CN109387210B - Vehicle navigation method and device - Google Patents
Vehicle navigation method and device Download PDFInfo
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- CN109387210B CN109387210B CN201710652413.1A CN201710652413A CN109387210B CN 109387210 B CN109387210 B CN 109387210B CN 201710652413 A CN201710652413 A CN 201710652413A CN 109387210 B CN109387210 B CN 109387210B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/36—Input/output arrangements for on-board computers
Abstract
The invention provides a vehicle navigation method and a vehicle navigation device, wherein the method comprises the following steps: determining a current lane where the target vehicle is located according to the running track of the target vehicle; acquiring a lane to be driven of a target vehicle in the process of reaching a destination from a current lane according to the current lane and a navigation path; acquiring a target road condition of a current lane and a target road condition of each lane to be driven; and marking the current lane and the target road condition of each lane to be driven on the navigation path. The method realizes the road condition marking based on the lane, so that the vehicle can acquire the road conditions of the current lane and the lane to be driven in the driving process, the accuracy of judging the road conditions and the navigation precision are improved, and the problem of low accuracy of judging the road conditions in the navigation method based on road display road conditions in the prior art is solved.
Description
Technical Field
The invention relates to the technical field of vehicle navigation, in particular to a vehicle navigation method and a vehicle navigation device.
Background
With the development of navigation technology, vehicle navigation brings great convenience to the life of people. Typically, a navigation path is planned by inputting a starting point and a destination in navigation software. In addition, in the process of vehicle driving, the speed limit of the road and the congestion condition of the road can be broadcasted and reminded.
With the widening of the road surface, the number of lanes increases, and there are cases that a lane going to a certain direction queues up and waits for a vehicle, and a lane going to another direction passes smoothly. However, in the current navigation method, only one road condition can be indicated for the same road, and the accuracy of judging the road condition is not high.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, a first objective of the present invention is to provide a vehicle navigation method to mark a road condition based on a lane, so that a vehicle can know the road condition of a current lane and a lane to be driven during driving, and the accuracy of road condition judgment and the navigation precision are improved, so as to solve the problem of low accuracy of road condition judgment in the navigation method based on road display in the prior art.
A second object of the present invention is to provide a vehicle navigation device.
A third object of the invention is to propose a computer device.
A fourth object of the invention is to propose a computer program product.
A fifth object of the invention is to propose a non-transitory computer-readable storage medium.
To achieve the above object, an embodiment of a first aspect of the present invention provides a vehicle navigation method, including:
determining a current lane where a target vehicle is located according to a running track of the target vehicle;
acquiring a lane to be driven of the target vehicle in the process of reaching the destination from the current lane according to the current lane and the navigation path;
acquiring the target road condition of the current lane and the target road condition of each lane to be driven;
and marking the current lane and the target road condition of each lane to be driven on the navigated path.
As an optional implementation manner in the embodiment of the first aspect, the acquiring a target road condition of the current lane includes:
acquiring historical driving data as sample data;
acquiring a first probability of each road condition of the current lane based on the sample data and a preset Bayesian classification algorithm;
and taking the road condition corresponding to the maximum first probability as the target road condition of the current lane.
As an optional implementation manner in an embodiment of the first aspect, the obtaining a first probability under each road condition of the current lane based on the sample data and a preset bayesian classification algorithm includes:
acquiring a second probability of the current lane under the ith road condition at the current passing moment according to the sample data; the historical driving data comprises driving data of the current lane and a lane next to the current lane;
acquiring a third probability that the current lane is possibly identified as a jth road condition when the current lane is in the ith road condition;
acquiring a fourth probability that the next lane is possibly identified as the kth road condition when the current lane is in the ith road condition;
obtaining a combined probability that the current lane is possibly identified as a jth road condition and the next lane is possibly identified as a kth road condition under the ith road condition according to the third probability and the fourth probability under the ith road condition;
obtaining a first probability of the current lane under the ith road condition based on the second probability under the ith road condition and the joint probability under the ith road condition;
wherein i is more than or equal to 1 and less than or equal to N; j is more than or equal to 1 and less than or equal to N, and k is more than or equal to 1 and less than or equal to N.
As an optional implementation manner of the embodiment of the first aspect, the acquiring a target road condition of each lane to be traveled includes:
for each vehicle to be driven, receiving driving data of each vehicle driven on the lane to be driven;
acquiring the running speed of each vehicle from the running data;
and determining the target road condition of the lane to be driven according to the driving speed.
As an optional implementation manner of the embodiment of the first aspect, the determining a target road condition of the lane to be traveled according to the traveling speed includes:
carrying out weighted average on the running speeds of all vehicles to obtain the weighted running speed of the lane to be run;
comparing the weighted running speed with a preset running speed range of each road condition, and determining a target running speed range in which the weighted running speed falls;
and taking the road condition corresponding to the target driving speed range as the target road condition of the lane to be driven.
As an optional implementation manner of the embodiment of the first aspect, before determining the current lane where the target vehicle is located according to the traveling track of the target vehicle, the method further includes:
and acquiring a starting point and a destination of a user, and navigating the path for the target vehicle according to the starting point and the destination.
As an optional implementation manner of the embodiment of the first aspect, the marking the target road condition of the current lane and each lane to be traveled on the navigated path includes:
marking the target road condition of the current lane on the navigated path according to a marking format corresponding to the target road condition of the current lane, and displaying the target road condition through a display screen;
and marking the target road condition of the lane to be driven on the navigated path according to a marking format corresponding to the target road condition of the lane to be driven, and displaying the target road condition through a display screen.
The vehicle navigation method determines a current lane where a target vehicle is located according to a running track of the target vehicle, acquires lanes to be run of the target vehicle in the process of reaching a destination from the current lane according to the current lane and a navigation path, acquires a target road condition of the current lane and a target road condition of each lane to be run, and marks the current lane and the target road condition of each lane to be run on the navigation path. In the embodiment, the current lane where the target vehicle is located and the lane to be driven in the process of reaching the destination from the current lane are determined, the target road condition of the current lane and the target road condition of each lane to be driven are obtained, and marking is performed on the navigation path, so that road condition marking based on the lanes is realized, the road conditions of the current lane and the lane to be driven can be obtained by the vehicle in the driving process, the accuracy of road condition judgment and the navigation precision are improved, and the problem of low road condition judgment accuracy in the navigation method based on road display road condition in the prior art is solved.
To achieve the above object, a second aspect of the present invention provides a vehicle navigation device, including:
the determining module is used for determining a current lane where the target vehicle is located according to the running track of the target vehicle;
the first acquisition module is used for acquiring a lane to be driven of the target vehicle in the process of reaching the destination from the current lane according to the current lane and the navigation path;
the second acquisition module is used for acquiring the target road condition of the current lane and the target road condition of each lane to be driven;
and the marking module is used for marking the current lane and the target road condition of each lane to be driven on the navigated path.
As an optional implementation manner of the embodiment of the second aspect, the second obtaining module includes:
the system comprises a first acquisition unit, a second acquisition unit and a control unit, wherein the first acquisition unit is used for acquiring historical driving data as sample data;
the second acquisition unit is used for acquiring a first probability of each road condition of the current lane based on the sample data and a preset Bayesian classification algorithm;
and the determining unit is used for taking the road condition corresponding to the maximum first probability as the target road condition of the current lane.
As an optional implementation manner of the embodiment of the second aspect, the second obtaining unit is configured to:
acquiring a second probability of the current lane under the ith road condition at the current passing moment according to the sample data; the historical driving data comprises driving data of the current lane and a lane next to the current lane;
acquiring a third probability that the current lane is possibly identified as a jth road condition when the current lane is in the ith road condition;
acquiring a fourth probability that the next lane is possibly identified as the kth road condition when the current lane is in the ith road condition;
obtaining a combined probability that the current lane is possibly identified as a jth road condition and the next lane is possibly identified as a kth road condition under the ith road condition according to the third probability and the fourth probability under the ith road condition;
obtaining a first probability of the current lane under the ith road condition based on the second probability under the ith road condition and the joint probability under the ith road condition;
wherein i is more than or equal to 1 and less than or equal to N; j is more than or equal to 1 and less than or equal to N, and k is more than or equal to 1 and less than or equal to N.
As an optional implementation manner of the embodiment of the second aspect, the second obtaining module is further configured to:
for each vehicle to be driven, receiving driving data of each vehicle driven on the lane to be driven;
acquiring the running speed of each vehicle from the running data;
and determining the target road condition of the lane to be driven according to the driving speed.
As an optional implementation manner of the embodiment of the second aspect, the second obtaining module is further configured to:
carrying out weighted average on the running speeds of all vehicles to obtain the weighted running speed of the lane to be run;
comparing the weighted running speed with a preset running speed range of each road condition, and determining a target running speed range in which the weighted running speed falls;
and taking the road condition corresponding to the target driving speed range as the target road condition of the lane to be driven.
As an optional implementation manner of the embodiment of the second aspect, the vehicle navigation apparatus further includes: and the navigation module is used for acquiring a departure point and a destination of a user and navigating the path for the target vehicle according to the departure point and the destination.
As an optional implementation manner of the embodiment of the second aspect, the marking module is further configured to:
marking the target road condition of the current lane on the navigated path according to a marking format corresponding to the target road condition of the current lane, and displaying the target road condition through a display screen;
and marking the target road condition of the lane to be driven on the navigated path according to a marking format corresponding to the target road condition of the lane to be driven, and displaying the target road condition through a display screen.
The vehicle navigation device of the embodiment of the invention determines the current lane where the target vehicle is located according to the running track of the target vehicle, acquires the lanes to be run of the target vehicle in the process of reaching the destination from the current lane according to the current lane and the navigation path, acquires the target road condition of the current lane and the target road condition of each lane to be run, and marks the current lane and the target road condition of each lane to be run on the navigation path. In the embodiment, the current lane where the target vehicle is located and the lane to be driven in the process of reaching the destination from the current lane are determined, the target road condition of the current lane and the target road condition of each lane to be driven are obtained, and marking is performed on the navigation path, so that road condition marking based on the lanes is realized, the road conditions of the current lane and the lane to be driven can be obtained by the vehicle in the driving process, the accuracy of road condition judgment and the navigation precision are improved, and the problem of low road condition judgment accuracy in the navigation method based on road display road condition in the prior art is solved.
To achieve the above object, a third embodiment of the present invention provides a computer device, including a processor and a memory; wherein the processor executes a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to implement the vehicle navigation method according to the embodiment of the first aspect.
To achieve the above object, a fourth aspect of the present invention provides a computer program product, wherein instructions of the computer program product, when executed by a processor, perform the vehicle navigation method according to the first aspect.
To achieve the above object, a fifth embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program, when being executed by a processor, implementing the vehicle navigation method according to the first embodiment.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic flow chart of a vehicle navigation method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of the distribution of lane directions on a road according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a navigation path displaying a current lane marker according to an embodiment of the present invention;
FIG. 4 is a schematic flow chart diagram illustrating another vehicle navigation method according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a vehicle driving track according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a car navigation device according to an embodiment of the present invention;
FIG. 7 is a schematic structural diagram of another vehicle navigation device according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of another vehicle navigation device according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The following explains a vehicle navigation method and apparatus according to an embodiment of the present invention with reference to the drawings.
With the development of navigation technology, vehicle navigation brings great convenience to the life of people. Typically, a navigation path is planned by inputting a starting point and a destination in navigation software. In addition, in the process of vehicle driving, the speed limit of the road and the congestion condition of the road can be broadcasted and reminded.
Currently, common navigation software, such as Baidu maps, Gaode maps, and the like, displays road conditions based on roads. However, as the road surface of a road is widened, the number of lanes increases, and there are cases that a lane going to a certain direction queues up and waits for a vehicle, and a lane going to another direction runs smoothly.
To solve the problem, an embodiment of the present invention provides a vehicle navigation method to mark a road condition based on a lane, so that a vehicle can obtain the road condition of a current lane and a lane to be driven during driving, and the accuracy of road condition determination and the navigation precision are improved, so as to solve the problem of low accuracy of road condition determination in the navigation method based on road display in the prior art.
The execution main body of the vehicle navigation method provided by the embodiment of the invention is terminal equipment, wherein the terminal equipment can be mobile terminals such as mobile phones and iPads, and can also be vehicle-mounted equipment.
Fig. 1 is a schematic flow chart of a vehicle navigation method according to an embodiment of the present invention.
As shown in fig. 1, the vehicle navigation method includes the steps of:
and S101, determining the current lane where the target vehicle is located according to the running track of the target vehicle.
In this embodiment, cameras may be installed on both sides of the vehicle, and the driving track of the target vehicle is obtained by shooting surrounding scenes with the cameras, so as to determine the lane position where the vehicle is located. And then, determining the lane direction of the target vehicle according to the lane position, the navigation direction or the pre-stored distribution condition of each lane direction in each road.
For example, assuming the pre-stored allocation of each lane direction in the current driving road of the target vehicle, as shown in fig. 2, the leftmost lane is a straight lane, the second lane on the left is a straight lane, the third lane on the left is a left-turn lane, and the fourth lane on the left is a right-turn lane.
In the process that the target vehicle runs on the current road, if a rail is arranged in the image shot by the left camera and the target vehicle is close to the rail, and other vehicles are arranged in the image shot by the right camera, the lane where the target vehicle runs currently can be determined to be the leftmost lane, and the lane where the current vehicle is located can be determined to be the straight lane by combining the lane direction distribution condition. If the images shot by the cameras on the two sides are images of vehicles, the fact that the target vehicle needs to go straight is determined according to the navigation direction, and the lane where the target vehicle currently runs can be determined to be the second straight lane on the left side by combining the images shot by the cameras on the two sides and the pre-stored distribution condition of each lane direction in the road where the target vehicle currently runs.
S102, acquiring a lane to be driven of the target vehicle in the process of reaching the destination from the current lane according to the current lane and the navigation path.
In this embodiment, the distribution condition of the lane direction in each road may be stored in advance. In the running process of the target vehicle, the lane to be run of the target vehicle in the process of reaching the destination from the current lane can be obtained according to the current lane and the pre-stored distribution condition of the lane direction in each road.
For example, the current lane where the target vehicle is located is a left-turn lane, and the lane to be traveled in the process of reaching the destination is determined to be a straight lane and a right-turn lane by combining the navigation path. That is, the target vehicle enters the straight lane after turning left from the current lane, and enters the right-turn lane after passing through the traffic light, and can reach the destination after turning right.
S103, acquiring the target road condition of the current lane and the target road condition of each lane to be driven.
In this embodiment, the road conditions of the lanes can be divided into four categories: extremely congested, slow-moving, unblocked, etc. And calculating the average running speed of the vehicle according to the vehicle running data, such as the running speed, reported by all vehicles on the current lane. And determining the target road condition of the current lane where the target vehicle is located according to the road condition corresponding to the average running speed.
Likewise, for each lane to be driven, the target road condition of each lane to be driven can be calculated by using the method.
And S104, marking the current lane and the target road condition of each lane to be driven on the navigation path.
After the target road condition of the current lane and the target road condition of the lane to be driven are obtained, the target road condition of the current lane and the target road condition of each lane to be driven can be marked on the navigation path.
As an example, the target road condition of the current lane may be marked on the navigated path according to a marking format corresponding to the target road condition of the current lane, and displayed on the display screen. For example, as shown in fig. 3, the current lane where the target vehicle is located is a left-turn lane, the target road condition is smooth, the left-turn lane symbol may be marked as green on the navigation path, and the current lane and the straight lane symbol may be displayed on the display screen.
Similarly, the target road condition of each lane to be driven is marked on the navigation path according to the marking format corresponding to the target road condition of the lane to be driven, and the target road condition is displayed through the display screen.
The following describes a vehicle navigation method according to an embodiment of the present invention, by way of another embodiment.
As shown in fig. 4, the vehicle navigation method includes:
s201, a departure point and a destination of a user are obtained, and a target vehicle is navigated according to the departure point and the destination.
And the user opens the navigation software on the terminal equipment and inputs a starting point and a destination. At this time, the navigation software acquires a departure point and a destination, and provides a navigation path for the target vehicle according to the departure point and the destination.
And S202, determining the current lane where the target vehicle is located according to the running track of the target vehicle.
In this embodiment, a time duration may be preset, the driving data of the target vehicle within the time duration may be collected, and the driving trajectory of the target vehicle may be formed based on the driving data. For example, the driving data includes that the vehicle travels straight after starting, and then turns left after a certain distance, a trajectory may be formed as the driving trajectory shown in fig. 5, and it may be determined that the target vehicle turns left and then enters the left lane based on the driving trajectory, that is, it may be determined that the target vehicle is currently located in the left lane.
S203, acquiring a lane to be driven of the target vehicle in the process that the current lane reaches the destination according to the current lane and the navigation path.
Step S203 is similar to step S102 in the above embodiments, and is not repeated here.
And S204, acquiring the target road condition of the current lane based on the historical driving data and a preset Bayesian classification algorithm.
When the lane where the target vehicle is located is judged according to the running track of the target vehicle, the formation of the track of the target vehicle, namely the next lane, needs to be waited, so that the problem that the reported vehicle data cannot be obtained in time exists for the current road. For the data delay problem, the influence of the road condition of the next lane to be driven on the road condition of the current lane is considered, the road condition of the current lane can be calculated based on the delay data, and the road condition of the current lane at the moment can be predicted by using a probability statistical method.
In this embodiment, the first probability under each road condition of the current lane is obtained based on the historical driving data and a preset bayesian classification algorithm, and the road condition corresponding to the maximum first probability is used as the target road condition of the current lane. The historical driving data comprises driving data of a current lane and a lane next to the current lane.
The Bayesian classification algorithm solves the classification problem. Mathematically, the classification problem can be defined as follows: has already been assembled C ═ y1,y2,…ynAnd I ═ x1,x2,…xmDetermining a mapping rule y ═ f (x)i) So that any xiE.g. I, with and only one yiE C, so that yi∈f(xi) This is true. Wherein, C is a category set, each element in C is a category, I is called a feature set, and each element in I is a categoryAnd f is a classifier. It can be seen that the input of the classifier is the feature, and the output is the corresponding class, that is, given the feature, the class of the feature can be obtained by bayesian classification.
In this embodiment, the feature set is a road condition of a lane next to the current lane at the same time and a road condition of the current lane calculated based on the delay data, and the category set is a road condition category of the current lane.
In this embodiment, a specific process of obtaining the first probability of the current lane under the ith road condition based on the historical driving data and the preset bayesian classification algorithm is as follows:
firstly, the history forming data is used as sample data, and the second probability P (C) under the ith road condition of the current lane at the current passing time can be calculated through the sample datai)。
Then, according to the sample data, a third probability P (X) that the current lane is possibly identified as the jth road condition under the ith road condition is calculatedj|Ci) And a fourth probability P (Y) that the next lane is likely to be identified as the k-th road condition when the current lane is under the k-th road conditionk|Ci). Wherein i is more than or equal to 1 and less than or equal to N; j is more than or equal to 1 and less than or equal to N, k is more than or equal to 1 and less than or equal to N, and N represents the number of road condition categories.
In this embodiment, it is assumed that the current lane is the jth road condition and the next lane is the kth road condition are independent from each other, so that the third probability P (X) under the ith road condition is obtainedj|Ci) And a fourth probability P (Y)k|Ci) Calculating the joint probability P (X) of the current lane being possibly identified as the jth road condition and the next lane being possibly identified as the kth road condition under the ith road conditionj,Yk|Ci)＝P(Xj|Ci)*P(Yk|Ci)。
Finally, according to a Bayesian formula, a first probability P (C) under the ith road condition of the current lane can be calculatedi|Xj,Yk) As shown in equation (1).
Wherein, P (X)j) Probability of the current lane being the jth road condition, P (Y)k) Probability of the next lane being the jth road condition, P (X)j) And P (Y)k) Can be obtained by calculation according to the sample data.
After the first probability under each road condition of the current lane is calculated by the method, the first probability under each road condition of the current lane is compared, and the road condition corresponding to the maximum first probability is used as the target road condition of the current lane.
For example, the road conditions of the lanes are divided into four categories, namely extremely congested, slow running and unblocked. Assuming that the road condition of the current lane is smooth at the moment and the road condition of the next lane is congested at the moment based on the delay data, and calculating the target road condition of the current lane based on the fact that the road condition of the current lane is smooth at the moment and the road condition of the next lane is congested at the moment.
Take the first probability that the current road condition of the lane is extremely congested as an example. Firstly, according to the sample data, a second probability P (C) that the current lane road condition is extremely congested can be calculated1) And the probability P (X) that the current road condition of the lane is smooth in the sample data4) And the probability P (Y) that the road condition of the next lane is congested in the sample data2). Then, under the condition that the current road condition is extremely congested according to the sample data, the probability P (X) that the current road condition is unblocked is obtained through calculation based on the delay data4|C1) And the probability P (Y) that the road condition of the next lane is congested in the case that the current road condition is extremely congested2|C1). Then, according to a Bayesian formula, a first probability P (C) that the road condition of the current lane is extremely congested can be calculated1|X4,Y2) As shown in equation (2).
Similarly, the first probabilities of the current road condition of the lane being congestion, slow running and smooth can be calculated and are respectively P (C)2|X4,Y2)、P(C3|X4,Y2)、P(C4|X4,Y2)。
Comparing the first probability that the current road condition of the lane is extremely congested, slow running and unblocked, namely comparing P (C)1|X4,Y2)、P(C2|X4,Y2)、P(C3|X4,Y2)、P(C4|X4,Y2) The traffic information of the current lane is obtained according to the delay data, and the traffic information of the current lane is calculated according to the delay data.
And S205, acquiring the target road condition of each lane to be driven based on the driving data of each vehicle on the lane to be driven.
During the running process of the target vehicle, the vehicles on each lane to be run can upload the running data, so that the terminal device can receive the running data of the vehicles running on the lanes to be run. The driving data may include a driving speed of the vehicle.
And acquiring the running speed of each vehicle on the lane to be driven from the running data for each lane to be driven. And then, determining the target road condition of the lane to be driven according to the driving speed.
Specifically, the running speeds of all vehicles on each lane to be run are weighted and averaged to obtain a weighted running speed of the lane to be run, and the weight may be set to 1 in the calculation process. In this embodiment, the corresponding relationship between the driving speed range and the road condition of the lane may be pre-established, after the weighted driving speed is obtained, the weighted driving speed is compared with the preset driving speed range of each road condition, the target driving speed range in which the weighted driving speed falls is determined, and then the road condition corresponding to the target driving speed range is used as the target road condition of the lane to be driven.
For example, the road condition of the lane corresponding to the running speed less than 10km/h is extremely congested, the road condition of the lane corresponding to [10km/h, 15km/h) is congested, the road condition of the lane corresponding to [15km/h,30km/h ] is slow running, and the road condition of the lane corresponding to more than 30km/h is smooth. And calculating the weighted driving speed of a certain lane to be driven to be 35km/h, wherein the corresponding driving speed range is over 30km/h, and the road condition of the lane corresponding to the driving speed range is smooth, so that the target road condition of the lane to be driven can be determined to be smooth.
And S206, marking the current lane and the target road condition of each lane to be driven on the navigation path.
In this embodiment, the corresponding relationship between the lane road condition and the color of the lane direction symbol on the navigation path may be established in advance. For example, the lane road conditions are extremely congested, slow running and smooth, and the colors of the corresponding lane direction symbols are red, orange, yellow and green respectively.
In this embodiment, according to the current lane where the target vehicle is located and the target road condition of the current lane, the target road condition of the current lane may be marked on the navigation path according to the mark format corresponding to the target road condition of the current lane, and displayed on the display screen.
For example, the current lane where the target vehicle is located is a left-turn lane, and the target road condition of the current lane is smooth, and the left-turn symbol of the current lane may be displayed as green on the display screen.
Similarly, the road condition of the lane to be driven can be marked according to a preset format on the navigation path and displayed on the display screen.
It should be noted that the vehicle navigation method provided in this embodiment may also be applied to a server. The server can execute the steps, and then the marking result is fed back to the terminal device and displayed by the terminal device.
The vehicle navigation method determines a current lane where a target vehicle is located according to a running track of the target vehicle, acquires lanes to be run of the target vehicle in the process of reaching a destination from the current lane according to the current lane and a navigation path, acquires a target road condition of the current lane and a target road condition of each lane to be run, and marks the current lane and the target road condition of each lane to be run on the navigation path. In the embodiment, the current lane where the target vehicle is located and the lane to be driven in the process of reaching the destination from the current lane are determined, the target road condition of the current lane and the target road condition of each lane to be driven are obtained, and marking is performed on the navigation path, so that road condition marking based on the lanes is realized, the road conditions of the current lane and the lane to be driven can be obtained by the vehicle in the driving process, the accuracy of road condition judgment and the navigation precision are improved, and the problem of low road condition judgment accuracy in the navigation method based on road display road condition in the prior art is solved.
In order to implement the above embodiment, the present invention further provides a vehicle navigation device.
As shown in fig. 6, the vehicular navigation apparatus includes: a determination module 610, a first acquisition module 620, a second acquisition module 630, and a marking module 640.
The determining module 610 is configured to determine a current lane where the target vehicle is located according to the driving track of the target vehicle.
The first obtaining module 620 is configured to obtain a lane to be traveled by the target vehicle in a process of reaching the destination from the current lane according to the current lane and the navigated path.
The second obtaining module 630 is configured to obtain a target road condition of the current lane and a target road condition of each lane to be driven.
The marking module 640 is used for marking the current lane and the target road condition of each lane to be driven on the navigated path.
In a possible implementation manner of this embodiment, as shown in fig. 7, the second obtaining module 630 includes: a first acquisition unit 631, a second acquisition unit 632, a determination unit 633.
The first obtaining unit 631 is configured to obtain historical driving data as sample data.
The second obtaining unit 632 is configured to obtain a first probability under each condition of the current lane based on the sample data and a preset bayesian classification algorithm.
The determining unit 633 is configured to use the road condition corresponding to the maximum first probability as the target road condition of the current lane.
In a possible implementation manner of this embodiment, the second obtaining unit 632 is configured to:
according to the sample data, acquiring a second probability of the current lane under the ith road condition at the current passing moment; the historical driving data comprises driving data of a current lane and a lane next to the current lane;
acquiring a third probability that the current lane is possibly identified as a jth road condition when the current lane is in the ith road condition;
acquiring a fourth probability that the next lane is possibly identified as the kth road condition when the current lane is in the ith road condition;
according to the third probability and the fourth probability under the ith road condition, obtaining the joint probability that the current lane under the ith road condition can be identified as the jth road condition and the next lane can be identified as the kth road condition;
obtaining a first probability of the current lane under the ith road condition based on the second probability under the ith road condition and the combined probability under the ith road condition;
wherein i is more than or equal to 1 and less than or equal to N; j is more than or equal to 1 and less than or equal to N, and k is more than or equal to 1 and less than or equal to N.
In a possible implementation manner of this embodiment, the second obtaining module 630 is further configured to:
for each vehicle to be driven, receiving driving data of each vehicle driven on a lane to be driven;
acquiring the running speed of each vehicle from the running data;
and determining the target road condition of the lane to be driven according to the driving speed.
In a possible implementation manner of this embodiment, the second obtaining module 630 is further configured to:
carrying out weighted average on the running speeds of all vehicles to obtain the weighted running speed of the lane to be run;
comparing the weighted running speed with a preset running speed range of each road condition, and determining a target running speed range in which the weighted running speed falls;
and taking the road condition corresponding to the target driving speed range as the target road condition of the lane to be driven.
In one possible implementation manner of the present embodiment, as shown in fig. 8, the vehicular navigation apparatus further includes: a navigation module 650.
The navigation module 650 is configured to obtain a starting point and a destination of the user, and navigate the route for the target vehicle according to the starting point and the destination.
In a possible implementation manner of this embodiment, the marking module 640 is further configured to:
marking the target road condition of the current lane on the navigation path according to a marking format corresponding to the target road condition of the current lane, and displaying the target road condition through a display screen;
and marking the target road condition of the lane to be driven on the navigation path according to a marking format corresponding to the target road condition of the lane to be driven, and displaying the target road condition through a display screen.
It should be noted that the foregoing explanation of the vehicle navigation method embodiment is also applicable to the vehicle navigation apparatus of the present embodiment, and is not repeated herein.
The vehicle navigation device of the embodiment of the invention determines the current lane where the target vehicle is located according to the running track of the target vehicle, acquires the lanes to be run of the target vehicle in the process of reaching the destination from the current lane according to the current lane and the navigation path, acquires the target road condition of the current lane and the target road condition of each lane to be run, and marks the current lane and the target road condition of each lane to be run on the navigation path. In the embodiment, the current lane where the target vehicle is located and the lane to be driven in the process of reaching the destination from the current lane are determined, the target road condition of the current lane and the target road condition of each lane to be driven are obtained, and marking is performed on the navigation path, so that road condition marking based on the lanes is realized, the road conditions of the current lane and the lane to be driven can be obtained by the vehicle in the driving process, the accuracy of road condition judgment and the navigation precision are improved, and the problem of low road condition judgment accuracy in the navigation method based on road display road condition in the prior art is solved.
In order to implement the above embodiments, the present invention proposes a computer device, including a processor and a memory; wherein the processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory for implementing the vehicle navigation method as described in the foregoing embodiment.
In order to implement the above embodiments, the present invention further provides a computer program product, and instructions in the computer program product, when executed by a processor, perform the vehicle navigation method according to the foregoing embodiments.
In order to implement the above-described embodiments, the present invention also proposes a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the vehicle navigation method as described in the foregoing embodiments.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present invention may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A vehicle navigation method, comprising:
determining a current lane where a target vehicle is located according to a running track of the target vehicle;
acquiring a lane to be driven of the target vehicle in the process of reaching the destination from the current lane according to the current lane and the navigation path;
acquiring the target road condition of the current lane and the target road condition of each lane to be driven;
marking the current lane and the target road condition of each lane to be driven on the navigated path;
the acquiring of the target road condition of the current lane comprises the following steps:
acquiring historical driving data as sample data;
acquiring a first probability of each road condition of the current lane based on the sample data and a preset Bayesian classification algorithm;
taking the road condition corresponding to the maximum first probability as the target road condition of the current lane;
the obtaining of the first probability of each condition of the current lane based on the sample data and a preset Bayesian classification algorithm includes:
acquiring a second probability of the current lane under the ith road condition at the current passing moment according to the sample data; the historical driving data comprises driving data of the current lane and a lane next to the current lane;
acquiring a third probability that the current lane is possibly identified as a jth road condition when the current lane is in the ith road condition;
acquiring a fourth probability that the next lane is possibly identified as the kth road condition when the current lane is in the ith road condition;
obtaining a combined probability that the current lane is possibly identified as a jth road condition and the next lane is possibly identified as a kth road condition under the ith road condition according to the third probability and the fourth probability under the ith road condition;
obtaining a first probability of the current lane under the ith road condition based on the second probability under the ith road condition and the joint probability under the ith road condition;
wherein i is more than or equal to 1 and less than or equal to N; j is more than or equal to 1 and less than or equal to N, k is more than or equal to 1 and less than or equal to N, and N represents the number of road condition categories.
2. The vehicle navigation method according to claim 1, wherein the obtaining of the target road condition of each lane to be traveled comprises:
for each vehicle to be driven, receiving driving data of each vehicle driven on the lane to be driven;
acquiring the running speed of each vehicle from the running data;
and determining the target road condition of the lane to be driven according to the driving speed.
3. The vehicle navigation method according to claim 2, wherein the determining the target road condition of the lane to be traveled according to the traveling speed comprises:
carrying out weighted average on the running speeds of all vehicles to obtain the weighted running speed of the lane to be run;
comparing the weighted running speed with a preset running speed range of each road condition, and determining a target running speed range in which the weighted running speed falls;
and taking the road condition corresponding to the target driving speed range as the target road condition of the lane to be driven.
4. The vehicle navigation method according to any one of claims 1 to 3, wherein before determining the current lane in which the target vehicle is located according to the travel track of the target vehicle, the method further comprises:
and acquiring a starting point and a destination of a user, and navigating the path for the target vehicle according to the starting point and the destination.
5. The vehicle navigation method according to any one of claims 1 to 3, wherein the marking of the target road condition of the current lane and each lane to be traveled on the navigated path comprises:
marking the target road condition of the current lane on the navigated path according to a marking format corresponding to the target road condition of the current lane, and displaying the target road condition through a display screen;
and marking the target road condition of the lane to be driven on the navigated path according to a marking format corresponding to the target road condition of the lane to be driven, and displaying the target road condition through a display screen.
6. A vehicular navigation apparatus, characterized by comprising:
the determining module is used for determining a current lane where the target vehicle is located according to the running track of the target vehicle;
the first acquisition module is used for acquiring a lane to be driven of the target vehicle in the process of reaching the destination from the current lane according to the current lane and the navigation path;
the second acquisition module is used for acquiring the target road condition of the current lane and the target road condition of each lane to be driven;
the marking module is used for marking the current lane and the target road condition of each lane to be driven on the navigated path;
the second obtaining module includes:
the system comprises a first acquisition unit, a second acquisition unit and a control unit, wherein the first acquisition unit is used for acquiring historical driving data as sample data;
the second acquisition unit is used for acquiring a first probability of each road condition of the current lane based on the sample data and a preset Bayesian classification algorithm;
the determining unit is used for taking the road condition corresponding to the maximum first probability as the target road condition of the current lane;
the second obtaining unit is configured to:
acquiring a second probability of the current lane under the ith road condition at the current passing moment according to the sample data; the historical driving data comprises driving data of the current lane and a lane next to the current lane;
acquiring a third probability that the current lane is possibly identified as a jth road condition when the current lane is in the ith road condition;
acquiring a fourth probability that the next lane is possibly identified as the kth road condition when the current lane is in the ith road condition;
obtaining a combined probability that the current lane is possibly identified as a jth road condition and the next lane is possibly identified as a kth road condition under the ith road condition according to the third probability and the fourth probability under the ith road condition;
obtaining a first probability of the current lane under the ith road condition based on the second probability under the ith road condition and the joint probability under the ith road condition;
wherein i is more than or equal to 1 and less than or equal to N; j is more than or equal to 1 and less than or equal to N, k is more than or equal to 1 and less than or equal to N, and N represents the number of road condition categories.
7. The vehicle navigation device of claim 6, wherein the second obtaining module is further configured to:
for each vehicle to be driven, receiving driving data of each vehicle driven on the lane to be driven;
acquiring the running speed of each vehicle from the running data;
and determining the target road condition of the lane to be driven according to the driving speed.
8. The vehicle navigation device of claim 7, wherein the second obtaining module is further configured to:
carrying out weighted average on the running speeds of all vehicles to obtain the weighted running speed of the lane to be run;
comparing the weighted running speed with a preset running speed range of each road condition, and determining a target running speed range in which the weighted running speed falls;
and taking the road condition corresponding to the target driving speed range as the target road condition of the lane to be driven.
9. A computer device comprising a processor and a memory; wherein the processor executes a program corresponding to the executable program code by reading the executable program code stored in the memory for implementing the vehicle navigation method according to any one of claims 1 to 5.
10. A non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the vehicle navigation method of any one of claims 1-5.
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| CN109782776B (en) * | 2019-03-28 | 2022-07-29 | 北京百度网讯科技有限公司 | Lane selection method and device for unmanned vehicle and storage medium |
| CN111798658A (en) * | 2019-11-08 | 2020-10-20 | 方勤 | Traffic lane passing efficiency detection platform |
| CN111582030B (en) * | 2020-04-02 | 2023-08-29 | 北京百度网讯科技有限公司 | Traffic light identification method and device, electronic equipment and computer storage medium |
| CN112325896B (en) * | 2020-10-30 | 2023-03-14 | 上海商汤临港智能科技有限公司 | Navigation method, navigation device, intelligent driving equipment and storage medium |
| CN114092911B (en) * | 2021-11-23 | 2023-08-01 | 北京百度网讯科技有限公司 | Road identification method, device, electronic equipment and storage medium |
| CN114537450A (en) * | 2022-04-25 | 2022-05-27 | 小米汽车科技有限公司 | Vehicle control method, device, medium, chip, electronic device and vehicle |
| CN114863285B (en) * | 2022-05-27 | 2023-09-05 | 北京百度网讯科技有限公司 | Method, device, equipment and storage medium for identifying target road |
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