CN109318894B - Vehicle driving assistance system, vehicle driving assistance method, and vehicle - Google Patents

Vehicle driving assistance system, vehicle driving assistance method, and vehicle Download PDF

Info

Publication number
CN109318894B
CN109318894B CN201710642223.1A CN201710642223A CN109318894B CN 109318894 B CN109318894 B CN 109318894B CN 201710642223 A CN201710642223 A CN 201710642223A CN 109318894 B CN109318894 B CN 109318894B
Authority
CN
China
Prior art keywords
vehicle
oncoming
current
turning operation
calculation unit
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.)
Active
Application number
CN201710642223.1A
Other languages
Chinese (zh)
Other versions
CN109318894A (en
Inventor
唐帅
孙铎
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Audi AG
Original Assignee
Audi AG
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Audi AG filed Critical Audi AG
Priority to CN201710642223.1A priority Critical patent/CN109318894B/en
Publication of CN109318894A publication Critical patent/CN109318894A/en
Application granted granted Critical
Publication of CN109318894B publication Critical patent/CN109318894B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/095—Predicting travel path or likelihood of collision
    • B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/095—Predicting travel path or likelihood of collision
    • B60W30/0953—Predicting travel path or likelihood of collision the prediction being responsive to vehicle dynamic parameters
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/04—Traffic conditions
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
    • B60W40/09—Driving style or behaviour
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/0097—Predicting future conditions
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W50/0098—Details of control systems ensuring comfort, safety or stability not otherwise provided for
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects
    • B60W2554/404—Characteristics
    • B60W2554/4041—Position

Abstract

The present invention provides a vehicle driving assistance system, a vehicle driving assistance method, and a vehicle, the system being mounted on or applied to a host vehicle to perform a hazard warning when the host vehicle performs a turning operation, and including: a detection unit configured to detect whether or not the own vehicle is in a turning position, and detect whether or not there is an oncoming vehicle in an oncoming lane of a lane in which the own vehicle is present; and a calculation unit configured to predict whether there is a risk of collision with an oncoming vehicle during a current turning operation of the host vehicle, in a case where the host vehicle is at a turning position and there is the oncoming vehicle in the oncoming lane, wherein the calculation unit is configured to perform the prediction of the risk of collision based on driving behavior habits of a current driver of the host vehicle.

Description

Vehicle driving assistance system, vehicle driving assistance method, and vehicle
Technical Field
The present invention relates to the field of vehicle driving assistance. In particular, the present invention relates to a vehicle driving assist system, a vehicle driving assist method, and a vehicle, which are capable of performing a hazard warning when the vehicle is about to turn around.
Background
During the driving process of the vehicle, especially during the driving process of urban roads, scenes needing to be turned around are frequently encountered. In many cases, a separate traffic light is not set for turning around to control the passing of the vehicle, so that a driver needs to observe the situation of the oncoming vehicle to determine the turning around time. In addition, since the turnaround is an operation that is complicated and occupies a large space, the turnaround often affects traffic to the lane, such as forcing oncoming vehicles to decelerate and even to stop waiting until the turnaround operation is completed. In some cases, there may be a dangerous situation such as collision with an oncoming vehicle.
Therefore, it is necessary to provide a vehicle driving assist system and method that detects a traffic condition of an oncoming lane when a vehicle is about to make a turn around operation and makes a hazard warning in order to assist a driver in completing the turn around operation without hindering the traffic of the oncoming lane and/or without causing a hazard such as a collision.
Disclosure of Invention
An object of the present invention is to provide a vehicle driving assistance system, a vehicle driving assistance method, and a vehicle that can perform a danger warning when the vehicle makes a turn, and assist a driver in completing the turn without hindering traffic to a lane and/or causing danger (e.g., collision). Another object of the present invention is to provide a vehicle driving assistance system, a vehicle driving assistance method, and a vehicle, which can perform a hazard warning at the time of starting a turning operation of the vehicle individually based on a driving behavior habit of a driver, so that the hazard warning is more accurate.
The present invention provides a vehicle driving assist system that is mounted on or applied to a host vehicle to perform a hazard warning when the host vehicle performs a turning operation, the system including: a detection unit configured to detect whether or not a host vehicle is in a turning position, and detect whether or not there is an oncoming vehicle in an oncoming lane of a lane in which the host vehicle is present; and a calculation unit configured to predict whether there is a risk of collision with the oncoming vehicle during a current turning operation of the own vehicle, in a case where the own vehicle is at the turning position and the oncoming vehicle is present in the oncoming lane, wherein the calculation unit is configured to perform the prediction of the risk of collision based on driving behavior habits of a current driver of the own vehicle.
According to an embodiment of the present invention, the calculation unit is configured to predict the traveling trajectories of the host vehicle and the oncoming vehicle within a time length for which the host vehicle completes the current turning operation, and predict whether there is a risk of collision with the oncoming vehicle during the current turning operation of the host vehicle, based on the predicted traveling trajectories of both, wherein the time length for which the host vehicle completes the current turning operation is obtained based on driving behavior habits of the current driver of the host vehicle.
According to an embodiment of the present invention, wherein the calculation unit is configured to store in advance a function for a current driver of the host vehicle for calculating a length of time for the host vehicle to complete the current turning operation, wherein parameters of the function are optimized by machine learning based on data collected in past turning operations of the current driver of the host vehicle.
According to an embodiment of the present invention, wherein the variables of the function include a width of an available space for the host vehicle to perform the current turning operation and an initial speed of the host vehicle at the time of the current turning operation.
According to the embodiment of the present invention, the width of the space available in which the subject vehicle performs the current turning operation is detected by the detection unit, and is determined by both the width of the oncoming lane and the obstacles around it.
According to an embodiment of the present invention, wherein the calculation unit is configured to predict the travel locus of the oncoming vehicle based on a current speed of the oncoming vehicle.
According to an embodiment of the present invention, wherein the calculation unit is configured to predict the travel locus of the oncoming vehicle based on the current speed and deceleration of the oncoming vehicle.
According to an embodiment of the present invention, wherein the deceleration of the oncoming vehicle is determined according to a category of the oncoming vehicle.
According to an embodiment of the present invention, wherein the calculation unit is configured to predict the running locus of the own vehicle based on an initial speed at which the own vehicle performs the current turning operation and a preset maximum steering angle.
According to an embodiment of the present invention, the detection unit further includes an identification information acquisition element for acquiring identification information of a current driver of the own vehicle, and the calculation unit is further configured to previously store a plurality of functions for calculating a length of time for the own vehicle to complete the current turning operation, respectively, corresponding to each of a plurality of drivers experienced by the own vehicle history, wherein the plurality of drivers includes the current driver of the own vehicle, and parameters of each of the plurality of functions are optimized by machine learning based on data collected in previous turning operations of the corresponding driver, wherein the calculation unit is configured to acquire a corresponding function for calculating the length of time for the own vehicle to complete the current turning operation from the plurality of functions based on the acquired identification information of the current driver of the own vehicle.
According to an embodiment of the present invention, the vehicle driving assist system further includes: an output unit that issues a warning to a driver and/or automatically decelerates or stops the own vehicle in a case where the calculation unit predicts that there is a risk of collision with the oncoming vehicle during the current turning operation of the own vehicle.
The invention also provides a vehicle driving assistance method for performing danger early warning when the vehicle performs a turning operation, the method comprising the following steps: detecting whether the vehicle is in a turning position or not, and detecting whether an oncoming vehicle exists in an oncoming lane of a lane where the vehicle is located; and predicting whether there is a risk of collision with the oncoming vehicle during a current turn-around operation of the host vehicle, in a case where the host vehicle is in the turn-around position and the oncoming vehicle is present in the oncoming lane, wherein the risk of collision is predicted based on driving behavior habits of a current driver of the host vehicle.
According to an embodiment of the present invention, the vehicle driving assist method further includes the steps of: the method includes predicting the running tracks of the vehicle and the oncoming vehicle within the time length of the current turning operation of the vehicle, and predicting whether the collision risk with the oncoming vehicle exists during the current turning operation of the vehicle based on the predicted running tracks of the vehicle and the oncoming vehicle, wherein the time length of the current turning operation of the vehicle is obtained based on the driving behavior habit of the current driver of the vehicle.
According to an embodiment of the present invention, the vehicle driving assist method further includes the steps of: a function for calculating a length of time for which the present driver of the own vehicle completes the present turning operation is stored in advance, wherein parameters of the function are optimized by machine learning based on data acquired in past turning operations of the present driver of the own vehicle.
According to an embodiment of the present invention, the variables of the function include a width of an available space for the host vehicle to perform the current turning operation and an initial speed of the host vehicle at the time of the current turning operation.
According to the embodiment of the invention, the width of the available space for the vehicle to perform the current turning operation is detected by the detection unit and is jointly determined by the width of the opposite lane and the obstacles around the opposite lane.
According to an embodiment of the present invention, the vehicle driving assist method further includes the steps of: predicting a travel track of the oncoming vehicle based on a current speed of the oncoming vehicle.
According to an embodiment of the present invention, the vehicle driving assist method further includes the steps of: predicting a travel locus of the oncoming vehicle based on the current speed and deceleration of the oncoming vehicle.
According to an embodiment of the present invention, the deceleration of the oncoming vehicle is determined according to the category of the oncoming vehicle.
According to an embodiment of the present invention, the vehicle driving assist method further includes the steps of: and predicting the running track of the vehicle based on the initial speed and the preset maximum steering angle when the vehicle performs the current turning operation.
According to an embodiment of the present invention, the vehicle driving assist method further includes the steps of: acquiring identity information of a current driver of the vehicle; and pre-storing a plurality of functions for calculating a length of time for which the current turning operation of the host vehicle is completed, respectively corresponding to each of a plurality of drivers experienced by the host vehicle history, wherein the plurality of drivers include the current driver of the host vehicle, and parameters of each of the plurality of functions are optimized by machine learning based on data collected in the previous turning operation of the corresponding driver, wherein the method further comprises the steps of: and acquiring a corresponding function for calculating the time length of the current turning operation of the vehicle from the plurality of functions based on the acquired identity information of the current driver of the vehicle.
According to an embodiment of the present invention, the vehicle driving assist method further includes the steps of: in the case where it is predicted that there is a risk of collision with the oncoming vehicle during the current turning operation of the own vehicle, a warning is issued to the driver and/or the own vehicle is automatically decelerated or stopped.
An aspect of the present invention also provides a vehicle mounted with or adapted to apply the vehicular drive assist system of any of the above embodiments.
Thus, according to the vehicle driving assistance system, the vehicle driving assistance method, and the vehicle of the embodiments of the invention, it is possible to perform the danger early warning when the vehicle turns around, and to assist the driver to complete the turning around operation without obstructing the traffic to the lane and/or without causing danger (e.g., collision). In addition, according to the vehicle driving assistance system, the vehicle driving assistance method and the vehicle, the danger early warning can be performed when the vehicle is turned around according to the driving behavior habit of the driver, so that the danger early warning is more accurate.
Drawings
Features, advantages and technical effects of exemplary embodiments of the present invention will be described below with reference to the accompanying drawings, in which like reference numerals represent like elements, and wherein:
fig. 1 shows a schematic block diagram of a vehicle driving assistance system according to an embodiment of the invention.
Fig. 2 shows a case where the vehicle a is in a turnaround position and there is an oncoming vehicle B in an oncoming lane.
Fig. 3 shows a schematic flowchart of a driving assistance method for vehicle according to an embodiment of the invention.
Detailed Description
Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. The following detailed description and drawings are illustrative of the principles of the invention, which is not limited to the preferred embodiments described, but is defined by the claims.
Fig. 1 shows a schematic block diagram of a vehicle driving assistance system 100 according to an embodiment of the invention. As shown in fig. 1, the vehicle driving assist system 100 may be mounted on or applied to a vehicle a to perform a hazard warning when the vehicle a makes a turn. Specifically, the vehicle driving assist system 100 may include a detection unit 10, a calculation unit 20, and an output unit 30. The respective units of the vehicle driving assistance system 100 may be configured to operate in such a manner that the components in the respective units are connected to each other. The connection means may include a system bus, a network, and/or other suitable connection means. According to other embodiments of the invention, the vehicle driving assistance system 100 may include more, fewer or different units, and each unit may include more, fewer or different components. Furthermore, the units and components may be combined or separated in various ways.
Next, the configuration and function of each unit and/or component of the driving assistance system 100 for vehicle according to the embodiment of the invention will be specifically described.
The detection unit 10 includes an external detection device and an internal detection device. The external detection device is configured to acquire traffic information of an environment in which the vehicle a is located. Specifically, the external detection device may be configured to detect whether the vehicle is in a turnaround position based on the acquired traffic information. In the case where the vehicle a is in the turnaround position, the external detection device is configured to further detect whether there is an oncoming vehicle B within a predetermined range in an oncoming lane of a lane in which the vehicle a is present. Here, there may be one or more lanes in which the vehicle a is located. Since the turning operation of the vehicle a may involve more than one oncoming lane, the external detection device may be configured to detect whether there is an oncoming vehicle B on all the oncoming lanes. In the case where there is an oncoming vehicle B, the external detection device is also configured to further detect the movement parameters of the oncoming vehicle B, such as the position, speed, and acceleration. The predetermined range described here may be a maximum distance range to the vehicle a that can be detected by the external detection device, or may be an empirically preset distance range such as 100m, 200m, or the like. Further, the external detection device may also be configured to detect the category of the oncoming vehicle B (such as a truck, a bus, a minibus, a four-door sedan, and the like). Fig. 2 schematically shows a case where the vehicle a is in a turnaround position and there is an oncoming vehicle B in an oncoming lane.
Specifically, the external detection device may include various sensors mounted on the vehicle a, such as a position sensor such as a GPS sensor, an image sensor such as a camera, a laser sensor, a radar sensor, an ultrasonic sensor, an infrared sensor, and the like. The external detection device may utilize any combination of these sensors to acquire traffic information and perform subsequent detection. For example, the external detection device may acquire current position information of the vehicle a using a GPS sensor or a vision-based positioning method to detect whether the vehicle a is at a certain intersection and is in a U-turn lane to determine whether the vehicle a is in a U-turn position. The external detection device may also acquire an image of the surroundings of the vehicle a using a camera, and recognize a U-turn sign in the intersection and the lane using computer vision and image processing techniques to determine whether the vehicle a is in a U-turn position. Further, the external detection device may also determine whether the vehicle a is in a U-turn position by acquiring map information and a navigation route of the vehicle a by communicating with a navigation apparatus mounted on the vehicle a.
In the case where it is determined that the vehicle a is in the U-turn position, the external detection device may be configured to detect whether there is an oncoming vehicle B within a predetermined range on the oncoming lane using traffic information acquired by any combination of a camera, a laser sensor, a radar sensor, an ultrasonic sensor, an infrared sensor, and the like, and further acquire motion parameters of the oncoming vehicle B, such as a position, a speed, an acceleration, and the like, in the case where the oncoming vehicle B is detected.
In a preferred embodiment, the external detection device is further configured to determine the available space for the vehicle a to make the current turn. Specifically, the exterior detection device is configured to determine a width W of an available space for the vehicle a to make a current turn, which is defined to coincide with the width direction of the oncoming lane. Specifically, the external detection device may be configured to acquire the width of the lane opposite to the lane in which the vehicle a is located, using the GPS sensor. The external detection device may also be configured to take an image of the environment around the vehicle a with a camera or the like, recognize a road boundary (such as a curb, a fence, a lane line, etc.) by computer vision and image processing techniques, and detect the width of the oncoming lane. Here, since there may be a plurality of oncoming lanes, the widths of all the oncoming lanes are detected. Further, the influence of the temporarily appearing obstacle around the oncoming lane on the available space for the current turn of the vehicle a is also taken into consideration. The external detection unit may detect the position, shape, and the like of an obstacle such as a parked vehicle, a pedestrian, or the like around the oncoming lane by any combination of a camera, a laser sensor, a radar sensor, an ultrasonic sensor, an infrared sensor, or the like. Thus, the external detection device can determine the width W of the available space for the vehicle a to perform the current turning operation based on the actual width of the oncoming lane and the obstacle information around the oncoming lane.
The internal detection device of the detection unit 10 may be configured to acquire the motion parameters of the vehicle a. The interior detection device 10 can detect motion parameters of the vehicle a such as speed, acceleration, steering angle, etc., as needed. The interior detection device mainly acquires the motion parameters of the vehicle a through various sensors of the vehicle a itself, such as a speed sensor that measures the speed of the vehicle a, a steering angle sensor that measures the steering angle of the vehicle a, an acceleration sensor that measures the acceleration of the vehicle a, and the like.
In a preferred embodiment, the internal detection means are also configured to be able to acquire identity information of the current driver of the vehicle a. Specifically, the internal detection device may include an identification information acquisition element for acquiring identification information of the current driver, and the identification information acquisition element may be a fingerprint information acquisition element, a face information acquisition element, or the like. The fingerprint information acquisition element may be provided at a suitable position in the cabin of the vehicle a, such as an activation control key, a steering wheel, or the like, to conveniently acquire the fingerprint of the driver. Of course, the fingerprint information acquisition element may be provided at other positions of the vehicle a, such as a handle of a door beside the driver's seat, a vehicle key, and the like, as long as it is convenient to acquire the fingerprint of the driver. The face information acquisition element may be an image sensor, such as a camera, provided in the vicinity of the rear view mirror, provided at a suitable position in the cabin of the vehicle a so as to acquire an image of the face of the driver. The internal detection means may identify the current driver status based on the fingerprint or facial image of the current driver. Further, the driver can actively input his or her identification information through an input device or the like of the vehicle a so that the internal detection device recognizes his or her identification.
Next, the configuration and function of the calculation unit 20 according to the embodiment of the present invention will be specifically described. The calculation unit 20 is particularly realized by a processor and a memory. The processor may include one or more general-purpose processors and/or one or more special-purpose processors (e.g., image processors, digital signal processing, etc.). The memory may include one or more volatile and/or one or more non-volatile memories. The memory may be integrally formed with the processor or separately formed. The memory may contain instructions that are executed by the processor to perform various functions. The memory may also store data needed and generated when the computing unit 20 executes instructions, and the like.
In the embodiment of the present invention, the calculation unit 20 is configured to predict whether there is a potential danger for the vehicle a to perform the current turning operation based on the current traffic condition in the case where the vehicle a is at the turning position and there is an oncoming vehicle B in the oncoming lane. Specifically, the calculation unit 20 can predict the potential danger by predicting whether the vehicle a will collide with the oncoming vehicle B during the current turn-around operation. In addition, since the turning operation is a complicated operation for the driver, the space, time, and the like required for the different drivers to perform the turning operation are different, and even the space, time, and the like required for the same driver to perform the turning operation varies as the driving experience increases. Preferably, the calculation unit 20 is configured to determine whether there is a risk of collision with the oncoming vehicle B during the current turning operation of the vehicle a, based on the driving behavior habit of the current driver of the vehicle a. In this way, the vehicle driving assistance system 100 can provide individualized driving assistance for different drivers, and thus the danger warning is more accurate.
In an exemplary embodiment, the calculation unit 20 may be configured to predict the travel locus of the vehicle a and the travel locus of the oncoming vehicle B, and determine whether there is a risk of collision with the oncoming vehicle B during the current turning operation of the vehicle a by determining whether the travel loci of both coincide at a certain point in time during the turning operation of the vehicle a. Since the influence of the driving behavior habits of different drivers and the driving behavior habits of the same driver at different periods on the current turning operation of the vehicle a can be mainly reflected by the time for completing the current turning operation, in a preferred embodiment, the calculation unit 20 may be configured to first obtain the length of time for the vehicle a to complete the current turning operation based on the driving behavior habits of the current driver of the vehicle a, and then predict the traveling tracks of the vehicle a and the oncoming vehicle B within the length of time. Here, the length of time for which the vehicle a completes the current turning operation refers to the time from when the vehicle a starts the turning operation, that is, the steering angle of the vehicle a becomes greater than a certain threshold (for example, the steering angle of the steering wheel is greater than 90 °, or the steering angle of the wheels is greater than 10 °), to when the vehicle a completes the turning operation. The vehicle a completing the turn-around operation means that the vehicle a has the vehicle front direction toward the traveling direction of the target lane and the speed of the vehicle a is equal to or greater than a certain threshold value. The threshold value may be set for the resistance tolerance of the u-turn vehicle to the oncoming traffic according to local regulations and driving habits. For example, the threshold may be equal to 0, may be equal to 50% of the speed limit of the target lane, may be equal to 100% of the speed limit of the target lane, may be equal to 50% of the current speed of the oncoming vehicle B, and may be equal to 100% of the current speed of the oncoming vehicle B. Here, the current speed of the oncoming car B may be a speed detected by the detection unit 10 when the oncoming car B is detected.
Specifically, the calculation unit 20 may store in advance a function t ═ f (V) for the current driver of the vehicle a to calculate the time at which the vehicle a completes the current turning operation (i.e., the turning operation time) for the current driver of the vehicle aAW) in which VARefers to an initial speed of the vehicle a at the time of the current turning operation (i.e., a speed of the vehicle a at the start of the current turning operation, for example, a speed of the vehicle a when the steering angle becomes larger than a certain threshold value (e.g., the steering angle of the steering wheel is larger than 90 °, or the steering angle of the wheels is larger than 10 °), and W is a width of an available space for the vehicle a to perform the current turning operation. VAAnd W as a function t ═ f (V)AW) can be detected by the detection unit 10 as described above. And the function t ═ f (V)AW) is then set individually for the current driver. Specifically, the function t ═ f (V)AW) can be optimized by machine learning. For example, the calculation unit 20 may collect relevant data during the current driver's past turn before the current turn, and based on these data, pair the function t ═ f (V)AW) is optimized so that a function t ═ f (V) matching the current driver's driving behavior habits is obtainedA,W)。
In an exemplary embodiment, the computing unit 20 may collectAnd stores the identity information of each driver experienced by the vehicle a historically before the current turning operation, and sets a corresponding function t ═ f (V) for each driverAW). And, for each function t ═ f (V)AW), the calculation unit 20 collects relevant data during the corresponding driver's turn in the past before the current turn, and on the basis of these data, the respective function t ═ f (V) by machine learningAW) is optimized to obtain a function t ═ f (V) for each driver that matches the driving behavior habit of the driverAW). When the calculation unit 20 predicts the travel tracks of the vehicle a and the oncoming vehicle B, the function t ═ f (V) corresponding thereto may be acquired from the current driver identification information of the vehicle a acquired by the detection unit 10 (V)AW). Thus, the time length of the vehicle a completing the current turning operation, which is matched with the driving behavior habit of the current driver, can be calculated.
After the time length for which the vehicle a completes the current turning operation is obtained, the calculation unit 20 may predict the travel locus of the oncoming vehicle B within the time length. In one exemplary embodiment, the travel locus of the oncoming vehicle B during the current turning operation of the vehicle a can be predicted on the assumption that the oncoming vehicle B continues traveling at the current speed without decelerating.
Further, the calculation unit 20 may also predict the travel locus of the vehicle a during the current turning operation of the vehicle a. The running locus of the vehicle a can be predicted with the initial speed of the vehicle a when the current turning operation is performed and the preset maximum steering angle as initial conditions. Further, the traveling locus prediction of the vehicle a may also take into account the influence of the width W of the space available for the vehicle a to perform the current turning operation.
Based on the predicted travel locus of the vehicle a and the travel locus of the oncoming vehicle B, the calculation unit 20 can determine whether both coincide at a certain point in time within the length of time for which the vehicle a completes the current turn-around operation. If the overlap occurs, it means that the vehicle a performs a turning operation at this time and collides with the oncoming vehicle B. In this case, the output unit 30 of the system 100 issues a warning to the driver of the vehicle a. The output unit 30 may also automatically control the vehicle a to decelerate or stop the vehicle a. If no coincidence occurs, it means that it is safe for the vehicle a to perform a turning operation at this time. The output unit 30 may prompt the driver to perform a turning operation as soon as possible. The output unit 30 may warn or remind the driver in a visual or audible manner.
Thus, the driving assistance system 100 for vehicle according to the present invention can perform a danger warning when the vehicle a performs a turning operation, thereby preventing the vehicle from being dangerous. In addition, when the vehicle driving auxiliary system performs the danger early warning, the driving behavior habit of the current driver of the vehicle A is considered, so that the danger early warning is more accurate.
Further, in the above-described embodiment, the calculation unit 20 predicts the travel locus of the oncoming vehicle B in the case where the oncoming vehicle B continues traveling at the current speed without decelerating. In this case, only a case where the traveling of the oncoming vehicle B is not hindered at all, that is, a case where the oncoming vehicle B is not forced to decelerate, is regarded as a safe case where the turning operation of the vehicle a is permitted. In this case, the invention will give the most conservative warning and/or active intervention.
However, in some areas, driving habits may be tolerated for the turning vehicle to block the oncoming traffic. If the user is given warnings or brakes each time the vehicle is turned around with criteria that do not slow the oncoming vehicle, driving behavior that is not in line with the locality may result, resulting in a poor user experience. Therefore, in other embodiments, the calculation unit 20 may also predict the travel locus in the case where the oncoming vehicle B travels at the current speed but decelerates. Here, the deceleration of the oncoming vehicle B may be determined according to the category of the oncoming vehicle B. For example, the detection unit 10 may detect the kind of oncoming vehicle B, such as a bus, a four-door car, a truck, a van, or the like, and the calculation unit 20 obtains the deceleration of the oncoming vehicle B from the kind of oncoming vehicle B, for example, from the decelerations corresponding to the respective kinds of vehicles stored in advance, or calculates the deceleration of the oncoming vehicle B from a function stored in advance. For a bus, the deceleration of oncoming vehicle B may be 5m/s2For a four-door sedan, the deceleration of oncoming vehicle B may be 10m/s2. The deceleration of oncoming traffic may be set to slow the oncoming traffic, rather than hard braking. Thereby, the calculation unit 20 can obtain the travel locus during the current turning operation of the vehicle a in the case where the oncoming vehicle B travels at the current speed and slowly decelerates. Based on the predicted driving track of the oncoming vehicle B, the warning and active intervention of the present invention may be initiated only if it is determined that the vehicle a and the oncoming vehicle B, which decelerates slowly, will certainly collide. The vehicular drive assist system 100 may be provided with a switching device to facilitate the user to switch the use mode of the vehicular drive assist system 100 between the above two cases so that the system 100 adapts to the local driving habits.
Next, a driving assistance method for vehicle according to an embodiment of the invention will be described in detail. Fig. 3 shows a flow chart of a driving assistance method for vehicle according to an embodiment of the invention.
In step S1, it is detected whether the vehicle a is in the turnaround position. As described above, whether the vehicle a is in the turning position may be detected by the position information acquired by the GPS sensor, the surrounding environment information of the vehicle a photographed by the camera, the map information and the navigation path of the navigation device of the vehicle a, and the like. Step S1 may be periodically performed in real time during the travel of the vehicle a. For example, step S1 may begin in response to the start of vehicle a. When it is determined that the vehicle a is at the turnaround position, the process proceeds to step S2.
In step S2, it is detected whether there is an oncoming vehicle B within a predetermined range in an oncoming lane of the lane in which the vehicle a is present. In the case where it is detected that the oncoming vehicle B is present, the movement parameters of the position, speed, acceleration, and the like of the oncoming vehicle B are also acquired in step S2, and then the flow proceeds to step S3.
In step S3, the width W of the space available for the vehicle a to perform the current U-shaped operation and the initial speed V at the time of the turning operation of the vehicle a are detectedA(i.e., the speed at which the vehicle a starts to make a turn). As described above, the width W is determined based on the actual width of the oncoming lane of the lane in which the vehicle a is located and the obstacles such as parked vehicles and pedestrians that temporarily exist around the oncoming lane. Here, widthW may be detected at the detection of the initial velocity VAPreviously, and the initial velocity VAIt may be acquired when the steering angle of the vehicle a becomes larger than a certain threshold value (for example, the steering wheel steering angle is larger than 90 °, or the wheel steering angle is larger than 10 °). Thus, an accurate initial velocity V can be obtainedAThe value is obtained.
In step S4, a function for calculating the length of time for which the vehicle a completes the current turning operation is acquired for the current driver of the vehicle a, and the length of time is calculated. In the exemplary embodiment, the corresponding function is acquired from a plurality of functions for calculating the length of time for which the vehicle a completes the current turning operation for a plurality of drivers that have been experienced historically by the vehicle a, which are stored in advance, based on the identity information of the current driver. In particular, the parameters of each of the plurality of functions are optimized by machine learning based on data collected in a corresponding driver's past turn-around maneuver. The detection or input of the current driver' S identification information may be performed before step S4, for example, at the start of the vehicle a.
In step S5, based on the time length calculated in step S4, the travel trajectories of the vehicle a and the oncoming vehicle B within the time length are predicted. It may be assumed that the oncoming vehicle B travels at the current speed without decelerating to obtain the travel locus of the oncoming vehicle B during the current turning operation of the vehicle a. It is also possible to assume that the oncoming vehicle B travels at the current speed and gradually decelerates to obtain the travel locus of the oncoming vehicle B during the current turning operation of the vehicle a. Here, the current speed of the oncoming vehicle B is the speed of the oncoming vehicle B detected in step S2. The deceleration of the oncoming vehicle B may be determined according to the category of the oncoming vehicle B. The above two ways of predicting the travel locus of the oncoming vehicle B may enable the vehicle driving assistance method of the invention to provide two different safety levels. Therefore, it is possible to set a selection step at the time of starting the vehicle a or the vehicle driving assist system 100, facilitating the user to select an appropriate safety level as desired.
In step S5, the travel locus of the vehicle a is predicted under the initial conditions of the initial speed of the vehicle a at the time of the current turning operation and the preset maximum steering angle.
In step S6, it is predicted whether there is a risk of collision with the oncoming vehicle B during the turnaround of the vehicle a, based on the predicted travel trajectories of the vehicle a and the oncoming vehicle B. This is mainly achieved by judging whether or not the running trajectories of the vehicle a and the oncoming vehicle B coincide at a certain point in time within the time length for which the vehicle a completes the current turning operation. If so, the flow proceeds to step S7. In step S7, a warning is issued to the driver of the vehicle a. Further, the vehicle a may be automatically controlled to decelerate or stop. If not, the process proceeds to step S8, where the driver is prompted to perform a turn-around operation as soon as possible.
Therefore, according to the vehicle driving assistance method of the embodiment of the invention, the danger early warning can be performed when the vehicle A performs the turning operation, so that the vehicle is prevented from being dangerous. In addition, according to the vehicle driving auxiliary method, when the danger early warning is carried out, the driving behavior habit of the current driver of the vehicle A is considered, so that the danger early warning is more accurate.
The invention also provides a vehicle equipped with or adapted to apply the vehicle driving assistance system of the embodiment described above. The vehicular drive assist system is adapted to execute the vehicular drive assist method of the above-described embodiment.
While the invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the construction and methods of the embodiments described above. On the contrary, the invention is intended to cover various modifications and equivalent arrangements. In addition, while the various elements and method steps of the disclosed invention are shown in various example combinations and configurations, other combinations, including more, less or all of the elements or method steps, are also within the scope of the invention.

Claims (13)

1. A vehicle driving assist system that is mounted on or applied to a host vehicle to perform a hazard warning when the host vehicle performs a turning operation, the system comprising:
a detection unit configured to detect whether or not a host vehicle is in a turning position, and detect whether or not there is an oncoming vehicle in an oncoming lane of a lane in which the host vehicle is present; and
a calculation unit configured to predict whether there is a risk of collision with the oncoming vehicle during a current turn-around operation of the own vehicle, in a case where the own vehicle is at the turn-around position and the oncoming vehicle is present in the oncoming lane, wherein
The calculation unit is configured to make the prediction of the collision risk based on driving behavior habits of a current driver of the own vehicle.
2. The vehicular drive assist system according to claim 1, wherein
The calculation unit is configured to predict the traveling trajectories of the own vehicle and the oncoming vehicle within a time length of completion of a current turn-around operation of the own vehicle, which is obtained based on a driving behavior habit of a current driver of the own vehicle, and predict whether there is a risk of collision with the oncoming vehicle during the current turn-around operation of the own vehicle, based on the predicted traveling trajectories of both.
3. The vehicular drive assist system according to claim 2, wherein
The calculation unit is configured to store in advance a function for a current driver of the host vehicle for calculating a length of time for the host vehicle to complete a current turning operation, wherein parameters of the function are optimized by machine learning based on data collected in past turning operations of the current driver of the host vehicle.
4. The vehicular drive assist system according to claim 3, wherein
The variables of the function include the width of the available space for the vehicle to perform the current turning operation and the initial speed of the vehicle when performing the current turning operation.
5. The vehicular drive assist system according to claim 4, wherein
The width of the available space for the vehicle to perform the current turning operation is detected by the detection unit and is determined by the width of the opposite lane and the obstacles around the opposite lane.
6. The vehicular drive assist system according to claim 2, wherein
The calculation unit is configured to predict a travel locus of the oncoming vehicle based on a current speed of the oncoming vehicle.
7. The vehicular drive assist system according to claim 2, wherein
The calculation unit is configured to predict a travel locus of the oncoming vehicle based on a current speed and deceleration of the oncoming vehicle.
8. The vehicular drive assist system according to claim 7, wherein
The deceleration of the oncoming vehicle is determined according to the category of the oncoming vehicle.
9. The vehicular drive assist system according to claim 2, wherein
The calculation unit is configured to predict a running locus of the own vehicle based on an initial speed of the own vehicle at the time of the current turning operation and a preset maximum steering angle.
10. The vehicular drive assist system according to claim 3, wherein
The detection unit further includes an identification information acquisition element for acquiring identification information of a current driver of the own vehicle, and
the calculation unit is further configured to store in advance a plurality of functions for calculating a length of time for which the own vehicle completes a current turning operation, respectively, corresponding to each of a plurality of drivers experienced by the own vehicle history, wherein the plurality of drivers includes the current driver of the own vehicle, and parameters of each of the plurality of functions are optimized by machine learning based on data collected in past turning operations of the corresponding driver, wherein
The calculation unit is configured to acquire a corresponding function for calculating a length of time for which the own vehicle completes the current U-turn operation from the plurality of functions based on the acquired identity information of the current driver of the own vehicle.
11. The vehicular drive assist system according to claim 1, further comprising:
an output unit that issues a warning to a driver and/or automatically decelerates or stops the own vehicle in a case where the calculation unit predicts that there is a risk of collision with the oncoming vehicle during the current turning operation of the own vehicle.
12. A vehicle driving assist method for performing a hazard warning when a turn-around operation of a host vehicle is performed, the method comprising the steps of:
detecting whether the vehicle is in a turning position or not, and detecting whether an oncoming vehicle exists in an oncoming lane of a lane where the vehicle is located; and
predicting whether there is a risk of collision with the oncoming vehicle during a current turn-around operation of the host vehicle in a case where the host vehicle is at the turn-around position and the oncoming vehicle is present in the oncoming lane
Predicting the collision risk based on driving behavior habits of a current driver of the vehicle.
13. A vehicle mounted or adapted to apply the vehicle driving assistance system according to any one of claims 1 to 11.
CN201710642223.1A 2017-07-31 2017-07-31 Vehicle driving assistance system, vehicle driving assistance method, and vehicle Active CN109318894B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201710642223.1A CN109318894B (en) 2017-07-31 2017-07-31 Vehicle driving assistance system, vehicle driving assistance method, and vehicle

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201710642223.1A CN109318894B (en) 2017-07-31 2017-07-31 Vehicle driving assistance system, vehicle driving assistance method, and vehicle

Publications (2)

Publication Number Publication Date
CN109318894A CN109318894A (en) 2019-02-12
CN109318894B true CN109318894B (en) 2021-09-28

Family

ID=65245813

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201710642223.1A Active CN109318894B (en) 2017-07-31 2017-07-31 Vehicle driving assistance system, vehicle driving assistance method, and vehicle

Country Status (1)

Country Link
CN (1) CN109318894B (en)

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110789450B (en) * 2018-08-02 2021-10-26 长城汽车股份有限公司 Vehicle meeting danger alarm prompting method and system and vehicle
CN109828573B (en) * 2019-02-20 2022-09-20 百度在线网络技术（北京）有限公司 Unmanned vehicle control method, device and storage medium
CN110293955A (en) * 2019-06-26 2019-10-01 重庆长安汽车股份有限公司 A kind of U-shaped control system and the method for turning around automatically in automatic Pilot
CN112918472A (en) * 2019-12-05 2021-06-08 奥迪股份公司 Vehicle driving assistance system, vehicle using the same, and corresponding method and medium
CN113200042A (en) * 2020-02-03 2021-08-03 奥迪股份公司 Vehicle driving assistance system and method, and corresponding computer-readable storage medium
EP4137378B1 (en) * 2020-04-15 2023-12-27 Nissan Motor Co., Ltd. Travel assistance method and travel assistance device

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20130021992A (en) * 2011-08-24 2013-03-06 현대모비스 주식회사 U-turn assistance system and method of vehicle
CN103052865A (en) * 2010-09-17 2013-04-17 爱信艾达株式会社 Driving support device, driving support method, and computer program
US8610595B1 (en) * 2012-07-19 2013-12-17 Salmaan F. F. M. S. Aleteeby Vehicle U-turn safety alert system
CN104750753A (en) * 2013-12-31 2015-07-01 中国移动通信集团公司 Method and equipment for generating driving behavior reports
WO2016091306A1 (en) * 2014-12-10 2016-06-16 Here Global B.V. Apparatus and associated method for providing u-turn guidance
CN106184223A (en) * 2016-09-28 2016-12-07 北京新能源汽车股份有限公司 A kind of automatic Pilot control method, device and automobile
CN106364485A (en) * 2016-08-30 2017-02-01 戴姆勒股份公司 Operation method for communication equipment, communication equipment for vehicle and wearable equipment

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103052865A (en) * 2010-09-17 2013-04-17 爱信艾达株式会社 Driving support device, driving support method, and computer program
KR20130021992A (en) * 2011-08-24 2013-03-06 현대모비스 주식회사 U-turn assistance system and method of vehicle
US8610595B1 (en) * 2012-07-19 2013-12-17 Salmaan F. F. M. S. Aleteeby Vehicle U-turn safety alert system
CN104750753A (en) * 2013-12-31 2015-07-01 中国移动通信集团公司 Method and equipment for generating driving behavior reports
WO2016091306A1 (en) * 2014-12-10 2016-06-16 Here Global B.V. Apparatus and associated method for providing u-turn guidance
CN106364485A (en) * 2016-08-30 2017-02-01 戴姆勒股份公司 Operation method for communication equipment, communication equipment for vehicle and wearable equipment
CN106184223A (en) * 2016-09-28 2016-12-07 北京新能源汽车股份有限公司 A kind of automatic Pilot control method, device and automobile

Also Published As

Publication number Publication date
CN109318894A (en) 2019-02-12

Similar Documents

Publication Publication Date Title
CN109318894B (en) Vehicle driving assistance system, vehicle driving assistance method, and vehicle
US9963149B2 (en) Vehicle control device
EP3091370B1 (en) Method and arrangement for determining safe vehicle trajectories
CN112389466B (en) Method, device and equipment for automatically avoiding vehicle and storage medium
CN110001643B (en) Vehicle control device, vehicle control method, storage medium, and information acquisition device
CN109841088B (en) Vehicle driving assistance system and method
JP7107349B2 (en) System and method for adapting alarm activation timing
KR101999079B1 (en) Display device control method and display device
CN113365894B (en) Vehicle travel control method and travel control device
CN109383367B (en) Vehicle exterior notification device
JP7158352B2 (en) DRIVING ASSIST DEVICE, VEHICLE CONTROL METHOD, AND PROGRAM
JP2019160032A (en) Vehicle control device, vehicle control method, and program
US11348463B2 (en) Travel control device, travel control method, and storage medium storing program
GB2560244A (en) Vehicle lane changing
US11377150B2 (en) Vehicle control apparatus, vehicle, and control method
US20220118970A1 (en) Systems and methods for selectively modifying collision alert thresholds
CN112193246A (en) Vehicle and method for performing inter-vehicle distance control
CN111373457A (en) Vehicle control device, vehicle, and vehicle control method
CN114126940A (en) Electronic control device
WO2021187202A1 (en) Systems and methods for adapting activation of alerts according to curvature of a target path
JP7318692B2 (en) Systems and methods for adaptive rear-impact warning
CN113370972B (en) Travel control device, travel control method, and computer-readable storage medium storing program
CN111746534A (en) Vehicle driving assistance system, vehicle including the same, and corresponding method and medium
WO2022123278A1 (en) Travel assistance method and travel assistance device
JP2023032069A (en) Vehicle control device

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