CN115131965A - Vehicle control method, device, system, electronic device and storage medium - Google Patents
Vehicle control method, device, system, electronic device and storage medium Download PDFInfo
- Publication number
- CN115131965A CN115131965A CN202210724762.0A CN202210724762A CN115131965A CN 115131965 A CN115131965 A CN 115131965A CN 202210724762 A CN202210724762 A CN 202210724762A CN 115131965 A CN115131965 A CN 115131965A
- Authority
- CN
- China
- Prior art keywords
- time
- vehicle
- target
- determining
- relevant
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/167—Driving aids for lane monitoring, lane changing, e.g. blind spot detection
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention provides a vehicle control method, a device, a system, electronic equipment and a storage medium, wherein the method comprises the steps of determining related vehicles if a target vehicle is in a state to be converged, predicting relevant predicted convergence time of each related vehicle, predicting target predicted convergence time of the target vehicle, determining relevant vehicle distance, relevant interval and target interval, determining effective time windows, determining a plurality of candidate times based on each effective time window, controlling the target vehicle to converge at a convergence position at a preferred time, and realizing auxiliary control of convergence of the target vehicles.
Description
Technical Field
The embodiment of the application relates to the technical field of automobiles, in particular to a vehicle control method, device and system, electronic equipment and a storage medium.
Background
The invention and the development of the assistant driving bring great convenience to the human driving and reduce the fatigue of the driver, but the confluence of the ramp or the confluence caused by the reduction of the road is always a difficult point of the assistant driving, and the assistant driving is very easy to bring very poor driving feeling to the driver under the scene and even cause traffic accidents. In recent years. The technology in the field of auxiliary driving is rapidly developed, and the performance of a sensor and the performance of an ADAS (advanced driver assisted system) map are improved, so that a technical foundation is laid for solving the special scene.
In the related technology, vehicles needing to be converged are generally called in a unified mode by means of an intelligent networking technology, the passing time of the convergence is distributed, and all vehicles are controlled to pass through the convergence points according to the distributed time so as to achieve safe convergence.
Disclosure of Invention
In view of the above drawbacks of the prior art, the present invention provides a vehicle control method, apparatus, system, electronic device and storage medium to solve the above technical problems.
The invention provides a vehicle control method, which comprises the following steps:
if the target vehicle is in a to-be-converged state, determining a relevant area according to the position of the target vehicle, and determining a plurality of vehicles in the relevant area as relevant vehicles;
acquiring a confluence position and a related vehicle position of each related vehicle, and predicting a related predicted confluence time of each related vehicle and a target predicted confluence time of the target vehicle;
sequencing each related vehicle according to the related predicted convergence time, determining a related vehicle distance according to the related vehicle position of each related vehicle in a related vehicle group, determining a related interval according to the related predicted convergence time of each related vehicle in the related vehicle group, and determining a target interval of each related vehicle according to a target predicted convergence time and the related predicted convergence time of each related vehicle in the related vehicle group, wherein the related vehicle group comprises two related vehicles which are adjacent in sequence;
determining the relevant predicted convergence time of each relevant vehicle in at least one relevant vehicle group as an effective time window according to the relevant vehicle distance, the relevant interval and the target interval;
and determining a plurality of candidate moments based on the effective time windows, and controlling the target vehicles to converge at the converging position at a preferred moment, wherein the preferred moment is one of the candidate moments.
In an embodiment of the present invention, if a target vehicle is in a to-be-merged state, a relevant area is determined according to a target vehicle position of the target vehicle, and a plurality of vehicles located in the relevant area are determined as relevant vehicles, and the method includes:
acquiring at least one of the current driving state and the current acceleration value, determining a target convergence distance according to the target vehicle position and the convergence position, and determining a vehicle area of the target vehicle according to the target vehicle position;
if the target vehicle meets preset vehicle condition conditions, the target vehicle is in a to-be-converged state, wherein the preset vehicle condition conditions include at least one of the following conditions, the target convergence distance is smaller than a preset convergence threshold value, the vehicle region includes a preset region, the current driving state includes a preset driving state, and the current acceleration value is smaller than a preset acceleration threshold value.
In an embodiment of the present invention, determining a plurality of candidate moments based on each of the valid time windows, and controlling the target vehicle to converge at the converging position at a preferred moment includes:
determining a plurality of candidate moments based on each effective time window, and determining one candidate moment as the preferred moment;
acquiring the target vehicle speed of the target vehicle, and determining a target convergence distance according to the target vehicle position and the convergence position;
determining a target acceleration according to the target vehicle speed, the target convergence distance and the preferred time;
and controlling the target vehicle to accelerate according to the target acceleration so that the target vehicle performs confluence at the confluence position at the optimal time.
In an embodiment of the present invention, determining the relevant predicted merging time of each relevant vehicle in at least one relevant vehicle group as the valid time window according to the relevant inter-vehicle distance, the relevant interval, and the target interval includes:
and if the related vehicle group meets a preset window condition, determining the related predicted convergence time of each related vehicle in the related vehicle group as an effective time window, wherein the preset window condition comprises that the related vehicle distance is greater than a preset vehicle distance threshold value, the related interval is greater than a first preset interval threshold value, and the target interval is greater than a second preset interval threshold value.
In an embodiment of the present invention, before determining a plurality of candidate time instants based on each of the valid time windows, the method includes:
determining a post-vehicle estimated time according to the target prediction convergence time and a preset first coefficient, and determining the post-vehicle estimated time or a first preset estimated time as a theoretical estimated time, wherein the preset first coefficient is greater than 1;
determining an estimated window extreme value based on the theoretical estimated time and a first target estimated time, wherein the first target estimated time is the largest relevant predicted convergence time in all relevant predicted convergence times;
and determining a post-vehicle estimated time window according to the first target estimated time and the estimated window extreme value, and determining the post-vehicle estimated time window as an effective time window.
In an embodiment of the present invention, before determining a plurality of candidate time instants based on each of the valid time windows, the method includes:
if the target prediction convergence time is earlier than each relevant prediction convergence time, determining a vehicle front prediction time window according to a second preset prediction time and a second target prediction time, determining the vehicle front prediction time window as an effective time window, and determining the second target prediction time as the minimum relevant prediction convergence time in each relevant prediction convergence time.
In an embodiment of the present invention, before the target vehicle performs the merging at the merging position, the method includes:
re-determining a new effective time window, and determining a plurality of new moments to be selected based on the new effective time window;
determining new preferred time based on each new candidate time;
if the new and old time difference between the new priority time and the preferred time is smaller than a preset time difference threshold value, controlling the target vehicle to converge at the converging position at the preferred time;
and if the new and old time difference between the new priority time and the preferred time is larger than a preset time difference threshold value, controlling the target vehicle to perform confluence at the confluence position at the new preferred time.
In an embodiment of the present invention, after determining a plurality of candidate times based on each of the valid time windows, the method controls the target vehicle to perform merging at the merging position at a preferred time, and includes:
acquiring a target vehicle position of the target vehicle and a related interval of a target related vehicle group, and determining the related interval as a front-rear time interval of the candidate time, wherein the target related vehicle group is the related vehicle group of the effective time window where the candidate time is located;
determining a time change amount according to the target predicted convergence time and the candidate time;
determining the front vehicle collision time according to the candidate time and the relevant predicted convergence time of a first target relevant vehicle in the target relevant vehicle group, wherein the first target relevant vehicle is a relevant vehicle with a smaller relevant predicted convergence time in the target relevant vehicle group;
determining the rear vehicle collision time according to the candidate time and the relevant predicted convergence time of a second target relevant vehicle in the target relevant vehicle group, wherein the second target relevant vehicle is a relevant vehicle with a larger relevant predicted convergence time in the target relevant vehicle group;
determining a target confluence distance according to the target vehicle position and the confluence position, and determining a speed error based on the target confluence distance, the time to be selected and a preset target speed;
and determining one candidate moment as a preferred moment based on the front-back time interval, the time change amount, the front vehicle collision time, the rear vehicle collision time and the speed error of each candidate moment.
In an embodiment of the present invention, one candidate time is determined as a preferred time based on a front-rear time interval, a time change amount, a front vehicle collision time, a rear vehicle collision time, and a speed error of each candidate time;
determining the minimum value in the time intervals before and after each time to be selected as the minimum time interval;
determining the maximum value in the time change quantity of each time to be selected as the maximum change quantity;
determining the minimum value in the collision time of the front vehicle at each moment to be selected as the minimum time of the front vehicle;
determining the minimum value in the rear vehicle collision time of each candidate moment as the rear vehicle minimum time;
determining the maximum value of the speed errors of the moments to be selected as the maximum error;
determining a cost value of the candidate moment based on the candidate moment, the minimum time interval, the maximum change amount, the minimum time of the front vehicle, the minimum time of the rear vehicle and the maximum error;
and determining the candidate moment with the minimum cost value as the preferred moment.
In an embodiment of the present invention, determining the cost value of the candidate time based on the candidate time, the minimum time interval, the maximum change amount, the minimum time of the preceding vehicle, the minimum time of the following vehicle, and the maximum error includes:
wherein, f (t) i ) For the ith candidate time t i The Gain1 is a preset second coefficient, and the TimeChange is the candidate time t i Of the time change, TimeChange max For maximum variation, Gain2 is a predetermined third coefficient, TimeGap min For the minimum time interval, TimeGap is the time t to be selected i Before and after the time interval of (1), Gain3 is a preset fourth coefficient, Fttc min The minimum time of the front vehicle, Fttc is the time t to be selected i The Gain4 is a preset fifth coefficient, Rttc min The minimum time of the rear vehicle is Rttc which is the time t to be selected i The rear vehicle collision time is given by a preset sixth coefficient Gain5 and a candidate time t i Velocity error, VelError max Is the maximum error.
The present invention also provides a vehicle control apparatus, the apparatus including:
the relevant vehicle determining module is used for determining a relevant area according to the position of a target vehicle of the target vehicle and determining a plurality of vehicles in the relevant area as relevant vehicles if the target vehicle is in a to-be-converged state;
the acquisition and prediction module is used for acquiring a confluence position and related vehicle positions of the related vehicles, predicting related predicted confluence time of the related vehicles and target predicted confluence time of the target vehicle;
the sequencing module is used for sequencing the related vehicles according to the related predicted convergence time, determining related vehicle distances according to the related vehicle positions of the related vehicles in the related vehicle group, determining related intervals according to the related predicted convergence time of the related vehicles in the related vehicle group, and determining the target intervals of the related vehicles according to the target predicted convergence time and the related predicted convergence time of the related vehicles in the related vehicle group, wherein the related vehicle group comprises two related vehicles which are adjacent in sequence;
an effective time window determination module, configured to determine, as an effective time window, a relevant predicted convergence time of each relevant vehicle in at least one relevant vehicle group according to the relevant inter-vehicle distance, the relevant interval, and the target interval;
and the control module is used for determining a plurality of candidate moments based on each effective time window and controlling the target vehicle to converge at the converging position at a preferred moment, wherein the preferred moment is one of the candidate moments.
The invention also provides a vehicle control system, which comprises a satellite positioning module, a navigation map module, an image acquisition module, a millimeter wave radar module, a controller and a memory;
the satellite positioning module is used for providing a target vehicle position of a target vehicle;
the navigation map module is used for providing a confluence position, and determining a target confluence distance and a confluence direction according to the target vehicle position and the confluence position;
the image acquisition module is used for outputting a lane curve equation, front target information and front passable area points of a current lane and an adjacent lane;
the millimeter wave radar module is used for outputting vehicle target information and radar reflection point data so as to determine related vehicles and related vehicle positions of the related vehicles;
one or more computer programs stored in the memory;
the controller calls the computer program to execute the vehicle control method according to any one of claims 1 to 10.
The invention provides an electronic device, comprising:
one or more processors;
a storage device for storing one or more programs that, when executed by the one or more processors, cause the electronic equipment to implement the vehicle control method as in any one of the above embodiments.
The present invention provides a computer-readable storage medium having stored thereon computer-readable instructions which, when executed by a processor of a computer, cause the computer to execute the vehicle control method of any one of the above embodiments.
The invention has the beneficial effects that: the method determines related vehicles if the target vehicles are in a to-be-converged state, predicts related predicted convergence time of each related vehicle and target predicted convergence time of the target vehicles, determines related vehicle distance, related intervals and target intervals, can determine effective time windows, determines a plurality of to-be-selected time based on each effective time window, controls the target vehicles to converge at a convergence position at a preferred time, can assist in controlling the target vehicles to converge, is high in safety, does not need to limit the related vehicles to be intelligent internet automobiles, has low requirements for information exchange capacity of the automobiles to the outside, does not need cloud platform calculation distribution, is low in communication and calculation cost, and is high in availability.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. It is obvious that the drawings in the following description are only some embodiments of the application, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. In the drawings:
FIG. 1 is a schematic illustration of an environment in which a vehicle control method according to an exemplary embodiment of the present application may be implemented;
FIG. 2 is a flow chart illustrating a vehicle control method according to an exemplary embodiment of the present application;
FIG. 3 is a vehicle screening ID schematic diagram as illustrated in an exemplary embodiment of the present application;
FIG. 4 is a flow chart illustrating a particular vehicle control method in accordance with an exemplary embodiment of the present application;
fig. 5 is a block diagram showing a vehicle control apparatus according to an exemplary embodiment of the present application;
FIG. 6 is a block diagram of a vehicle control system shown in an exemplary embodiment of the present application;
FIG. 7 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the disclosure of the present specification, wherein the following description is made for the embodiments of the present invention with reference to the accompanying drawings and the preferred embodiments. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It should be understood that the preferred embodiments are illustrative of the invention only and are not limiting upon the scope of the invention.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the drawings only show the components related to the present invention rather than being drawn according to the number, shape and size of the components in actual implementation, and the type, amount and proportion of each component in actual implementation can be changed freely, and the layout of the components can be more complicated.
In the following description, numerous details are set forth to provide a more thorough explanation of embodiments of the present invention, however, it will be apparent to one skilled in the art that embodiments of the present invention may be practiced without these specific details, and in other embodiments, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring embodiments of the present invention.
ADAS (advanced driving assistance system) collects environmental data inside and outside a vehicle through various sensors mounted on the vehicle, and performs technical processing such as identification, detection, and tracking of static or dynamic objects, so that a driver can perceive possible dangers in the shortest time, thereby improving driving safety. The ADAS is used for acquiring environmental data inside and outside a vehicle in real time through various sensors so as to predict the environment in front of the vehicle, wherein the sensors mainly comprise a vision sensor, a millimeter wave radar sensor, a laser radar sensor and the like.
V2X (vehicle to outside information exchange), the car networking has established new car technical development direction through integrating Global Positioning System (GPS) navigation technique, car to car communication technique, radio communication and remote sensing technique, has realized the compatibility of manual driving and autopilot.
In brief, the vehicle model matched with the system can automatically select the driving route with the best road condition through analyzing the real-time traffic information in an automatic driving mode, thereby greatly relieving traffic jam. In addition, by using the vehicle-mounted sensor and the camera system, the surrounding environment can be sensed and rapidly adjusted, so that zero traffic accidents are realized. For example, if a pedestrian suddenly appears, it may be automatically decelerated to a safe speed or stopped.
Referring to fig. 1, fig. 1 is a schematic environmental diagram illustrating an implementation environment of a vehicle control method according to an exemplary embodiment of the present application. As shown in fig. 1, an exemplary vehicle control system includes a target vehicle 101, a plurality of associated vehicles 102, 103, and a server 104, where the target vehicle 101 and associated vehicles may be any vehicles provided by those skilled in the art. The server may be a server required by those skilled in the art, and is not limited herein. The figure includes two ramps a and a ramp B (the method provided in the embodiment of the present application is not limited to be used in a ramp scene, and other scenes requiring lane convergence may also be applicable), and the traveling direction of the vehicle is the direction shown as traveling upward along the ramp. The figures are only examples of two associated vehicles, the number of which can be chosen by the skilled person as desired. The method provided by the embodiment of the application can be realized based on equipment carried by the target vehicle, and the obtained preferred time can be issued to the target vehicle after the calculation is carried out by the server according to the method provided by the embodiment of the application. The server may also be equipped with a data receiving end of a satellite positioning system or an ADAS map. In an alternative embodiment, the vehicle control system may also be implemented without the server described above, relying on the computing power of the target vehicle itself to effect the determination of the preferred time.
The invention and the development of the assistant driving bring great convenience to the human driving, reduce the fatigue of the driver, but the convergence of the ramp or the convergence caused by the reduction of the road is always the difficulty of the assistant driving, and the assistant driving is very easy to bring very poor driving feeling to the driver under the scene, even traffic accidents. In recent years. The technology in the field of driving assistance is rapidly developed, and the performance of a sensor and the performance of an ADAS (advanced driving assistance system) map are improved, so that a technical basis is laid for solving the special scene.
In the related technology, vehicles needing to be converged are generally called in a unified mode by means of an intelligent networking technology, the passing time of the convergence is distributed, and all vehicles are controlled to pass through the convergence points according to the distributed time so as to achieve safe convergence. To solve these problems, embodiments of the present application respectively propose a vehicle control method, a vehicle control apparatus, a vehicle control system, an electronic device, a computer-readable storage medium, and a computer program product, which will be described in detail below.
Referring to fig. 2, fig. 2 is a flowchart illustrating a vehicle control method according to an exemplary embodiment of the present application. The method may be applied to the implementation environment shown in fig. 1 and specifically executed by at least one of a server in the implementation environment, a processor and a controller in the target vehicle, and so on. It should be understood that the method may be applied to other exemplary implementation environments and is specifically executed by devices in other implementation environments, and the embodiment does not limit the implementation environment to which the method is applied.
As shown in fig. 2, in an exemplary embodiment, the vehicle control method includes at least steps S201 to S205, which are described in detail as follows:
in step S201, if the target vehicle is in a to-be-merged state, a relevant area is determined according to the target vehicle position of the target vehicle, and a plurality of vehicles located in the relevant area are determined as relevant vehicles.
The target vehicle may be a vehicle with a communication function running on the road surface, and the position of the target vehicle may be determined by satellite positioning, or other methods known to those skilled in the art.
In an alternative embodiment, determining a plurality of vehicles located in the area of interest as vehicles of interest comprises:
identifying a plurality of vehicles in the relevant area to obtain surrounding vehicle IDs, and identifying a target vehicle to obtain a target vehicle ID;
determining a convergence direction according to the current road information and lane information of the target vehicle;
and screening a plurality of vehicles in the relevant area based on the confluence direction to determine the relevant vehicles.
Wherein the relevant area may be an area preset by a person skilled in the art, for example, an area 50 meters around the target vehicle position, etc. The relevant area may also be an area that can be covered by the millimeter wave radar and/or the camera provided in the target vehicle itself.
Referring to fig. 3, fig. 3 is a schematic view of a vehicle screening ID shown in an exemplary embodiment of the present application. That is, an exemplary vehicle map shown in fig. 3 can be obtained by displaying the target vehicle and a plurality of vehicles located in the relevant area according to their IDs. Based on fig. 3, where HV/55 is the target vehicle ID, the remaining numbers are the IDs of a plurality of vehicles located in the relevant area, where "1, 2, 3, 4, 5" identifies the lane number. When the direction of convergence is to converge to the left, only the left vehicle (vehicle in front of HV/55, lanes 1, 2) needs to be considered at this time. If there is convergence to the right, only the right vehicle (the vehicle in front of HV/55, lanes 4, 5) needs to be considered.
The road information may be the trend of the current road (such as going straight, merging into a certain road, decreasing lanes of the road, etc.), the intersection condition with other roads, such as merging into a certain road ahead, etc. The determination of the converging direction may be implemented by methods known to those skilled in the art, and will not be described herein.
By means of the method, obstacles (vehicles) outside the relevant area can be temporarily ignored, occupation of calculation force is reduced, and calculation speed is improved.
In an optional embodiment, if the target vehicle is in a to-be-merged state, determining a relevant area according to a target vehicle position of the target vehicle, and before determining a plurality of vehicles located in the relevant area as relevant vehicles, it is further necessary to determine whether the target vehicle is in the to-be-merged state, the method including:
acquiring at least one of a current driving state and a current acceleration value, determining a target convergence distance according to a target vehicle position and a convergence position, and determining a vehicle area of the target vehicle according to the target vehicle position;
and if the target vehicle meets the preset vehicle condition, the target vehicle is in a to-be-converged state, wherein the preset vehicle condition comprises at least one of the following conditions, the target convergence distance is smaller than a preset convergence threshold value, the vehicle region comprises a preset region, the current driving state comprises a preset driving state, and the current acceleration value is smaller than a preset acceleration threshold value.
The current driving state includes manual driving, assisted driving, and the like, and a person skilled in the art can distinguish the current driving state as needed, and based on the current driving state, it can be determined whether the current target vehicle needs to execute the vehicle control method provided in this embodiment. The current acceleration value may be an acceleration value in an acceleration state, or may be a deceleration value in a deceleration state, which is not limited herein. It may be determined whether the target vehicle is in rapid acceleration or rapid deceleration based on the acceleration value. The target merging distance is also how far the target vehicle has reached the merging position. The vehicle region can be defined by those skilled in the art as required, for example, a preset region is 500 meters away from the confluence position, and other regions are beyond 500 meters away from the confluence position. For another example, in the case of lane reduction, the vehicle area of the target vehicle located on the reduced lane is the preset area, or two lanes are combined into one lane in front of the reduced lane, the vehicle areas of the target vehicles located on the two lanes are both the preset area, and the target vehicles of the other lanes are the non-preset area. For example, the vehicle area of the target vehicle on the ramp is the preset area. In other words, the preset area includes, but is not limited to, ramp, lane-reduced related lane, and the like.
In one embodiment, the predetermined vehicle condition is at least one of:
the method comprises the following steps that 1, an ADAS map displays that a vehicle is in a ramp (a vehicle area comprises a preset area);
2. the distance from the confluence point to the confluence point is less than 150m (the target confluence distance is less than a preset confluence threshold);
3. the self-vehicle is in high-level auxiliary driving, namely, the self-vehicle is controlled by the auxiliary driving horizontally and vertically (the current driving state comprises a preset driving state);
4. the self-vehicle does not accelerate or decelerate suddenly (the current acceleration value is smaller than the preset acceleration threshold value).
In other words, if the target vehicle does not meet the preset vehicle condition, it is continuously determined whether the target vehicle meets the preset vehicle condition, and if not, the method provided by the embodiment is not executed, and the method known by those skilled in the art may be used to implement the method, and if so, the method provided by the embodiment may be used to implement the control of the target vehicle.
Step S202, a merging position and a relevant vehicle position of each relevant vehicle are acquired, and a relevant predicted merging timing of each relevant vehicle and a target predicted merging timing of the target vehicle are predicted.
The convergence position may be obtained by an ADAS map, and the position of the relevant vehicle may be obtained by satellite positioning, but the requirement on configuration, communication, and the like of the relevant vehicle is high. The mode of collecting the position of the relevant vehicle by using the millimeter wave radar and the camera can be realized by adopting a mode known by those skilled in the art, and details are not repeated herein.
In an alternative embodiment, the relevant predicted merging time is determined according to the distance of the relevant vehicle from the merging position (relevant merging distance), the speed of the relevant vehicle, and a preset acceleration coefficient. And determining the target predicted convergence time according to the target convergence distance, the speed of the target vehicle and a preset acceleration coefficient. For different related vehicles or target vehicles, the preset acceleration coefficients may be the same, and the preset acceleration coefficient corresponding to the vehicle may also be determined according to parameters such as speed and acceleration of the vehicle.
For example, the correlation predicted bus time and the target predicted bus time are determined as follows.
If there is no vehicle ahead of the vehicle (which may be a related vehicle or a target vehicle), the time (related predicted confluence time or target predicted confluence time) at which it reaches the confluence point (confluence position) is estimated as:
where Time represents a relevant predicted convergence Time to the convergence point or a target predicted convergence Time (depending on whether a currently input parameter is a parameter of a relevant vehicle or a parameter of a target vehicle), Distance represents a Distance of the vehicle from the convergence point, speed represents a current vehicle speed, and Gain is an influence factor (preset acceleration coefficient) due to acceleration.
The Gain can be obtained by inquiring a two-dimensional table, the input of the two-dimensional table is the Distance from the current to the confluence point and the current acceleration and deceleration of the relevant vehicle, and the output is a coefficient Gain. The two-dimensional table may be preset by a person skilled in the art. The specific setting manner of the two-dimensional table is not described herein.
If there is a vehicle ahead of the vehicle, the time to reach the merge point (the relevant predicted merge time or the target predicted merge time) is estimated in such a manner that if the vehicle speed is greater than that of the preceding vehicle, then
Wherein Time represents a relative predicted convergence Time or a target predicted convergence Time to the convergence point, Time Front Indicating a preceding vehicle arrival sink for a vehicleTime of flow point, Distance represents the Distance between the vehicle and the vehicle ahead, v represents the speed of the vehicle (the speed of the associated vehicle or the speed of the target vehicle), v represents the speed of the vehicle itself f Indicating the speed of the vehicle ahead, Gain is an influencing factor (preset acceleration factor) due to acceleration.
If the speed of the vehicle is less than the speed of the vehicle ahead of the associated vehicle, then the time for the vehicle to reach the merge point is calculated using a method (equation (1)) in which there is no vehicle ahead.
By the method, the time when the current target vehicle and the related vehicle are expected to be merged into the confluence position can be known. It should be noted that the parameters of the correlation predicted convergence time, the target predicted convergence time, and the correlation time dimension determined based on the above two parameters mentioned in the present embodiment may be a specific time, such as XX minutes and XX seconds in XX month and XX month, and may also be expressed by how long it is from the current time, such as 15 seconds.
Step S203, sequencing the relevant vehicles according to the relevant predicted convergence time, determining the relevant vehicle distance according to the relevant vehicle positions of the relevant vehicles in the relevant vehicle group, determining the relevant interval according to the relevant predicted convergence time of the relevant vehicles in the relevant vehicle group, and determining the target interval of the relevant vehicles according to the target predicted convergence time and the relevant predicted convergence time of the relevant vehicles in the relevant vehicle group.
Wherein the related vehicle group comprises two related vehicles which are adjacent in sequence. Two related vehicles in the related vehicle group can be located in the same lane or different lanes. The relevant vehicle distance may be a straight distance or a distance in a certain direction as specified by a person skilled in the art.
Taking the example that the correlation predicted merging time of two adjacent correlation vehicles in the order of the correlation vehicle group is 15 seconds and 20 seconds, respectively, the correlation interval is 5 seconds.
The target interval may be either one or the smallest of two time differences determined by the target predicted convergence time and the correlation predicted convergence time of each of the related vehicles in the related vehicle group, or may be a time difference between the target predicted convergence time and an earlier correlation predicted convergence time of each of the related vehicles in the related vehicle group. Continuing with the example where the relevant predicted merging time of two relevant vehicles in the order of two adjacent relevant vehicles included in the relevant vehicle group is 15 seconds and 20 seconds, respectively, the target predicted merging time is 18 seconds, where the two time differences are 3 seconds and 2 seconds, respectively, then the target interval may be 3 seconds or 2 seconds. When the target interval is a time difference between the target predicted merging time and the earlier associated predicted merging time in each associated vehicle in the associated vehicle group (collision time of the target vehicle with the preceding vehicle), the target interval is 3 seconds.
And step S204, determining the relevant predicted convergence time of each relevant vehicle in at least one relevant vehicle group as an effective time window according to the relevant vehicle distance, the relevant interval and the target interval.
In an alternative embodiment, determining the relevant predicted convergence time for each relevant vehicle in the at least one relevant vehicle group as the valid time window based on the relevant vehicle distance, the relevant interval, and the target interval comprises:
and if the related vehicle group meets a preset window condition, determining the related predicted convergence time of each related vehicle in the related vehicle group as an effective time window, wherein the preset window condition comprises that the related vehicle distance is greater than a preset vehicle distance threshold value, the related interval is greater than a first preset interval threshold value, and the target interval is greater than a second preset interval threshold value.
It will be appreciated that the determination of the validity time window is a check of the validity of each gap between vehicles (i.e. the distance between two vehicles is sufficient for the incoming vehicle). A gap needs to satisfy at least one of the following conditions (preset window conditions) to be calculated as a valid gap (valid time window):
1. the distance of two vehicles needs to be greater than a minimum value of 7m (the relevant vehicle distance is greater than a preset vehicle distance threshold);
2. the time interval between two vehicles is greater than a certain time (the correlation interval is greater than a first preset interval threshold);
3. the time to ttc (time to collision) with the preceding vehicle (target interval greater than the second preset interval threshold) needs to be greater than 1.5s if the gap between the two vehicles (two vehicles of the correlated vehicle group) converges.
The preset inter-vehicle distance threshold, the first preset interval threshold, and the second preset interval threshold may be set by a person skilled in the art as needed, which is only an example and does not limit the parameter selection in the embodiment of the present application.
It should be noted that, if there is no valid time window, the method may be ended, and an application for manual control of the target vehicle is made, or on the premise of ensuring the safety of the target vehicle, the valid time window is determined again until a new valid time window is determined.
And S205, determining a plurality of candidate moments based on each effective time window, and controlling the target vehicles to perform confluence at a confluence position at a preferred moment.
The preferred time is a time to be selected, and the preferred time may be randomly selected, or may be selected with reference to the following embodiments.
The determination of the candidate time may be to select one or more time points under a certain effective time window, where if the effective time window is [ 11s, 15s ], the candidate time is (11.6s, 11.12s … … 14.4.4 s, 15s), and the candidate time may be an arithmetic progression in the effective time window or may be a plurality of randomly selected time points. The determination mode of the candidate time can also be defined by those skilled in the art according to the needs.
In an optional embodiment, determining a plurality of candidate moments based on the respective valid time windows, and controlling the target vehicle to converge at the converging position at the preferred moment comprises:
determining a plurality of candidate moments based on each effective time window, and determining one candidate moment as a preferred moment;
acquiring the target vehicle speed of a target vehicle, and determining a target convergence distance according to the target vehicle position and the convergence position;
determining a target acceleration according to the target vehicle speed, the target convergence distance and the preferred time;
the control target vehicle performs acceleration running in accordance with the target acceleration so that the target vehicles perform confluence at a confluence position at a preferable timing.
For example, one exemplary way of determining the target acceleration that the target vehicle should perform is calculated from the preferred time is as follows:
where a is the target acceleration, Dis is the target convergence distance, v is the target vehicle speed, and t is the available duration.
It should be noted that, as described in the above embodiment, if the parameter of the correlation predicted bus time, the target predicted bus time, and the correlation time dimension determined based on the above two parameters may be a specific time, for example, XX minutes and XX seconds in XX month XX, then XX minutes and XX seconds in XX month XX is preferable, in this case, in the formula, the confluent time needs to be determined based on the preferable time and the current time, for example, the current time is 42 minutes 03 seconds when 11 month 1 day 12 of 2020 year, and 42 minutes 15 seconds when 2020 year 11 month 1 day 12 of year, then the usable time period is 12 seconds. If the relevant predicted convergence time, the target predicted convergence time, and the parameter of the relevant time dimension determined based on the two parameters are represented by how long from the current time, such as 15 seconds, the available time length can directly use the current time.
After the target acceleration is determined in the above manner, the target vehicle can be operated to perform safe and comfortable passing of the confluence position (confluence point) according to the calculated target acceleration.
In an optional embodiment, before determining the multiple candidate time instants based on the valid time windows, the method includes:
determining a post-vehicle estimated time according to the target prediction convergence time and a preset first coefficient, determining the post-vehicle estimated time or the first preset estimated time as a theoretical estimated time, wherein the preset first coefficient is greater than 1;
determining an estimated window extreme value based on the theoretical estimated time and a first target estimated time, wherein the first target estimated time is the maximum relevant predicted convergence time in all relevant predicted convergence times;
and determining the post-vehicle estimated time window according to the first target estimated time and the estimated window extreme value, and determining the post-vehicle estimated time window as an effective time window.
In an optional embodiment, before determining the multiple candidate time instants based on the valid time windows, the method includes:
if the target predicted convergence time is earlier than each related predicted convergence time, namely the time of the target vehicle theoretically converging into the convergence position is earlier than each related vehicle, determining a vehicle front predicted time window according to the second preset predicted time and the second target predicted time, and determining the vehicle front predicted time window as an effective time window. And the second target estimated time is the minimum related predicted convergence time in all the related predicted convergence times.
In the above embodiment, the second preset estimated time may be 0 (current time), or may be a time preset by a person skilled in the art.
That is, in the above embodiment, the valid time window is determined only for the related vehicle group, but sometimes there may be one valid time window after the related vehicle that has passed last, or there may be one valid time window before the earliest one of the related predicted merging times if the target predicted merging time of the target vehicle is earlier than the related predicted merging times, and in order to avoid the lack of the valid time window, the present embodiment can make up for the lack of the time window after the related vehicle that has passed last and the time window in which the target predicted merging time of the target vehicle is earlier than the related predicted merging times in the method provided in the above embodiment by determining the predicted time window as the valid time window. The first preset estimated time may be a value preset by a person skilled in the art, such as 10 seconds after the target estimated time.
In one embodiment, if the relevant vehicle has no front vehicle, 0 is taken as the minimum passing time, the passing time of the relevant vehicle is taken as the maximum passing time, a vehicle front estimated time window is determined according to the minimum passing time and the maximum passing time, if the relevant vehicle has no rear vehicle, the relevant predicted confluence time +10s (first preset estimated time) of the relevant vehicle and 2 times of the maximum passing time of the relevant predicted confluence time are taken, and the passing time of the relevant vehicle is taken as the minimum passing time, and a vehicle rear estimated time window is determined according to the minimum passing time and the maximum passing time.
In an alternative embodiment, before the target vehicle performs the merging at the merging position, the method includes:
re-determining a new effective time window, and determining a plurality of new moments to be selected based on the new effective time window;
determining new preferred time based on each new candidate time;
if the new and old time difference between the new priority time and the preferred time is smaller than a preset time difference threshold value, the control target vehicles carry out confluence at the confluence position at the preferred time;
and if the new and old time difference between the new priority time and the preferred time is larger than a preset time difference threshold value, the control target vehicles carry out confluence at the confluence position at the new preferred time.
Therefore, frequent change of the preferred time can be avoided, and the target time is switched when the difference value between the new preferred time and the original preferred time reaches a certain range.
In an optional embodiment, after determining a plurality of candidate times based on the respective valid time windows, the control target vehicle performs merging at the preferred time at the merging position, and the method includes:
acquiring a target vehicle position of a target vehicle and a relevant interval of a target relevant vehicle group, and determining the relevant interval as a time interval before and after a candidate moment, wherein the target relevant vehicle group is a relevant vehicle group of an effective time window of the candidate moment;
determining a time change amount according to the target predicted convergence time and the candidate time;
determining the collision time of the front vehicle according to the time to be selected and the related predicted convergence time of a first target related vehicle in the target related vehicle group, wherein the first target related vehicle is a related vehicle with smaller related predicted convergence time in the target related vehicle group;
determining the rear vehicle collision time according to the time to be selected and the related predicted convergence time of a second target related vehicle in the target related vehicle group, wherein the second target related vehicle is a related vehicle with a larger related predicted convergence time in the target related vehicle group;
determining a target confluence distance according to the position of a target vehicle and the confluence position, and determining a speed error based on the target confluence distance, the time to be selected and a preset target speed, wherein the preset target speed can be a certain value preset by a person skilled in the art, and can also be the speed of a vehicle before the target vehicle exists as the preset target speed, or the speed limit of a road as the preset target speed;
and determining one candidate moment as a preferred moment based on the front and rear time intervals, the time change amount, the front vehicle collision time, the rear vehicle collision time and the speed error of each candidate moment.
In an optional embodiment, one candidate moment is determined to be included as the preferred moment based on the front and rear time intervals, the time change amount, the front vehicle collision time, the rear vehicle collision time and the speed error of each candidate moment;
determining the minimum value in the time intervals before and after each time to be selected as the minimum time interval;
determining the maximum value in the time variation of each time to be selected as the maximum variation;
determining the minimum value in the collision time of the front vehicle at each candidate moment as the minimum time of the front vehicle;
determining the minimum value in the rear vehicle collision time of each time to be selected as the rear vehicle minimum time;
determining the maximum value of the speed errors at each time to be selected as the maximum error;
determining the cost value of the time to be selected based on the time to be selected, the minimum time interval, the maximum change amount, the minimum time of the front vehicle, the minimum time of the rear vehicle and the maximum error;
and determining the candidate moment with the minimum cost value as the preferred moment.
In an optional embodiment, determining the cost value of the candidate time based on the candidate time, the minimum time interval, the maximum change amount, the minimum time of the leading car, the minimum time of the trailing car, and the maximum error includes:
wherein, f (t) i ) For the ith candidate moment t i The Gain1 is a preset second coefficient, and the TimeChange is the candidate time t i Of the time change, TimeChange max For maximum variation, Gain2 is a predetermined third coefficient, TimeGap min For the minimum time interval, TimeGap is the time t to be selected i Before and after the time interval of (1), Gain3 is a preset fourth coefficient, Fttc min The minimum time of the front vehicle, Fttc is the time t to be selected i The front vehicle collision time of (1), Gain4 is a preset fifth coefficient, Rttc min The minimum time of the rear vehicle and Rttc is the time t to be selected i The rear vehicle collision time, Gain5 is a preset sixth coefficient, and VelError is a candidate time t i Velocity error, VelError max Is the maximum error.
In an alternative embodiment, if it is determined that the valid time window is not reached, then manual take-over of the target vehicle may be sought, or control of the target vehicle may be performed in other ways known to those skilled in the art.
According to the method provided by the embodiment, if the target vehicle is in a to-be-converged state, the related vehicles are determined, the related predicted convergence time of each related vehicle is predicted, the target predicted convergence time of the target vehicle is determined, the related vehicle distance, the related interval and the target interval are determined, the effective time windows can be determined, the multiple to-be-selected times are determined based on the effective time windows, the target vehicles are controlled to converge at the convergence position at the preferred time, the target vehicles can be controlled to be converged, the safety is higher, the related vehicles do not need to be limited to be intelligent internet-connected vehicles, the requirement on the information exchange capacity of the vehicles to the outside is lower, the calculation distribution of a cloud platform is not needed, the communication and calculation cost is low, and the availability is high.
The method of the embodiment provides a driving assistance technical scheme which is small in calculation amount, does not need to depend on a V2X communication technology, does not need the cooperation of other vehicles, can independently complete safe convergence, improves the scene coverage capability of assisted driving, and improves the application range of the auxiliary driving. By implementing the method, the following steps can be carried out:
1. the target vehicle applying the method of the embodiment can be assisted to carry out safe and comfortable confluence, and the safety and the efficiency in confluence are improved.
2. According to the preference weights (preset second coefficient, third coefficient, fourth coefficient, fifth coefficient and sixth coefficient) of different cost functions, different driving styles can be adjusted, and the driving habits of different drivers are met.
3. And additional vehicle-to-vehicle communication, vehicle-to-road communication and other auxiliary equipment are not needed, so that the cost is reduced.
In the following, the method mentioned in the above embodiment is exemplarily explained by an exemplary embodiment, please refer to fig. 4, fig. 4 is a flowchart of a specific vehicle control method shown in an exemplary embodiment of the present application, and as shown in fig. 4, the implementation process of the method is as follows:
step 1: and judging a confluence scene. And (3) obtaining a convergence scene according to ADAS map, satellite positioning and visual positioning fusion, judging whether the self state of the self vehicle (target vehicle) and the state of the obstacle (related vehicle) meet the convergence condition of entering the auxiliary driving, and entering the next step (step 2) if the self state of the self vehicle and the state of the obstacle (related vehicle) meet the convergence condition of entering the auxiliary driving. Otherwise, the condition judgment is continued.
Wherein, whether a convergence scene is entered is judged. One exemplary specific condition includes the following:
1, displaying the vehicle in a ramp by an ADAS map;
2. the distance from the convergence point is less than 150 m;
3. the self vehicle is in high-level assistant driving, namely, the self vehicle is controlled by assistant driving horizontally and vertically;
4. the self-vehicle does not accelerate or decelerate suddenly.
Step 2: obstacle screening (determination of relevant vehicles). According to the convergence scene, vehicles in a certain range in front of and behind the roads on two adjacent sides and vehicles in front of the roads on the own lane are selected. And removing the rest useless obstacles to reduce the subsequent calculation amount. And ID numbering is carried out on the screened obstacles.
Referring to fig. 3, the labels are marked on all the surrounding obstacles according to the areas, the obstacle on the left lane of the vehicle, the obstacle in front of the vehicle lane and the obstacle on the right lane of the vehicle are selected, and the labels are marked according to the corresponding areas. Obstacles outside the area are temporarily disregarded. Meanwhile, the convergence direction of the forward convergence is judged by considering the road information given by the ADAS map and combining the information of the current lane. If left-hand confluent, only the left-hand vehicle need be considered at this time. If there is a right hand side merge, only the right hand vehicle needs to be considered.
And step 3: aiming at the screened obstacles, the time of each obstacle passing through the confluence point is estimated by utilizing the current distance between the current obstacle and the vehicle, the current speed and the current acceleration, the speed limit of the current road, the acceleration and deceleration capacity limit of the vehicle and the mutual influence limit between the vehicle and the vehicle.
And calculating the time of reaching the obstacle point of all screened obstacles. If there is no vehicle in front of the vehicle, then
The estimate of its time to the point of convergence may be seen in equation (1) if there is a vehicle in front of the vehicle, the estimate of its time to the point of convergence may be seen as equation (2) if the vehicle speed is greater than the vehicle ahead. If the vehicle speed is lower than that of the front vehicle, the time when the vehicle reaches the confluence point is calculated by using a method without a vehicle in front of the vehicle.
And 4, step 4: checking the gap between the target vehicles (determination of effective time window), wherein the speed difference between the vehicles should not be larger than a certain value, the following distance at least meets the minimum value of 7m, the time difference passing through the confluence point is not smaller than 0.8s, the target gap is determined to meet the passing condition of the self-vehicle, and the vehicle interval meeting the condition is recorded. If there are no gaps satisfying the condition, the process jumps to step 8.
The validity of each gap between vehicles (i.e. the distance between two vehicles satisfies the import from the vehicle) is checked. Voids need to satisfy several exemplary conditions to be effective:
1. the distance of two vehicles needs to be greater than a minimum value of 7 m;
2. the time interval between two vehicles is greater than a certain time;
3. the ttc (time to collision) of the own vehicle with the preceding vehicle needs to be more than 1.5s if the own vehicle converges at the gap between the two vehicles.
And 5: scattering points (candidate moments) of each vehicle interval meeting the conditions, uniformly taking 50 time points, considering the time from the vehicle to the point under the assumption that the vehicle passes the point and the time difference T reaching the point without addition or subtraction for each point Error Difference V between the speed from the vehicle to the point and the target speed Error Time of collision F between the host vehicle and the front and rear vehicles when the host vehicle reaches the point ttc And R _ ttc, time difference TG of target vehicle gap. And simultaneously finding out the extreme value of each parameter to realize the normalization of each parameter, and constructing a cost function when the self-vehicle acts at the target time according to the parameters:
in the formula, f (t) i ) As a cost function, t i Indicating the time (candidate time) when the vehicle arrives at the confluence point with the time as a target; k is a radical of 1 、k 2 、k 3 、k 4 、k 5 For the weight coefficient occupied by each parameter in the cost function, different weight coefficients can enable the auxiliary driving to select different driving styles, namely a g function (g) 1 、g 2 、g 3 、g 4 、g 5 ) Is an arbitrary smooth monotonically increasing function or quadratic function.
For example, scattering points (candidate time) are performed for each of the valid slots (valid time windows) and the correlation parameters of each point are calculated. The point scattering method comprises the steps of taking the passing convergence time of a front vehicle of a gap as the minimum time, taking 0 as the minimum passing time if the gap has no front vehicle, taking the passing time of a rear vehicle of the gap as the maximum time, and taking the maximum value of the estimated time of +10s and 2 times of passing convergence points of the front vehicle if the gap has no rear vehicle. Obtaining effective time windows after obtaining the minimum passing time and the maximum passing time, uniformly selecting 50 points (selecting the time to be selected can be realized in a random selection mode and the like) in the effective time windows as the time when the self-vehicle passes through the confluence point, and calculating and storing the following parameters for each point:
TimeChange: the time change amount, i.e., the amount of change from the time the current state of the vehicle passes the merge point to the time the vehicle passes the merge point. The larger the amount of change, the larger the acceleration or deceleration required from the vehicle.
TimeGap: the time difference (front-rear time interval) between the vehicles passing through the confluence point before and after the gap is indicated, and the larger the time difference is, the safer the gap is. Otherwise, it is more dangerous.
F _ ttc refers to the collision time (front vehicle collision time) between the vehicle and the front vehicle when the vehicle passes through the confluence point at the time, and the smaller F _ ttc represents that the vehicle is more likely to collide with the front vehicle and is more dangerous.
And R _ ttc refers to the collision time (rear vehicle collision time) between the self vehicle and the rear vehicle when the self vehicle passes through the confluence point at the time, and the smaller R _ ttc represents that the self vehicle is easier to collide with the rear vehicle and is more dangerous.
VelError means an error (speed error) from a target speed at the merging point when the vehicle passes through the merging point at that time.
The target speed is selected in the following mode: if no obstacle (the relevant vehicle in front of the target vehicle) exists, the road speed limit is taken as the target speed, and if the obstacle exists, the obstacle speed is taken as the target speed.
And recording the extreme values of each parameter during calculation so as to facilitate the normalization use of the cost function in the next step.
And 6: and finding the point with the minimum cost function value as the optimal point to become the target. In order to avoid frequent jump of the point, a threshold value is set, and the target time is changed when the target time point changes and exceeds a certain value.
For example, the evaluation is performed using a cost function for each time point in all valid slots, and the cost function can refer to formula (4).
After all points are traversed, the time with the minimum cost value is selected as the preferred time. Meanwhile, in order to avoid frequent change of the preferred time, after a selected time value is the preferred time, the preferred time is switched until the difference between the new preferred time and the original preferred time reaches a certain range.
And 7: from the obtained preferred time (target time), the acceleration value (target acceleration) can be calculated by combining the current vehicle speed (target vehicle speed) of the vehicle and the distance (target merging distance) to the target point (merging point). And controlling the vehicle to safely pass through the confluence point at the target time.
For example, the target acceleration may be determined according to equation (3).
And 8: and judging whether the convergence scene meets exit conditions or not, wherein the exit conditions comprise that the distance to the convergence point is insufficient or the road is congested, if no convergence opportunity exists, the driver is requested to take over, if the exit conditions are not met, the method returns to the step of screening the obstacles (step 2), and continues to search for proper gap convergence.
Fig. 5 is a block diagram of a vehicle control apparatus shown in an exemplary embodiment of the present application. The apparatus may be applied to the implementation environment shown in fig. 1. The apparatus may also be applied to other exemplary implementation environments, and is specifically configured in other devices, and the embodiment does not limit the implementation environment to which the apparatus is applied.
As shown in fig. 5, the exemplary vehicle control device 500 includes:
a relevant vehicle determining module 501, configured to determine a relevant area according to a target vehicle position of a target vehicle and determine a plurality of vehicles located in the relevant area as relevant vehicles if the target vehicle is in a to-be-merged state;
an acquisition prediction module 502 for acquiring a merging position and a related vehicle position of each related vehicle, predicting a related predicted merging time of each related vehicle, and a target predicted merging time of a target vehicle;
a sorting module 503, configured to sort the relevant vehicles according to the relevant predicted merging time, determine a relevant inter-vehicle distance according to the relevant vehicle positions of the relevant vehicles in the relevant vehicle group, determine a relevant interval according to the relevant predicted merging time of the relevant vehicles in the relevant vehicle group, and determine a target interval of the relevant vehicles according to the target predicted merging time and the relevant predicted merging time of the relevant vehicles in the relevant vehicle group, where the relevant vehicle group includes two relevant vehicles that are adjacent to each other in a sorting manner;
an effective time window determination module 504 configured to determine a relevant predicted convergence time of each relevant vehicle in the at least one relevant vehicle group as an effective time window according to the relevant inter-vehicle distance, the relevant interval, and the target interval;
and the control module 505 is configured to determine multiple candidate moments based on each valid time window, and control the target vehicle to perform confluence at the confluence position at a preferred moment, where the preferred moment is one of the candidate moments.
It should be noted that the vehicle control apparatus provided in the foregoing embodiment and the vehicle control method provided in fig. 2 belong to the same concept, and specific ways in which the respective modules and units perform operations have been described in detail in the method embodiment, and are not described herein again. In practical applications, the vehicle control device provided in the above embodiments may distribute the functions to different functional modules according to needs, that is, divide the internal structure of the device into different functional modules to complete all or part of the functions described above, which is not limited herein.
Fig. 6 is a block diagram of a vehicle control system shown in an exemplary embodiment of the present application. The system may be applied to the implementation environment shown in fig. 1. The system may also be applied to other exemplary implementation environments and is specifically configured in other devices, and the embodiment does not limit the implementation environment to which the system is applied.
As shown in FIG. 6, the exemplary vehicle control system 600 includes a satellite positioning module 601, a navigation map module 602, an image acquisition module 603, a millimeter wave radar module 604, a controller 605, and a memory 606, wherein:
the satellite positioning module 601 is used for providing a target vehicle position of a target vehicle;
the navigation map module 602 is configured to provide a convergence position, determine a target convergence distance according to the target vehicle position and the convergence position, and determine a convergence direction;
the image acquisition module 603 is configured to output a lane curve equation, front target information, and front passable region points of a current lane and an adjacent lane, and may be a camera or other devices;
the millimeter wave radar module 604 is configured to output vehicle target information and radar reflection point data to determine a relevant vehicle and a relevant vehicle position of the relevant vehicle;
one or more computer programs are stored in the memory 605;
the controller 606 invokes a computer program to execute the vehicle control method in any of the above embodiments.
It should be noted that the vehicle control system provided in the foregoing embodiment and the vehicle control method provided in the foregoing embodiment in fig. 2 belong to the same concept, and specific manners in which the respective modules and units perform operations have been described in detail in the method embodiment, and are not described again here. In practical applications, the vehicle control system provided in the above embodiment may distribute the above functions to different functional modules according to needs, that is, divide the internal structure of the system into different functional modules to complete all or part of the above described functions, which is not limited herein.
An embodiment of the present application further provides an electronic device, including: one or more processors; a storage device for storing one or more programs that, when executed by the one or more processors, cause the electronic apparatus to implement the vehicle control method provided in the above-described respective embodiments.
FIG. 7 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application. It should be noted that the computer system 700 of the electronic device shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 7, the computer system 700 includes a Central Processing Unit (CPU) 1701 which can perform various appropriate actions and processes, such as executing the method described in the above embodiments, according to a program stored in a Read-Only Memory (ROM) 702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data necessary for system operation are also stored. The CPU 701, ROM 702, and RAM 703 are connected to each other via a bus 704. An Input/Output (I/O) interface 705 is also connected to the bus 704.
The following components are connected to the I/O interface 705: an input portion 706 including a keyboard, a mouse, and the like; an output section 707 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and a speaker; a storage section 708 including a hard disk and the like; and a communication section 709 including a Network interface card such as a LAN (Local Area Network) card, a modem, and the like. The communication section 709 performs communication processing via a network such as the internet. A drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that the computer program read out therefrom is mounted into the storage section 708 as necessary.
In particular, according to embodiments of the application, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method illustrated by the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 709, and/or installed from the removable medium 711. The computer program executes various functions defined in the system of the present application when executed by a Central Processing Unit (CPU) 701.
It should be noted that the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium may be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM), a flash Memory, an optical fiber, a portable Compact Disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer-readable signal medium may comprise a propagated data signal with a computer-readable computer program embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves.
Yet another aspect of the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a vehicle control method as described above. The computer-readable storage medium may be included in the electronic device described in the above embodiment, or may exist alone without being assembled into the electronic device.
Another aspect of the application also provides a computer program product or computer program comprising 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 executes the vehicle control method provided in the above-described embodiments.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (14)
1.A vehicle control method, characterized by comprising:
if the target vehicle is in a to-be-converged state, determining a relevant area according to the position of the target vehicle, and determining a plurality of vehicles in the relevant area as relevant vehicles;
acquiring a confluence position and a related vehicle position of each related vehicle, and predicting a related predicted confluence time of each related vehicle and a target predicted confluence time of the target vehicle;
sequencing each related vehicle according to the related predicted convergence time, determining a related vehicle distance according to the related vehicle position of each related vehicle in a related vehicle group, determining a related interval according to the related predicted convergence time of each related vehicle in the related vehicle group, and determining a target interval of each related vehicle according to a target predicted convergence time and the related predicted convergence time of each related vehicle in the related vehicle group, wherein the related vehicle group comprises two related vehicles which are adjacent in sequence;
determining the relevant predicted convergence time of each relevant vehicle in at least one relevant vehicle group as an effective time window according to the relevant vehicle distance, the relevant interval and the target interval;
and determining a plurality of candidate moments based on the effective time windows, and controlling the target vehicles to converge at the converging position at a preferred moment, wherein the preferred moment is one of the candidate moments.
2. The method according to claim 1, wherein if a target vehicle is in a to-be-confluent state, a relevant area is determined based on a target vehicle position of the target vehicle, and before a plurality of vehicles located in the relevant area are determined as relevant vehicles, the method comprises:
acquiring at least one of the current driving state and the current acceleration value, determining a target convergence distance according to the target vehicle position and the convergence position, and determining a vehicle area of the target vehicle according to the target vehicle position;
if the target vehicle meets preset vehicle condition conditions, the target vehicle is in a to-be-converged state, wherein the preset vehicle condition conditions include at least one of the following conditions, the target convergence distance is smaller than a preset convergence threshold value, the vehicle region includes a preset region, the current driving state includes a preset driving state, and the current acceleration value is smaller than a preset acceleration threshold value.
3. The method of claim 1, wherein determining a plurality of candidate times based on each of the valid time windows and controlling the target vehicle to merge at the merge location at a preferred time comprises:
determining a plurality of candidate moments based on each effective time window, and determining one candidate moment as the preferred moment;
acquiring the target vehicle speed of the target vehicle, and determining a target convergence distance according to the target vehicle position and the convergence position;
determining a target acceleration according to the target vehicle speed, the target convergence distance and the preferred time;
and controlling the target vehicles to perform acceleration running according to the target acceleration so that the target vehicles perform confluence at the confluence position at a preferable time.
4. The method of claim 1, wherein determining the relative predicted convergence time for each of the related vehicles in the at least one related vehicle group as an effective time window based on the related vehicle distance, the related interval, and the target interval comprises:
and if the related vehicle group meets a preset window condition, determining the related predicted convergence time of each related vehicle in the related vehicle group as an effective time window, wherein the preset window condition comprises that the related vehicle distance is greater than a preset vehicle distance threshold value, the related interval is greater than a first preset interval threshold value, and the target interval is greater than a second preset interval threshold value.
5. The method of any one of claims 1-4, wherein determining a plurality of candidate time instants before based on each of the valid time windows comprises:
determining a post-vehicle estimated time according to the target prediction convergence time and a preset first coefficient, and determining the post-vehicle estimated time or a first preset estimated time as a theoretical estimated time, wherein the preset first coefficient is greater than 1;
determining an estimated window extreme value based on the theoretical estimated time and a first target estimated time, wherein the first target estimated time is the largest relevant predicted convergence time in all relevant predicted convergence times;
and determining a post-vehicle estimated time window according to the first target estimated time and the estimated window extreme value, and determining the post-vehicle estimated time window as an effective time window.
6. The method of any one of claims 1-4, wherein determining a plurality of candidate time instants before based on each of the valid time windows comprises:
if the target prediction convergence time is earlier than each relevant prediction convergence time, determining a vehicle front prediction time window according to a second preset prediction time and a second target prediction time, determining the vehicle front prediction time window as an effective time window, and determining the second target prediction time as the minimum relevant prediction convergence time in each relevant prediction convergence time.
7. The method of any one of claims 1-4, wherein the target vehicle is ahead of the sink location, the method comprising:
re-determining a new effective time window, and determining a plurality of new moments to be selected based on the new effective time window;
determining new preferred time based on each new candidate time;
if the new and old time difference between the new priority time and the preferred time is smaller than a preset time difference threshold value, controlling the target vehicle to converge at the converging position at the preferred time;
and if the new and old time difference between the new priority time and the preferred time is larger than a preset time difference threshold value, controlling the target vehicle to perform confluence at the confluence position at the new preferred time.
8. The method according to any one of claims 1 to 4, wherein after determining a plurality of candidate times based on each of the valid time windows, controlling the target vehicle before merging at the merging location at a preferred time, the method comprises:
acquiring the position of a target vehicle of the target vehicle and the relevant interval of a target relevant vehicle group, and determining the relevant interval as the time interval before and after the candidate moment, wherein the target relevant vehicle group is the relevant vehicle group of the effective time window where the candidate moment is located;
determining a time change amount according to the target predicted convergence time and the candidate time;
determining the front vehicle collision time according to the candidate time and the relevant predicted convergence time of a first target relevant vehicle in the target relevant vehicle group, wherein the first target relevant vehicle is a relevant vehicle with smaller relevant predicted convergence time in the target relevant vehicle group;
determining the rear vehicle collision time according to the candidate time and the relevant predicted convergence time of a second target relevant vehicle in the target relevant vehicle group, wherein the second target relevant vehicle is a relevant vehicle with a larger relevant predicted convergence time in the target relevant vehicle group;
determining a target confluence distance according to the target vehicle position and the confluence position, and determining a speed error based on the target confluence distance, the time to be selected and a preset target speed;
and determining one candidate moment as a preferred moment based on the front-back time interval, the time change amount, the front vehicle collision time, the rear vehicle collision time and the speed error of each candidate moment.
9. The method of claim 8, wherein determining one of the candidate moments as a preferred moment based on a preceding and following time interval, a time change amount, a preceding vehicle collision time, a following vehicle collision time, a speed error of each of the candidate moments comprises;
determining the minimum value in the time intervals before and after each time to be selected as the minimum time interval;
determining the maximum value in the time change quantity of each time to be selected as the maximum change quantity;
determining the minimum value in the collision time of the front vehicle at each moment to be selected as the minimum time of the front vehicle;
determining the minimum value in the rear vehicle collision time of each candidate moment as the rear vehicle minimum time;
determining the maximum value of the speed errors of the moments to be selected as the maximum error;
determining a cost value of the candidate moment based on the candidate moment, the minimum time interval, the maximum change amount, the minimum time of the front vehicle, the minimum time of the rear vehicle and the maximum error;
and determining the candidate moment with the minimum cost value as the preferred moment.
10. The method of claim 9, wherein determining the cost value for the candidate time based on the candidate time, the minimum time interval, the maximum amount of change, the leading minimum time, the trailing minimum time, and the maximum error comprises:
wherein, f (t) i ) For the ith candidate moment t i The Gain1 is a preset second coefficient, and the TimeChange is the candidate time t i Of the time change, TimeChange max For maximum variation, Gain2 is a predetermined third coefficient, TimeGap min For the minimum time interval, TimeGap is the time t to be selected i Before and after the time interval of (1), Gain3 is a preset fourth coefficient, Fttc min The minimum time of the front vehicle, Fttc is the time t to be selected i The front vehicle collision time of (1), Gain4 is a preset fifth coefficient, Rttc min The minimum time of the rear vehicle and Rttc is the time t to be selected i The rear vehicle collision time is given by a preset sixth coefficient Gain5 and a candidate time t i Velocity error, VelError max Is the maximum error.
11. A vehicle control apparatus, characterized in that the apparatus comprises:
the relevant vehicle determining module is used for determining a relevant area according to the position of a target vehicle of the target vehicle and determining a plurality of vehicles in the relevant area as relevant vehicles if the target vehicle is in a to-be-converged state;
the acquisition and prediction module is used for acquiring a confluence position and related vehicle positions of the related vehicles, predicting related predicted confluence time of the related vehicles and target predicted confluence time of the target vehicle;
the sequencing module is used for sequencing the related vehicles according to the related predicted convergence time, determining related vehicle distances according to the related vehicle positions of the related vehicles in the related vehicle group, determining related intervals according to the related predicted convergence time of the related vehicles in the related vehicle group, and determining the target intervals of the related vehicles according to the target predicted convergence time and the related predicted convergence time of the related vehicles in the related vehicle group, wherein the related vehicle group comprises two related vehicles which are adjacent in sequence;
an effective time window determination module, configured to determine, as an effective time window, a relevant predicted convergence time of each relevant vehicle in at least one relevant vehicle group according to the relevant inter-vehicle distance, the relevant interval, and the target interval;
and the control module is used for determining a plurality of candidate moments based on the effective time windows and controlling the target vehicle to converge at the converging position at a preferred moment, wherein the preferred moment is one of the candidate moments.
12. A vehicle control system is characterized by comprising a satellite positioning module, a navigation map module, an image acquisition module, a millimeter wave radar module, a controller and a memory;
the satellite positioning module is used for providing a target vehicle position of a target vehicle;
the navigation map module is used for providing a confluence position, and determining a target confluence distance and a confluence direction according to the target vehicle position and the confluence position;
the image acquisition module is used for outputting a lane curve equation, front target information and front passable area points of a current lane and an adjacent lane;
the millimeter wave radar module is used for outputting vehicle target information and radar reflection point data so as to determine related vehicles and related vehicle positions of the related vehicles;
one or more computer programs stored in the memory;
the controller calls the computer program to execute the vehicle control method according to any one of claims 1 to 10.
13. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs that, when executed by the one or more processors, cause the electronic device to implement the vehicle control method according to any one of claims 1 to 10.
14. A computer-readable storage medium, having stored thereon computer-readable instructions, which, when executed by a processor of a computer, cause the computer to execute the vehicle control method of any one of claims 1 to 10.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210724762.0A CN115131965B (en) | 2022-06-23 | 2022-06-23 | Vehicle control method, device, system, electronic equipment and storage medium |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210724762.0A CN115131965B (en) | 2022-06-23 | 2022-06-23 | Vehicle control method, device, system, electronic equipment and storage medium |
Publications (2)
Publication Number | Publication Date |
---|---|
CN115131965A true CN115131965A (en) | 2022-09-30 |
CN115131965B CN115131965B (en) | 2023-07-07 |
Family
ID=83380591
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210724762.0A Active CN115131965B (en) | 2022-06-23 | 2022-06-23 | Vehicle control method, device, system, electronic equipment and storage medium |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN115131965B (en) |
Citations (18)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20130099911A1 (en) * | 2011-10-20 | 2013-04-25 | GM Global Technology Operations LLC | Highway Merge Assistant and Control |
CN110111605A (en) * | 2019-06-12 | 2019-08-09 | 吉林大学 | Automatic driving vehicle entrance ring road based on dynamic game travels decision-making technique |
CN110570049A (en) * | 2019-09-19 | 2019-12-13 | 西南交通大学 | expressway mixed traffic flow convergence collaborative optimization bottom layer control method |
CN110660213A (en) * | 2019-10-11 | 2020-01-07 | 中国联合网络通信集团有限公司 | Ramp vehicle merging method, road side equipment and vehicle |
CN110782704A (en) * | 2019-11-01 | 2020-02-11 | 北京星云互联科技有限公司 | Traffic guidance method, device and system based on vehicle-road cooperation and storage medium |
CN110853378A (en) * | 2019-11-19 | 2020-02-28 | 中国联合网络通信集团有限公司 | Vehicle ramp afflux management method and system |
CN110930697A (en) * | 2019-11-12 | 2020-03-27 | 南京航空航天大学 | Rule-based intelligent networked vehicle cooperative convergence control method |
CN111127908A (en) * | 2019-12-30 | 2020-05-08 | 戴姆勒股份公司 | Automatic driving control method for vehicle confluence |
CN111599194A (en) * | 2020-05-27 | 2020-08-28 | 中汽研汽车检验中心(天津)有限公司 | System and method for guiding speed of heterogeneous traffic flow on entrance ramp of expressway |
CN111968377A (en) * | 2020-08-31 | 2020-11-20 | 姜忠太 | Vehicle network-based vehicle track optimization method for fuel saving and driving comfort |
CN112650224A (en) * | 2020-12-11 | 2021-04-13 | 国汽(北京)智能网联汽车研究院有限公司 | Method, device, equipment and storage medium for automatic driving simulation |
CN112758092A (en) * | 2021-01-29 | 2021-05-07 | 重庆长安汽车股份有限公司 | Expressway ramp speed limit control method, system, vehicle and storage medium |
US20210241623A1 (en) * | 2020-02-04 | 2021-08-05 | Toyota Motor Engineering & Manufacturing North America, Inc. | Ramp merging assistance |
CN113345240A (en) * | 2021-08-03 | 2021-09-03 | 华砺智行(武汉)科技有限公司 | Highway vehicle importing method and system based on intelligent networking environment |
US20210295703A1 (en) * | 2020-03-17 | 2021-09-23 | Honda Motor Co., Ltd. | Systems and methods for cooperative ramp merge |
CN113936461A (en) * | 2021-10-15 | 2022-01-14 | 吉林大学 | Simulation method and system for mixed driving of vehicles at signal control intersection |
CN114067559A (en) * | 2021-09-27 | 2022-02-18 | 北京交通大学 | Confluence optimization control method for merging special lane for automatic vehicle into common lane |
CN114241757A (en) * | 2021-12-09 | 2022-03-25 | 宁波大学 | Entrance ramp cooperative convergence control method for intelligent networked vehicle |
-
2022
- 2022-06-23 CN CN202210724762.0A patent/CN115131965B/en active Active
Patent Citations (18)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20130099911A1 (en) * | 2011-10-20 | 2013-04-25 | GM Global Technology Operations LLC | Highway Merge Assistant and Control |
CN110111605A (en) * | 2019-06-12 | 2019-08-09 | 吉林大学 | Automatic driving vehicle entrance ring road based on dynamic game travels decision-making technique |
CN110570049A (en) * | 2019-09-19 | 2019-12-13 | 西南交通大学 | expressway mixed traffic flow convergence collaborative optimization bottom layer control method |
CN110660213A (en) * | 2019-10-11 | 2020-01-07 | 中国联合网络通信集团有限公司 | Ramp vehicle merging method, road side equipment and vehicle |
CN110782704A (en) * | 2019-11-01 | 2020-02-11 | 北京星云互联科技有限公司 | Traffic guidance method, device and system based on vehicle-road cooperation and storage medium |
CN110930697A (en) * | 2019-11-12 | 2020-03-27 | 南京航空航天大学 | Rule-based intelligent networked vehicle cooperative convergence control method |
CN110853378A (en) * | 2019-11-19 | 2020-02-28 | 中国联合网络通信集团有限公司 | Vehicle ramp afflux management method and system |
CN111127908A (en) * | 2019-12-30 | 2020-05-08 | 戴姆勒股份公司 | Automatic driving control method for vehicle confluence |
US20210241623A1 (en) * | 2020-02-04 | 2021-08-05 | Toyota Motor Engineering & Manufacturing North America, Inc. | Ramp merging assistance |
US20210295703A1 (en) * | 2020-03-17 | 2021-09-23 | Honda Motor Co., Ltd. | Systems and methods for cooperative ramp merge |
CN111599194A (en) * | 2020-05-27 | 2020-08-28 | 中汽研汽车检验中心(天津)有限公司 | System and method for guiding speed of heterogeneous traffic flow on entrance ramp of expressway |
CN111968377A (en) * | 2020-08-31 | 2020-11-20 | 姜忠太 | Vehicle network-based vehicle track optimization method for fuel saving and driving comfort |
CN112650224A (en) * | 2020-12-11 | 2021-04-13 | 国汽(北京)智能网联汽车研究院有限公司 | Method, device, equipment and storage medium for automatic driving simulation |
CN112758092A (en) * | 2021-01-29 | 2021-05-07 | 重庆长安汽车股份有限公司 | Expressway ramp speed limit control method, system, vehicle and storage medium |
CN113345240A (en) * | 2021-08-03 | 2021-09-03 | 华砺智行(武汉)科技有限公司 | Highway vehicle importing method and system based on intelligent networking environment |
CN114067559A (en) * | 2021-09-27 | 2022-02-18 | 北京交通大学 | Confluence optimization control method for merging special lane for automatic vehicle into common lane |
CN113936461A (en) * | 2021-10-15 | 2022-01-14 | 吉林大学 | Simulation method and system for mixed driving of vehicles at signal control intersection |
CN114241757A (en) * | 2021-12-09 | 2022-03-25 | 宁波大学 | Entrance ramp cooperative convergence control method for intelligent networked vehicle |
Non-Patent Citations (3)
Title |
---|
曹丹妮等: "考虑自动车队强度的高速公路非常规瓶颈交通流控制策略研究", 《中国公路学报》, no. 3, pages 78 - 88 * |
洛玉乐: "匝道合流区网联车辆协同控制策略研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》, no. 3, pages 034 - 2143 * |
邸允冉: "混合驾驶环境下快速路入口匝道协调控制", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》, no. 3, pages 034 - 1622 * |
Also Published As
Publication number | Publication date |
---|---|
CN115131965B (en) | 2023-07-07 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
RU2762786C1 (en) | Trajectory planning | |
CN108628300B (en) | Route determination device, vehicle control device, route determination method, and storage medium | |
JP6493923B2 (en) | Information display device, information display method, and information display program | |
CN110099831B (en) | Vehicle control system, vehicle control method, and storage medium | |
CN110562258B (en) | Method for vehicle automatic lane change decision, vehicle-mounted equipment and storage medium | |
RU2719495C2 (en) | Method and device for driving assistance | |
US20200180637A1 (en) | Apparatus and method for controlling running of vehicle | |
JP6676697B2 (en) | Vehicle control device, vehicle control method, and program | |
CN110060467B (en) | Vehicle control device | |
CN110506194B (en) | Driving control method and driving control device | |
US11205342B2 (en) | Traffic information processing device | |
RU2719080C2 (en) | Method and device for driving assistance | |
CN112937607B (en) | Internet automatic driving system and method for scenic spot sightseeing vehicle | |
US11221226B2 (en) | Passing gate determining device, vehicle control system, passing gate determining method, and storage medium | |
JP6460420B2 (en) | Information display device, information display method, and information display program | |
CN112829753B (en) | Guard bar estimation method based on millimeter wave radar, vehicle-mounted equipment and storage medium | |
CN113291309A (en) | Periphery recognition device, periphery recognition method, and storage medium | |
US11935417B2 (en) | Systems and methods for cooperatively managing mixed traffic at an intersection | |
JP2024095712A (en) | Output device, control method, program, and storage medium | |
CN114170823A (en) | Vehicle allocation system, vehicle allocation server and vehicle allocation method | |
EP3626570A1 (en) | Driving assistance method and driving assistance apparatus | |
CN112689584B (en) | Automatic driving control method and automatic driving control system | |
CN114771533A (en) | Control method, device, equipment, vehicle and medium for automatic driving vehicle | |
JP6747405B2 (en) | Own vehicle position confidence calculator | |
CN110599790B (en) | Method for intelligent driving vehicle to get on and stop, vehicle-mounted equipment and storage medium |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |