road continuous state are obtained;

the determining of the traffic flow change information of the target road in the preset time period according to the traffic flow at different collection time points comprises the following steps:

determining flow change time points from each acquisition time point based on a preset change point identification algorithm;

for any two adjacent flow change time points, executing the following steps:

determining the time of the flow change time point with the time before in the flow change time points adjacent to any two positions as the starting time of the continuous state of the target road, and determining the time of the flow change time point with the time after as the ending time of the continuous state of the target road; and the number of the first and second groups,

and determining a flow value corresponding to the continuous state of the target road according to the flows corresponding to the flow change time points adjacent to any two positions.

In an optional embodiment, the traffic state change information includes: the state change type and the change time of the target road;

the determining the traffic state change information of the target road in the preset time period according to the traffic flow change information includes:

sequencing the continuous states of the target roads according to the sequence of the starting time or the ending time of the continuous states of the target roads; and the number of the first and second groups,

for each adjacent two target road continuation states, executing:

detecting whether the flow values of the continuous states of any two adjacent target roads meet at least one preset condition;

if yes, determining a state change type corresponding to the continuous state of the two arbitrarily adjacent target roads according to the mapping relation between the at least one preset condition and the state change type; and (c) a second step of,

and determining the starting time of the target road continuous state with the later starting time as the change time in the two target road continuous states.

In an optional implementation, acquiring target vehicle trajectory data of a vehicle driving through a target road within a preset time period comprises:

acquiring target vehicle track data of vehicles driving through a target road within a plurality of preset time periods; the time attributes of the starting time and the ending time of the running in different preset time periods are the same;

the determining of the traffic flow change information of the target road in the preset time period according to the target vehicle track data includes:

determining traffic flow change information of the target road in each preset time period according to the target vehicle track data in each preset time period;

and determining the traffic state change information of the target road in each preset time period according to the traffic flow change information of the target road in each preset time period.

In an optional implementation manner, after determining the traffic state change information of the target road in each preset time period according to the traffic flow change information of the target road in each preset time period, the method further includes:

and determining a traffic rule change result of the target road according to the traffic state change information corresponding to each preset time period.

In an optional implementation manner, the determining, according to the traffic state change information corresponding to each preset time period, a traffic rule change result of the target road includes:

judging whether the number of the continuous preset time periods with the same traffic state change information exceeds a preset number threshold or a percentage threshold;

if so, determining a traffic rule change result of the target road based on the traffic state change information of the continuous preset time period which is the same as the traffic state change information.

In a second aspect, an embodiment of the present application provides a road condition monitoring device, including:

the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring target vehicle track data of a vehicle driving through a target road within a preset time period;

the first determining module is used for determining traffic flow change information of the target road in the preset time period according to the target vehicle track data;

and the second determining module is used for determining the traffic state change information of the target road in the preset time period according to the traffic flow change information.

In an optional implementation manner, the first determining module is configured to determine traffic flow change information of the target road in the preset time period according to the target vehicle trajectory data in the following manner:

In an optional embodiment, the first determining module, before determining the traffic flow change information of the target road in the preset time period according to the traffic flow at different collection time points, is further configured to:

detecting whether the flow at each acquisition time point is abnormal or not;

and if so, correcting the flow at the abnormal acquisition time point.

In an alternative embodiment, the first determining module is configured to detect whether there is an abnormality in the flow rate at each collection time point by:

for each acquisition time point, performing:

In an optional embodiment, the first determining module is configured to determine whether there is an abnormality in the flow rate corresponding to the acquisition time point according to the outlier factor corresponding to the acquisition time point by using the following method:

In an optional embodiment, the first determining module is configured to correct the flow at the abnormal acquisition time point by:

the first determining module is used for determining traffic flow change information of the target road in the preset time period according to the traffic flow at different acquisition time points in the following way:

for any two adjacent flow change time points, executing:

determining the time of the flow change time point with the time before in the flow change time points adjacent to any two positions as the starting time of the continuous state of the target road, and determining the time of the flow change time point with the time after as the ending time of the continuous state of the target road; and

and determining a flow value corresponding to the continuous state of the target road according to the flow corresponding to the flow change time points adjacent to any two positions.

the second determining module is configured to determine traffic state change information of the target road in the preset time period according to the traffic flow change information in the following manner:

sequencing the continuous states of the target roads according to the sequence of the starting time or the ending time of the continuous states of the target roads; and

for each adjacent two target road continuation states, executing:

if so, determining the state change type corresponding to the continuous state of the two arbitrary adjacent target roads according to the mapping relation between the at least one preset condition and the state change type; and the number of the first and second groups,

In an alternative embodiment, the acquiring module is configured to acquire target vehicle trajectory data of a vehicle that travels through a target road within a preset time period, and includes:

the first determining module is configured to determine, according to the target vehicle trajectory data, traffic flow change information of the target road in the preset time period in the following manner, where the determining includes:

In an alternative embodiment, the method further comprises: and the third determining module is used for determining a traffic rule change result of the target road according to the traffic state change information corresponding to each preset time period.

In an optional implementation manner, the third determining module is configured to determine a traffic rule change result of the target road according to traffic state change information corresponding to each preset time period by using the following manner, and includes:

In a third aspect, an embodiment of the present application provides an electronic device, including: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating via the bus when the electronic device is running, the machine-readable instructions being executable by the processor to perform the steps of the road condition monitoring method according to any one of the first aspect.

In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to perform the steps of the road condition monitoring method according to any one of the first aspect.

According to the embodiment of the application, the target vehicle track data of the vehicle driving through the target road in the preset time period is acquired, the traffic flow change information of the target road in the preset time period is determined according to the target vehicle track data, and the traffic state change information of the target road in the preset time period is generated according to the traffic flow change information, so that the traffic state change information of the road is automatically generated based on the vehicle track data.

In addition, according to some embodiments of the application, traffic flow change information of the target road in each preset time period can be determined according to the target vehicle track data in each preset time period, traffic state change information of the target road in each preset time period can be determined according to the traffic flow change information of the target road in each preset time period, then a traffic rule change result of the target road is determined according to the traffic state change information corresponding to each preset time period, and then the traffic rule change result of the target road is accurately identified based on the target vehicle track data corresponding to each preset time period.

In order to make the aforementioned objects, features and advantages of the present application comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.

Fig. 1 is a flowchart illustrating a road condition monitoring method provided in an embodiment of the present application;

fig. 2 is a flowchart illustrating a specific manner of determining traffic flow change information of a target road in the preset time period in the road state monitoring method according to the embodiment of the present application;

fig. 3 is a flowchart illustrating a specific manner of determining start time and end time corresponding to each target road duration state in the road status monitoring method according to the embodiment of the present application;

fig. 4 is a flowchart illustrating another specific manner of determining traffic flow change information of the target road in the preset time period according to the target vehicle trajectory data in the road state monitoring method provided in the embodiments of the present application;

fig. 5 is a flowchart illustrating a specific manner of determining traffic state change information of a target road within a preset time period in a road state monitoring method according to embodiments of the present application;

FIG. 6 is a flow chart illustrating another method for monitoring a road condition according to an embodiment of the present disclosure;

fig. 7 is a schematic diagram illustrating a road condition monitoring device provided in an embodiment of the present application;

fig. 8 shows a schematic diagram of an electronic device provided in an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, as generally described and illustrated in the figures herein, could be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined or explained in subsequent figures.

Research shows that the current traffic state change information of the traffic network is usually acquired in a way of actively acquiring road state data from a traffic management department or in a way of actively reporting by a driver when the current traffic state change information is acquired, and the acquisition way of the traffic state change information has certain hysteresis and poor accuracy.

Based on the research, the application provides a road state monitoring method and device, which can determine the traffic state change information of a target road in a preset time period based on vehicle track data, and can obtain the traffic state change information more timely and more accurately compared with the current traffic state change information obtaining mode.

To facilitate understanding of the present embodiment, first, a road condition monitoring method disclosed in the embodiments of the present application is described in detail, and an execution subject of the method for detecting a prevailing inefficiency cause provided in the embodiments of the present application is generally an electronic device with computing capability.

Example one

Referring to fig. 1, a flowchart of a road condition monitoring method provided in an embodiment of the present application is shown, where the method includes steps S101 to S103, where:

s101: target vehicle trajectory data of a vehicle driving through a target road within a preset time period is acquired.

In specific implementation, the preset time period may be specifically set according to actual needs, for example, the preset time period may be set to 15 minutes, one hour, three hours, 5 hours, 24 hours, and the like.

The target road includes: at least one target road segment and/or at least one target intersection. In the case where the target road includes a target section, the target vehicle trajectory data includes trajectory data of a vehicle that has traveled through the target section within a preset time period; in the case where the target road includes a target intersection, the target vehicle trajectory data includes trajectory data of vehicles that have traveled through the target intersection within a preset time period.

The target road segment typically includes at least one road direction, for example, one or more of east west, west east, north, and north south.

The target intersection also typically includes at least one road direction, including, for example: one or more of east-west straight going, east-north turning, east-south turning, west-east straight going, west-north turning, west-south turning, north-south straight going, north-west turning, north-east turning, south-north straight going, south-west turning, and south-east turning.

When the target road includes a target road segment and a target intersection, the target road segment and the target intersection usually have a connection relationship, and the target road segment is usually an upstream road segment or a downstream road segment of at least one road direction of the target intersection, so that the target road segment and the corresponding road direction of the target intersection also have a corresponding relationship. The specific target road setting mode can refer to the prior road setting mode, and is not described in detail herein.

When acquiring target vehicle trajectory data for target roads having different road directions, target vehicle trajectory data of a vehicle driving in the road direction on the target road within a preset time period is acquired for each road direction on the target road.

Correspondingly, in S102, traffic flow change information of the target road in the road direction within a preset time period is determined according to the target vehicle trajectory data corresponding to each road direction.

In step S103, traffic state change information of the target road in each road direction within a preset time period is determined according to traffic flow change information of the target road in each road direction within the preset time period.

Receiving the above S101, the method for monitoring a road state provided in the embodiment of the present application further includes, after acquiring target vehicle trajectory data:

s102: and determining traffic flow change information of the target road in the preset time period according to the target vehicle track data.

In a particular implementation, the flow rate refers to the number of vehicles passing through the target road per unit time. The larger the flow rate, the more vehicles are considered to pass through the target road. The flow values of the target roads are different, and the corresponding target road continuous states are also different.

The target road continuation state includes: pass and no pass. Wherein:

the passage further comprises: unblocked, slow moving and congested; in general, the target road continuation state is a traffic value when the road is congested, which is larger than the traffic value when the road is slow traveling, and which is larger than the traffic value when the road is clear. When the target road is in a continuous state and is in a passing state, the corresponding flow value is usually larger than a certain flow threshold value; it should be noted that, in the case of few or no vehicles passing through the target road, the flow rate corresponding to the target road is less than a certain flow rate threshold.

The traffic prohibition includes: the method is characterized in that the road is totally closed, the road is semi-closed, the left turn is forbidden at the intersection, the right turn is forbidden at the intersection, and the turn around is forbidden at the intersection.

The road is totally closed, and the traffic in a certain road direction is 0 or a numerical value close to 0 due to the fact that the road is semi-closed, the intersection is prohibited from turning left, the intersection is prohibited from turning right and the intersection is prohibited from turning around.

Specifically, referring to fig. 2, an embodiment of the present application further provides a specific manner for determining traffic flow change information of the target road in the preset time period according to the target vehicle trajectory data, including:

s201: and determining the flow of a plurality of acquisition time points in the preset time period according to the target vehicle track data.

Specifically, because the range covered by the target road is relatively large, the flow condition of the target road cannot be comprehensively reflected by using a group of data, and therefore at least one detection position can be set in the target road according to actual needs; for each detection position, a group of flow data corresponding to the detection position exists, namely the flow of the detection position at a plurality of acquisition time points in a preset time period.

For example, for a target road segment, a detection position is respectively arranged at an inlet section and an outlet section of the target road segment, and the detection positions are respectively used for detecting the flow of the inlet section and the outlet section of the target road segment.

Aiming at a target intersection, a detection position can be set in each road direction of the target intersection and is respectively used for detecting the flow data of each phase of the target intersection, wherein each phase corresponds to one road direction.

For each detection position, the flow of each detection position at a plurality of acquisition time points within a preset time period can be acquired in the following manner:

the vehicle track data is a group of data consisting of different positioning points, and each positioning point comprises the geographic coordinates of the positioning point and the positioning time of the positioning point. According to the geographic coordinates of the positioning points and the positioning time of the positioning points, the number of vehicles passing through the detection area in a time period containing the acquisition time point can be determined; the flow rate of the inspection location at the acquisition time point is then determined based on the number of vehicles passing through the inspection area and the duration of a time period containing the acquisition time point.

Such as: assuming that the collection time point is 17: 01' 30 ″, the time period including the collection time point is 17:01 to 17:02, the number of vehicles passing through the detection area at 17:01 to 17:02 is 27, and the duration of the time period is 60 seconds, so that the flow rate of the detection position at the collection time point can be determined to be 0.45 vehicle/second according to the number of vehicles 27 and the duration of the time period of 60 seconds. It should be noted that the unit of the flow rate can be set according to actual needs. For example, 0.45 vehicles/second can also be expressed as: 27 vehicles/minute, 1620 vehicles/hour, etc.

S202: and determining traffic flow change information of the target road in the preset time period according to the traffic flow at different acquisition time points.

In a specific implementation, the traffic flow variation information of the target road in the preset time period may be the traffic flow variation information of each detection position in the preset time period.

The traffic flow change information includes, for each detected position: the flow value corresponding to at least one target road continuous state, and the starting time and the ending time corresponding to each target road continuous state.

Here, the target road may have a plurality of different target road continuation states within a preset time period. Different target road continuous states correspond to different flow values; in one possible case, the flow values for the same target road continuation status are also different.

Referring to fig. 3, in one possible implementation, the start time and the end time corresponding to each target road duration state may be determined in the following manner:

s301: and determining the flow change time point from each acquisition time point based on a preset change point identification algorithm.

S302: for any two adjacent flow change time points, executing:

and determining the time of the flow change time point with the time before as the starting time of the continuous state of the target road, and determining the time of the flow change time point with the time after as the ending time of the continuous state of the target road.

In a specific implementation, a flow change time point may be determined from the respective acquisition time points using, for example, a bayesian network change point identification algorithm, a distance-based change point identification algorithm, or the like.

The variable point identification point algorithm can determine a flow change time point from each acquisition time point, wherein the flow change time point is used for distinguishing different target road continuous states, namely, two adjacent target road continuous states are separated by one flow change time point, and the flow change time point is not only the ending time of the previous target road continuous state, but also the starting time corresponding to the next target road continuous state.

For example, the collection time points include a 1-a 200, and the corresponding collection time points are B1-B200, respectively, wherein the determined flow rate change time points include: a57, A103 and A175, 4 determined target road continuous states are respectively C1-C4, wherein:

if the starting time point corresponding to the target road continuation state C1 is a1 and the ending time point is a57, the enlightenment time corresponding to the target road continuation state C1 is B1 and the ending time is B57;

if the starting time point corresponding to the target road continuous state C2 is a57 and the ending time point is a103, the starting time corresponding to the target road continuous state C2 is B57 and the ending time is B103;

if the starting time point corresponding to the target road continuous state C3 is a103 and the ending time point is a175, the starting time corresponding to the target road continuous state C3 is B103 and the ending time is B175;

if the start time point and the end time point of the target road continuation state C4 are a175 and a200, respectively, the start time and the end time of the target road continuation state C3 are B175 and B200, respectively.

In a possible implementation manner, the flow value corresponding to each target road duration state may be an average value of the flow values corresponding to the respective collection time points of the target road in the target road duration state.

For example, the target roads correspond to the collection time points M1-M100 in one of the target road continuous states, and the flow values corresponding to the collection time points are M1-M100 in sequence, then the flow values corresponding to the target road continuous states may be represented as:

wherein m is_iAnd the flow value corresponding to the ith acquisition time point.

In another possible implementation, the flow value corresponding to each target road continuous state may also be determined according to the flow at any two adjacent flow change time points.

For example, an average value of the flow rates at the flow rate change time points adjacent to the two positions is determined as the flow rate value of the target road continuation state corresponding to the flow rate change time points adjacent to the two positions.

Referring to fig. 4, an embodiment of the present application further provides another specific manner for determining traffic flow change information of the target road in the preset time period according to the target vehicle trajectory data, where the specific manner includes:

s401: and determining the flow of a plurality of acquisition time points in the preset time period according to the target vehicle track data.

Here, the specific implementation method of S401 is similar to that of S201, and is not described herein again.

S402: detecting whether the flow at each acquisition time point is abnormal or not; if yes, jumping to S403; if not, jumping to S405.

In particular implementations, the presence of anomalies in the flow rate at each acquisition time point may be detected in one or more of a variety of ways.

In one possible embodiment, the following method can be used to detect whether there is an anomaly at each acquisition time point:

for each acquisition time point a, performing:

m acquisition time points o with a time difference from the acquisition time point within a first preset time difference threshold are determined₁～o_m(ii) a Acquiring an outlier corresponding to the acquisition time point according to the flow at the acquisition time point and the determined m acquisition times; and determining whether the flow corresponding to the acquisition time point is abnormal or not according to the outlier factor corresponding to the acquisition time point.

In a specific implementation, the outlier factor is used to characterize a magnitude of a difference between the current acquisition time point and the determined flow corresponding to the plurality of acquisition time points. Specifically, the Local Outlier Factor (LOF) may be obtained by using an LOF algorithm.

Here, when determining whether there is an abnormality in the acquisition time point according to the outlier factor, it may be detected whether the outlier factor corresponding to the acquisition time point is greater than a preset outlier factor threshold; if so, determining that the flow corresponding to the acquisition time point is abnormal.

In another possible embodiment, the following method can be further used to detect whether there is an abnormality at each acquisition time point:

clustering each acquisition time point according to the flow of each acquisition time point to form a plurality of classifications; for each classification, dividing each acquisition time point in the classification into a plurality of groups according to the continuous relation of each acquisition time point in the classification; detecting whether the number of the acquisition time points in any one group exceeds a preset number; if not, the traffic of the collection time point in the packet is considered to be abnormal.

Specifically, when clustering is performed on each acquisition time point, any one of the acquisition time points which are not classified may be determined as a clustering center, then a plurality of acquisition time points belonging to the same class as the clustering center are obtained according to the difference between the flow rates of other acquisition time points and the clustering center, and each acquisition time point in the class is determined as the acquisition time point which is classified; returning to the step of determining any one of the collection time points which are not classified as a clustering center; and finishing clustering all the acquisition time points through multiple iterations.

In addition, when clustering is performed on each acquisition time point, a preset number of clustering centers can be determined, and then according to the flow difference between each other acquisition time point and each clustering center, each other acquisition time point is divided into the corresponding classification of each clustering center, so that clustering of all acquisition time points is completed.

After the collection time points are clustered according to the flow corresponding to each collection time point, the flow corresponding to the collection time point in each classification is relatively close. The positions of the different acquisition time points in the time axis may not be adjacent. And if the number of the acquisition time points in a continuous relation with the acquisition time point A in a certain classification is too small, the acquisition time point A is considered as an abnormal acquisition time point.

In order to determine the acquisition time points at which there is an abnormality, the respective acquisition time points in each classification may be divided into a plurality of groups according to whether there is a continuous relationship between the respective acquisition time points in the classification.

For example, the acquisition time points include: A1-A100, A1 and A2 are adjacent acquisition time points on a time axis, and then A1 and A2 are considered to have a continuous relation; a1 and a50 are non-adjacent acquisition time points on the time axis, and a1 and a50 are not considered to have a continuous relationship.

More specifically, for some collection time points, for example, when the collection time points A1-a 100 are clustered, a 30-a 50, a 52-a 54 and a99 are clustered, and the preset number is set to 3. Wherein, A30-A50 are acquisition time points with continuous relation, and A52 and A54 have continuous relation; although the numbers of A52-A54 do not exceed the preset number of 3, and there is no continuous relationship between A50 and A52, but, in the whole time axis, there is only one acquisition time point a51 between a50 and a52, there may be an acquisition time point a51 between a50 and a52 that is an acquisition time point at which there is an anomaly, since all of A30-A50 and A52-A54 have no abnormal acquisition time points, in order to eliminate the occurrence of such a case, in another embodiment of the present application, when detecting whether there is an abnormality in the traffic of the collection time points in a certain packet, except for satisfying that the number of collection time points in the packet does not exceed a preset number, the time difference between the acquisition time point in the packet and the other adjacent packets is larger than a preset time difference threshold value, or the number of acquisition time points existing between the packet and other adjacent packets and not belonging to the same packet is larger than a preset number threshold.

S403: and correcting the flow of the abnormal acquisition time point. Jump to S404.

And obtaining the corrected flow of the abnormal acquisition time point.

Here, the flow rate at the acquisition time point where there is an abnormality may be corrected in the following manner:

determining a plurality of acquisition time points of which the time difference with the acquisition time point with the abnormality is within a second preset time difference threshold; and determining the average value of the flow of the plurality of determined acquisition time points as the flow of the acquisition time point with the abnormality.

Alternatively, the first and second electrodes may be,

determining a preset number of target acquisition time points which have continuous relation with the abnormal acquisition time points; and determining the average value of the flow of the determined preset number of target acquisition time points as the flow of the acquisition time points with abnormity.

For example, in the acquisition time points A1 to a100, if abnormality is detected in a66, it is preset that two acquisition time points are 2, a64 and a65 may be determined as target acquisition time points, a65 and a67 may be determined as target acquisition time points, or a67 and a68 may be determined as target acquisition time points. After the target acquisition time point is determined, the corrected flow of the acquisition time point with the abnormality is determined according to the average value of the flow corresponding to the target acquisition time point, and the detected flow (original flow value) of the acquisition time point with the abnormality is replaced by the corrected flow of the acquisition time point with the abnormality.

S404: and determining traffic flow change information of the target road in the preset time period according to the corrected flow of the abnormal acquisition time point and the flow of the non-abnormal acquisition time point.

Here, the flow rates at different time points for specifying the traffic flow change information are realized by correcting the flow rate at the abnormal collection time point to obtain a corrected flow rate at the abnormal collection time point and flow rates at the collection time points at which no abnormality exists.

S405: and determining traffic flow change information of the target road in the preset time period according to the traffic flow at different acquisition time points.

The specific implementation manner of S404 and S405 is similar to that of S202, and is not described herein again.

With reference to S102, after determining the traffic flow change information of the target road in the preset time period, the embodiment of the present application further includes:

s103: and determining the traffic state change information of the target road in the preset time period according to the traffic flow change information.

In specific implementation, because the traffic values corresponding to different target road continuous states are different, the traffic state change information of the target road in a preset time period can be determined according to the traffic flow change information.

The traffic state change information can represent the conversion condition of the target road in different continuous states. It includes: the type of change in state of the target road and the time of change.

The specific state change type includes two elements: a continuation state before the state of the target road is changed, and a continuation state after the continuation state of the target road is changed.

The change time is the change time of the two previous and next continuous states.

For example, according to the traffic flow change information, it is determined that the flow of the target road section falls to 0 or close to 0 in a certain time period, and the flow of the corresponding entrance section or exit section falls to 0 or close to 0, and then the continuous state of the target road section is converted from passage to road closure. On the contrary, if the flow rate of the target road section rises from 0 to exceed a certain threshold value within a certain time period, and the flow rate of the corresponding entrance section or exit section rises from 0 or close to 0 to exceed the certain threshold value, the continuous state of the target road section is converted from road closure to passing.

If the flow of the target road section is determined to be reduced to 0 or close to 0 in a certain time period according to the traffic flow change information, and the flow of the corresponding entrance section or exit section is reduced to exceed the threshold value, the continuous state of the target road section is converted into semi-closed road from passing. On the contrary, if the flow rate of the target section rises from 0 or close to 0 to exceed a certain threshold value within a certain time period, and the flow rate rise amount of the corresponding entrance section or exit section exceeds the threshold value, the continuous state of the target section is converted from the road semi-closed state to the passing state.

If the left-turn phase flow of the target intersection is determined to be reduced to be close to 0 according to the traffic flow change information, but the flow change of the corresponding road section is smaller, the continuous state of the target intersection is determined to be converted into the intersection forbidden to turn left.

If the left turn phase flow of the target intersection is determined to be reduced to be close to 0 according to the traffic flow change information, but the flow change of the road section corresponding to the target intersection is small, the continuous state of the target intersection is determined to be converted into the intersection forbidden to turn right.

If the left turn phase flow of the target intersection is determined to be reduced to be close to 0 according to the traffic flow change information, but the flow change of the corresponding road section is small, the continuous state of the target intersection is determined to be converted into the intersection forbidding right turn.

If the turn-around phase flow of the target intersection is determined to be reduced to be close to 0 according to the vehicle flow change information, but the flow change of the corresponding road section is smaller, the continuous state of the target intersection is determined to be converted into the intersection forbidden to turn around.

Specifically, referring to fig. 5, an embodiment of the present application provides a method for determining traffic state change information of a target road in a preset time period according to traffic flow change information:

s501: and sequencing the continuous states of the target roads according to the sequence of the starting time or the ending time of the continuous states of the target roads.

Here, since the consecutive target road continuation states have continuity in time, the target road continuation states may be sorted in accordance with the order of the start time or the end time of each target road continuation state.

For each adjacent two target road continuation states, executing:

s502: detecting whether the flow values of the continuous states of the two adjacent target roads meet at least one preset condition or not; if so, the process jumps to S503 and S504.

S503: and determining the state change types corresponding to the continuous states of the two arbitrary adjacent target roads according to the mapping relation between the at least one preset condition and the state change types.

If not, the continuous state transition of the two adjacent target road continuous states is not considered to occur.

Illustratively, for a target road segment:

the target road section is provided with two detection positions P and Q which are respectively positioned at an inlet section and an outlet section of the target road section; the continuous states of two adjacent target roads are respectively M and N; wherein the flow rate of the detection position P in the target road continuous state M is

The flow rate in the target road continuation state N is

Detecting the flow rate of the position Q in the target road continuous state M as

The flow rate in the target road continuation state N is

The preset conditions and the corresponding state change types are one or more of the following:

preset condition 1:

and

is greater than a preset first flow threshold, and

and/or

And less than a preset second flow threshold; the corresponding state change types are: the traffic is converted into the road full-closed state;

preset condition 2:

and

is greater than a preset first flow threshold, and

and

the difference between them is greater than a preset difference threshold, and/or

And

the difference between the two is greater than a preset first difference threshold; the corresponding state change types are: converting from passage to road semi-closure;

preset condition 3:

and

is less than a preset second flow threshold, and

and/or

And greater than a preset first flow threshold; the corresponding state change types are: converting from closed to open;

aiming at the target intersection:

the target road section has three detection positions P, Q and R which are respectively positioned at a left turn phase, a right turn phase and a U-turn phase of the target intersection; the continuous states of two adjacent target roads are respectively M and N; wherein the flow rate of the detection position P in the target road continuous state M is

The flow rate in the target road continuous state N is

The flow rate of the detection position Q in the target road continuous state M is

The flow rate in the target road continuous state N is

Detecting the flow rate of the position R in the target road continuous state M as

The flow rate in the target road continuous state N is

The flow of the road section corresponding to the target intersection in the target road continuous state M is S^m', the flow rate in the target road continuation state N is Sⁿ′。

Presetting conditions and corresponding state change types, wherein the conditions comprise one or more of the following conditions:

preset condition 4:

is greater than a preset first flow threshold value,

less than a preset second flow threshold, and simultaneously, S^m' and Sⁿ' the difference between the values is less than a preset second difference threshold; the corresponding state change types are: from possible left turn to prohibited left turn.

Preset condition 5:

less than a preset second flow threshold value,

greater than a preset first flow threshold, while S^m' and Sⁿ' the difference between the values is less than a preset second difference threshold; the corresponding state change types are: from disabled left turn to enabled left turn.

Preset condition 6:

is greater than a preset first flow threshold value,

less than a preset second flow threshold while S^m' and Sⁿ' the difference between the values is less than a preset second difference threshold; the corresponding state change types are: from possible right turn to prohibited right turn.

Preset condition 7:

less than a preset second flow threshold value,

greater than a preset first flow threshold, while S^m' and Sⁿ' the difference between the values is less than a preset second difference threshold; the corresponding state change types are: the right turn is converted from the prohibition of the right turn to the right turn possible.

Preset condition 8:

is greater than a preset first flow threshold value,

less than a preset second flow threshold while S^m' and Sⁿ' the difference between the values is less than a preset second difference threshold; the corresponding state change types are: the mode of turning around can be changed into the mode of prohibiting turning around.

Preset condition 9:

less than a preset second flow threshold value,

greater than a preset first flow threshold and, at the same time, S^m' and Sⁿ' the difference between the values is less than a preset second difference threshold; the corresponding state change types are: the mode of forbidding turning around is converted into the mode of turning around.

It should be noted that the second flow threshold may be a value closer to 0, and may be specifically set according to actual needs.

S504: and determining the starting time of the target road continuous state with the later starting time as the change time in the two target road continuous states.

Here, the end time of the target road state whose end time is before, of the two target road continuation states, may be determined as the change time.

Example two

Referring to fig. 6, a second embodiment of the present application further provides another road condition monitoring method. The method comprises the following steps:

s601: acquiring target vehicle track data of vehicles driving through a target road within a plurality of preset time periods; the time attributes of the starting time and the ending time of the driving in different preset time periods are the same.

For example, if the number of the plurality of preset time periods is 7, target vehicle trajectory data of vehicles driving through the target road within the same preset time period within 7 consecutive days is acquired. For example, the preset time period is 7: 00-10: 00 per day, and the preset time period is 7; the target vehicle track data is track data of vehicles driving through the target road at 7: 00-10: 00 every day in one week.

For each preset time period, the acquisition manner of the target vehicle trajectory data is similar to that of S101, and is not described herein again.

S602: and determining traffic flow change information of the target road in each preset time period according to the target vehicle track data in each preset time period.

Here, for each preset time period, the manner of determining the traffic flow change information corresponding to the preset time period is similar to that in S102, and details thereof are not repeated here.

S603: and determining the traffic state change information of the target road in each preset time period according to the traffic flow change information of the target road in each preset time period.

Here, for each preset time period, a specific manner of determining the traffic state change information corresponding to each preset time period is similar to that in S604 described above, and is not described herein again.

In addition, in another embodiment of the present application, the method further includes:

s604: and determining a traffic rule change result of the target road according to the traffic state change information corresponding to each preset time period.

In specific implementation, the traffic state change information corresponding to each preset time period can be used for representing the temporary change of the target road state. On the basis, the traffic rule change result of the target road is determined according to the traffic state change information corresponding to each preset time period, and the traffic rule change result can be used for representing the long-time change of the state of the target road.

Specifically, the traffic regulation change result of the target road may be determined in the following manner:

judging whether the number of the continuous preset time periods with the same traffic state change information exceeds a preset number threshold value or not; if so, determining a traffic rule change result of the target road based on the traffic state change information of the continuous preset time period which is the same as the traffic state change information.

Here, the traffic state change information determined for the target road generally has one or more sets; the traffic state change information is the same, which means that the state change type and the change time of the target road are the same. The preset time periods with the same traffic state change information here refer to the preset time periods including at least one group of the same traffic state change information, and are not all the same traffic state change information corresponding to two preset time periods (in the case that the traffic state change information exceeds 1 group).

For example, the preset time period is 50, D1 to D50, respectively, and the preset number threshold is 20; all of D25 to D50 include the same traffic state change information. Wherein, D25-D50 include a group of same traffic state change information:

type of state change: switching from being able to turn left to being prohibited from turning left;

the change time is as follows: 7:00.

If the target intersection is allowed to turn left at 7:00 in other preset time periods, or the target intersection is allowed to turn left at 7:00 in the current passing rule, the result of the change of the passing rule of the target road can be determined as follows: the target intersection prohibits left turns at 7: 00.

According to the embodiment of the application, the traffic flow change information of the target road in each preset time period can be determined according to the target vehicle track data in each preset time period, the traffic state change information of the target road in each preset time period is determined according to the traffic flow change information of the target road in each preset time period, then the traffic rule change result of the target road is determined according to the traffic state change information corresponding to each preset time period, and the traffic rule change result of the target road is accurately identified based on the target vehicle track data corresponding to a plurality of preset time periods.

In addition, in another embodiment of the present application, a plurality of target roads belonging to the same area may also be determined, and the plurality of target roads have a connection relationship therebetween; according to the road state monitoring method provided by the embodiment of the application, the traffic state change information of each target road is determined, and then the traffic state change information of the road in the area is determined according to the traffic state change information of each target road.

For example, the target roads include W1 to W50; wherein, the target roads W35, W36 and W37 are connected in sequence;

the acquired traffic state change information of the target roads W35, W36, W37 includes: the passage is converted into full sealing, and the corresponding change time is as follows: 7:00. It can be determined that the roads composed of W35, W36 and W37 are completely closed at 7:00 by the passage according to the passage state change information of the target roads W35, W36 and W37.

Based on the same inventive concept, the embodiment of the present application further provides a road state monitoring device corresponding to the road state monitoring method, and as the principle of solving the problem of the device in the embodiment of the present application is similar to that of the road state monitoring method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and repeated details are not repeated.

EXAMPLE III

Referring to fig. 7, which is a schematic view of a road condition monitoring device provided in the third embodiment of the present application, the device includes: an acquisition module 71, a first determination module 72, a second determination module 73; wherein the content of the first and second substances,

an obtaining module 71, configured to obtain target vehicle trajectory data of a vehicle that travels through a target road within a preset time period;

the first determining module 72 is configured to determine traffic flow change information of the target road in the preset time period according to the target vehicle trajectory data;

and a second determining module 73, configured to determine, according to the traffic flow change information, traffic state change information of the target road in the preset time period.

According to the embodiment of the application, the target vehicle track data of the vehicles driving through the target road in the preset time period is obtained, the traffic flow change information of the target road in the preset time period is determined according to the target vehicle track data, and then the traffic state change information of the target road in the preset time period is generated according to the traffic flow change information, so that the traffic state change information of the road is automatically generated based on the vehicle track data.

In an optional implementation manner, the first determining module 72 is configured to determine traffic flow change information of the target road in the preset time period according to the target vehicle trajectory data in the following manner:

In an optional embodiment, the first determining module 72, before determining the traffic flow variation information of the target road in the preset time period according to the traffic flow at different collection time points, is further configured to:

detecting whether the flow at each acquisition time point is abnormal or not;

and if so, correcting the flow at the abnormal acquisition time point.

In an alternative embodiment, the first determining module 72 is configured to detect whether there is an abnormality in the flow rate at each collection time point by:

for each acquisition time point, performing:

In an optional embodiment, the first determining module 72 is configured to determine whether there is an abnormality in the flow rate corresponding to the acquisition time point according to the outlier factor corresponding to the acquisition time point by using the following manner:

In an alternative embodiment, the first determining module 72 is configured to correct the flow at the abnormal collection time point by:

the first determining module 72 is configured to determine traffic flow change information of the target road in the preset time period according to the traffic flows at different collection time points in the following manner:

for any two adjacent flow change time points, executing:

the second determining module 73 is configured to determine, according to the traffic flow change information, traffic state change information of the target road in the preset time period in the following manner:

for each adjacent two target road continuation states, executing:

In an alternative embodiment, the obtaining module 71 is configured to obtain the target vehicle trajectory data of the vehicle that travels through the target road within the preset time period, and includes:

the first determining module 72 is configured to determine, according to the target vehicle trajectory data, that the traffic flow change information of the target road in the preset time period includes:

In an alternative embodiment, the method further comprises: and a third determining module 74, configured to determine a traffic rule change result of the target road according to the traffic state change information corresponding to each preset time period.

In an optional implementation manner, the third determining module 74 is configured to determine a traffic rule change result of the target road according to the traffic state change information corresponding to each preset time period by using the following manner, and includes:

if so, determining a traffic rule change result of the target road based on the traffic state change information of the continuous preset time period which is the same as the traffic state change information. The description of the processing flow of each module in the device and the interaction flow between the modules may refer to the related description in the above method embodiments, and will not be described in detail here.

Example four

An embodiment of the present application further provides a computer device 800, as shown in fig. 8, which is a schematic structural diagram of the computer device 800 provided in the embodiment of the present application, and includes:

a processor 81, a memory 82, and a bus 83; the memory 82 is used for storing execution instructions and includes a memory 821 and an external memory 822; the memory 821 herein is also called an internal memory, and is used for temporarily storing operation data in the processor 81 and data exchanged with the external memory 822 such as a hard disk, the processor 81 performs data exchange with the external memory 822 through the internal memory 821, and when the computer device 800 operates, the processor 81 and the memory 82 communicate through the bus 83, so that the processor 81 executes the following instructions in a user mode:

In one possible embodiment, the instructions executed by the processor 81 for determining the traffic flow variation information of the target road in the preset time period according to the target vehicle trajectory data includes:

In a possible implementation, the instructions executed by the processor 81 before determining the traffic flow variation information of the target road in the preset time period according to the traffic flow at different collection time points further include:

detecting whether the flow at each acquisition time point is abnormal or not;

and if so, correcting the flow at the abnormal acquisition time point.

In a possible implementation, the instructions executed by the processor 81 for detecting whether there is an anomaly in the flow at each acquisition time point include:

for each acquisition time point, performing:

In a possible implementation manner, in the instructions executed by the processor 81, the determining whether there is an abnormality in the flow rate corresponding to the acquisition time point according to the outlier factor corresponding to the acquisition time point includes:

In a possible embodiment, the instructions executed by the processor 81 for correcting the flow at the abnormal collection time point include:

In one possible embodiment, the processor 81 executes instructions that include the following information on the change in the traffic flow: the method comprises the steps that a flow value corresponding to at least one target road continuous state and starting time and ending time corresponding to each target road continuous state are obtained;

for any two adjacent flow change time points, executing:

In a possible implementation manner, the instructions executed by the processor 81 include, for the traffic state change information: the state change type and the change time of the target road;

for each adjacent two target road continuation states, executing:

In one possible embodiment, the instructions executed by the processor 81 for obtaining target vehicle trajectory data of a vehicle traveling on a target road within a preset time period include:

In a possible implementation manner, the instructions executed by the processor 81, after determining the traffic state change information of the target road in each preset time period according to the traffic flow change information of the target road in each preset time period, further include:

In a possible implementation manner, in the instructions executed by the processor 81, the determining a traffic rule change result of the target road according to the traffic state change information corresponding to each preset time period includes:

In addition, an embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program performs the steps of the road condition monitoring method in the above method embodiment.

The computer program product of the method and the device for monitoring a road state provided in the embodiments of the present application includes a computer readable storage medium storing a program code, where instructions included in the program code may be used to execute the method described in the foregoing method embodiments, and specific implementation may refer to the method embodiments, and will not be described herein again.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the apparatus described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solutions of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used to illustrate the technical solutions of the present application, but not to limit the technical solutions, and the scope of the present application is not limited to the above-mentioned embodiments, although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: those skilled in the art can still make modifications or changes to the embodiments described in the foregoing embodiments, or make equivalent substitutions for some features, within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the exemplary embodiments of the present application, and are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of monitoring road conditions, comprising:

determining the traffic state change information of the target road in the preset time period according to the traffic flow change information;

the determining of the traffic flow change information of the target road in the preset time period according to the target vehicle trajectory data includes:

determining traffic flow change information of the target road in the preset time period according to the traffic flow at different acquisition time points;

determining flow values corresponding to target road continuous states included in traffic flow change information of any two position adjacent flow change time points according to flows corresponding to the any two position adjacent flow change time points aiming at the any two position adjacent flow change time points; wherein the target road continuation state includes: passing and forbidding passing;

detecting the flow value of the continuous state of any two adjacent target roads according to the continuous state of each two adjacent target roads, and judging whether the flow value meets at least one preset condition;

if so, determining the state change type included in the traffic state change information corresponding to the continuous states of the two adjacent arbitrary target roads according to the mapping relation between the at least one preset condition and the state change type.

2. The method according to claim 1, wherein before determining the traffic flow change information of the target road in the preset time period according to the traffic flow at different collection time points, the method further comprises:

detecting whether the flow at each acquisition time point is abnormal or not;

and if so, correcting the flow at the abnormal acquisition time point.

3. The method of claim 2, wherein the detecting whether there is an anomaly in the flow at each acquisition time point comprises:

for each acquisition time point, performing:

4. The method of claim 3, wherein determining whether the flow rate corresponding to the acquisition time point is abnormal according to the outlier factor corresponding to the acquisition time point comprises:

5. The method of claim 2, wherein the detecting whether there is an anomaly in the flow at each acquisition time point comprises:

6. The method according to claim 2, wherein the correcting the flow rate at the abnormal collection time point comprises:

determining a plurality of acquisition time points of which the time difference with the acquisition time point with the abnormality is within a second preset time difference threshold value;

and determining the average value of the determined flow rates of the plurality of acquisition time points as the flow rate of the acquisition time point with the abnormality.

7. The method according to claim 1, wherein the traffic flow change information further includes a start time and an end time corresponding to each of the target road continuation states;

for any two adjacent flow change time points, executing:

and determining the time of the flow change time point which is at the front time as the starting time of the continuous state of the target road, and determining the time of the flow change time point which is at the back time as the ending time of the continuous state of the target road.

8. The method of claim 7, wherein the traffic status change information further includes a change time of a status change type;

for each adjacent two target road continuation states, executing:

and determining the starting time of the target road continuous state with the starting time behind in any two adjacent target road continuous states as the change time.

9. The method of claim 1, wherein obtaining target vehicle trajectory data for vehicles traveling over a target road for a preset period of time comprises:

10. The method according to claim 9, wherein after determining the traffic state change information of the target road in each preset time period according to the traffic flow change information of the target road in each preset time period, the method further comprises:

11. The method according to claim 10, wherein the determining a traffic rule change result of the target road according to the traffic state change information corresponding to each preset time period comprises:

12. A road condition monitoring device, comprising:

the second determining module is used for determining the traffic state change information of the target road in the preset time period according to the traffic flow change information;

the first determining module is configured to determine traffic flow change information of the target road in the preset time period according to the target vehicle trajectory data in the following manner:

determining the flow of a plurality of acquisition time points in the preset time period according to the target vehicle track data; determining traffic flow change information of the target road in the preset time period according to the traffic flow at different acquisition time points;

for any two adjacent flow change time points, determining a flow value corresponding to a target road continuous state included in traffic flow change information of the adjacent flow change time points according to the flow corresponding to the adjacent flow change time points of the any two positions; wherein the target road continuation state includes: passing and forbidding passing;

aiming at continuous states of every two adjacent target roads, detecting flow values of the continuous states of any two adjacent target roads, and judging whether the flow values meet at least one preset condition; if so, determining the state change type included in the traffic state change information corresponding to the continuous states of the two adjacent arbitrary target roads according to the mapping relation between the at least one preset condition and the state change type.

13. The apparatus of claim 12, wherein the first determining module, before determining the traffic flow change information of the target road in the preset time period according to the traffic flow at different collecting time points, is further configured to:

detecting whether the flow at each acquisition time point is abnormal or not;

and if so, correcting the flow at the abnormal acquisition time point.

14. The apparatus of claim 13, wherein the first determining module is configured to detect whether there is an anomaly in the flow rate at each collection time point by:

for each acquisition time point, performing:

15. The apparatus according to claim 14, wherein the first determining module is configured to determine whether there is an abnormality in the flow rate corresponding to the collecting time point according to the outlier factor corresponding to the collecting time point by:

16. The apparatus of claim 13, wherein the first determining module is configured to detect whether there is an anomaly in the flow rate at each collection time point by:

17. The apparatus of claim 13, wherein the first determining module is configured to correct the flow at the abnormal collection time point by:

18. The apparatus according to claim 12, wherein the traffic flow change information further includes a start time and an end time corresponding to each of the target road continuation statuses;

for any two adjacent flow change time points, executing:

19. The apparatus of claim 18, wherein the traffic status change information further comprises a change time of a status change type;

the second determination module is to:

for each adjacent two target road continuation states, executing:

20. The apparatus of claim 12, wherein the obtaining module is configured to obtain the target vehicle trajectory data of the vehicle driving through the target road within the preset time period by:

the first determining module is configured to determine traffic flow change information of the target road in the preset time period according to the target vehicle trajectory data in the following manner, where the determining includes:

21. The apparatus of claim 20, further comprising: and the third determining module is used for determining a traffic rule change result of the target road according to the traffic state change information corresponding to each preset time period.

22. The apparatus of claim 21, wherein the third determining module is configured to determine a traffic regulation change result of the target road according to the traffic status change information corresponding to each preset time period by using the following manner, and the determining module includes:

23. An electronic device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating over the bus when the electronic device is operating, the machine-readable instructions when executed by the processor performing the steps of the road condition monitoring method according to any one of claims 1 to 11.

24. A computer-readable storage medium, characterized in that a computer program is stored thereon, which computer program, when being executed by a processor, is adapted to carry out the steps of the road condition monitoring method according to any one of claims 1 to 11.