Driving assistance system and lane change determining unit and method thereof

Technical field

The present application relates to the technical field of assisted driving, in particular to a driving assistance system and a lane change determining unit and lane change determining method thereof.

Background art

As the motor vehicle industry rapidly develops, the use of driving assistance systems, which represent advanced motor vehicle technology, is becoming ever more widespread in vehicles. A driving assistance system uses various sensors mounted on a vehicle to sense travelling states of a principal vehicle and vehicles in the vicinity in the course of motor vehicle travel, and subjects the sensed data to mathematical operations and analysis in order to obtain information which is of help to driving, thereby realizing assisted driving.

An assisted driving system has numerous functions, and is capable of realizing assisted driving in many respects. The provision of lane change information of a target vehicle to the principal vehicle is a beneficial function, enabling the principal vehicle to execute an appropriate driving strategy in response to a lane change situation of the target vehicle.

In the prior art, driving situation information relating to a lane change of a target vehicle, detected by a sensor of the principal vehicle, is generally used to determine a lane change situation of the target vehicle; these items of driving situation information relating to a lane change include for example a transverse vehicle speed of the target vehicle, a position of the target vehicle in relation to a lane line, and a direction indicator lamp situation of the target vehicle. However, if the lane change situation of the target vehicle is determined solely on the basis of these items of driving situation information relating to a lane change, the problem of erroneous determination of the actual lane change situation will often arise. For example, due to driver inexperience, the target vehicle often sways transversely, but there is no intention to change lane. As another example, the target vehicle is customarily driven close to the lane line, but there is no intention to change lane. As another example, a left direction indicator lamp is activated on the target vehicle due to an erroneous operation, but there is no intention to change lane. Furthermore, the solution in the prior art also has the problem that lane change behaviour of the target vehicle cannot be determined in a timely manner.

Thus, it is hoped that an improved technical solution can be provided to solve the abovementioned problems in the prior art.

Summary of the invention

In view of the abovementioned problems in the prior art, the present application provides a technical solution for determining a lane change intention of a target vehicle, the solution being capable of providing lane change situation information with better accuracy and timeliness to a principal vehicle.

To this end, according to one aspect of the present application, a lane change determining unit for use in a driving assistance system is provided, and comprises: an acquisition module, configured to acquire information containing travelling states of a principal vehicle and a vehicle in the vicinity thereof; a processing module, configured to determine a lane traffic efficiency of each lane on the basis of the information acquired by the acquisition module, the processing module assessing a driving mood of a target vehicle on the basis of the acquired travelling states, and the processing module being further configured to determine a first lane change probability value of the target vehicle on the basis of the lane traffic efficiency and the driving mood of the target vehicle; and a generating module, configured to generate a lane change intention signal indicating a lane change intention of the target vehicle on the basis of the first lane change probability value, to assist the driving of the principal vehicle.

According to a feasible embodiment of the present application, the processing module determines the lane traffic efficiency of each lane on the basis of the number of vehicles passing through each lane per unit time and/or the average speed-per-hour of a vehicle flow in each lane; and the processing module calculates the number of vehicles passing through each lane per unit time and/or the average speed-per-hour of the vehicle flow in each lane on the basis of the information acquired by the acquisition module; or the processing module determines the number of vehicles passing through each lane per unit time and/or the average speed-per-hour of the vehicle flow in each lane on the basis of information acquired by the acquisition module from a cloud server.

According to a feasible embodiment of the present application, the processing module assesses the driving mood of the target vehicle in the following way: a transverse speed variance and a longitudinal speed variance of the target vehicle are calculated on the basis of the acquired travelling states; and the greater a transverse speed fluctuation characterized by the transverse speed variance of the target vehicle and the greater a longitudinal speed fluctuation characterized by the longitudinal speed variance, the more radical the driving mood of the target vehicle is assessed to be.

According to a feasible embodiment of the present application, the processing module assesses the driving mood of the target vehicle in the following way: an acceleration of the target vehicle is calculated on the basis of the acquired travelling states; and the more unstable the speed of the target vehicle is indicated to be by the acceleration thereof, the more radical the driving mood of the target vehicle is assessed to be.

According to a feasible embodiment of the present application, the processing module assesses the driving mood of the target vehicle in the following way: a following distance of the target vehicle is calculated on the basis of the acquired travelling states; a following distance variance is calculated on the basis of the following distance of the target vehicle within a period of time, and the greater a following distance fluctuation indicated by the following distance variance, the more radical the driving mood of the target vehicle is assessed to be; and/or a following distance minimum value is determined on the basis of the following distance of the target vehicle within a period of time, and the smaller the following distance minimum value, the more radical the driving mood of the target vehicle is assessed to be.

According to a feasible embodiment of the present application, the acquisition module is configured to acquire a lane change frequency of the target vehicle per unit time; and the processing module assesses the driving mood of the target vehicle in the following way: the more often that lane changes occur as indicated by the acquired lane change frequency of the target vehicle, the more radical the driving mood of the target vehicle is assessed to be.

According to a feasible embodiment of the present application, the processing module is configured to: determine the first lane change probability value as indicating that the target vehicle has a lane change intention, when a traffic efficiency of a current lane of the target vehicle is lower than a traffic efficiency of a lane to which it might change and the driving mood of the target vehicle is confirmed as being radical; wherein the traffic efficiency of the current lane of the target vehicle being lower than the traffic efficiency of the lane to which it might change means that: a vehicle speed offered to the target vehicle by the current lane thereof and calculated on the basis of the lane traffic efficiency is lower than a vehicle speed offered to the target vehicle by a lane to which it might change and calculated on the basis of the lane traffic efficiency.

According to a feasible embodiment of the present application, when the target vehicle is travelling in an adjacent lane, a vehicle having a vehicle speed less than or equal to that of the target vehicle is or will be in front of the target vehicle, a principal lane is able to offer to the target vehicle a travelling speed greater than a current vehicle speed thereof, and the driving mood of the target vehicle is determined as being radical, the lane change determining unit determines the lane change intention signal as indicating that the target vehicle has a lane change intention to cut into the principal lane from the adjacent lane.

According to a feasible embodiment of the present application, when the target vehicle is travelling in a principal lane, a vehicle having a vehicle speed less than or equal to that of the target vehicle is in front of the target vehicle, an adjacent lane is able to offer to the target vehicle a travelling speed greater than a current vehicle speed thereof, and the driving mood of the target vehicle is determined as being radical, the lane change determining unit determines the lane change intention signal as indicating that the target vehicle has a lane change intention to cut out of the principal lane to the adjacent lane.

According to a feasible embodiment of the present application, the acquisition module is configured to acquire a transverse speed of the target vehicle, position information in relation to a lane line, and direction indicator lamp information; the processing module is configured to calculate a second lane change probability value of the target vehicle on the basis of the acquired transverse speed of the target vehicle, position information in relation to the lane line, and direction indicator lamp information, and adjust the first lane change probability value on the basis of the second lane change probability value; the generating module is configured to generate the lane change intention signal indicating the lane change intention of the target vehicle on the basis of the adjusted first lane change probability value.

According to a feasible embodiment of the present application, the step of the processing module adjusting the first lane change probability value on the basis of the second lane change probability value comprises: increasing the first lane change probability value when the lane change intention indicated by the second lane change probability value is the same as the lane change intention indicated by the first lane change probability value; decreasing the first lane change probability value when the lane change intention indicated by the second lane change probability value is not the same as the lane change intention indicated by the first lane change probability value.

According to a feasible embodiment of the present application, the lane change determining unit transmits the lane change intention signal to a target selection unit of an ACC system of the principal vehicle, so that the ACC system re selects a tracking object for the principal vehicle in response to the lane change intention signal.

According to another aspect of the present application, a lane change determining method for a driving assistance system is provided, optionally implemented by means of the lane change determining unit described above, the method comprising: acquiring information containing travelling states of a principal vehicle and a vehicle in the vicinity thereof; determining a lane traffic efficiency of each lane on the basis of the acquired information; calculating a driving mood of a target vehicle on the basis of the acquired travelling states; determining a first lane change probability value of the target vehicle on the basis of the lane traffic efficiency and the driving mood of the target vehicle; and generating a lane change intention signal indicating a lane change intention of the target vehicle on the basis of the first lane change probability value, to assist the driving of the principal vehicle.

According to another aspect of the present application, a driving assistance system is provided, comprising: a measuring apparatus, for measuring information containing travelling states of a principal vehicle and a vehicle in the vicinity thereof; a decision making apparatus, connected to the measuring apparatus and comprising the lane change determining unit according to any one of Claims 1 - 12, the decision making apparatus being configured to provide decision making information for assisted driving to the principal vehicle by means of the lane change determining unit.

According to a feasible embodiment of the present application, the driving assistance system is configured to exchange information with a vehicle in the vicinity via the Internet of Vehicles; and/or the driving assistance system is configured to exchange information with a cloud server by wireless communication.

According to the technical solution of the present application, more accurate target vehicle lane change situation information can be provided to the principal vehicle, so as to assist the principal vehicle in determining an appropriate driving strategy. Moreover, according to the technical solution of the present application, target vehicle lane change situation information can be predicted more quickly, so as to enable the ACC system of the principal vehicle to switch the tracking target in response to the information in a more timely manner, thereby avoiding uncomfortable travelling caused by the ACC system selecting the wrong tracking object.

Brief description of the drawings

The features, characteristics, advantages and benefits of the present invention will become obvious through the following detailed description in conjunction with the drawings.

Fig. 1 shows a schematic block diagram of a driving assistance system according to a feasible embodiment of the present application.

Fig. 2 shows a schematic block diagram of a lane change determining unit of the driving assistance system in fig. 1.

Figs. 3A - 3C show some embodiments of a target vehicle cutting into a principal lane from an adjacent lane.

Figs. 4A - 4C show some embodiments of a target vehicle cutting out of a principal lane to an adjacent lane.

Fig. 5 shows a flow chart of a lane change determining method for a driving assistance system according to a feasible embodiment of the present application.

Particular embodiments

Some feasible embodiments of the present application are described below in conjunction with the drawings.

The present application relates generally to an assisted driving technology, used for providing lane change situation information of a target vehicle to a principal vehicle.

Fig. 1 shows schematically a driving assistance system 100 according to a feasible embodiment of the present application. The driving assistance system 100 is disposed on a vehicle, and comprises a measuring apparatus 110 and a decision making apparatus 120.

In this embodiment, the measuring apparatus 110 is used for measuring travelling states of the principal vehicle and vehicles in the vicinity. The measuring apparatus 110 may comprise a radar device 130 and a camera device 140. The radar device 130 is used for detecting positions and travelling speeds (including longitudinal speeds and transverse speeds) of vehicles in the vicinity. The camera device 140 is used for capturing vehicle travelling state information and lane traffic flow information. For example, the camera device 140 captures an image containing position information of a target vehicle in relation to a lane line and direction indicator lamp information of the target vehicle. The measuring apparatus 110 may also comprise a sensor of the principal vehicle, for measuring the travelling state of the principal vehicle.

In this embodiment, the decision making apparatus 120 is in communicative connection with the measuring apparatus 110 via a bus, in order to perform information exchange therebetween. The decision making apparatus 120 is used for providing, to the principal vehicle, decision making information which is of help to assisted driving. The decision making apparatus 120 comprises a lane change determining unit 150 and a tracking target selection unit 160.

The lane change determining unit 150 is used for determining, on the basis of information measured by the measuring apparatus 110, lane change situation information of the target vehicle, which is used to indicate a lane change intention of the target vehicle.

The tracking target selection unit 160 is connected to the lane change determining unit 150, and is used for selecting a tracking object for the principal vehicle, in order to control a vehicle speed of the principal vehicle. The tracking target selection unit 160 is for example determined by a perception system of the principal vehicle. The tracking target selection unit 160 is for example a target selection unit, used to determine a tracking target for the principal vehicle, of an adaptive cruise control (ACC) system of the principal vehicle. The tracking target selection unit 160 switches the tracking object for the principal vehicle, in response to lane change situation information of the target vehicle received from the lane change determining unit 150. For example, when the lane change situation information indicates that the target vehicle will cut into a principal lane or cut into the principal lane from a current lane thereof, the ACC system can switch the tracking object for the principal vehicle in a timely manner on the basis of the information.

It should be understood that the driving assistance system 100 according to the present application can exchange information with vehicles in the vicinity via the Internet of Vehicles; that is to say, the driving assistance system 100 of the principal vehicle can acquire data information measured by other vehicles via the Internet of Vehicles, for use in lane change determination. The driving assistance system 100 according to the present application can communicate with a cloud server wirelessly; that is to say, the driving assistance system 100 of the principal vehicle can acquire data information from the cloud server via a communication interface of the principal vehicle, for use in lane change determination.

As can be seen, the technical solution according to the present application can quickly and accurately determine lane change situation information of the target vehicle for the principal vehicle. Moreover, the ACC system of the principal vehicle can re-select the tracking object for the principal vehicle in a timely manner on the basis of the lane change situation information, thereby avoiding an uncomfortable travelling experience caused by the ACC system incorrectly selecting the tracking target as a result of not having obtained lane change information in a timely manner.

Fig. 2 shows schematically the lane change determining unit 150 in fig. 1 according to a feasible embodiment of the present application; the lane change determining unit comprises an acquisition module 151, a processing module 152 and a generating module 153. These modules of the lane change determining unit 150, and operating processes thereof, are described below.

The acquisition module 151 is used for acquiring information containing driving states of the principal vehicle and vehicles in the vicinity, to be provided to the processing module 152 to undergo analytical computation. The acquisition module 151 may acquire information from the measuring apparatus 110 of the principal vehicle. For example, the acquisition module 151 acquires positions and vehicle speeds (including transverse vehicle speeds and longitudinal vehicle speeds) of vehicles in the vicinity from the radar device 130. The acquisition module 151 acquires an image, containing driving state information of the principal vehicle and vehicles in the vicinity and lane traffic flow information, from the camera device 140. The acquisition module 151 may also acquire these items of information from vehicles in the vicinity via the Internet of Vehicles. For example, the acquisition module 151 of the principal vehicle acquires, via the Internet of Vehicles, information measured by a measuring apparatus of a vehicle in the vicinity. The acquisition module 151 may also acquire these items of information from a cloud server by wireless communication.

The processing module 152 is in communicative connection with the acquisition module 151, and used for subjecting data information acquired by the acquisition module 151 to analytical processing, in order to obtain a traffic efficiency of each lane and a driving mood of the target vehicle, and thereby determine the lane change intention of the target vehicle.

In some embodiments, the processing module 152 may calculate the traffic efficiency of each lane on the basis of the number of vehicles passing through each lane per unit time. The processing module 152 may also calculate the traffic efficiency of each lane on the basis of the average speed-per-hour of a vehicle flow in each lane. The processing module 152 may also calculate the traffic efficiency of each lane on the basis of two parameters, specifically the number of vehicles in each lane and the average speed-per-hour of the vehicle flow in each lane. For example, the processing module 152 uses a mathematical model to perform data fusion, and thereby calculates the traffic efficiency of each lane.

In some embodiments, the processing module 152 determines two parameters, specifically the number of vehicles in each lane and the average speed-per-hour of the vehicle flow in each lane, on the basis of data information acquired from the cloud server by the acquisition module 151; for example, the processing module 152 seeks out the two parameters from information acquired by the cloud server, and does not need to perform calculation.

The processing module 152 determines the driving mood of the target vehicle on the basis of information acquired by the acquisition module 151. In the present application, the driving mood may be understood to be the degree of radicalness in the manner of driving of the driver of the vehicle. For example, a radical driving mood indicates that the driver of the vehicle always wants to reach a destination quickly by constantly seeking and switching to a lane having higher traffic efficiency. A gentle (non-radical) driving mood indicates that the driver of the vehicle can accept relatively stable travel in the current lane to reach a destination slowly. In other words, the more agitated the driving mood of the target vehicle, the stronger the lane change intention of the target vehicle.

In some embodiments, the processing module 152 may calculate a speed variance of the target vehicle on the basis of acquired speed information of a vehicle in the vicinity, and assess the driving mood of the target vehicle on the basis of the speed variance of the target vehicle. For example, the processing module 152 may calculate a transverse speed variance and a longitudinal speed variance of the target vehicle on the basis of acquired speed information. The transverse speed variance characterizes transverse speed fluctuation of the vehicle; the longitudinal speed variance of the vehicle characterizes longitudinal speed fluctuation of the vehicle. The greater the transverse fluctuation characterized by the transverse speed variance of the target vehicle, and the greater the longitudinal fluctuation characterized by the longitudinal speed variance of the target vehicle, the more radical the driving mood of the target vehicle is assessed to be by the processing module 152.

In some embodiments, the processing module 152 may calculate an acceleration of the target vehicle on the basis of acquired speed information, and assess the driving mood of the target vehicle according to the acceleration of the target vehicle. The acceleration of the vehicle can characterize whether the vehicle speed is stable. For example, the more unstable (e.g. sometimes accelerating and sometimes decelerating) the vehicle speed of the target vehicle is indicated to be by the acceleration of the target vehicle, the more radical the driving mood of the target vehicle is assessed to be by the processing module 152.

In some embodiments, the processing module 152 may calculate a following distance of the target vehicle on the basis of acquired position information, and assess the driving mood of the target vehicle according to the following distance of the target vehicle. For example, the processing module 152 may calculate the variance of following distance on the basis of the following distance of the target vehicle within a period of time. The variance of following distance characterizes fluctuation of following distance. The greater the following distance fluctuation characterized by the following distance variance of the target vehicle, the more radical the driving mood of the target vehicle is assessed to be by the processing module 152. The processing module 152 may also determine a minimum following distance on the basis of the following distance of the target vehicle within a period of time, and assess the driving mood of the target vehicle on the basis of the minimum following distance. The smaller the minimum following distance of the target vehicle within a period of time, the more radical the driving mood of the target vehicle is assessed to be by the processing module 152. The processing module 152 may also determine the driving mood of the target vehicle on the basis of two parameters, specifically the following distance variance and the minimum following distance; for example, the processing module 152 uses a mathematical model to perform data fusion, and thereby calculates the driving mood of the target vehicle.

In some embodiments, the processing module 152 may assess the driving mood of the target vehicle according to a lane change frequency of the target vehicle per unit time. The lane change frequency of the target vehicle may be measured by means of a sensor of the principal vehicle, or may be captured by means of a camera device above a transportation road and transmitted to an assisted driving system of the principal vehicle, or may be obtained from the cloud server. The more often the target vehicle changes lane as characterized by the lane change frequency of the target vehicle per unit time, the more radical the driving mood of the target vehicle is assessed to be by the processing module 152.

In some embodiments, the processing module 152 may determine the driving mood of the target vehicle on the basis of one or more of the speed variance, acceleration, following distance and lane change frequency of the target vehicle as described above; for example, the processing module 152 uses a mathematical model to perform data fusion, and thereby calculates the driving mood of the target vehicle.

It should be understood that the processing module 152 may use a degree- indicative value to indicate the driving mood of the target vehicle; the value is for example a probability value or scoring value. That is to say, in the abovementioned implementation, the processing module 152 assesses (determines) the driving mood of the target vehicle to be a degree-indicative value.

It should be understood that only some embodiments of the determination of the driving mood of the target vehicle are described above; the driving mood of the target vehicle could also be assessed in other ways, with no restriction to those set out here.

When the lane traffic efficiency and the target vehicle driving mood have been determined, the lane change determining unit 150 determines a lane change probability value of the target vehicle on the basis of the lane traffic efficiency and the target vehicle driving mood, to characterize the lane change intention of the target vehicle.

Based on the lane traffic efficiency, a vehicle speed which the lane is able to offer to a vehicle travelling thereon can be determined. For example, if a vehicle speed offered to the target vehicle by the current lane thereof and calculated on the basis of the lane traffic efficiency is lower than a vehicle speed offered to the target vehicle by a lane to which it might change and calculated on the basis of the lane traffic efficiency, then it is determined that the traffic efficiency of the current lane of the target vehicle is lower than the traffic efficiency of the lane to which it might change. When the traffic efficiency of the lane in which the target vehicle is located is lower than the traffic efficiency of the lane to which it might change, and the driving mood of the target vehicle is confirmed as being radical, a first lane change probability value is determined to indicate that the target vehicle has a strong lane change intention.

In one case, the target vehicle is travelling in an adjacent lane adjoining the principal lane, and a vehicle having a vehicle speed less than or equal to that of the target vehicle is or will be in front of the target vehicle (e.g. will cut into the lane); the principal lane is able to offer to the target vehicle a travelling speed that is greater than the current vehicle speed thereof, and if the driving mood of the target vehicle is determined as being radical, the lane change determining unit 150 generates a lane change intention signal indicating that the target vehicle has a strong lane change intention to cut into the principal lane from the adjacent lane. Some practical instances in which the target vehicle might cut into the principal lane are set out below in conjunction with the drawings.

Figs. 3A - 3C show practical instances of the target vehicle cutting into the principal lane, taking two lanes as an example (a principal lane LI and an adjacent lane L2, with a target vehicle 31 travelling on the adjacent lane L2).

As shown in fig. 3A, the target vehicle 31 is travelling in the adjacent lane L2, with a vehicle speed of 90 km/h. A vehicle 32, with a vehicle speed of 80 km/h which is lower than that of the target vehicle, is in the adjacent lane in front of the target vehicle 31. A principal vehicle 30 has a vehicle speed of 80 km/h in the principal lane LI. At this time, if the driving mood of the target vehicle 31 is determined as being radical, the target vehicle 31 is highly likely to cut into the principal lane LI from the adjacent lane L2, i.e. the target vehicle 31 has a strong lane change intention to cut into the principal lane LI.

As shown in fig. 3B, the target vehicle 31 is travelling in the adjacent lane L2, with a vehicle speed of 70 km/h. A vehicle 33 with a vehicle speed of 60 km/h in the principal lane is about to cut into the adjacent lane from the principal lane, i.e. the vehicle 33 with a lower vehicle speed than the target vehicle is about to cut into a frontward region of the lane in which the target vehicle is travelling, and this will force the target vehicle to decelerate. The vehicle speed of the principal vehicle in the principal lane is 70 km/h. At this time, if the driving mood of the target vehicle is determined as being radical, the target vehicle 31 is highly likely to cut into the principal lane LI from the adjacent lane L2, i.e. the target vehicle 31 has a strong lane change intention to cut into the principal lane LI.

As shown in fig. 3C, the target vehicle 31 is travelling in the adjacent lane L2, with a vehicle speed of 65 km/h. A vehicle 34, with a vehicle speed of 60 km/h which is lower than that of the target vehicle, is in the adjacent lane in front of the target vehicle 31. The principal vehicle has a vehicle speed of 60 km/h in the principal lane. A vehicle 35, with a vehicle speed greater than that of the target vehicle, is in the principal lane in a position in front of and to one side of the target vehicle. That is to say, even if the target vehicle 31 cuts into the principal lane LI and a vehicle is travelling in front of the target vehicle after the target vehicle cuts in, the principal lane will be able to offer a vehicle speed greater than the current vehicle speed thereof. At this time, if the driving mood of the target vehicle 31 is determined as being radical, the target vehicle 31 is highly likely to cut into the principal lane LI from the adjacent lane L2, i.e. the target vehicle 31 will have a strong lane change intention to cut into the principal lane. In another case, the target vehicle is travelling in the principal lane, and a vehicle having a vehicle speed less than or equal to that of the target vehicle is in front of the target vehicle; an adjacent lane is able to offer to the target vehicle a travelling speed that is greater than the current vehicle speed thereof, and if the driving mood of the target vehicle is determined as being radical, the lane change determining unit 150 generates a lane change intention signal indicating that the target vehicle has a strong lane change intention to cut out of the principal lane to the adjacent lane. Some practical instances in which the target vehicle might cut out of the principal lane are set out below in conjunction with the drawings.

Figs. 4A and 4B show two lanes, i.e. the principal lane LI and adjacent lane L2. Fig. 4C shows three lanes, i.e. the principal lane LI and adjacent lanes L2 and L3. The target vehicle 31 is travelling on the principal lane LI.

As shown in fig. 4A, the target vehicle 31 is travelling in the principal lane LI, with a vehicle speed of 70 km/h. A vehicle 36, with a vehicle speed of 70 km/h which is equal to that of the target vehicle, is in the principal lane in front of the target vehicle 31. The principal vehicle has a vehicle speed of 70 km/h in the principal lane. A vehicle 37 with a vehicle speed of 60 km/h (lower than that of the target vehicle) is in the adjacent lane L2, behind and to one side of the target vehicle. That is to say, if the target vehicle cuts into the adjacent lane L2, it will be able to travel at a speed higher than the current vehicle speed. At this time, if the driving mood of the target vehicle 31 is determined as being radical, the target vehicle 31 is highly likely to cut out of the principal lane to the adjacent lane, i.e. the target vehicle 31 has a strong lane change intention to cut out of the principal lane.

As shown in fig. 4B, the target vehicle 31 is travelling in the principal lane

LI, with a vehicle speed of 65 km/h. A vehicle 38, with a vehicle speed of 60 km/h which is lower than that of the target vehicle 31, is in the principal lane in front of the target vehicle 31. The principal vehicle 30 has a vehicle speed of 60 km/h in the principal lane. A vehicle 39 with a vehicle speed of 60 km/h - 80 km/h is in the adjacent lane L2, in front of and to one side of the target vehicle 31. That is to say, if the target vehicle 31 cuts into the adjacent lane L2, it will be able to travel at a speed higher than the current vehicle speed. At this time, if the driving mood of the target vehicle 31 is determined as being radical, the target vehicle 31 is highly likely to cut out of the principal lane to the adjacent lane, i.e. the target vehicle 31 has a strong lane change intention to cut out of the principal lane.

As shown in fig. 4C, the target vehicle 31 is travelling in the principal lane

LI, with a vehicle speed of 65 km/h. A vehicle 40, with a vehicle speed of 65 km/h which is equal to that of the target vehicle, is in the principal lane in front of the target vehicle 31. The principal vehicle has a vehicle speed of 60 km/h in the principal lane LI. A vehicle 41 with a vehicle speed of 60 km/h is in the adjacent lane L2, in front of and to one side of the target vehicle 31, and the vehicle 41 is about to cut out of the current lane L2 thereof to lane L3 which adjoins the current lane thereof. That is to say, if the target vehicle 31 cuts into the adjacent lane L2, it will be able to travel at a speed higher than the current vehicle speed. At this time, if the driving mood of the target vehicle 31 is determined as being radical, the target vehicle 31 is highly likely to cut out of the principal lane to the adjacent lane, i.e. the target vehicle 31 has a strong lane change intention to cut out of the principal lane.

According to another manner of implementation of this manner of implementation, the lane change determining unit 150 determines the lane change intention of the target vehicle on the basis of a greater amount of information, and thereby provides a more accurate target vehicle lane change intention signal.

In this manner of implementation, the acquisition module 151 acquires the transverse speed of the target vehicle, position information in relation to a lane line, and direction indicator lamp information. The processing module 152 calculates a second lane change probability value of the target vehicle on the basis of these items of acquired information, and combines this with the first lane change probability value determined in the manner described above to determine the lane change intention of the target vehicle. For example, if the lane change intentions characterized by the calculated second lane change probability value and first lane change probability value are the same, the first lane change probability value is adjusted to a larger value than that determined previously. Conversely, if the lane change intentions characterized by the calculated second lane change probability value and first lane change probability value are not the same, the first lane change probability value is adjusted to a smaller value than that determined previously.

The generating module 153 generates a lane change intention signal indicating the lane change intention of the target vehicle on the basis of the first lane change probability value; the lane change intention signal for example comprises a lane change probability value and a lane change direction.

In some embodiments, the lane change determining unit 150 transmits the generated lane change intention signal to the ACC system of the principal vehicle, so that the target selection unit of the ACC system of the principal vehicle re-selects the tracking target on the basis of the signal. Thus, when it is determined that the target vehicle cuts into the principal lane or cuts out of the principal lane, the ACC system can execute a corresponding response in a timely manner, thereby avoiding the problem of uncomfortable driving or inappropriate deceleration caused by the ACC system selecting the wrong tracking object as a result of not being able to obtain lane change information in a timely manner.

Fig. 5 shows a lane change determining method 500 for use in the driving assistance system 100 according to a feasible embodiment of the present invention. Optionally, the lane change determining method 500 is implemented by the lane change determining unit 150 described above. However, it must be pointed out that the principles of the present application are not limited to a lane change determining unit of a specific type and structure.

As shown in fig. 5, in step 510, information containing travelling states of the principal vehicle and a vehicle in the vicinity thereof is acquired. In step 520, the lane traffic efficiency of each lane is determined on the basis of the acquired information. In step 530, the driving mood of the target vehicle is calculated on the basis of the acquired travelling states of vehicles in the vicinity. In step 540, the first lane change probability value of the target vehicle is determined on the basis of the lane traffic efficiency and the driving mood of the target vehicle. In step 550, the lane change intention signal indicating the lane change intention of the target vehicle is generated on the basis of the first lane change probability value, to assist the driving of the principal vehicle.

It should be understood that the operating process of the lane change determining unit 150 is likewise suitable for the method 500. Thus, the various relevant features described above in relation to the lane change determining unit 150 are likewise applicable here.

A machine-readable storage medium having an executable instruction stored thereon is also provided according to an embodiment of the present invention, wherein the executable instruction, when executed, causes a machine to perform the method 500.

Although some embodiments have been described above, these embodiments are merely set out for demonstrative purposes, and are not intended to limit the scope of the present invention. The attached claims and equivalent replacements thereof are intended to include all amendments, substitutions and alterations made within the scope and purport of the present invention.