CN110550105A - Driving assistance system and method - Google Patents

Abstract

The present invention provides a driving assistance system and method. The driving assistance system is installed or applied to the vehicle and includes: a blind spot judgment unit configured to judge whether there is a blind spot in the road ahead of the vehicle. The blind spot is caused by the presence of an obstruction a road area that cannot be detected by the sensor of the host vehicle; a virtual moving body setting unit configured to assume a virtual moving body in the blind spot if there is a blind spot, and to set a driving state of the virtual moving body; and a danger prediction unit , which is configured to determine whether the own vehicle will collide with the virtual moving body, so as to predict whether the own vehicle will collide with a vehicle driving out of the blind spot.

Description

Driving assistance system and method

technical field

The invention relates to the automotive field of vehicles. More particularly, the present invention relates to a driving assistance system and method for providing hazard warning and driving assistance in the event of a blind spot in the road ahead of the vehicle.

Background technique

In recent years, for vehicles such as automobiles, various driving assistance systems have been developed and applied, which detect the driving environment of the vehicle through sensor devices such as cameras, lasers, and/or radars, assist the driver in driving, and provide the driver with danger warnings.

However, in some cases, the vehicle's sensors cannot detect some road areas due to the presence of obstacles. As shown in Figure 1, due to the occlusion of the wall, the driver of vehicle A cannot see the traffic conditions behind the wall. Therefore, when vehicle A makes a right turn, it is likely to collide with cyclist B. In addition, due to the occlusion of the wall, the sensor of vehicle A cannot detect the road area behind the wall, and thus cannot provide danger warning.

Therefore, there is a need for a driving assistance system and method capable of providing danger warning even when the road ahead of the vehicle is in a road area that cannot be detected by the sensor due to an obstruction.

Contents of the invention

An object of the present invention is to provide a driving assistance system and method, which can provide danger warning and assist the driver to drive the vehicle to avoid accidents when there is a blind spot in the road ahead of the vehicle.

One aspect of the present invention provides a driving assistance system, which is installed or applied to the host vehicle and includes: a blind spot judgment unit configured to judge whether there is a blind spot in the road ahead of the host vehicle, the blind spot being blocked due to the presence of an obstruction a road area that cannot be detected by the sensor of the host vehicle; a virtual moving body setting unit configured to assume a virtual moving body in the blind area in the presence of the blind area, and set the driving of the virtual moving body state; and a risk prediction unit configured to determine whether the own vehicle will collide with the virtual moving body, so as to predict whether the own vehicle will collide with a vehicle driving out of the blind spot.

According to an embodiment of the present invention, wherein, the blind spot judging unit is configured to judge whether there is a blind spot based on pre-stored map information and sensor data of the sensor of the own vehicle and determine the starting point of the blind spot on the side of the own vehicle. start boundary.

According to an embodiment of the present invention, the virtual moving body is set to have the historical average traffic speed of the road section where the blind spot is located.

According to an embodiment of the present invention, the historical average traffic speed is the historical average traffic speed in the current time period of a day.

According to an embodiment of the present invention, wherein the virtual mobile body setting unit is configured to assume the virtual mobile body only when the historical average unit time traffic flow of the road section where the blind spot is located is greater than a predetermined threshold.

According to an embodiment of the present invention, the historical average traffic flow per unit time is the historical average traffic volume per unit time in the current time period of a day.

According to an embodiment of the present invention, wherein the virtual mobile body setting unit is configured to acquire the historical average traffic speed of the road section where the blind spot is located from an external device.

According to an embodiment of the present invention, wherein the virtual mobile body setting unit is configured to acquire the historical average unit time traffic volume of the road section where the blind spot is located from an external device.

According to an embodiment of the present invention, wherein the external device is configured to obtain its position, speed and direction of motion data and sensor data from several vehicles in the road network within a predetermined period of time in the past, the sensor data includes The data related to the position, speed and direction of movement of the traffic participants, and the external device is configured to calculate the historical average traffic speed and historical average traffic volume per unit time of the road section where the blind spot is located based on the acquired data.

According to an embodiment of the present invention, wherein, the risk prediction unit is configured to calculate the collision time between the own vehicle and the virtual moving body based on the driving state of the own vehicle and the driving state of the virtual moving body, and based on the collision time Determine the collision risk level.

According to an embodiment of the present invention, the driving assistance system further includes: a driving assistance unit configured to output a driving assistance instruction based on the determined collision risk level, the driving assistance instruction including at least one of the following items: Outputting a warning to a driver of the host vehicle; outputting a warning to the external environment of the host vehicle; decelerating, driving at a predetermined speed, or stopping the host vehicle; and steering the host vehicle.

According to another aspect of the present invention, there is also provided a vehicle on which the driving assistance system described in any embodiment is installed or applied.

According to another aspect of the present invention, there is also provided a driving assistance method, including the following steps: judging whether there is a blind spot in the road ahead of the vehicle, and the blind spot cannot be detected by the sensor of the vehicle due to the presence of an obstruction road area; assume a virtual mobile body in the blind area in the presence of the blind area, and set the driving state of the virtual mobile body; and judge whether the vehicle will collide with the virtual mobile body to predict Whether the vehicle will collide with a vehicle driving out of the blind spot.

According to an embodiment of the present invention, it is judged whether there is the blind area and the initial boundary of the blind area is determined based on the pre-stored map information and the sensor data of the sensor of the own vehicle.

According to an embodiment of the present invention, the driving state of the virtual mobile body is set to have the historical average traffic speed of the road section where the blind spot is located.

According to an embodiment of the present invention, the historical average traffic speed is the historical average traffic speed in the current time period of a day.

According to an embodiment of the present invention, the virtual moving body is assumed only when the historical average unit time traffic flow of the road section where the blind spot is located is greater than a predetermined value.

According to an embodiment of the present invention, the historical average traffic volume per unit time is the historical average traffic volume per unit time in the current time period of a day.

According to an embodiment of the present invention, the driving assistance method further includes: acquiring the historical average traffic speed of the road section where the blind spot is located from an external device.

According to an embodiment of the present invention, the driving assistance method further includes: acquiring, from an external device, the historical average traffic volume per unit time of the road section where the blind spot is located.

According to an embodiment of the present invention, wherein the external device is configured to obtain its position, speed and direction data and sensor data from several vehicles in the road network within a predetermined length of time in the past, the sensor data includes The data related to the position, speed and direction of the traffic participants, and the external device is configured to calculate the historical average traffic speed and the historical average traffic volume per unit time of the road section where the blind spot is located based on the acquired data.

According to an embodiment of the present invention, the driving assistance method further includes: calculating the collision time between the own vehicle and the virtual moving body based on the driving state of the own vehicle and the driving state of the virtual moving body, and calculating the collision time based on the collision time Determine the collision risk level.

According to an embodiment of the present invention, the driving assistance method further includes: outputting a driving assistance instruction based on the determined collision risk level, the driving assistance instruction including at least one of the following items: outputting to the driver of the host vehicle warning; outputting a warning to the external environment of the host vehicle; decelerating, running at a predetermined speed, or stopping the host vehicle; and turning the host vehicle.

Therefore, the driving assistance system and method according to the embodiments of the present invention can provide danger warning and assist the driver to drive the vehicle in the case of blind spots in the road ahead of the vehicle, so as to avoid accidents.

Description of drawings

In the following, the features, advantages and technical effects of exemplary embodiments of the present invention will be described with reference to the accompanying drawings, in which like reference numerals represent similar elements, wherein:

FIG. 1 shows an example of a scene where there is a blind spot in the road ahead of the vehicle.

FIG. 2 shows a structural block diagram of a driving assistance system according to an embodiment of the present invention.

Fig. 3 shows blind spots determined in the scene example shown in Fig. 1 and a hypothetical virtual moving body according to an embodiment of the present invention.

Fig. 4 shows a flowchart of a driving assistance method according to an embodiment of the present invention.

Detailed ways

Hereinafter, embodiments of the present invention are described with reference to the drawings. The following detailed description and accompanying drawings serve to illustrate the principles of the present invention. The present invention is not limited to the described preferred embodiments, but the scope of the present invention is defined by the claims.

A driving assistance system according to an embodiment of the present invention may be mounted on a vehicle or applied to a vehicle. The vehicle may be an internal combustion engine vehicle driven by an internal combustion engine, an electric vehicle or a fuel cell vehicle driven by an electric motor, a hybrid vehicle driven by both, or a vehicle having other drive sources. The driver assistance system can connect and communicate with the vehicle's control system and each other. For the sake of brevity, well-known power and handling devices, transmission systems, etc. components of the vehicle have not been described in detail.

FIG. 2 is a schematic diagram of a driving assistance system according to an embodiment of the present invention. The driving assistance system shown in FIG. 2 is installed or applied to the vehicle 1, and provides danger warning when there is a blind spot in the road ahead of the vehicle 1, and can also provide driving assistance to the vehicle 1 to avoid accidents. In this paper, the blind spot refers to the road area in the road ahead of the vehicle that cannot be detected by the sensor device on the vehicle due to the presence of obstructions. Of course, the blind spot is also invisible to the driver of the vehicle 1 . Here, the shelter can include objects on both sides of the road (such as walls and houses and other buildings, bushes, fences, mountains, etc.), and can also include objects on the road, such as temporary structures on the road, occlusion caused by the shape of the road itself, etc. .

As shown in FIG. 2 , the driving assistance system 100 includes a sensor device 10 , a storage device 20 , a communication device 30 , a computing device 40 and an output device 50 . These devices of the driving assistance system 100 can communicate with each other via a CAN bus or the like to transfer data and instructions to each other.

The sensor device 10 may include an internal sensor 11 and an external sensor 12 . The internal sensor 11 may be an internal sensor commonly installed on the vehicle 1 , including but not limited to a GNSS sensor, a speed sensor, an acceleration sensor, a steering angle sensor, and the like. The interior sensor 11 is used to detect the position, speed, acceleration, steering angle, traveling direction, etc. of the vehicle 1 . A combination of the position, speed, acceleration, traveling direction, etc. of the vehicle 1 can represent the traveling state of the vehicle 1 .

The external sensor 12 may be an external sensor normally installed on the vehicle 1 . The external sensor 12 may include an image sensor such as a camera, an ultrasonic sensor, a radar sensor and/or a laser sensor, and the like. The sensor data of the external sensor 12 can be used to detect the surrounding environment conditions of the vehicle 1, such as detecting the driving state (position, speed, acceleration, etc.) of other traffic participants (such as pedestrians, bicycles, motorcycles, other motor vehicles, etc.) around the vehicle 1. , driving direction, etc.), and the road conditions around the vehicle 1, especially the road ahead, such as the position and outline of lane lines, fences, curbs on the road, and objects on both sides of the road (such as buildings, bushes, fences, mountains, etc.) Wait.

The storage device 20 may be a common storage device such as a hard disk. According to an embodiment of the present invention, the storage device 20 is used to pre-store various map information such as road shapes, building positions and outlines, rivers, and railways.

The communication device 30 can be devices such as Bluetooth, antenna, etc., and the communication device 30 can be configured to communicate with external devices such as remote servers through wireless methods such as Bluetooth, Wi-Fi, and mobile networks, so as to obtain information from the external device or transmit information to the external device. information.

Computing device 40 may be a central processing unit (CPU) or an electronic control unit (ECU). The calculation device 40 can acquire data from the sensor device 10 , the storage device 20 , the communication device 30 , etc., and perform various processes to predict the potential collision risk of the vehicle 1 . According to some embodiments, the computing device 40 also distinguishes the level of potential collision risk, and may output driving assistance instructions according to the level of potential collision risk, so as to warn or assist the driving of the driver.

The output device 50 may include a display installed on the vehicle 1 , a speaker, and a power system, a transmission system, and a braking system of the vehicle 1 , so as to perform corresponding operations in response to driving assistance instructions.

According to a specific embodiment, the computing device 40 includes a blind spot determination unit 41 , a virtual moving object setting unit 42 , a danger prediction unit 43 and a driving assistance unit 44 .

The blind spot judging unit 41 is configured to judge whether there is a blind spot in the road ahead of the vehicle 1 . In an exemplary embodiment, the blind spot determination unit 41 performs the above determination based on the sensor data of the external sensor 12 of the vehicle 1 and the map information pre-stored in the storage device 20 . The blind spot determination unit 41 acquires pre-stored map information from the storage device 20, and determines the complete shape of the road ahead of the vehicle 1 based on the map information. In addition, the blind spot judgment unit 41 acquires its sensor data from the external sensor 12, and determines the road conditions around the vehicle 1, especially ahead, based on the sensor data, such as lane lines, fences, curbs on the road, and objects on both sides of the road. position and contour etc. By comparing the road conditions determined based on sensor data with the complete shape of the road ahead, the blind spot judgment unit 41 can judge whether there is an area in the road ahead of the vehicle 1 that cannot be detected by the external sensor 12 , ie, a blind spot.

When the blind spot judgment unit 41 judges that there is a blind spot on the road ahead of the vehicle 1 , the blind spot judgment unit 41 can further identify the range of the blind spot, for example, clarify the initial boundary of the blind spot on the vehicle 1 side. The dead zone judging unit 41 determines the start boundary of the blind zone based on the sensor data of the external sensor 12 . For example, the blind spot determination unit 41 can determine the farthest object detectable at various angles (for example, within the angle range of 120°-180° in front of the vehicle 1 ) at the front of the vehicle 1 based on the sensor data of the external sensor 12, and through these The connecting line of the farthest object determines the starting boundary of the dead zone.

The blind spot judgment by the blind spot judging unit 41 and the determination of the start boundary will be described with reference to FIG. 3 . FIG. 3 shows an example of the scene shown in FIG. 1 , where road L1 intersects road L2 to form an intersection C, and vehicle 1 is traveling on road L1 towards the intersection C. Walls W exist on both sides of the road L1 and the road L2. When the vehicle 1 is about to enter the intersection C, the blind spot determination unit 41 acquires the pre-stored map information from the storage device 20 and determines the complete shape of the road L1 and the road L2 near the intersection C, and acquires sensor data from the external sensor 12 and determines the vehicle 1 road conditions ahead. By comparing the state of the road ahead determined based on the sensor data with the complete shapes of road L1 and road L2, blind spot determination unit 41 may determine that blind spot B exists in road L2. At the same time, the dead zone judging unit 41 may determine the starting boundary B1 of the blind zone B based on the sensor data of the external sensor 12 . In an exemplary embodiment, the blind spot judgment unit 41 may be based on the positions of walls, lane lines on the road, curbs, signs on both sides of the road, etc. captured by the camera, and objects detected by ultrasonic sensors, laser sensors, etc. to determine the farthest object detectable at different angles in front of the vehicle 1. The starting boundary B1 of the blind area B is the connection line of the farthest object along each angle.

The virtual moving body setting unit 42 is configured to assume a virtual moving body in the blind area if there is a blind area, and set the driving state of the virtual moving body. The running state of the virtual moving body is represented by the position, speed and driving direction of the virtual moving body. In an exemplary embodiment, the virtual mobile body is assumed to be in a blind spot, and is traveling toward the vehicle 1 at the historical average traffic speed of the road section where the blind spot is located. In particular, it may be assumed that the virtual mobile body is currently located at the initial boundary of the blind zone.

In the scene example shown in FIG. 3 , the virtual mobile body setting unit 42 can assume that the rider 2 is located at the starting boundary B1 of the blind spot B at the current moment, and is using the road L2 on the current road segment L2. The historical average traffic speed V of -1 is traveling towards the intersection C.

According to an embodiment of the present invention, the virtual mobile body setting unit 42 acquires the historical average traffic speed of the road section where the blind spot is located from an external device. Specifically, the virtual mobile body setting unit 42 can communicate with external devices in a wireless manner through the communication device 30 to obtain the above-mentioned historical average traffic speed. Here, the external device may be a remote server. A remote server may be arranged to communicate with several vehicles within the road network and obtain from these vehicles their position, speed, direction etc. data and their sensor data. Here, the sensor data includes data related to the position, speed, acceleration, driving direction, etc. of other traffic participants (such as pedestrians, bicycles, motorcycles, other motor vehicles, etc.) around the corresponding vehicle. Thus, the remote server can use a statistical method to obtain the average traffic speed of each road in the road network or even each section of each road. Here, the road network may be the road network of all or part of the city or region where the vehicle 1 is located. A road section refers to any one of several sections obtained by dividing a certain road with a predetermined length (eg, 5m, 10m, etc.).

The remote server may have been communicating with and obtaining relevant data from a number of vehicles within the road network for a predetermined length of time in the past. Thereby, the historical average traffic flow speed in the past predetermined time length can be obtained. The predetermined length of time in the past may be, for example, past months, weeks, days, or hours from the current moment. Additionally, the remote server can calculate historical average traffic speeds for different time periods of the day (eg, 8:00 am to 8:30 am).

According to some embodiments, the remote server can also calculate the historical average traffic volume per unit time of each road or even each section of each road in the road network based on the data obtained from several vehicles. In particular, the remote server can also calculate the historical average vehicle flow per unit time during different time periods (for example, 8:00 am to 8:30 am) in a day.

Thus, the virtual mobile body setting unit 42 can also obtain the historical average unit time traffic volume of the road section where the blind spot is located from the remote server. According to some embodiments, the virtual mobile body setting unit 42 is configured to assume a virtual mobile body only when the historical average vehicle flow per unit time is greater than a predetermined threshold. In these embodiments, the historical average unit time traffic volume can be the historical average unit time traffic volume of the current time period (the current moment is 8:10 in the morning, the current time period can be, for example, 8:00 to 8:30 in the morning) in a day. flow.

The danger prediction unit 43 is configured to predict whether the vehicle 1 will collide with a vehicle coming out of the blind spot. The risk prediction unit 43 predicts the above-mentioned collision risk by judging whether the vehicle 1 will collide with the virtual moving body. Specifically, the risk prediction unit 43 can calculate the collision time TTC based on the driving state of the vehicle 1 and the virtual moving body, and judge whether the vehicle 1 will collide with The virtual moving body collides. According to an embodiment of the present invention, the driving state of the vehicle 1 is determined by the position, velocity, acceleration, motion direction, etc. detected by the internal sensor 11 , and the driving state of the virtual moving body is set by the virtual moving body setting unit 42 . When the time to collision TTC is less than the predetermined time threshold, the risk prediction unit 43 determines that the vehicle 1 will collide with the virtual moving object, and thus predicts that the vehicle 1 has a risk of colliding with a vehicle exiting the blind spot.

According to other embodiments, the risk prediction unit 43 may set multiple different time thresholds, and determine multiple collision risk levels according to the magnitude relationship between the collision time TTC and each of the multiple time thresholds. In an exemplary embodiment, four different time thresholds T1, T2, T3 and T4 may be set, where T1>T2>T3>T4. When T2<TTC<T1, the risk prediction unit 43 determines that the vehicle 1 is in the first level at which the collision risk is low. By analogy, when T3<TTC<T2, the risk prediction unit 43 determines that the vehicle 1 is at a second level with a higher collision risk than the first level; when T4<TTC<T3, the risk prediction unit 43 determines that the vehicle 1 is at a collision risk Higher third level; when TTC<T4, the risk prediction unit 43 determines that the vehicle 1 is in the fourth level with extremely high collision risk.

The driving assistance unit 44 is configured to output a driving assistance instruction based on the collision risk level determined by the danger prediction unit 43 . The driving assistance instruction may be output to the output device 50 . The output device 50 performs corresponding operations by executing the received driving assistance instruction, so as to issue a warning to the driver or assist the driver to drive the vehicle 1 . The driving assistance instruction may be one or more of the following: outputting a warning to the driver of the vehicle 1; outputting a warning to the external environment of the vehicle 1; causing the vehicle 1 to slow down, drive at a predetermined speed, or stop; and causing the vehicle 1 to turn.

The driving assistance unit 44 may output different driving assistance instructions or a combination thereof based on different collision risk levels. In an exemplary embodiment, when the collision risk level determined by the danger prediction unit 43 is the first level, the driving assistance unit 44 outputs a driving assistance instruction to output a warning to the driver of the vehicle 1, and the speaker or display of the vehicle 1 receives the instruction. Command and issue an audio or visual warning to the driver of the vehicle 1 .

When the collision risk level determined by the danger prediction unit 43 is the second level, the driving assistance unit 44 outputs a driving assistance instruction for outputting a warning to the external environment of the vehicle 1, and the horn or headlights of the vehicle 1 receive the instruction and sound the horn. Sound or flash the headlights to remind vehicles that may drive out of the blind spot, such as vehicles that are about to travel from the blind spot B to the intersection C on the road L2 shown in FIG. 3 .

When the collision risk level determined by the risk prediction unit 43 is the third level, the driving assistance unit 44 outputs a driving assistance command to decelerate the vehicle 1 and turn in the direction opposite to the virtual moving body (to avoid lateral movement), and the braking and braking of the vehicle 1 The steering system receives this instruction and controls the vehicle 1 to decelerate and turn. According to some embodiments, the deceleration value of the vehicle 1 , the deceleration target speed, the lateral avoidance distance, etc. are determined according to the time to collision TTC.

When the collision risk level determined by the risk prediction unit 43 is the fourth level, the collision time TTC is very small (for example, less than 1 s), and at this time, the vehicle 1 is very likely to collide with a vehicle driving out of the blind spot. In this case, the driving assistance unit 44 outputs a driving assistance instruction to stop the vehicle 1 or move the vehicle 1 at a very small speed (such as 3 m/s, etc.), the power system, transmission system and braking system of the vehicle 1, etc. This instruction is received, and the vehicle 1 is stopped or controlled to move at the target speed. Furthermore, according to some embodiments, the risk prediction unit 43 continuously calculates the collision time TTC between the vehicle 1 and the virtual moving body at predetermined time intervals, and determines the relationship between the collision time TTC and T4. When the time to collision TTC becomes greater than T4, a new collision risk level is determined. The driving assistance unit 44 outputs a new driving assistance instruction according to the new collision risk level, so that the vehicle 1 travels according to the new driving assistance instruction. Alternatively, when the vehicle 1 is moving at a very small speed, the blind spot judging unit 41 continuously monitors the change of the start boundary of the blind spot. Until when a large part of the blind spot becomes detectable, the vehicle 1 can resume normal driving.

Therefore, the driving assistance system according to the embodiment of the present invention can provide danger warning and assist the driving of the vehicle 1 to avoid accidents when there is a blind spot in the road ahead of the vehicle 1 .

Next, a driving assistance method according to an embodiment of the present invention will be described in detail. The driving assistance method according to the embodiment of the present invention can be realized by using the driving assistance system in any of the above embodiments. Fig. 4 shows a flowchart of a driving assistance method according to an embodiment of the present invention.

The driving assistance method according to the embodiment of the present invention can be manually activated by the driver. For example, when the driver sees an obstruction in the road ahead, he manually activates the driving assistance method according to the present invention through buttons installed on the vehicle 1 or keys on the touch screen. Furthermore, the driving assistance method can also be started automatically when the vehicle 1 starts to drive.

As shown in FIG. 4 , after the driving assistance method is started, in step S10 , it is determined whether there is a blind spot in the road ahead of the vehicle 1 . Specifically, pre-stored map information is acquired from the storage device 20, and the complete road shape of the road ahead of the vehicle 1 is determined based on the map information. At the same time, sensor data are acquired from external sensors 12 and based on the sensor data the road conditions around the vehicle 1 , in particular in front, are determined. By comparing the two, it can be determined whether there is a blind spot in the road ahead of the vehicle 1 . Furthermore, the starting boundary of the blind spot on the side of the vehicle 1 is determined on the basis of the determined road conditions around the vehicle 1 , in particular ahead.

When it is judged that there is a blind spot in the road ahead of the vehicle 1, the method proceeds to step S20, wherein a virtual moving body (for example, the cyclist 2 in FIG. 3 ) is assumed in the blind spot, and the driving state of the virtual moving body is set. Specifically, the driving state of the virtual mobile body is set to be located at the initial boundary of the blind spot at the current moment, and move toward the direction of the vehicle 1 at the historical average traffic speed of the road section where the blind spot is located. Taking the cyclist 2 in Figure 3 as an example, it can be assumed that the cyclist 2 is located at the starting boundary B1 of the blind spot B at the current moment, and is heading towards the intersection with the historical average traffic speed V of the section L2-1 of the road L2 where the blind spot B is located. C driving. In this step, the historical average traffic speed of the road section where the blind spot is located is obtained from an external device, such as a remote server. The historical average traffic speed may be the historical average traffic speed in a current time period of a day (for example, the current time is 8:10 am, and the current time period may be 8:00-8:30 am).

After step S20, the method proceeds to step S30. In step S30, it is predicted whether the vehicle 1 will collide with a vehicle driving out of the blind spot. Specifically, this step is implemented by judging whether the vehicle 1 will collide with the virtual moving body. More specifically, based on the running state of the vehicle 1 and the running state of the virtual moving body, the collision time TTC of both can be calculated. Then, it can be judged whether the vehicle 1 will collide with the virtual moving body by comparing the collision time TTC with a predetermined time threshold.

When the time to collision TTC is smaller than the predetermined time threshold, it is predicted that the vehicle 1 will collide with a vehicle coming out of the blind spot. In this case, the method proceeds to step S40 in which a collision risk level is determined. By setting multiple time thresholds, the collision risk level can be determined according to the magnitude relationship between the collision time TTC and each of the multiple time thresholds.

After step S40, the method proceeds to step S50. In step S50, a driving assistance command is output according to the determined collision risk level. According to different collision risk levels, the driving assistance instruction can be one or more of the following items: output a warning to the driver of the vehicle 1; output a warning to the external environment of the vehicle 1; slow down the vehicle 1 and drive at a predetermined speed or stop; and steer the vehicle 1 .

In step S60, the output device 50 receives the driving assistance instruction and executes related actions. For example, a speaker, a display, etc. of the vehicle 1 receive a driving assistance instruction to output a warning to the driver of the vehicle 1, and issue an audio or visual warning. The horn, headlights, etc. of the vehicle 1 may receive a driving assistance instruction to output a warning to the external environment of the vehicle 1, and whistle or flash to warn a vehicle that may exit from a blind spot. The transmission and braking system of the vehicle 1 can receive a driving assistance command to decelerate the vehicle 1, run at a predetermined speed or stop, and make the vehicle 1 slow down, run at a predetermined speed or stop. The steering system of the vehicle 1 can receive a driving assistance command to turn the vehicle 1, and turn the vehicle 1, for example, turn to the opposite direction of the virtual moving object to avoid laterally.

When it is predicted in step S30 that the vehicle 1 will not collide with a vehicle driving out of the blind spot (that is, the time to collision TTC is greater than the predetermined time threshold), the method directly enters step S50 to output a driving assistance instruction, which includes Outputting a warning to the driver of the vehicle 1 ; and/or outputting a warning to the environment outside the vehicle 1 .

Therefore, according to the driving assistance method of the embodiment of the present invention, it is possible to provide danger warning and assist the driving of the vehicle when there is a blind spot in the road ahead of the vehicle 1, so as to avoid accidents.

In the above embodiments, when it is determined that there is a blind spot in the road ahead of the vehicle 1 , the method assumes a virtual moving body in the blind spot and sets the state of the virtual moving body. However, according to other embodiments of the present invention, when it is determined that there is a blind spot in the road ahead of the vehicle 1 (step S10), the method proceeds to step S70. In step S70, it is judged whether the historical average traffic volume per unit time of the road section where the blind spot is located is greater than a predetermined threshold. When the historical average vehicle flow per unit time is greater than the predetermined threshold, the method enters step S20. When the historical average traffic flow per unit time is less than the predetermined threshold, it is considered that the risk of collision between the vehicle 1 and the vehicle exiting the blind spot is very low, and the method can directly enter step S50. In step S50 , a driving assistance instruction is output, the driving assistance instruction including outputting a warning to the driver of the vehicle 1 ; and/or outputting a warning to the external environment of the vehicle 1 .

While the invention has been described with reference to exemplary embodiments, it should be understood that the invention is not limited to the constructions and methods of the above-described embodiments. On the contrary, the invention is intended to cover various modification examples and equivalent arrangements. In addition, while the various elements and method steps of the disclosed invention are shown in various exemplary combinations and configurations, other combinations, including more, less, or method steps, are also within the scope of the invention .

Claims (23)

1. A driving assistance system installed or applied to this vehicle and comprising: A blind spot judging unit configured to judge whether there is a blind spot in the road ahead of the own vehicle, the blind spot being a road area that cannot be detected by the sensor of the own vehicle due to the presence of an obstruction; a virtual moving body setting unit configured to assume a virtual moving body in the blind area if the blind area exists, and set a driving state of the virtual moving body; and A risk prediction unit configured to determine whether the own vehicle will collide with the virtual moving body, so as to predict whether the own vehicle will collide with a vehicle driving out of the blind spot. 2. The driving assistance system according to claim 1, wherein: The blind spot judging unit is configured to judge whether there is the blind spot based on pre-stored map information and sensor data of the sensor of the own vehicle, and determine a starting boundary of the blind spot on the side of the own vehicle. 3. The driving assistance system according to claim 1 or 2, wherein: The virtual moving body is set to have the historical average traffic speed of the road section where the blind spot is located. 4. The driving assistance system according to claim 3, wherein: The historical average traffic speed is the historical average traffic speed in the current time period of a day. 5. The driving assistance system according to claim 1 or 2, wherein: The virtual moving object setting unit is configured to assume the virtual moving object only when the historical average unit time traffic flow of the road section where the blind spot is located is greater than a predetermined threshold. 6. The driving assistance system according to claim 5, wherein: The historical average traffic volume per unit time is the historical average traffic volume per unit time in the current time period of a day. 7. The driving assistance system according to claim 3, wherein: The virtual mobile body setting unit is configured to obtain the historical average traffic speed of the road section where the blind spot is located from an external device. 8. The driving assistance system according to claim 5, wherein: The virtual mobile body setting unit is configured to obtain, from an external device, the historical average traffic flow per unit time of the road section where the blind spot is located. 9. The driving assistance system according to claim 7 or 8, wherein: The external device is configured to obtain its position, speed and direction of motion data and sensor data from a number of vehicles within the road network within a predetermined time period in the past, the sensor data including the position, speed and direction of traffic participants around the corresponding vehicle. data about the direction of motion, and The external device is configured to calculate, based on the acquired data, the historical average traffic speed and the historical average traffic volume per unit time of the road section where the blind spot is located. 10. The driving assistance system according to claim 1 or 2, wherein: The risk prediction unit is configured to calculate a collision time of the host vehicle and the virtual moving body based on a running state of the own vehicle and a running state of the virtual moving body, and determine a collision risk level based on the collision time. 11. The driver assistance system according to claim 10, further comprising: a driving assistance unit configured to output a driving assistance instruction based on the determined collision risk level, the driving assistance instruction comprising at least one of the following: outputting a warning to the driver of the host vehicle; Outputting a warning to the external environment of the host vehicle; slow down, drive or stop the vehicle at a predetermined speed; and Steer the vehicle. 12. A vehicle on which the driving assistance system according to any one of claims 1-11 is installed or applied. 13. A driving assistance method, comprising the steps of: Judging whether there is a blind spot in the road ahead of the vehicle, the blind spot is a road area that cannot be detected by the sensor of the vehicle due to the presence of an obstruction; Assuming a virtual mobile body in the blind area in the presence of the blind area, and setting the driving state of the virtual mobile body; and Judging whether the own vehicle will collide with the virtual moving body, so as to predict whether the own vehicle will collide with a vehicle driving out of the blind spot. 14. The driving assistance method according to claim 13, wherein, Based on pre-stored map information and sensor data of the sensor of the vehicle, it is judged whether there is the blind area and the initial boundary of the blind area is determined. 15. The driving assistance method according to claim 13 or 14, wherein: The driving state of the virtual mobile body is set to have the historical average traffic speed of the road section where the blind spot is located. 16. The driving assistance method according to claim 15, wherein, The historical average traffic speed is the historical average traffic speed in the current time period of a day. 17. The driving assistance method according to claim 13 or 14, wherein, The virtual moving body is assumed only when the historical average vehicle flow per unit time of the road section where the blind spot is located is greater than a predetermined value. 18. The driving assistance method according to claim 17, wherein, The historical average traffic volume per unit time is the historical average traffic volume per unit time in the current time period of a day. 19. The driving assistance method according to claim 15, further comprising: The historical average traffic speed of the road section where the blind spot is located is acquired from an external device. 20. The driving assistance method according to claim 17, further comprising: The historical average unit time traffic volume of the road section where the blind spot is located is obtained from an external device. 21. The driving assistance method according to claim 19 or 20, wherein, The external device is configured to obtain its position, speed and direction data and sensor data from a number of vehicles within the road network within a predetermined length of time in the past, the sensor data including the position, speed and direction of traffic participants around the corresponding vehicles relevant data, and The external device is configured to calculate the historical average traffic flow speed and the historical average traffic flow per unit time of the road section where the blind spot is located based on the acquired data. 22. The driving assistance method according to claim 13 or 14, further comprising: A collision time between the own vehicle and the virtual moving body is calculated based on the running state of the own vehicle and the running state of the virtual moving body, and a collision risk level is determined based on the collision time. 23. The driving assistance method according to claim 22, further comprising: Outputting a driving assistance instruction based on the determined collision risk level, the driving assistance instruction including at least one of: outputting a warning to the driver of the host vehicle; Outputting a warning to the external environment of the host vehicle; slow down, drive or stop the vehicle at a predetermined speed; and Steer the vehicle.