CN114299712B - Data processing method, device, equipment and readable storage medium - Google Patents

Data processing method, device, equipment and readable storage medium Download PDF

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Publication number
CN114299712B
CN114299712B CN202111420690.2A CN202111420690A CN114299712B CN 114299712 B CN114299712 B CN 114299712B CN 202111420690 A CN202111420690 A CN 202111420690A CN 114299712 B CN114299712 B CN 114299712B
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vehicle
lane change
speed
attribute information
determining
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CN114299712A (en
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吴跃进
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Tencent Technology Shenzhen Co Ltd
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Tencent Technology Shenzhen Co Ltd
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Abstract

The application discloses a data processing method, a device, equipment and a readable storage medium, wherein the method comprises the following steps: acquiring a historical driving track associated with a road intersection; the historical driving track refers to the driving track before the driving vehicle turns to the intersection at the road intersection; acquiring a vehicle position in a historical driving track and driving attribute information corresponding to the vehicle position; determining a speed change function corresponding to the historical driving track according to the driving attribute information, and determining a reference lane change position associated with the historical driving track according to the speed change function; and determining the optimal lane change position for the target running vehicle in the running range of the road intersection according to the reference lane change position. By adopting the method and the device, the optimal lane change position can be determined for different road intersections in a targeted manner, and the adaptation degree between the road intersections and the lane change positions is improved. The embodiment of the application can be applied to various scenes such as cloud technology, artificial intelligence, intelligent traffic, auxiliary driving and the like.

Description

Data processing method, device, equipment and readable storage medium
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a data processing method, apparatus, device, and readable storage medium.
Background
With the development of urban progress, road traffic is increasingly complex, for example, a plurality of guide lanes exist for a certain intersection, and a corresponding driving operation can be performed at the intersection only when the corresponding guide lane is driven (for example, left-turning driving can be performed when the intersection is reached only when the left-turning guide lane is driven).
At present, when a vehicle is traveling toward an intersection, if turning traveling behavior (such as left turn, right turn, turning around, etc.) is desired to be generated at the intersection, the vehicle needs to travel on a guide lane corresponding to the turning traveling behavior before the turning traveling behavior can be generated at the intersection. For example, when a left turn is desired at an intersection, the vehicle needs to travel on a left turn guide lane in advance, when a right turn is desired, the vehicle needs to travel on a right turn guide lane in advance, and when a turn is desired, the vehicle needs to travel on a turn guide lane in advance. It will be appreciated that in general, if a right turn at an intersection is desired, and the vehicle is now traveling on a guide lane other than the right turn, the vehicle may be driven on the right-turn guide lane by changing the lane in advance, so that the vehicle can make a right turn when arriving at the intersection, under the premise of allowing the lane change.
However, because of various traffic conditions, the traffic flow is large, if the lane change is too early, the running influence can be caused for surrounding vehicles to come and go, and the running speed of the vehicle is also influenced; if the lane change is too late, the lane change may be caused to be out of date, so that the road cannot be correctly turned at the intersection. The method is characterized in that the method comprises the steps of determining a lane changing time, wherein the lane changing time is determined by a method of determining the lane changing time according to the type of the lane changing time, and the method is characterized in that the lane changing time is determined by a method of determining the lane changing time according to the type of the lane changing time.
Disclosure of Invention
The embodiment of the application provides a data processing method, a device, equipment and a readable storage medium, which can pointedly determine the optimal lane change position for different road intersections and improve the adaptation degree between the road intersections and the lane change position.
In one aspect, an embodiment of the present application provides a data processing method, including:
Acquiring a historical driving track associated with a road intersection; the historical driving track refers to the driving track before the driving vehicle turns to the intersection at the road intersection;
acquiring a vehicle position in a historical driving track and driving attribute information corresponding to the vehicle position;
determining a speed change function corresponding to the historical driving track according to the driving attribute information, and determining a reference lane change position associated with the historical driving track according to the speed change function;
and determining the optimal lane change position for the target running vehicle in the running range of the road intersection according to the reference lane change position.
In one aspect, another data processing method is provided in an embodiment of the present application, including:
when the fact that the vehicle to be steered reaches the driving range of the road intersection is detected, acquiring an optimal lane changing position;
displaying a lane change indication animation comprising an optimal lane change position in a terminal navigation interface; the lane change instruction animation is used for guiding an object corresponding to the vehicle to be steered, and controlling the vehicle to be steered to run into the target lane from the lane change position; the target lane refers to a lane for performing an intersection turning action at a road intersection.
An aspect of an embodiment of the present application provides a data processing apparatus, including:
The driving track acquisition module is used for acquiring a historical driving track associated with the road intersection; the historical driving track refers to the driving track before the driving vehicle turns to the intersection at the road intersection;
the driving information acquisition module is used for acquiring the vehicle position in the historical driving track and driving attribute information corresponding to the vehicle position;
the function determining module is used for determining a speed change function corresponding to the historical driving track according to the driving attribute information;
the reference position determining module is used for determining a reference lane change position associated with the historical driving track according to the speed change function;
and the optimal position determining module is used for determining the optimal lane change position for the target running vehicle in the running range of the road intersection according to the reference lane change position.
In one embodiment, the number of vehicle positions is at least two;
a function determination module comprising:
the position filtering unit is used for filtering at least two vehicle positions according to the driving attribute information to obtain filtered vehicle positions;
and the function determining unit is used for determining a speed change function corresponding to the historical driving track according to the driving attribute information of the filtered vehicle position.
In one embodiment, the at least two vehicle positions include a vehicle position K j J is a positive integer; the driving attribute information comprises time attribute information, position coordinate attribute information, positioning accuracy attribute information, driving speed attribute information and offset angle attribute information;
a location filtering unit comprising:
a matching subunit for matching the filtered vehicle position K j Matching the time attribute information of (2) with the time demand index;
a matching subunit for matching the vehicle position K j Matching the position coordinate attribute information of the (b) with the position coordinate requirement index;
a matching subunit for matching the vehicle position K j Matching the positioning precision attribute information of the (2) with the precision requirement index;
a matching subunit for matching the vehicle position K j Matching the running speed attribute information of (2) with the running speed requirement index;
a matching subunit for matching the vehicle position K j Matching the offset angle attribute information of the (2) with an offset angle requirement index;
a filtering position determining subunit for determining the position K of the vehicle j The time attribute information of (2) satisfies the time stamp requirement index and the vehicle position K j Position coordinate attribute information satisfaction bits of (a)Coordinate demand index and vehicle position K j The positioning accuracy attribute information of (1) meets the accuracy requirement index, and the vehicle position K j The driving speed attribute information of (1) satisfies the driving speed requirement index and the vehicle position K j The offset angle attribute information of (1) meets the offset angle requirement index, and the vehicle position K j If the offset angle attribute information of (1) meets the offset angle requirement index, the vehicle position K is determined j As a filtered vehicle location.
In one embodiment, the travel attribute information includes travel speed attribute information; the number of the filtered vehicle positions is at least two, and the at least two filtered vehicle positions comprise the filtered vehicle position K m M is a positive integer;
a function determination unit comprising:
a distance determination subunit for determining the filtered vehicle position K m The interval distance between the road crossing and the road crossing is used as a first interval distance;
a speed coordinate determination subunit for acquiring the filtered vehicle position K m Corresponding running speed attribute information, the first interval distance and the filtered vehicle position K m Corresponding running speed attribute information forming a filtered vehicle position K m Corresponding speed coordinates;
and the function determining subunit is used for determining a speed change function corresponding to the historical driving track according to at least two speed coordinates when determining the speed coordinates corresponding to at least two filtered vehicle positions respectively.
In one embodiment, the function determining subunit is further specifically configured to obtain a linear fitting model, and perform linear fitting on at least two velocity coordinates according to the linear fitting model to obtain a linear fitting function;
the function determining subunit is further specifically configured to determine the linear fitting function as a speed change function corresponding to the historical driving track.
In one embodiment, the function determining subunit is further specifically configured to input at least two velocity coordinates to the linear fitting model, and determine N candidate linear fitting functions corresponding to the at least two velocity coordinates through the linear fitting model; n is a positive integer;
the function determining subunit is further specifically configured to determine error reference values corresponding to the N candidate linear fitting functions respectively based on at least two velocity coordinates;
the function determining subunit is further specifically configured to obtain a minimum error reference value of the N error reference values, and determine a candidate linear fitting function corresponding to the minimum error reference value of the N candidate linear fitting functions as the linear fitting function.
In one embodiment, the N candidate linear fit functions include candidate linear fit function F x X is a positive integer;
the function determination subunit is also specifically configured to obtain a candidate linear fitting function F x Drawing a fitting curve in a curve coordinate system; the curve coordinate system is a coordinate system constructed by a distance axis and a speed axis;
the function determination subunit is further specifically configured to obtain candidate velocity coordinates on the drawn fitting curve, and determine a candidate linear fitting function F according to the candidate velocity coordinates and at least two velocity coordinates x Corresponding error reference values.
In one embodiment, the speed change function includes a separation distance between the vehicle location and the road junction;
a reference position determination module comprising:
a partial derivative determining unit for determining a partial derivative between the speed change function and a separation distance between the vehicle position and the road junction;
and the reference position determining unit is used for estimating a variable value of the interval distance between the vehicle position and the road intersection through the partial derivative and determining the variable value as the reference lane change position.
In one embodiment, the number of historical travel tracks is at least two; the reference lane-change locations include one or more reference lane-change locations associated with at least two historical travel tracks;
an optimal position determination module comprising:
a separation distance determining unit, configured to use separation distances between one or more reference lane change positions and the road junction, as second separation distances;
The interval distance sequencing unit is used for sequencing the one or more second interval distances according to the order of the magnitudes of the one or more second interval distances to obtain an interval distance sequence;
and the optimal position determining unit is used for determining the optimal lane change position according to the interval distance sequence.
In one embodiment, the optimal position determining unit comprises:
the summation processing subunit is used for carrying out summation processing on the interval distance sequence to obtain an operation distance;
the distance average value determining subunit is used for obtaining the total number of one or more second interval distances and determining an interval distance average value corresponding to the interval distance sequence according to the operation distance and the total number;
and the optimal position determining subunit is used for acquiring the numerical attribute to which the total number belongs and determining the optimal lane change position according to the numerical attribute and the interval distance mean value.
In one embodiment, the optimal position determining subunit is further specifically configured to determine, if the numerical attribute is an odd attribute, a second interval distance in the interval distance sequence at the central position as a central interval distance, determine an average value between an interval distance average value and the central interval distance as a first optimal interval distance, and determine a position where the first optimal interval distance is located as an optimal lane change position;
The optimal position determining subunit is further specifically configured to determine, if the numerical attribute is an even attribute, a second interval distance in the center position in the interval distance sequence as an interval distance to be operated, perform average value operation on the interval distance to be operated to obtain an average value operation distance, determine, as a second optimal interval distance, an average value between an interval distance average value and the average value operation distance, and determine, as an optimal lane change position, a position where the second optimal interval distance is located.
In one embodiment, the data processing apparatus further comprises:
the position acquisition module is used for acquiring an optimal lane change position when the target running vehicle is detected to reach the running range of the road intersection;
the adaptive speed acquisition module is used for acquiring the adaptive lane change speed corresponding to the optimal lane change position when the target running vehicle is detected to reach the optimal lane change position;
and the lane change running module is used for switching the running speed of the target running vehicle from the current running speed to the adaptive lane change speed and controlling the target running vehicle to perform lane change running from the optimal lane change position at the adaptive lane change running speed.
In one aspect, another data processing apparatus is provided in an embodiment of the present application, including:
The optimal position acquisition module is used for acquiring an optimal lane change position when detecting that the vehicle to be steered reaches the driving range of the road intersection;
the animation display module is used for displaying a lane change indication animation comprising the optimal lane change position in the terminal navigation interface; the lane change instruction animation is used for guiding an object corresponding to the vehicle to be steered, and controlling the vehicle to be steered to run into the target lane from the lane change position; the target lane refers to a lane for performing an intersection turning action at a road intersection.
In one aspect, a computer device is provided, including: a processor and a memory;
the memory stores a computer program that, when executed by the processor, causes the processor to perform the methods of embodiments of the present application.
In one aspect, embodiments of the present application provide a computer-readable storage medium storing a computer program, where the computer program includes program instructions that, when executed by a processor, perform a method in an embodiment of the present application.
In one aspect of the present application, a computer program product or computer program is provided that includes computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the method provided in an aspect of the embodiments of the present application.
In the embodiment of the application, a historical driving track associated with a road intersection can be obtained, wherein the historical driving track can be the driving track of a driving vehicle before the intersection steering action occurs at the road intersection; according to the driving attribute information corresponding to the vehicle position included in the history driving track, a speed change function corresponding to the history driving track can be determined, and according to the speed change function, a reference lane change position associated with the history driving track can be determined; and determining the optimal lane change position for the target running vehicle in the running range of the road intersection according to the reference lane change position. It should be understood that, the present application can determine the reference lane change position (reference lane change timing) corresponding to the historical driving track associated with the road intersection, and the reference lane change position based on the historical driving track can mine the optimal lane change position (i.e. the lane change timing most suitable for the road intersection) of the road intersection. In conclusion, the method and the device can pointedly determine the optimal lane change positions for different road intersections, and improve the adaptation degree between the road intersections and the lane change positions.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a network architecture diagram provided in an embodiment of the present application;
FIG. 2 is a flow chart of a method for data processing according to an embodiment of the present disclosure;
fig. 3a is a schematic illustration of an intersection of a road provided in an embodiment of the present application;
FIG. 3b is a schematic diagram of a historical driving track provided in an embodiment of the present application;
FIG. 3c is a graph illustrating a speed change function provided by an embodiment of the present application;
fig. 4 is a schematic view of a scene of a lane change navigation hint according to an embodiment of the present application;
FIG. 5 is a schematic flow chart of determining a speed change function according to an embodiment of the present application;
FIG. 6 is a flow chart of a data processing method according to an embodiment of the present application;
fig. 7 is a schematic view of a scene of lane change based on an optimal lane change position according to an embodiment of the present application;
FIG. 8 is a schematic diagram of a data processing apparatus according to an embodiment of the present application;
FIG. 9 is a schematic diagram of another data processing apparatus according to an embodiment of the present application;
fig. 10 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
The present application relates to the field of intelligent transportation, and for ease of understanding, the following will first describe intelligent transportation and its related concepts.
The intelligent vehicle-road cooperative system (Intelligent Vehicle Infrastructure Cooperative Systems, IVICS), which is simply called a vehicle-road cooperative system, is one development direction of an Intelligent Transportation System (ITS). The vehicle-road cooperative system adopts advanced wireless communication, new generation internet and other technologies, carries out vehicle-vehicle and vehicle-road dynamic real-time information interaction in all directions, develops vehicle active safety control and road cooperative management on the basis of full-time idle dynamic traffic information acquisition and fusion, fully realizes effective cooperation of people and vehicles and roads, ensures traffic safety, improves traffic efficiency, and forms a safe, efficient and environment-friendly road traffic system.
The intelligent transportation system (Intelligent Traffic System, ITS), also called intelligent transportation system (Intelligent Transportation System), is a comprehensive transportation system which uses advanced scientific technology (information technology, computer technology, data communication technology, sensor technology, electronic control technology, automatic control theory, operation study, artificial intelligence, etc.) effectively and comprehensively for transportation, service control and vehicle manufacturing, and enhances the connection among vehicles, roads and users, thereby forming a comprehensive transportation system for guaranteeing safety, improving efficiency, improving environment and saving energy.
The application relates to an automatic driving technology in an intelligent traffic system. Autopilot refers to the highly centralized control of a vehicle that is fully automated to drive the vehicle. The automatic driving technology has the functions of automatically waking up, starting and sleeping, automatically entering and exiting a parking lot, automatically cleaning, automatically driving, automatically stopping, automatically opening and closing a vehicle door, automatically recovering faults and the like, and has various operation modes such as normal operation, degraded operation, operation interruption and the like. The full-automatic operation can be realized, the energy sources can be saved, and the reasonable matching of the energy consumption and the speed of the system can be optimized.
Referring to fig. 1, fig. 1 is a network architecture diagram provided in an embodiment of the present application. As shown in fig. 1, the network architecture may include a service server 1000 and a terminal device cluster, which may include one or more terminal devices, the number of which will not be limited here. As shown in fig. 1, the plurality of terminal devices may include a terminal device 100a, a terminal device 100b, terminal devices 100c, …, a terminal device 100n; as shown in fig. 1, the terminal devices 100a, 100b, 100c, …, 100n may respectively perform network connection with the service server 1000, so that each terminal device may perform data interaction with the service server 1000 through the network connection.
It is to be understood that the terminal devices in the terminal device cluster shown in fig. 1 may include an intelligent traffic service terminal, and the service server 1000 may be an intelligent traffic service server (hereinafter, the terminal device 100a is referred to as an intelligent traffic service terminal 100a, and the service server is referred to as an intelligent traffic server 1000); taking the terminal device 100a in the terminal device cluster as an intelligent traffic service terminal as an example, a user can create a road intersection management task through the intelligent traffic service terminal, and realize related visual functions (for example, the user can configure which intersection the road intersection is for the road intersection management task, which intersection management item is, and the like) of managing, configuring, displaying, running and the like the road intersection management task through the intelligent traffic service terminal 100a, so that the intelligent traffic service terminal 100a can facilitate the user to efficiently perform systematic intersection management work.
Taking the road intersection configured by the user as the road intersection management task as the road intersection a, the intersection management project is taken as the lane change timing determining project as an example, further, the intelligent traffic service terminal 100a may send the road intersection management task created by the user and the information configured by the user (which may be referred to as task configuration information: may include a road intersection name, an intersection management project, and the like) to the intelligent traffic server 1000, and the intelligent traffic server 1000 may obtain, based on the road intersection management task, a historical driving track associated with the road intersection (may refer to a driving track before the intersection turning action of different driving vehicles occurs at the road intersection a), and determine a lane change timing with suitability to the road intersection (the lane change timing may be understood as a position where the lane change is most suitable for the lane change when the distance between the vehicles and the intersection is within a certain numerical range, that is, and will be referred to as an optimal lane change position hereinafter).
In the application, the specific process of determining the optimal lane change position of the road intersection based on the historical driving track can be as follows: the historical driving track can be a track formed by a plurality of GPS positions obtained by positioning through a global positioning system (Global Positioning System, abbreviated as GPS), wherein each GPS position is actually the position of each vehicle of the driving vehicle. The present application may acquire the vehicle position included in the history travel track and the travel attribute information corresponding to the vehicle position (travel related information of the traveling vehicle, for example, the travel attribute information may include a vehicle travel speed, a positioning time stamp, GPS positioning accuracy, an offset angle of a steering wheel compared to a road lane line, etc.), determine a speed change function corresponding to the history travel track according to the travel attribute information, determine a reference lane change position associated with the history travel track according to the speed change function (i.e., determine a speed change function according to a history travel track, and solve a lane change timing according to the speed change function to obtain a reference lane change position); subsequently, the intelligent transportation server 1000 may determine an optimal lane-changing position most adapted to the road junction a based on the reference lane-changing position of the historical driving trajectory.
It should be understood that the intelligent transportation server 1000 may return the optimal lane change position to the intelligent transportation service terminal 100a, and when a target traveling vehicle within the traveling range of the road junction a desires a turning action (i.e., a turning action) at the road junction a, the optimal lane change position of the road junction a may be determined by the intelligent transportation service terminal 100a, and then the speed-down lane change may be performed when traveling to the optimal lane change position.
The intelligent transportation server 1000 may refer to a server device that implements a background function related to an intelligent transportation system.
It should be understood that by acquiring a history travel track associated with a road intersection (a travel track of a traveling vehicle before an intersection turning action occurs at the road intersection) and acquiring a vehicle position thereof and travel attribute information corresponding to the vehicle position thereof, a speed change function corresponding to the history travel track can be determined according to the travel attribute information, a reference lane change position associated with the history travel track can be determined based on the speed change function, and an optimal lane change position adapted to the road intersection can be determined based on the reference lane change position. That is, the method and the device can dig out the most adaptive optimal lane change position for the road intersection according to the historical driving track of the road intersection, and can well improve the accuracy of the optimal lane change position.
The embodiment of the application can select one terminal device from a plurality of terminal devices as a target terminal device, and the terminal device can include: smart phones, tablet computers, notebook computers, desktop computers, smart televisions, smart speakers, desktop computers, smart watches, vehicle-mounted devices, smart voice interaction devices, smart home appliances, and the like carry smart terminals for multimedia data processing functions (e.g., video data playing functions, music data playing functions), but are not limited thereto. For example, the embodiment of the present application may use the terminal device 100a shown in fig. 1 as the target terminal device, where the target terminal device may be integrated with the target application, and at this time, the target terminal device may perform data interaction between the target application and the service server 1000.
It is understood that the method provided in the embodiments of the present application may be performed by a computer device, including but not limited to a terminal device or a service server. The service server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs, basic cloud computing services such as big data and artificial intelligence platforms.
The terminal device and the service server may be directly or indirectly connected through wired or wireless communication, which is not limited herein.
Alternatively, it is understood that the computer device (e.g., the service server 1000, the terminal device 100a, the terminal device 100b, etc.) may be a node in a distributed system, where the distributed system may be a blockchain system, and the blockchain system may be a distributed system formed by connecting the plurality of nodes through a network communication. Among them, a Peer-To-Peer (P2P) network may be formed between nodes, and the P2P protocol is an application layer protocol running on top of a transmission control protocol (TCP, transmission Control Protocol) protocol. In a distributed system, any form of computer device, such as a service server, terminal device, etc., can become a node in the blockchain system by joining the point-to-point network. For ease of understanding, the concept of blockchain will be described as follows: the block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like, and is mainly used for sorting data according to time sequence, encrypting the data into an account book, preventing the account book from being tampered and forged, and simultaneously verifying, storing and updating the data. When the computer equipment is a blockchain node, due to the characteristics of the blockchain, such as untampered characteristics and anti-counterfeiting characteristics, the data (such as historical driving tracks, optimal lane changing positions corresponding to road intersections and the like) in the method can be provided with authenticity and safety, so that the obtained result is more reliable after relevant data processing is performed based on the data.
Further, referring to fig. 2, fig. 2 is a method flow chart of a data processing method according to an embodiment of the present application. The data processing method may be performed by a service server (e.g., the service server 1000 in the embodiment corresponding to fig. 1) or may be performed by a terminal device (e.g., any one of the terminal devices in the terminal device cluster in the embodiment corresponding to fig. 1, such as the terminal device 100 a); the data processing method may also be executed by the terminal device together with the service server, and for ease of understanding, the following description will be given by way of example of the data processing method executed by the service server. As shown in fig. 2, the flow may include at least the following steps S101 to S104:
step S101, acquiring a historical driving track associated with a road intersection; the history travel track refers to a travel track of a traveling vehicle before an intersection turning action occurs at an intersection of a road.
In the present application, it is understood that in the road network, a road may be divided into a plurality of sub-roads, and the branching fork divided into the plurality of sub-roads may be referred to as a road intersection. For ease of understanding, please refer to fig. 3a, fig. 3a is a schematic diagram of a road junction according to an embodiment of the present application. As shown in fig. 3a, at the road intersection 30a, roads can be divided into garden 1, garden 2, garden 3, and garden 4, and the road 30a can be called a road intersection.
It will be appreciated that there are one or more road lanes for each road junction, each road lane may be understood as a guide lane, one guide lane allowing only one vehicle to travel in parallel, while guide lanes may be specifically divided into left turn guide lanes, straight guide lanes, right turn guide lanes, turn around guide lanes, etc., each guide lane may be specifically used to indicate a junction switch direction of a user at a road junction. For example, if a left turn mark exists on a certain road lane, the road lane can be determined as a left turn guiding lane, and when a vehicle drives to a road intersection, the vehicle can only drive to the left turn guiding lane and be positioned in the left turn guiding lane at the road intersection, so that the vehicle can perform left turn at the road intersection; for example, if a straight traveling sign exists on a certain road lane, the road lane may be determined as a straight traveling guide lane, and when a vehicle is driven to a road intersection, the vehicle can only travel on the straight traveling guide lane and be located in the straight traveling guide lane at the road intersection, and can be executed at the road intersection.
It can be understood that, during the actual driving process of the user, the navigation terminal application in the vehicle can acquire the vehicle position information of the vehicle in real time (after the user grants permission, the vehicle position information is acquired), for example, the GPS position information can be acquired through positioning by a global positioning system (Global Positioning System, abbreviated as GPS), and each GPS position information can form a GPS driving track, that is, the GPS driving track can reflect the actual driving process of the user. In this application, the historical driving track associated with a road intersection may refer to a driving track of a driving vehicle passing through the road intersection and before a turning action occurs at the road intersection (i.e. an intersection steering action occurs). That is, if a certain user passes through the road intersection and turns (e.g., turns left) at the road intersection while driving, a driving track for the user can be formed according to the GPS positions acquired by the navigation terminal application, and the corresponding driving track can be used as a candidate driving track due to the turning behavior at the road intersection. The candidate running track covers the track of the user at and after the road intersection, and the running track in front of the road intersection can be obtained from the candidate running track to serve as the historical running track.
Alternatively, it may be understood that, for facilitating subsequent calculation, when the running track of the vehicle position in front of the road intersection is obtained, the running track may be used as a running track to be cut, and the running track in a certain distance range (for example, within 1000 meters from the road intersection) in front of the road intersection may be obtained from the running track to be cut and used as a historical running track.
For easy understanding of the historical driving track, please refer to fig. 3b, fig. 3b is a schematic diagram of the historical driving track according to an embodiment of the present application. As shown in fig. 3b, for a certain road junction, there are a left turn guide lane 300a, a straight guide lane 300b, a right turn guide lane 300c, and a travel lane 300d. The running track of a vehicle may be shown in fig. 3b, where the running track may be composed of a plurality of GPS-located vehicle positions, where the running track may include a vehicle position 3000b and a vehicle position 3000a, and the running direction indicated by the running track is a direction from the vehicle position 3000b to the vehicle position 3000 a. That is, as shown in fig. 3b, the vehicle first travels in the straight-ahead guide lane 300b, then travels in the right-turn guide lane after traveling through the lane change, and then makes a right turn into the travel lane 300d when reaching the road junction. Since the travel locus is a travel locus where an intersection turning action (i.e., a right turn action) is generated at the road intersection, the travel locus can be taken as a reference travel locus for determining the optimal lane change position of the road intersection. It is to be understood that, of the travel tracks, the travel track preceding the road junction may be acquired as the history travel track associated with the road junction. For example, assuming that the vehicle position 3000a is the vehicle position at which the vehicle arrives at the road junction and the right turn behavior is generated, and assuming that the vehicle position 3000b is already within the travel range of the road junction (for example, within 1000 meters from the road junction), the travel locus formed by the start position 3000b, the end position 3000a, and all the vehicle positions between the start position 3000a and the end position 3000a may be referred to herein as one historic travel locus by taking the vehicle position 3000b as the start position and taking the vehicle position 3000a as the end position.
Step S102, acquiring the vehicle position in the historical driving track and driving attribute information corresponding to the vehicle position.
In the present application, as can be seen from the above description, the historical driving track may actually refer to a track composed of a plurality of GPS positioning positions (i.e., vehicle positions), and then the present application may obtain each vehicle position in the historical driving track and driving attribute information corresponding to each vehicle position.
It is to be understood that, here, the running attribute information may refer to corresponding running related information when the running vehicle is at the current vehicle position. For example, the travel attribute information of each vehicle position may include time information (i.e., time stamp information when the position is reached, which may be referred to as time attribute information), position coordinate information (e.g., longitude and latitude coordinate information of the current vehicle position, which may be referred to as position coordinate attribute information), accuracy information (e.g., positioning accuracy of GPS, which may be referred to as positioning accuracy attribute information), travel speed information (e.g., what the travel speed of the vehicle is when at the current vehicle position, which may be referred to as travel speed attribute information), direction angle information (e.g., an angle between the travel direction of the vehicle and a lane line of a lane at the current vehicle position, which may be referred to as offset angle attribute information), and the like.
Step S103, determining a speed change function corresponding to the historical driving track according to the driving attribute information, and determining a reference lane change position associated with the historical driving track according to the speed change function.
In the present application, the speed change function corresponding to the historical driving track may be determined according to the driving attribute information, such as the time attribute information, the position coordinate attribute information, the positioning accuracy attribute information, the driving speed attribute information, and the offset angle attribute information. The speed change function may include an independent variable, which may refer to a separation distance between the vehicle position and the road junction, and a dependent variable, which may refer to a corresponding travel speed at the vehicle position. For a specific implementation manner of determining the speed change function corresponding to the historical driving track according to the driving attribute information such as the time attribute information, the position coordinate attribute information, the positioning accuracy attribute information, the driving speed attribute information, the offset angle attribute information and the like, reference may be made to the description in the embodiment corresponding to fig. 4.
For easy understanding, please refer to formula (1), the speed change function corresponding to the historical driving track can be determined according to the driving attribute information as shown in formula (1):
y＝ax 2 +bx+c equation (1)
Where a in equation (1) may be referred to as a quadratic coefficient, b may be referred to as a first order coefficient, and c may be referred to as a constant term. The x in the formula (1) can be called an independent variable, the independent variable can be the distance between the independent variable and the road intersection, and the y in the formula (1) can be called a dependent variable, and the dependent variable can be used for representing the corresponding driving speed when the distance between the independent variable and the road intersection is a certain value through the difference of the independent variable x.
It is understood that after the speed change function corresponding to the historical driving locus is determined according to the driving attribute information, the reference lane change position associated with the historical driving locus may be determined according to the speed change function. That is, the lane-change timing for the historical travel track may be determined according to the speed change function. Taking the example of the speed change function as the unitary quadratic function shown in the above formula (1), the speed change function includes the interval distance (independent variable) between the vehicle position and the road junction, one specific implementation manner of determining the reference lane change position associated with the historical driving track according to the speed change function may be: determining a partial derivative between the speed change function and a separation distance between the vehicle location and the road junction; then, a variable value of the separation distance between the vehicle position and the road junction can be estimated by the partial derivative, and the variable value is determined as the reference lane change position.
For ease of understanding, a specific implementation of determining the reference lane-change position associated with the historical driving trajectory according to the speed change function will be described below in conjunction with the corresponding drawing of fig. 3 c. Fig. 3c is a schematic diagram of a speed change function according to an embodiment of the present application. The coordinate system shown in fig. 3c may be composed of a distance axis X and a travel speed axis Y, and the linear curve P (parabolic) in the coordinate system may refer to a curve obtained by plotting a speed change function, that is, the curve may be used to characterize the speed change function as shown in formula (1). As shown in fig. 3c, for the linear curve P, the deceleration point may be referred to as a reference point W, and as known by the evaluation method in the differential theory, a specific value of the deceleration point W may be obtained by solving the first partial derivative of the velocity change function with respect to X and making it a value 0 (which may be referred to as an invalid value). The X is an argument (i.e., the distance between the vehicle position and the road junction), that is, a partial derivative (e.g., first order partial derivative) between the speed change function and the distance between the vehicle position and the road junction may be determined, and let it be 0, so that the deceleration point (lane change timing) corresponding to the historical driving trajectory may be obtained.
The specific implementation manner for determining the specific value of the deceleration point can be as shown in the formula (2):
wherein in formula (2)The first order partial derivative of the solving speed change function Y with respect to the spacing distance x between the vehicle position and the road junction can be characterized, and 2ax+b can be used for characterizing the solved first order partial derivative. It will be appreciated that by taking the first partial derivative 2ax+b to be the value 0, the +.>And (wherein a is a constant value smaller than 0, and b is a constant value), determining a specific value of x through the constants a and b, wherein the specific value can be used as a reference lane change position corresponding to the historical driving track.
The speed change function is exemplified by a unitary quadratic function, and the expression of the speed change function is not limited to this. There may be different ways of determining the reference lane-change position for different forms of the speed-change function.
Step S104, determining the optimal lane change position for the target running vehicle in the running range of the road intersection according to the reference lane change position.
In this application, it is understood that, for a historical driving track, a reference lane change position associated therewith may be determined. Of course, for a certain historical driving track, there may be a case that the reference lane-change position cannot be determined, and then when the number of the historical driving tracks is at least two, one or more reference lane-change positions may be determined (one historical driving track may be associated with one reference lane-change position, then the total number of the reference lane-change positions is the same as the total number of the historical driving tracks, or a certain historical driving track cannot solve the reference lane-change positions, then the total number of the reference lane-change positions is different from the total number of the historical driving tracks, and the total number of the reference lane-change positions is smaller than the total number of the historical driving tracks).
It will be appreciated that, after determining the reference lane-change positions of each historical driving track, one or more reference lane-change positions are obtained, an optimal lane-change position may be determined based on the one or more reference lane-change positions. That is, the optimum lane change position adapted to the road junction is suitable for deceleration lane change travel at the optimum lane change position when the target travel vehicle travels within the travel range of the road junction.
For a target driving vehicle within the driving range of the road intersection according to the reference lane change position, one specific implementation manner of determining the optimal lane change position may be: the interval distance between one or more reference lane change positions and the road intersection can be obtained, and the interval distance between one or more reference lane change positions and the road intersection is used as a second interval distance; subsequently, the one or more second separation distances may be ordered in order of magnitude of the one or more second separation distances, thereby obtaining a separation distance sequence; subsequently, an optimal lane change position may be determined from the sequence of separation distances.
One specific implementation way for determining the optimal lane change position according to the interval distance sequence may be: the interval distance sequence can be summed to obtain an operation distance; then, the total number of one or more second interval distances can be obtained, and an interval distance average value corresponding to the interval distance sequence can be determined according to the operation distance and the total number; and then, acquiring the numerical attribute of the total number, and determining the optimal lane change position according to the numerical attribute and the interval distance mean value. The numerical attribute may include an odd number attribute and an even number attribute, that is, the total number is a specific numerical value, it may be determined whether the numerical value belongs to an odd number or an even number, and the optimal lane change position may be determined according to the numerical value attribute.
One specific implementation way for determining the optimal lane change position according to the numerical attribute and the interval distance mean value may be: if the numerical attribute is an odd attribute, a second interval distance at the central position in the interval distance sequence can be determined as a central interval distance, a mean value between an interval distance mean value and the central interval distance can be determined as a first optimal interval distance, and a position where the first optimal interval distance is located is determined as an optimal lane change position; if the numerical attribute is an even attribute, the second interval distance at the center position in the interval distance sequence can be determined as the interval distance to be operated, average operation processing can be performed on the interval distance to be operated to obtain an average operation distance, the average value between the interval distance average value and the average operation distance can be determined as the second optimal interval distance, and the position where the second optimal interval distance is located is determined as the optimal lane change position.
It will be appreciated that the lane-change timing may be understood as the distance from the road intersection (and may also be understood as a location point, for example, a location point 20m from the road intersection), and then each reference lane-change position (lane-change timing) may also be understood as a location point that is actually a distance from the road intersection, where each reference lane-change position may be referred to as a separation distance from the road intersection, referred to as a second separation distance. Taking the example that the reference lane change position includes a lane change position point 100m from the road intersection, a lane change position point 70m from the road intersection, a lane change position point 50m from the road intersection, and a lane change position point 30m from the road intersection, the second interval distances may include 100m, 70m, 50m, and 30m, and then all the second interval distances may be sorted according to the order of magnitude of the second interval distances to obtain the interval distance sequence. For example, the second distance intervals 100m, 80m, 50m, and 30m are sorted in order from the top to the bottom (i.e., from the far to the near road junction), and the distance sequences {100, 80, 50, 30} can be obtained after the sorting.
Further, the sum processing may be performed on the interval distance sequence to obtain an operation distance, where the sum processing is performed on the interval distance sequence to obtain an operation distance, that is, all second interval distances included in the interval distance sequence are subjected to addition processing, and then a sum value obtained by the addition processing is referred to as the operation distance. For example, for the distance sequence {100, 80, 50, 30}, all values in the distance sequence {100, 80, 50, 30} may be subjected to addition processing, that is, the second distance 100, the second distance 80, the second distance 50, and the second distance 30 may be subjected to addition processing to obtain a sum value 260, and the sum value 260 may be referred to as an operation distance.
Further, the total number of the second distances included in the sequence {100, 80, 50, 30} may be obtained, and based on the calculated distance 260 and the total number, a mean value of the distances corresponding to the sequence may be determined. For example, the total number of second intervals included in the interval sequence {100, 80, 50, 30} is 4, and the interval average value corresponding to the interval sequence {100, 80, 50, 30} is 65 (i.e., 260/4=65) can be determined based on the calculated distance 260 and the total number 4.
Further, a median value in the sequence of separation distances may be obtained. If the total number of the second interval distances included in the interval distance sequence is an odd number, the numerical value at the central position in the interval distance sequence can be directly obtained and used as a median value; if the total number of the second interval distances included in the interval distance sequence is even, two values exist at the center position of the interval distance sequence, the two second interval distances can be called as interval distances to be operated, and the average value between the two interval distances to be operated can be calculated, wherein the average value is the median value of the interval distance sequence. For example, for the sequence of separation distances {100, 80, 50, 30}, it includes a total number of second separation distances of 4, belonging to an even number. Then the second distance 80 and the second distance 50 at the center position can be obtained, the second distance 80 and the second distance 50 can be called as the distance to be calculated, the average value of the two second distances can be calculated as 65, and then the average value 65 can be called as the median value (which can be called as the average value calculation distance).
Further, the average value between the median 65 and the average value of the interval distances of the interval distance sequence 65 can be calculated as 65, and the average value 65 can be used as the optimal lane change position most suitable for the road intersection.
It should be noted that the above values (such as the second separation distance 100m, 80m, etc.) are all examples for easy understanding, and are not meant to be actually reference.
The optimal lane change position may be an optimal lane change position for a lane before an intersection turning operation is performed at the intersection. And since the intersection turning actions of the road intersection may include a left turn turning action, a right turn turning action, a turning around turning action, etc., the optimal lane change position for the road intersection may include an optimal lane change position for the left turn turning action (e.g., a position most suitable for changing lanes from a straight-guiding lane to a left turn-guiding lane), an optimal lane change position for the right turn turning action (e.g., a position most suitable for changing lanes from a straight-guiding lane to a right turn-guiding lane), an optimal lane change position for the turning around turning action (e.g., a position most suitable for changing lanes from a straight-guiding lane to a turning around guiding lane). The optimal lane-change position for an intersection turning action may be determined based on different historical travel trajectories, for example, the optimal lane-change position for a left-turn turning action may be determined based on a historical travel trajectory for a left-turn turning action occurring at a road intersection, the optimal lane-change position for a right-turn turning action may be determined based on a historical travel trajectory for a right-turn turning action occurring at a road intersection, and the historical travel trajectory for a turn-around turning action may be determined.
Of course, alternatively, in a possible embodiment, since the left-turn guiding lane, right-turn guiding lane, straight guiding lane and other lanes of the road intersection are actually parallel, equal in length and equal in width, the guiding lane of the road intersection includes only one left-turn guiding lane, one right-turn guiding lane and one straight guiding lane, and the straight guiding lane is located in a scene between the left-turn guiding lane and the right-turn guiding lane, the optimal lane changing position determined based on the historical driving track of the left-turn guiding lane occurring at the road intersection may be the optimal lane changing position for the right-turn guiding action, in addition to the optimal lane changing position for the left-turn guiding action, but the lane changing direction is different. For example, the determined optimal lane change position is at a certain position in the straight guiding lane, and when the traveling vehicle reaches the position, the lane change can be decelerated to the left guiding lane or the lane change can be decelerated to the right guiding lane.
It will be appreciated that after the optimal lane change position is determined, when the target traveling vehicle is within the traveling range of the road junction, a speed-down lane change may be performed when the optimal lane change position is reached. For example, when the user drives to a position 1000m away from the road junction, at this time, the target driving vehicle of the user is already within the driving range of the road junction, then the intelligent vehicle-mounted device in the target driving vehicle of the user can acquire the optimal lane change position associated with the road junction, if the user is determined to turn left at the road junction after navigating, but the lane where the current user is located is a straight lane, then the intelligent vehicle-mounted device can generate lane change voice prompt information based on the current vehicle position and the optimal lane change position, and output the lane change voice prompt information to prompt the user to perform speed reduction lane change when the user reaches the optimal lane change position.
The embodiment of the application can be applied to various scenes including, but not limited to, cloud technology, artificial intelligence, intelligent traffic, driving assistance and the like, and for convenience of understanding, please refer to fig. 4, fig. 4 is a schematic view of a scene of a lane change navigation prompt provided in the embodiment of the application. As shown in fig. 4, when a user drives on a left-turn steering lane, the intelligent vehicle-mounted terminal 100a in the vehicle determines that the user should turn right at a road junction to reach a destination, and the intelligent vehicle-mounted terminal 100a may output corresponding audio data to instruct the user to perform lane change and the like. For example, as shown in fig. 4, the intelligent vehicle-mounted terminal 100a may acquire that the current position of the vehicle (may be referred to as the current vehicle position) is on the left-turn guiding lane, and needs to change the lane from the straight guiding lane to the right-turn guiding lane. As shown in fig. 4, the intelligent in-vehicle terminal 100a may acquire the optimal lane change position from the left-hand guided lane to the straight lane, and as shown in fig. 4, assuming that the optimal lane change position from the left-hand guided lane to the straight lane acquired by the intelligent in-vehicle terminal 100a is the position 40a, the intelligent in-vehicle terminal 100a may acquire the distance (assumed to be 50 m) from the current vehicle position to the optimal lane change position 40a, and at this time, the intelligent in-vehicle terminal 100a may output audio data "please speed down lane change to the middle lane at 50m in front" for instructing the user to speed down lane change at the position 40 a.
When the user arrives at the position 40a, the intelligent vehicle-mounted terminal 100a can output audio data of 'please change the lane to the middle lane', which is used for indicating the user to speed up and change the lane to the straight lane at the moment; as shown in fig. 4, when the user changes lanes into the straight lane, the intelligent in-vehicle terminal 100a may acquire an optimal lane change position from the straight-guiding lane to the right-turning guiding lane, and as shown in fig. 4, assuming that the optimal lane change position from the straight-guiding lane to the right-turning guiding lane acquired by the intelligent in-vehicle terminal 100a is the position 40b, the intelligent in-vehicle terminal 100a may acquire a distance (assumed to be 200 m) from the current vehicle position to the optimal lane change position 40b, and at this time, the intelligent in-vehicle terminal 100a may output audio data "please forward 20m for a speed-down lane change to the right-turning lane" for instructing the user to perform the speed-down lane change at the position 40 b.
When the user arrives at the position 40b, the intelligent vehicle-mounted terminal 100a can output audio data of 'please change the lane to the rightmost lane', which is used for indicating the user to change the lane to the right-turn lane by speed reduction at the moment; as shown in fig. 4, when the user changes lanes into a right turn lane and travels to a road junction, the intelligent in-vehicle terminal 100a may output audio data "turn right, enter aa road" for instructing the user to turn right at the road junction, and travel to the lane where aa road is located.
Alternatively, it is understood that if the driving vehicle is an autonomous vehicle, the present application may also control the autonomous vehicle to perform lane change processing based on the rightmost lane change position. The specific implementation mode of the method can be as follows: when the target running vehicle is detected to reach the running range of the road junction, the optimal lane change position can be obtained; when the target running vehicle is detected to reach the optimal lane change position, the adaptive lane change speed corresponding to the optimal lane change position can be obtained; subsequently, the running speed of the target running vehicle may be switched from the current running speed to the adaptive lane change speed, and the target running vehicle may be controlled to perform lane change running from the optimal lane change position at the adaptive lane change running speed. That is, for an autonomous vehicle, the autonomous vehicle may be controlled to perform lane-change operations at a certain travel speed (e.g., an adapted lane-change speed) and a certain direction angle (i.e., an offset direction) when it reaches the optimal lane-change position.
It can be understood that, through the above description, the intersection turning action may include a left turning action, a right turning action, a turning action, or the like, and the embodiment of the present application may determine, based on the historical driving track, an optimal lane changing position that is most suitable for changing a lane to a left turning guide lane, a right turning guide lane, or a turning lane. In practice, the intersection steering action may also include an intersection straight-going action, and since the intersection is straight-going through the road intersection and the lane change occurs, the optimal lane change position provided in the embodiment of the present application is also suitable for determining the lane change time from lane change to a straight-going guiding lane, for example, the historical driving track before the intersection steering action (intersection straight-going action) occurs at the road intersection can be obtained, and then the lane change time suitable for lane change to the straight-going guiding lane is determined by filtering the vehicle position, determining the speed change function and determining the optimal lane change position.
It should be noted that, in the specific embodiments of the present application, related data such as user information (for example, a vehicle positioning position of a user, etc.) or user data needs to be acquired and processed after approval by a user, and when the embodiments of the present application are applied to specific products or technologies, user approval or approval needs to be obtained, and collection, use and processing of related data need to comply with related laws and regulations and standards of related countries and regions.
In the embodiment of the application, a historical driving track associated with a road intersection can be obtained, wherein the historical driving track can be the driving track of a driving vehicle before the intersection steering action occurs at the road intersection; according to the driving attribute information corresponding to the vehicle position included in the history driving track, a speed change function corresponding to the history driving track can be determined, and according to the speed change function, a reference lane change position associated with the history driving track can be determined; and determining the optimal lane change position for the target running vehicle in the running range of the road intersection according to the reference lane change position. It should be understood that, the present application can determine the reference lane change position (reference lane change timing) corresponding to the historical driving track associated with the road intersection, and the reference lane change position based on the historical driving track can mine the optimal lane change position (i.e. the lane change timing most suitable for the road intersection) of the road intersection. In conclusion, the method and the device can pointedly determine the optimal lane change positions for different road intersections, and improve the adaptation degree between the road intersections and the lane change positions.
Further, referring to fig. 5, fig. 5 is a schematic flow chart of determining a speed change function according to an embodiment of the present application. The flow may correspond to the flow of determining the speed change function corresponding to the historical driving track according to the driving attribute information such as the time attribute information, the position coordinate attribute information, the positioning accuracy attribute information, the driving speed attribute information, the offset angle attribute information, and the like in the embodiment corresponding to fig. 2. As shown in fig. 5, the flow may include at least the following steps S501 to S506:
step S501, acquiring a historical driving track associated with a road intersection; the history travel track refers to a travel track of a traveling vehicle before an intersection turning action occurs at an intersection of a road.
Specifically, for the specific implementation manner of the historical driving track and the historical driving track, reference may be made to the description of step S101 in the embodiment corresponding to fig. 2, which will not be repeated here.
Step S502, acquiring a vehicle position in the historical driving track and driving attribute information corresponding to the vehicle position.
Specifically, the historical driving track may actually refer to a track composed of a plurality of GPS positioning positions (i.e. vehicle positions), and then the present application may acquire each vehicle position in the historical driving track and driving attribute information corresponding to each vehicle position.
It is to be understood that, here, the running attribute information may refer to corresponding running related information when the running vehicle is at the current vehicle position. For example, the travel attribute information of each vehicle position may include time information (i.e., time stamp information when the position is reached, which may be referred to as time attribute information), position coordinate information (e.g., longitude and latitude coordinate information of the current vehicle position, which may be referred to as position coordinate attribute information), accuracy information (e.g., positioning accuracy of GPS, which may be referred to as positioning accuracy attribute information), travel speed information (e.g., what the travel speed of the vehicle is when at the current vehicle position, which may be referred to as travel speed attribute information), direction angle information (e.g., an angle between the travel direction of the vehicle and a lane line of a lane at the current vehicle position, which may be referred to as offset angle attribute information), and the like.
Step S503, filtering at least two vehicle positions according to the driving attribute information, to obtain filtered vehicle positions.
Specifically, the vehicle position in a historical driving track can be filtered based on the time attribute information, the position coordinate attribute information, the positioning precision attribute information, the driving speed attribute information and the offset angle attribute information of each vehicle position, and the attribute information can be unsatisfied And filtering and deleting the vehicle positions, and taking the vehicle positions meeting the requirements as the filtered vehicle positions. At least two vehicle positions are included in the historical driving track, and the at least two vehicle positions include a vehicle position K j For example, for a certain historical driving track, filtering at least two vehicle positions according to driving attribute information to obtain a specific implementation manner of the filtered vehicle position may be: the filtered vehicle position K can be used j Matching the time attribute information of (2) with the time demand index; the vehicle position K can be determined j Matching the position coordinate attribute information of the (b) with the position coordinate requirement index; the vehicle position K can be determined j Matching the positioning precision attribute information of the (2) with the precision requirement index; the vehicle position K can be determined j Matching the running speed attribute information of (2) with the running speed requirement index; the vehicle position K can be determined j Matching the offset angle attribute information of the (2) with an offset angle requirement index; if the vehicle is at position K j The time attribute information of (2) satisfies the time stamp requirement index and the vehicle position K j The position coordinate attribute information of (1) meets the position coordinate requirement index and the vehicle position K j The positioning accuracy attribute information of (1) meets the accuracy requirement index, and the vehicle position K j The driving speed attribute information of (1) satisfies the driving speed requirement index and the vehicle position K j The offset angle attribute information of (1) meets the offset angle requirement index, and the vehicle position K j If the offset angle attribute information of (a) meets the offset angle requirement index, the vehicle position K can be determined j As a filtered vehicle location.
That is, for a certain vehicle position, only when the time attribute information, the position coordinate attribute information, the positioning accuracy attribute information, the travel speed attribute information and the offset angle attribute information are all in accordance with the requirements, the vehicle position can be screened out as the filtered vehicle position; if any of the travel attribute information is not satisfactory (for example, the time attribute information is not satisfactory) for a certain vehicle position, it may be filtered and deleted.
It may be understood that, in the present application, the time requirement index may refer to a preset time requirement condition, and in the present application, the time requirement for each vehicle position may be: the time stamp of the current vehicle position (i.e., at which time the current vehicle position was reached) needs to be inconsistent with the time stamp of the last vehicle position, and the time stamp of the current vehicle position needs to be greater than the time stamp of the last vehicle position. For example, where vehicle position 1 and vehicle position 2 are two consecutive vehicle positions and vehicle position 1 is farther from the road junction, then the timestamp of vehicle position 2 needs to be greater than the timestamp of vehicle position 1.
It may be understood that the position coordinate requirement index in the present application may refer to a preset longitude and latitude coordinate requirement condition, and in the present application, the longitude and latitude coordinate requirement condition for each vehicle position may be: the longitude and latitude of the current vehicle position is different from the longitude and latitude of the last vehicle position. The accuracy requirement index in the present application may refer to a preset GPS positioning accuracy requirement condition, and in the present application, the positioning accuracy requirement for each vehicle position may be: the positioning accuracy of the current vehicle position needs to be less than an accuracy threshold (e.g., 30), which may be a manually specified value, it being understood that the smaller the positioning accuracy, the higher the positioning accuracy thereof.
The running speed demand index in the present application may refer to a preset running speed demand condition, and in the present application, the running speed demand for each vehicle position may be: the speed of travel of the current vehicle position needs to be greater than or equal to a speed threshold (e.g., 5 km/h), which may be a prescribed value. The offset angle requirement index in the present application may refer to a preset offset angle requirement condition, and in the present application, the offset angle requirement for each vehicle position may be: the offset angle of the current vehicle position needs to be less than an offset angle threshold (e.g., less than 60), which may be a prescribed value.
Alternatively, it may be appreciated that, for a certain historical driving track, the vehicle position included in the historical driving track may be filtered in the above manner, so as to obtain the filtered vehicle position. And then, counting the total number of the filtered vehicle positions, if the total number of the vehicle positions is lower than a preset number threshold, filtering and deleting the historical driving track, and determining the historical driving track based on the historical driving tracks with the number reaching the requirement of other filtered vehicle positions without referring to the historical driving track when the optimal lane change position is determined later.
Step S504, determining a speed change function corresponding to the historical driving track according to the driving attribute information of the filtered vehicle position.
Specifically, after the filtering, the travel speed attribute information (i.e., the travel speed) of each filtered vehicle position may be acquired, and a speed change function may be determined based on the travel speed. The specific implementation mode of the method can be as follows: the filtered vehicle position K can be used m The interval distance between the road crossing and the road crossing is used as a first interval distance; subsequently, the filtered vehicle position K may be obtained m Corresponding running speed attribute information, and a first interval distance and a filtered vehicle position K m Corresponding running speed attribute information forming a filtered vehicle position K m Corresponding speed coordinates; then, when determining the speed coordinates corresponding to the at least two filtered vehicle positions respectively, determining a speed change function corresponding to the historical driving track according to the at least two speed coordinates.
One specific implementation manner of determining the speed change function corresponding to the historical driving track according to at least two speed coordinates may be: a linear fitting model can be obtained, and then, at least two speed coordinates can be subjected to linear fitting according to the linear fitting model to obtain a linear fitting function; the linear fit function may then be determined as a speed change function corresponding to the historical travel track.
For performing linear fitting on at least two velocity coordinates according to a linear fitting model, one specific implementation way of obtaining the linear fitting function may be: at least two speed coordinates can be input into a linear fitting model, and N candidate linear fitting functions corresponding to the at least two speed coordinates are determined through the linear fitting model; n is a positive integer; subsequently, determining error reference values corresponding to the N candidate linear fitting functions respectively based on at least two speed coordinates; then, the minimum error reference value of the N error reference values may be obtained, and a candidate linear fitting function corresponding to the minimum error reference value of the N candidate linear fitting functions may be determined as the linear fitting function.
Wherein the N candidate linear fitting functions comprise candidate linear fitting functions F x For example, for determining error reference values corresponding to N candidate linear fit functions based on at least two velocity coordinates, one specific implementation manner may be: can obtain candidate linear fitting function F x Drawing a fitting curve in a curve coordinate system; the curve coordinate system may be a coordinate system constructed by a distance axis and a speed axis; then, candidate speed coordinates on the drawn fitting curve can be obtained, and the candidate linear fitting function F can be determined according to the candidate speed coordinates and at least two speed coordinates x Corresponding error reference values.
It will be appreciated that the present application may obtain each filtered vehicle position of a certain historical driving track, and then, may combine each filtered vehicle position with its corresponding driving speed to form a data set (first interval distance, driving speed), where in a curve coordinate system (coordinate system formed by the distance axis and the speed axis), each data set may be used as a real speed coordinate of the filtered vehicle position. The speed change function corresponding to the historical driving track can be determined based on the linear fitting model and the real speed coordinates.
The linear fitting model in the application may refer to a least square method model, and the real speed coordinates may be fitted into a linear fitting curve in a curve coordinate system by using a least square method, and a linear function corresponding to the linear fitting curve may be referred to as a speed change function.
Among these, the following will specifically describe for the purpose of facilitating understanding of the specific implementation of determining the speed change function. Where the least squares method (also called least squares method) can find the best matching function of the data (e.g., true velocity coordinates) by minimizing the sum of squares of the errors. Unknown data (for example, coefficient items of the speed change function) can be obtained simply by using a least square method, different fitting curves can be formed according to the unknown data (which can be called function composition data), and one fitting curve can correspond to one fitting function (which can be called candidate linear fitting function); the error reference value corresponding to each candidate linear fitting function may be calculated based on the true velocity coordinates using a least squares model, and then the smallest error reference value may be selected and its corresponding candidate linear fitting function may be used as the final linear fitting function (i.e., the velocity variation function).
It will be appreciated that the function composition data that make up the candidate linear fit function may be understood as the coefficient terms of the function (e.g., the candidate linear fit function may be expressed in the form shown in equation (1) above, and then the coefficient terms may include the quadratic term coefficient a, the quadratic term coefficient b, and the constant term c), and then for a candidate linear fit function, the sum of squares (i.e., the error reference value) for the error between the candidate linear fit function and the true velocity coordinate may be found, and then the candidate linear fit function with the minimum error from the true velocity coordinate may be found as the final velocity change function.
For ease of understanding, please refer to formula (3), formula (3) may be a specific method for calculating the error reference value (i.e. the sum of squares) of a candidate linear function:
wherein delta in formula (1) i Can be used to characterize the difference between the ith calculated value (i.e., the value calculated by the candidate linear fitting function) and the true value; f (x) i )-y i Can be used to characterize the difference between the ith calculated value and the ith true value, where x i Can be used to characterize the ith argument (e.g., distance), f (x i ) Can be used for characterizing the substitution of the ith independent variable into the candidate linear fitting function The calculated speed value obtained later (may be referred to as a calculated running speed); and y is i The method can be used for representing the true value (such as the true running speed) corresponding to the ith independent variable; s can be used for representing error reference values between candidate linear fitting functions and real speed coordinates, when S is minimum, the obtained quadratic term coefficient a, quadratic term coefficient b and constant term c can be final coefficients, and after the quadratic term coefficient a, quadratic term coefficient b and constant term c are all determined, the final linear fitting function can be determined. />
The specific method for solving a, b and c in the formula (1) can be as follows: the first partial derivatives of S with respect to a, b, c described above can be solved and made zero. The system of equations that can be satisfied by a, b, c, respectively, can be derived from this as shown in equation (4):
wherein,can be used to characterize the equation satisfied by coefficient a after partial derivative of coefficient a; />Can be used to characterize the equation satisfied by coefficient b after partial derivative of coefficient b; />Can be used to characterize the equation satisfied by coefficient c after partial derivative of coefficient c.
Wherein, by the above formula (4), the equation set shown in the formula (5) can be obtained by conversion:
and by the formula (5), the equation set shown in the formula (6) can be obtained by conversion:
Subsequently, equation (6) may be transformed, which may be converted into a vector product as shown in equation (7):
further, a system of equations characterizing the final results of coefficients a, b, and c may be solved, as shown in equation (8):
it will be appreciated that, by the above formula (8), the coefficients of the candidate linear fitting function can be determined (for example, when the candidate linear fitting function is as shown in formula (1), the quadratic term coefficient a, the first order term coefficient b and the constant term c can be obtained by solving, so that the error reference value between the candidate linear fitting function and the true velocity coordinate can be calculated, and then the quadratic term coefficient a, the first order term coefficient b and the constant term c with the minimum error reference value are determined as the final coefficients, and these coefficients can be combined to obtain the final velocity change function).
Step S505, determining a reference lane-change position associated with the historical driving track according to the speed change function.
Specifically, after the speed change function is determined, a reference lane change position associated with the historical driving track may be determined according to the speed change function. When the expression running of the speed change function is shown in formula (1), the curve of the speed change function in the curve coordinate system (the coordinate system constructed by the distance axis and the running speed axis) may be parabolic (as shown in fig. 3 c), and the reference lane change position may be understood as the speed reduction lane change position, and then the corresponding speed reduction point in the parabolic may be understood as the reference lane change position, and the determination manner for the speed reduction point in the parabolic may be: the first partial derivative of the velocity change function (e.g., F (x)) with respect to the independent variable (e.g., distance x) can be solved and set to 0, thereby obtaining a specific distance value of the deceleration point. The specific implementation manner may be referred to the description in step S103 in the embodiment corresponding to fig. 2, and will not be described herein.
Step S506, determining the optimal lane change position for the target running vehicle in the running range of the road intersection according to the reference lane change position.
Specifically, the historical driving track of the road intersection may include a plurality of (e.g., Q is a positive integer), and by determining the reference lane change positions of the historical driving track, one historical driving track may determine to obtain one reference lane change position (it should be noted that, in a possible case, a certain historical driving track may not be able to determine the reference lane change position), so that a plurality of reference lane change positions may be determined by a plurality of historical driving tracks, and the reference lane change positions may be ordered in order from far to near (i.e., from far to near or understood as from large to small) to the road intersection, so as to obtain a sequence, and an average value and a median value of the sequence may be obtained, and then the average value and the average value of the median value may be used as the optimal lane change position most adapted to the road intersection (i.e., when the distance from the road intersection is a certain specific value, the optimal lane change is adapted to speed reduction). For a specific implementation manner of determining the optimal lane change position according to the reference lane change position, reference may be made to the description in step S104 in the embodiment corresponding to fig. 2, which will not be repeated here.
In the embodiment of the application, a historical driving track associated with a road intersection can be obtained, wherein the historical driving track can be the driving track of a driving vehicle before the intersection steering action occurs at the road intersection; according to the driving attribute information corresponding to the vehicle position included in the history driving track, a speed change function corresponding to the history driving track can be determined, and according to the speed change function, a reference lane change position associated with the history driving track can be determined; and determining the optimal lane change position for the target running vehicle in the running range of the road intersection according to the reference lane change position. It should be understood that, the present application can determine the reference lane change position (reference lane change timing) corresponding to the historical driving track associated with the road intersection, and the reference lane change position based on the historical driving track can mine the optimal lane change position (i.e. the lane change timing most suitable for the road intersection) of the road intersection. In conclusion, the method and the device can pointedly determine the optimal lane change positions for different road intersections, and improve the adaptation degree between the road intersections and the lane change positions.
It can be appreciated that in the embodiment of the present application, after determining the optimal lane change position, the optimal lane change position may be applied to the navigation scene. For ease of understanding, referring to fig. 6, fig. 6 is a flowchart of a data processing method provided in the embodiment of the present application, where the flowchart may refer to a flowchart of applying an optimal lane change position, and as shown in fig. 6, the flowchart may at least include the following steps S601 to S603:
in step S601, when it is detected that the vehicle to be steered reaches the driving range of the road junction, the optimal lane change position is obtained.
Specifically, in the process that the user drives the vehicle to run, the intelligent vehicle-mounted terminal in the vehicle detects that the vehicle reaches the running range of the road intersection, at this time, the intelligent vehicle-mounted terminal determines that the user should turn at the road intersection (namely, the intersection steering action is required to be generated), and the vehicle can be called as a vehicle to be steered to run, and the intelligent vehicle-mounted terminal can acquire the optimal lane changing position at the road intersection. For a specific determination manner of the optimal lane change position, reference may be made to the embodiment corresponding to fig. 2, and description of determining the optimal lane change position will not be repeated here.
Step S602, displaying a lane change indication animation comprising an optimal lane change position in a terminal navigation interface; the lane change instruction animation is used for guiding an object corresponding to the vehicle to be steered, and controlling the vehicle to be steered to run into the target lane from the lane change position; the target lane refers to a lane for performing an intersection turning action at a road intersection.
Specifically, after the optimal lane change position is obtained, a lane change instruction animation including the optimal lane change position may be displayed in the terminal navigation interface, so as to prompt an object corresponding to the vehicle to be steered (which may be understood as an object driving the vehicle to be steered), and a speed reduction lane change process may be started at the position of driving to the optimal lane change position (for example, starting to reduce speed and change a steering wheel angle to drive into a corresponding lane.
Optionally, it may be understood that, in order to further improve navigation accuracy and improve safety in a lane change process, the present application may configure an adaptive driving speed and an adaptive offset angle for an optimal lane change position, when displaying a lane change indication animation, may output (or be called playing) voice prompt audio at the same time, which is used to prompt a user driving a vehicle to switch the driving speed to the adaptive driving speed when reaching the optimal lane change position, and switch the adaptive offset angle to the adaptive offset angle (may be understood as a steering wheel angle), and when the user drives the vehicle at the adaptive driving speed and the adaptive offset angle, may change a lane to a corresponding lane more safely. The adaptive travel speed may be a travel speed adapted to the lane change travel, and the adaptive offset angle may be an offset direction angle adapted to the lane change travel, and the adaptive travel speed is generally smaller.
When the lane change indicator animation is displayed, the speed-reducing lane change prompting audio data may be output (or referred to as playing), for example, the audio data "20 m ahead is the optimal lane change position, please rotate the steering wheel 45 degrees to the left at the optimal lane change position, and keep the speed of 1m/s to change to the leftmost lane" may be output. Therefore, the deceleration lane change prompting audio data can be used for prompting an object corresponding to the vehicle to be steered (the object to be steered can be understood as driving the vehicle to be steered), and the driving speed and the offset angle are switched at the position of reaching the optimal lane change position, so that the vehicle can change lanes to lanes corresponding to the turning action of the intersection.
For ease of understanding, please refer to fig. 7, fig. 7 is a schematic diagram of a scene of lane change based on an optimal lane change position according to an embodiment of the present application. As shown in fig. 7, assuming that the user drives the vehicle to expect a right turn at the road junction, when the user drives the vehicle to travel to the position 70a on the straight-ahead guide lane, which is already within the travel range of the road junction at this time, the intelligent in-vehicle terminal 700a can acquire the current position (i.e., the position 70 a) of the vehicle, and at the same time, can acquire the optimal lane change position from the straight-ahead guide lane to the right-turn guide lane. Subsequently, the intelligent in-vehicle terminal 700a may display the navigation route including the optimal lane change position 70b in the terminal navigation interface, and may highlight (e.g., zoom in) the optimal lane change position 70b when displaying the navigation route. As shown in fig. 7, in the navigation interface, the intelligent vehicle-mounted terminal 700a may further display a lane change indication animation 7000 for the optimal lane change position 70b, where the lane change indication animation 7000 may include a lane change indication arrow image and a lane change text "lane change here", for prompting the user to slow down and change a lane to a right turn guiding lane when reaching the optimal lane change position 70 b. Meanwhile, as shown in fig. 7, the distance (for example, 20 m) between the current position 70a and the optimal lane change position 70b can be obtained, so that when the lane change indication animation is displayed in the navigation interface, the audio of the speed reduction lane change prompt can be synchronously output to prompt the user to perform the speed reduction lane change processing at the optimal lane change position 70b from a multi-azimuth angle by 'please speed reduction lane change to right lane change at the position 20m in front'.
Further, as shown in fig. 7, when the user drives the vehicle to the optimal lane change position 70b, the intelligent in-vehicle apparatus 700a may display a lane change prompting text "start lane change" in the navigation interface, and at the same time, may output a speed-down lane change prompting audio "start lane change" for prompting the user to start a speed-down lane change onto the right turn guiding lane.
It should be understood that the method for excavating the optimal lane change position of the road intersection through the historical driving track is not limited to the method for configuring the fixed artificial experience value according to the complexity level or type of the intersection, and the suitability between the lane change position and the road intersection can be well improved. Meanwhile, the method for displaying the lane change indication animation and outputting the prompting audio data in the navigation interface can enrich navigation modes in a navigation scene, improve navigation precision and improve user experience; and the mode of adapting the running speed and the offset angle is configured for the optimal lane change position, so that the navigation accuracy can be further improved, the safety in the navigation process is improved, and the user experience is improved.
Further, referring to fig. 8, fig. 8 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application. The data processing apparatus may be a computer program (including program code) running in a computer device, for example the data processing apparatus is an application software; the data processing device may be used to perform the method shown in fig. 3. As shown in fig. 8, the data processing apparatus 1 may include: a driving track acquisition module 11, a driving information acquisition module 12, a function determination module 13, a reference position determination module 14, and an optimal position determination module 15.
A travel track acquisition module 11 for acquiring a history travel track associated with a road junction; the historical driving track refers to the driving track before the driving vehicle turns to the intersection at the road intersection;
a driving information obtaining module 12, configured to obtain a vehicle position in a historical driving track and driving attribute information corresponding to the vehicle position;
a function determining module 13, configured to determine a speed change function corresponding to the historical driving track according to the driving attribute information;
a reference position determining module 14 for determining a reference lane-change position associated with the historical driving trajectory according to the speed change function;
the optimal position determining module 15 is configured to determine an optimal lane change position for a target driving vehicle within a driving range of the road junction according to the reference lane change position.
The specific implementation manners of the driving track obtaining module 11, the driving information obtaining module 12, the function determining module 13, the reference position determining module 14, and the optimal position determining module 15 may be referred to the description of step S101 to step S104 in the embodiment corresponding to fig. 2, and will not be described herein.
In one embodiment, the number of vehicle positions is at least two;
The function determination module 13 may include: the position filtering unit 131 and the function determining unit 132.
A position filtering unit 131, configured to filter at least two vehicle positions according to the driving attribute information, so as to obtain a filtered vehicle position;
the function determining unit 132 is configured to determine a speed change function corresponding to the historical driving track according to the driving attribute information of the filtered vehicle position.
For a specific implementation manner of the location filtering unit 131 and the function determining unit 132, reference may be made to the description of determining the speed change function in steps S503 to S504 in the embodiment corresponding to fig. 5, which will not be described herein.
In one embodiment, the at least two vehicle positions include a vehicle position K j J is a positive integer; the driving attribute information comprises time attribute information, position coordinate attribute information, positioning accuracy attribute information, driving speed attribute information and offset angle attribute information;
the location filtering unit 131 may include: matching subunit 1311 and filtering position determining subunit 1312.
A matching subunit 1311 for matching the filtered vehicle position K j Matching the time attribute information of (2) with the time demand index;
The matching subunit 1311 is also configured to match the vehicle position K j Matching the position coordinate attribute information of the (b) with the position coordinate requirement index;
the matching subunit 1311 is also configured to match the vehicle position K j Matching the positioning precision attribute information of the (2) with the precision requirement index;
the matching subunit 1311 is also configured to match the vehicle position K j Matching the running speed attribute information of (2) with the running speed requirement index;
the matching subunit 1311 is also configured to match the vehicle position K j Matching the offset angle attribute information of the (2) with an offset angle requirement index;
a filter position determination subunit 1312 for determining if the vehicle position is K j The time attribute information of (2) satisfies the time stamp requirement index and the vehicle position K j The position coordinate attribute information of (1) meets the position coordinate requirement index and the vehicle position K j The positioning accuracy attribute information of (1) meets the accuracy requirement index, and the vehicle position K j The driving speed attribute information of (1) satisfies the driving speed requirement index and the vehicle position K j The offset angle attribute information of (1) meets the offset angle requirement index, and the vehicle position K j If the offset angle attribute information of (1) meets the offset angle requirement index, the vehicle position K is determined j As a filtered vehicle location.
For a specific implementation manner of the matching subunit 1311 and the filtering position determining subunit 1312, reference may be made to the description of filtering the vehicle position in step S503 in the embodiment corresponding to fig. 5, which will not be repeated here.
In one embodiment, the travel attribute information includes travel speed attribute information; the number of the filtered vehicle positions is at least two, and the at least two filtered vehicle positions comprise the filtered vehicle position K m M is a positive integer;
the function determination unit 132 may include: distance determination subunit 1321, velocity coordinate determination subunit 1322, and function determination subunit 1323.
A distance determination subunit 1321 for determining a filtered vehicle position K m The interval distance between the road crossing and the road crossing is used as a first interval distance;
a speed coordinate determination subunit 1322 for acquiring the filtered vehicle position K m Corresponding running speed attribute information, the first interval distance and the filtered vehicle position K m Corresponding running speed attribute information forming a filtered vehicle position K m Corresponding speed coordinates;
the function determining subunit 1323 is configured to determine, when determining the speed coordinates corresponding to the at least two filtered vehicle positions, a speed change function corresponding to the historical driving track according to the at least two speed coordinates.
The specific implementation manner of the distance determining subunit 1321, the speed coordinate determining subunit 1322, and the function determining subunit 1323 may refer to the description of determining the speed change function in step S504 in the embodiment corresponding to fig. 5, which will not be described herein.
In one embodiment, the function determining subunit 1323 is further specifically configured to obtain a linear fitting model, and perform linear fitting on at least two velocity coordinates according to the linear fitting model to obtain a linear fitting function;
the function determining subunit 1323 is further specifically configured to determine the linear fitting function as a speed change function corresponding to the historical driving track.
In one embodiment, the function determining subunit 1323 is further specifically configured to input at least two velocity coordinates to the linear fitting model, and determine N candidate linear fitting functions corresponding to the at least two velocity coordinates through the linear fitting model; n is a positive integer;
the function determining subunit 1323 is further specifically configured to determine error reference values corresponding to the N candidate linear fitting functions respectively based on at least two velocity coordinates;
the function determining subunit 1323 is further specifically configured to obtain a minimum error reference value of the N error reference values, and determine a candidate linear fitting function corresponding to the minimum error reference value of the N candidate linear fitting functions as the linear fitting function.
In one embodiment, the N candidate linear fit functions include candidate linear fit function F x X is a positive integer;
The function determination subunit 1323 is further specifically configured to obtain a candidate linear fitting function F x Drawing a fitting curve in a curve coordinate system; the curve coordinate system is a coordinate system constructed by a distance axis and a speed axis;
the function determining subunit 1323 is further specifically configured to obtain candidate velocity coordinates on the plotted fitting curve, and determine a candidate linear fitting function F according to the candidate velocity coordinates and at least two velocity coordinates x Corresponding error reference values.
In one embodiment, the speed change function includes a separation distance between the vehicle location and the road junction;
the reference position determination module 14 may include: the partial derivative determination unit 141 and the reference position determination unit 142.
A partial derivative determining unit 141 for determining a partial derivative between the speed change function and a separation distance between the vehicle position and the road junction;
the reference position determining unit 142 is configured to estimate a variable value of the separation distance between the vehicle position and the road junction by the partial derivative, and determine the variable value as the reference lane change position.
For a specific implementation manner of the partial derivative determining unit 141 and the reference position determining unit 142, reference may be made to the description of determining the reference lane change position in step S504 in the embodiment corresponding to fig. 5, which will not be repeated here.
In one embodiment, the number of historical travel tracks is at least two; the reference lane-change locations include one or more reference lane-change locations associated with at least two historical travel tracks;
the optimal position determination module 15 may include: a separation distance determining unit 151, a separation distance sorting unit 152, and an optimal position determining unit 153.
A separation distance determining unit 151 for taking, as a second separation distance, separation distances between one or more reference lane-change positions and road intersections, respectively;
a spacing distance sorting unit 152, configured to sort the one or more second spacing distances according to the order of magnitudes of the one or more second spacing distances, to obtain a spacing distance sequence;
an optimal position determining unit 153 for determining an optimal lane change position according to the sequence of separation distances.
For specific implementation manners of the interval distance determining unit 151, the interval distance sorting unit 152, and the optimal position determining unit 153, reference may be made to the description of determining the optimal lane change position in step S104 in the embodiment corresponding to fig. 2, which will not be repeated here.
In one embodiment, the optimal position determining unit 153 may include: a summation processing subunit 1531, a distance average determination subunit 1532, and an optimal position determination subunit 1533.
A summation processing subunit 1531, configured to perform summation processing on the interval distance sequence to obtain an operation distance;
a distance average value determining subunit 1532, configured to obtain a total number of one or more second interval distances, and determine an interval distance average value corresponding to the interval distance sequence according to the operation distance and the total number;
the optimal position determining subunit 1533 is configured to obtain the numerical attribute to which the total number belongs, and determine the optimal lane change position according to the numerical attribute and the average value of the interval distances.
For a specific implementation manner of the summing processing subunit 1531, the distance average determining subunit 1532, and the optimal position determining subunit 1533, reference may be made to the description of determining the optimal lane change position in step S104 in the embodiment corresponding to fig. 2, which will not be repeated here.
In one embodiment, the optimal position determining subunit 1533 is further specifically configured to determine, if the numerical attribute is an odd attribute, a second separation distance in the separation distance sequence at the center position as a center separation distance, determine a mean value between a separation distance mean value and the center separation distance as a first optimal separation distance, and determine a position at which the first optimal separation distance is located as an optimal lane change position;
The optimal position determining subunit 1533 is further specifically configured to determine, if the numerical attribute is an even attribute, a second interval distance in the center position in the interval distance sequence as an interval distance to be operated, perform average operation processing on the interval distance to be operated to obtain an average operation distance, determine an average value between the interval distance average value and the average operation distance as a second optimal interval distance, and determine a position where the second optimal interval distance is located as an optimal lane change position.
In one embodiment, the data processing apparatus 1 may further include: a position acquisition module 16, an adaptation speed acquisition module 17 and a lane departure module 18.
A position acquisition module 16 for acquiring an optimal lane change position when it is detected that the target traveling vehicle reaches the traveling range of the road junction;
an adaptive speed obtaining module 17, configured to obtain an adaptive lane change speed corresponding to the optimal lane change position when it is detected that the target traveling vehicle reaches the optimal lane change position;
the lane change running module 18 is configured to switch the running speed of the target running vehicle from the current running speed to an adaptive lane change speed, and control the target running vehicle to perform lane change running from the optimal lane change position at the adaptive lane change running speed.
The specific implementation manner of the position obtaining module 16, the adaptive speed obtaining module 17, and the lane change driving module 18 may be referred to the description in step S104 in the embodiment corresponding to fig. 2, and will not be described herein.
In the embodiment of the application, a historical driving track associated with a road intersection can be obtained, wherein the historical driving track can be the driving track of a driving vehicle before the intersection steering action occurs at the road intersection; according to the driving attribute information corresponding to the vehicle position included in the history driving track, a speed change function corresponding to the history driving track can be determined, and according to the speed change function, a reference lane change position associated with the history driving track can be determined; and determining the optimal lane change position for the target running vehicle in the running range of the road intersection according to the reference lane change position. It should be understood that, the present application can determine the reference lane change position (reference lane change timing) corresponding to the historical driving track associated with the road intersection, and the reference lane change position based on the historical driving track can mine the optimal lane change position (i.e. the lane change timing most suitable for the road intersection) of the road intersection. In conclusion, the method and the device can pointedly determine the optimal lane change positions for different road intersections, and improve the adaptation degree between the road intersections and the lane change positions.
Further, referring to fig. 9, fig. 9 is a schematic structural diagram of another data processing apparatus according to an embodiment of the present application. The data processing apparatus may be a computer program (including program code) running in a computer device, for example the data processing apparatus is an application software; the data processing device may be used to perform the method shown in fig. 6. As shown in fig. 9, the data processing apparatus 2 may include: the optimal position acquisition module 21 and the animation display module 22.
An optimal position obtaining module 21, configured to obtain an optimal lane change position when detecting that the vehicle to be steered reaches the driving range of the road junction;
an animation display module 22 for displaying a lane change instruction animation including an optimal lane change position in the terminal navigation interface; the lane change instruction animation is used for guiding an object corresponding to the vehicle to be steered, and controlling the vehicle to be steered to run into the target lane from the lane change position; the target lane refers to a lane for performing an intersection turning action at a road intersection.
The specific implementation manner of the optimal position obtaining module 21 and the animation display module 22 may be referred to the description of step S601 to step S602 in the embodiment corresponding to fig. 6, which will not be described herein again, and the beneficial effects thereof will not be described herein again.
Further, referring to fig. 10, fig. 10 is a schematic structural diagram of a computer device according to an embodiment of the present application. As shown in fig. 10, the data processing apparatus 1 in the embodiment corresponding to fig. 8 described above, or the data processing apparatus 2 in the embodiment corresponding to fig. 9 described above may be applied to the computer device 8000 described above, and the computer device 8000 described above may include: processor 8001, network interface 8004, and memory 8005, and further, the above-described computer device 8000 further includes: a user interface 8003, and at least one communication bus 8002. Wherein a communication bus 8002 is used to enable connected communications between these components. The user interface 8003 may include a Display screen (Display), a Keyboard (Keyboard), and the optional user interface 8003 may also include standard wired, wireless interfaces, among others. Network interface 8004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). Memory 8005 may be a high speed RAM memory or a non-volatile memory, such as at least one disk memory. Memory 8005 may optionally also be at least one memory device located remotely from the aforementioned processor 8001. As shown in fig. 10, an operating system, a network communication module, a user interface module, and a device control application program may be included in the memory 8005, which is one type of computer-readable storage medium.
In the computer device 8000 shown in fig. 10, the network interface 8004 may provide a network communication function; while user interface 8003 is primarily an interface for providing input to the user; and the processor 8001 may be used to invoke a device control application stored in the memory 8005 to implement:
acquiring a historical driving track associated with a road intersection; the historical driving track refers to the driving track before the driving vehicle turns to the intersection at the road intersection;
acquiring a vehicle position in a historical driving track and driving attribute information corresponding to the vehicle position;
determining a speed change function corresponding to the historical driving track according to the driving attribute information, and determining a reference lane change position associated with the historical driving track according to the speed change function;
and determining the optimal lane change position for the target running vehicle in the running range of the road intersection according to the reference lane change position.
It should be understood that the computer device 8000 described in the embodiments of the present application may perform the description of the data processing method in the embodiment corresponding to fig. 2 or fig. 6, or may perform the description of the data processing apparatus 1 in the embodiment corresponding to fig. 8, or the description of the data processing apparatus 2 in the embodiment corresponding to fig. 9, which are not repeated herein. In addition, the description of the beneficial effects of the same method is omitted.
Or implement:
when the fact that the vehicle to be steered reaches the driving range of the road intersection is detected, acquiring an optimal lane changing position;
displaying a lane change indication animation comprising an optimal lane change position in a terminal navigation interface; the lane change instruction animation is used for guiding an object corresponding to the vehicle to be steered, and controlling the vehicle to be steered to run into the target lane from the lane change position; the target lane refers to a lane for performing an intersection turning action at a road intersection.
Furthermore, it should be noted here that: the embodiments of the present application further provide a computer readable storage medium, where a computer program executed by the computer device 1000 for data processing mentioned above is stored, and the computer program includes program instructions, when executed by the processor, can perform the description of the data processing method in the embodiment corresponding to fig. 2 or fig. 6, and therefore, the description will not be repeated here. In addition, the description of the beneficial effects of the same method is omitted. For technical details not disclosed in the embodiments of the computer-readable storage medium according to the present application, please refer to the description of the method embodiments of the present application.
The computer readable storage medium may be the data processing apparatus provided in any one of the foregoing embodiments or an internal storage unit of the computer device, for example, a hard disk or a memory of the computer device. The computer readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash card (flash card) or the like, which are provided on the computer device. Further, the computer-readable storage medium may also include both internal storage units and external storage devices of the computer device. The computer-readable storage medium is used to store the computer program and other programs and data required by the computer device. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.
In one aspect of the present application, a computer program product or computer program is provided that includes computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the method provided in an aspect of the embodiments of the present application.
The terms first, second and the like in the description and in the claims and drawings of the embodiments of the present application are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the term "include" and any variations thereof is intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or device that comprises a list of steps or elements is not limited to the list of steps or modules but may, in the alternative, include other steps or modules not listed or inherent to such process, method, apparatus, article, or device.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The methods and related devices provided in the embodiments of the present application are described with reference to the method flowcharts and/or structure diagrams provided in the embodiments of the present application, and each flowchart and/or block of the method flowcharts and/or structure diagrams may be implemented by computer program instructions, and combinations of flowcharts and/or blocks in the flowchart and/or block diagrams. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or structural diagram block or blocks. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or structures.
The foregoing disclosure is only illustrative of the preferred embodiments of the present application and is not intended to limit the scope of the claims herein, as the equivalent of the claims herein shall be construed to fall within the scope of the claims herein.

Claims (17)

1. A method of data processing, comprising:
acquiring a historical driving track associated with a road intersection; the historical driving track refers to the driving track before the driving vehicle turns to the intersection at the road intersection;
acquiring a vehicle position in the historical driving track and driving attribute information corresponding to the vehicle position; the travel attribute information includes travel speed attribute information;
determining a speed change function corresponding to the historical driving track according to the driving attribute information, and determining a reference lane change position associated with the historical driving track according to the speed change function; the speed change function is used for reflecting running speed attribute information at the vehicle position, and the relation changes along with the change of the interval distance between the vehicle position and the road intersection; the reference lane change position refers to lane change time obtained by solving based on the speed change function;
Determining an optimal lane change position for a target running vehicle in the running range of the road intersection according to the reference lane change position; and the optimal lane change position refers to the lane change time indicated by the reference lane change position and most suitable for the road intersection.
2. The method of claim 1, wherein the number of vehicle locations is at least two;
the determining the speed change function corresponding to the historical driving track according to the driving attribute information comprises the following steps:
filtering the at least two vehicle positions according to the driving attribute information to obtain filtered vehicle positions; the filtered vehicle position refers to a vehicle position of which the running speed attribute information meets the requirement;
determining a speed change function corresponding to the historical driving track according to the driving attribute information of the filtered vehicle position; the speed change function is determined by linearly fitting the speed coordinates corresponding to the filtered vehicle position, and the speed coordinates corresponding to the filtered vehicle position are composed of the interval distance between the filtered vehicle position and the road intersection and the running speed attribute information of the filtered vehicle position.
3. The method of claim 2, wherein the at least two vehicle positions comprise a vehicle position K j J is a positive integer; the driving attribute information further comprises time attribute information, position coordinate attribute information, positioning precision attribute information and offset angle attribute information;
the filtering the at least two vehicle positions according to the driving attribute information to obtain a filtered vehicle position, including:
-filtering said filtered vehicle position K j Matching the time attribute information of (2) with the time demand index;
-determining the vehicle position K j Matching the position coordinate attribute information of the (b) with the position coordinate requirement index;
-determining the vehicle position K j Matching the positioning precision attribute information of the (2) with the precision requirement index;
-determining the vehicle position K j Matching the running speed attribute information of (2) with the running speed requirement index;
-determining the vehicle position K j Matching the offset angle attribute information of the (2) with an offset angle requirement index;
if the vehicle position K j The time attribute information of (2) satisfies the time demand index, and the vehicle position K j The location coordinate attribute information of (1) satisfies the locationCoordinate demand index, and the vehicle position K j The positioning accuracy attribute information of (a) satisfies the accuracy requirement index, and the vehicle position K j And the vehicle position K satisfies the running speed requirement index j The offset angle attribute information of (1) satisfies the offset angle demand index, and the vehicle position K j The vehicle position K is determined if the offset angle attribute information of the vehicle satisfies the offset angle requirement index j As the filtered vehicle position.
4. The method of claim 2, wherein the number of filtered vehicle positions is at least two, the at least two filtered vehicle positions including filtered vehicle position K m M is a positive integer;
the determining a speed change function corresponding to the historical driving track according to the driving attribute information of the filtered vehicle position comprises the following steps:
-filtering said filtered vehicle position K m The interval distance between the road crossing and the road crossing is used as a first interval distance;
acquiring the filtered vehicle position K m Corresponding running speed attribute information, and the first interval distance and the filtered vehicle position K m Corresponding running speed attribute information, composing the filtered vehicle position K m Corresponding speed coordinates;
when the speed coordinates corresponding to the at least two filtered vehicle positions are determined, determining a speed change function corresponding to the historical driving track according to the at least two speed coordinates; the speed change function is determined by linear fitting the at least two speed coordinates.
5. The method of claim 4, wherein determining a speed change function corresponding to the historical travel track from at least two speed coordinates comprises:
obtaining a linear fitting model, and performing linear fitting on the at least two speed coordinates according to the linear fitting model to obtain a linear fitting function; the linear fitting model refers to a least square method model;
and determining the linear fitting function as a speed change function corresponding to the historical driving track.
6. The method of claim 5, wherein said linearly fitting said at least two velocity coordinates according to said linear fitting model to obtain a linear fitting function, comprising:
inputting the at least two speed coordinates into the linear fitting model, and determining N candidate linear fitting functions corresponding to the at least two speed coordinates through the linear fitting model; n is a positive integer;
Determining error reference values respectively corresponding to the N candidate linear fitting functions based on the at least two speed coordinates; the N candidate linear fitting functions comprise candidate linear fitting functions F x X is a positive integer, the candidate linear fitting function F x The corresponding error reference value is based on the at least two velocity coordinates and the candidate linear fitting function F x The candidate speed coordinates in the drawn fitting curve in the curve coordinate system are determined together; the curve coordinate system is a coordinate system constructed by a distance axis and a speed axis;
and acquiring a minimum error reference value in N error reference values, and determining a candidate linear fitting function corresponding to the minimum error reference value in the N candidate linear fitting functions as the linear fitting function.
7. The method of claim 6, wherein determining error reference values for each of the N candidate linear fit functions based on the at least two velocity coordinates comprises:
obtaining the candidate linear fitting function F x Drawing a fitting curve in a curve coordinate system;
acquiring candidate speed seats on the drawn fitting curveDetermining the candidate linear fitting function F according to the candidate speed coordinates and the at least two speed coordinates x Corresponding error reference values.
8. The method of claim 1, wherein the speed change function comprises a separation distance between a vehicle location and a road junction;
the determining the reference lane-change position associated with the historical driving track according to the speed change function comprises the following steps:
determining a partial derivative between the speed change function and a separation distance between the vehicle location and a road junction;
estimating a variable value of the interval distance between the vehicle position and the road intersection through the partial derivative, and determining the variable value as the reference lane change position; the variable value is a value calculated when the partial derivative is made invalid.
9. The method of claim 1, wherein the number of historical travel tracks is at least two; the reference lane-change locations include one or more reference lane-change locations associated with the at least two historical travel tracks;
the determining an optimal lane change position for a target running vehicle in the running range of the road intersection according to the reference lane change position comprises the following steps:
taking the interval distance between the one or more reference lane change positions and the road intersection as a second interval distance;
Sequencing the one or more second interval distances according to the order of the magnitudes of the one or more second interval distances to obtain an interval distance sequence;
determining the optimal lane change position according to the interval distance sequence; the optimal lane change position is determined by calculating a spacing distance mean value corresponding to the spacing distance sequence based on the numerical attribute of the total number of the one or more second spacing distances; the numerical attributes include odd attributes and even attributes.
10. The method of claim 9, wherein said determining the optimal lane change location from the sequence of separation distances comprises:
summing the interval distance sequences to obtain an operation distance;
acquiring the total number of the one or more second interval distances, and determining an interval distance average value corresponding to the interval distance sequence according to the operation distance and the total number;
and acquiring the numerical attribute of the total number, and determining the optimal lane change position according to the numerical attribute and the interval distance mean value.
11. The method of claim 10, wherein said determining the optimal lane change location from the numerical attribute and the mean of the separation distances comprises:
If the numerical attribute is an odd attribute, determining a second interval distance at a central position in the interval distance sequence as a central interval distance, determining an average value between the interval distance average value and the central interval distance as a first optimal interval distance, and determining a position of the first optimal interval distance as the optimal lane change position;
if the numerical attribute is an even attribute, determining a second interval distance at a central position in the interval distance sequence as an interval distance to be operated, carrying out average value operation on the interval distance to be operated to obtain an average value operation distance, determining an average value between the interval distance average value and the average value operation distance as a second optimal interval distance, and determining a position of the second optimal interval distance as the optimal lane change position.
12. The method according to claim 1, wherein the method further comprises:
when the target running vehicle is detected to reach the running range of the road intersection, acquiring the optimal lane change position;
when the target running vehicle is detected to reach the optimal lane change position, acquiring an adaptive lane change speed corresponding to the optimal lane change position;
And switching the running speed of the target running vehicle from the current running speed to the adaptive lane change speed, and controlling the target running vehicle to perform lane change running from the optimal lane change position at the adaptive lane change running speed.
13. A method of data processing, comprising:
when the fact that the vehicle to be steered reaches the driving range of the road intersection is detected, acquiring an optimal lane changing position; the optimal lane change position refers to the lane change time indicated by the reference lane change position and most suitable for the road intersection; the reference lane change position is a reference lane change position which is determined according to a speed change function and is associated with the historical driving track; the historical driving track refers to the driving track before the driving vehicle turns to the intersection at the road intersection; the speed change function is determined according to the running attribute information corresponding to the vehicle position in the historical running track, and the running attribute information comprises running speed attribute information; the speed change function is used for reflecting running speed attribute information at the vehicle position, the relation changes along with the change of the interval distance between the vehicle position and the road intersection, and the reference lane change position refers to lane change time obtained by solving based on the speed change function;
Displaying a lane change indication animation comprising the optimal lane change position in a terminal navigation interface; the lane change instruction animation is used for guiding an object corresponding to the vehicle to be turned, and controlling the vehicle to be turned to run from the lane change position to the target lane; the target lane refers to a lane for performing an intersection turning action at the road intersection.
14. A data processing apparatus, comprising:
the driving track acquisition module is used for acquiring a historical driving track associated with the road intersection; the historical driving track refers to the driving track before the driving vehicle turns to the intersection at the road intersection;
the driving information acquisition module is used for acquiring the vehicle position in the historical driving track and driving attribute information corresponding to the vehicle position; the travel attribute information includes travel speed attribute information;
the function determining module is used for determining a speed change function corresponding to the historical driving track according to the driving attribute information; the speed change function is used for reflecting running speed attribute information at the vehicle position, and the relation changes along with the change of the interval distance between the vehicle position and the road intersection;
The reference position determining module is used for determining a reference lane change position associated with the historical driving track according to the speed change function; the reference lane change position refers to lane change time obtained by solving based on the speed change function;
the optimal position determining module is used for determining an optimal lane changing position for a target running vehicle in the running range of the road intersection according to the reference lane changing position; and the optimal lane change position refers to the lane change time indicated by the reference lane change position and most suitable for the road intersection.
15. A computer device, comprising: a processor, a memory, and a network interface;
the processor is connected to the memory, the network interface for providing network communication functions, the memory for storing program code, the processor for invoking the program code to cause the computer device to perform the method of any of claims 1-13.
16. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program adapted to be loaded by a processor and to perform the method of any of claims 1-13.
17. A computer program product, characterized in that it comprises computer instructions stored in a computer-readable storage medium, which are adapted to be read and executed by a processor, to cause a computer device with the processor to perform the method of any of claims 1-13.
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