DEVICE AND COMPUTER PROGRAM FOR CONTROLLING A VEHICLE FOLLOWING A TARGET VEHICLE

Abstract

Device (1) for controlling a vehicle (V) to track another vehicle, comprising: a detector (3) that detects other vehicles that exist in the vicinity of the controlled vehicle; a target vehicle tracking initiation device (40, S180a, S180b, S190) arranged to cause the controlled vehicle to track one of the other vehicles as a target vehicle if one of the other vehicles meets a predetermined target vehicle selection condition, wherein the predetermined target vehicle selection condition is necessary to select one of the other vehicles as a target vehicle; a route environment detection device (40, S110 to S130) which is arranged to detect an environment of a predicted route for which, using conditions of the predicted route, it is predicted that the controlled vehicle will travel on it; a lane-change permission determination device (40, S140, S140b) arranged to determine whether the predicted roadway permits lane changes, based on the detected surroundings of the predicted roadway; and a target vehicle selection condition setting device (40; S150, S160, S200) arranged to set the target vehicle selection condition based on a result of the determination, wherein the target vehicle selection condition setting device is configured to: to recognize the surrounding traffic conditions around the predicted route; to correct the target vehicle selection condition based on the detected ambient traffic conditions; to have stored a tracking history for each of the other vehicles, with the tracking history of each of the other vehicles representing whether a corresponding one of the other vehicles was selected as the target vehicle; the tracking history for each of the other vehicles as well as the ambient traffic conditions to identify the predicted route; and to correct the target vehicle selection condition for each of the other vehicles based on the tracking history for a corresponding one of the other vehicles.

Description

[0001] The invention relates to devices and computer programs for controlling a vehicle tracking a target vehicle, such as a vehicle traveling ahead.

[0002] DE 10 2007 029 483 A1 discloses a generic distance control device for motor vehicles, with a positioning system for locating vehicles driving ahead in the same lane and in adjacent lanes, a controller for regulating the speed of the vehicle as a function of the distance to a vehicle driving ahead in the same lane and an evaluation module for evaluating a probability of merging for vehicles located in an adjacent lane, characterized by a reaction module for triggering a graded reaction of the controller as a function of the probability of merging.

[0003] Furthermore, DE 10 2008 047 499 A1 discloses a method and a device for displaying a traffic situation underlying automatic distance control of a motor vehicle traveling in a target lane. According to the invention, at least one target object located in the target lane, to which the distance of the motor vehicle is controlled, and at least one other object relevant for the distance control are displayed, with the target object being displayed in a more prominent manner than the other relevant object.

[0004] Furthermore, DE 103 23 465 A1 discloses a device for controlling the speed of a vehicle, comprising a base unit that includes sensor means for detecting at least one area in front of the vehicle for the presence of objects, a display, and an electronic unit designed to display at least one detected object, if present, on the display. According to the invention, the base unit is designed to detect a driving scene with multiple objects via the sensor means, display it on the display, and perform a visualization that allows a user to determine whether an object, and which object, if multiple objects, is selected as the target object for a current or imminent speed control.

[0005] Finally, DE 10 2010 020 047 A1 discloses, among other things, a method for adapting a target distance specified for a vehicle's distance control system to a current traffic situation. The method determines the current traffic situation around the vehicle by evaluating the traffic situation, in which probabilities for a potential merger of other vehicles traveling in adjacent lanes and detected during the determination of the traffic situation in front of the vehicle into its first lane are determined. The traffic situation is additionally evaluated to determine whether the potential merger of a respective other vehicle would occur due to predefined emergency situations or without the existence of a predefined emergency situation. In the event that a determined probability for a potential merger of a other vehicle is above a predefined probability value,the severity of a target distance control in the distance control system is increased in order to achieve a faster response of the target distance control to the potential cutting-in of the other vehicle, and the specified target distance is adjusted in such a way that a potential cutting-in of the other vehicle is made easier by increasing the target distance in the event of one of the specified emergency situations and a potential cutting-in of the other vehicle is made more difficult by reducing the target distance in the absence of an emergency situation.

[0006] Furthermore, adaptive cruise control systems for controlling a distance from a first vehicle to a target second vehicle traveling in front of the first vehicle are known, one of which is disclosed in JP 2002-307 972 A.

[0007] The adaptive cruise control system disclosed in JP 2002-307972 A is installed in a first vehicle for controlling the vehicle; the vehicle is traveling in a lane of a road. The adaptive cruise control system detects another vehicle traveling in a lane adjacent to the lane of the first vehicle; the detected other vehicle is referred to as an adjacent vehicle.

[0008] The adaptive cruise control system also predicts the behavior of the adjacent vehicle and calculates the probability that the adjacent vehicle will perform a lane change from the adjacent or adjacent lane into the traveling lane. If the calculated probability is determined to be higher than a predetermined threshold, the adaptive cruise control system determines that the adjacent vehicle is likely to merge from the adjacent lane into the traveling lane and selects the adjacent vehicle as a target vehicle to track, i.e., follow, the controlled vehicle.

[0009] There are some road environments in which it is impossible for adjacent vehicles to enter a lane occupied by a controlled vehicle.

[0010] For example, if a lane separator or an obstacle is present between a lane in which a controlled vehicle with the adaptive cruise control system is traveling and a lane adjacent to the controlled vehicle's lane, it will be impossible for an adjacent vehicle traveling on the adjacent road to enter the controlled vehicle's lane. As another example, if the controlled vehicle is traveling in a lane into which neighboring vehicles traveling in an adjacent lane are prohibited by law or regulation, it will also be impossible for neighboring vehicles to enter the lane.

[0011] From the perspective of these road environments, the adaptive cruise control system disclosed in the patent publication may erroneously detect an adjacent vehicle as a target vehicle if the adjacent vehicle exhibits behavior tending toward the lane even though the adjacent vehicle is not intended to enter the lane.

[0012] That is, there may be a problem of low accuracy of detecting a neighboring vehicle as a target vehicle tracking the controlled vehicle.

[0013] It is therefore an object of the invention to solve the above-mentioned problem and to provide devices and computer programs capable of improving the accuracy of selecting a vehicle other than a target vehicle that is tracking a controlled vehicle.

[0014] This object is achieved by a device for controlling a vehicle to track another vehicle, having the features of patent claim 1, and alternatively by a computer program product for a device for controlling a vehicle to track another vehicle. Advantageous developments of the invention are the subject of the appended subclaims.

[0015] In accordance with a first exemplary aspect of the present disclosure, an apparatus is provided for controlling a vehicle to track another vehicle. The apparatus includes a detector that detects other vehicles that exist in the vicinity of the controlled vehicle. The apparatus includes a target vehicle tracking inducer arranged to cause the controlled vehicle to track one of the other vehicles as a target vehicle if one of the other vehicles satisfies a predetermined target vehicle selection condition. The predetermined target vehicle selection condition is required for selecting one of the other vehicles as a target vehicle.The device includes a road environment recognition device arranged to recognize an environment of a predicted road, for which the controlled vehicle is predicted to travel using conditions of the predicted road, or on which the controlled vehicle is predicted to travel using conditions of the predicted road. The device includes a lane change permission determination device arranged to determine whether the predicted road permits lane changes based on the recognized environment of the predicted road.

[0016] The apparatus includes a target vehicle selection condition setting means arranged to set the target vehicle selection condition based on a result of the determination.The target vehicle selection condition setting means is configured to detect the ambient traffic conditions around the predicted travel road, correct the target vehicle selection condition based on the detected ambient traffic conditions, have stored therein a tracking history for each of the other vehicles, the tracking history of each of the other vehicles representing whether a corresponding one of the other vehicles has been selected as the target vehicle, detect the tracking history for each of the other vehicles as the ambient traffic conditions around the predicted travel road, and correct the target vehicle selection condition for each of the other vehicles based on the tracking history for a corresponding one of the other vehicles.

[0017] In accordance with a second exemplary aspect of the present disclosure, a computer program product is provided for an apparatus for controlling a vehicle to track another vehicle. The apparatus includes a detector that detects other vehicles that exist in the vicinity of the controlled vehicle. The computer program product includes a computer-readable storage medium and a set of computer program instructions embedded or stored in the computer-readable storage medium. The instructions cause a computer to (i) causing the controlled vehicle to track one of the other vehicles as a target vehicle if one of the other vehicles satisfies a predetermined target vehicle selection condition, the predetermined target vehicle selection condition being necessary for selecting one of the other vehicles as a target vehicle; (ii) detecting an environment of a predicted route for which the controlled vehicle is predicted to travel using conditions of the predicted route; (iii) determining whether the predicted route allows lane changes based on the detected environment of the predicted route; and (iv) setting the target vehicle selection condition based on a result of the determination.

[0018] Setting the target vehicle selection condition includes detecting the ambient traffic conditions around the predicted travel road, correcting the target vehicle selection condition based on the detected ambient traffic conditions, having stored a tracking history for each of the other vehicles, the tracking history of each of the other vehicles representing whether a corresponding one of the other vehicles has been selected as the target vehicle, detecting the tracking history for each of the other vehicles as the ambient traffic conditions around the predicted travel road, and correcting the target vehicle selection condition for each of the other vehicles based on the tracking history for a corresponding one of the other vehicles.

[0019] In each of the first and second exemplary aspects of the present disclosure, a corresponding one of the controller and the computer sets the target vehicle selection condition based on the detected environment of the predicted travel road based on a result of determining whether the predicted travel road allows lane changes.

[0020] For example, if it is determined that the predicted road does not allow lane changes, a corresponding one of the controller and the computer changes the target vehicle selection condition so that it becomes more difficult for the other vehicles to be selected as the target vehicle, or so that the other vehicles become more difficult to select as the target vehicle if it is determined that the predicted road does not allow lane changes.

[0021] This makes it possible to reduce the probability that the neighboring vehicle moving in a lane adjacent to the current travel lane of the controlled vehicle is erroneously selected as the target vehicle tracking the controlled vehicle, even if a neighboring vehicle moving in a lane adjacent to the current travel lane of the controlled vehicle is swerving or tending toward the current travel lane. This results in an improvement in the accuracy of determining another vehicle as the target vehicle tracking the controlled vehicle.

[0022] Various aspects of the present disclosure may include and / or exclude different features and / or advantages depending on the application. Furthermore, various aspects of the present disclosure may combine one or more features of other embodiments depending on the application. Descriptions of features and / or advantages of particular embodiments should not be construed as limiting other embodiments or the claims.

[0023] Other aspects of the present disclosure will become more apparent from the following description of exemplary embodiments with reference to the accompanying drawings. Fig. 1A is a block diagram schematically showing an example of the overall structure of a driving support system according to an embodiment of the present disclosure; Fig. 1B is an enlarged view illustrating a polar coordinate system and a Cartesian coordinate system defined in front of a radar sensor of the driving support system; Fig. 2A is a flowchart schematically illustrating an example of the first part of a driving support task performed by a Fig. 1 shown driving support ECU or electronic control unit; Fig. 2B is a flowchart schematically illustrating an example of the next part of the driving assistance task; Fig. 3A is a view schematically illustrating a first lane type of a predicted travel road according to the embodiment; Fig. 3B is a view schematically illustrating a second lane type of a predicted travel road according to the embodiment; Fig. 3C is a view schematically illustrating a third lane type of a predicted travel road according to the embodiment; Fig. 4A shows an example of the shape of a predicted route according to the embodiment; Fig. 4B shows another example of the shape of a predicted route according to the embodiment; Fig. 5A is a diagram schematically illustrating a predetermined standard change curve of a same-lane probability of an adjacent vehicle traveling in a lane adjacent to a predicted traveling lane of a controlled vehicle while the adjacent vehicle is swerving in the vehicle width direction according to the embodiment; Fig. 5B is a diagram schematically illustrating a predetermined standard change curve of the same-lane probability of a preceding vehicle traveling ahead of the controlled vehicle on a predicted traveling lane of the controlled vehicle when the predicted traveling lane is a curved lane, according to the embodiment; each of the Fig. 5C and Fig. 5D is a diagram schematically illustrating a predetermined standard change curve of the same-lane probability of an encroaching vehicle traveling in an encroaching lane that merges with a predicted travel lane of the controlled vehicle when the encroaching lane attempts to merge with the predicted travel lane, according to the embodiment; Fig. 6 is a flowchart schematically illustrating an example of a driving support task executed by the driving support ECU according to a modification of the embodiment of the present disclosure; and Fig. 7 is a flowchart schematically illustrating an example of the first part of a modified driving support task executed by the driving support ECU according to another modification of the embodiment of the present disclosure.

[0024] An embodiment of the invention will be described below with reference to the accompanying drawings.

[0025] A driving assistance system 1 according to the embodiment is installed in a vehicle V for controlling the vehicle V and configured to perform driving assistance for a driver of the vehicle V. In particular, the driving assistance system 1 is configured to perform a cruise control task.

[0026] The cruise control task is designed to detect the shape of an upcoming section of road on which the vehicle V is predicted to travel, and to control the speed of the vehicle V such that the speed is maintained within a predetermined range while the vehicle V travels the upcoming section of road. An upcoming section of road on which the vehicle V is predicted to travel is referred to as a predicted travel road. In other words, a current travel road of the vehicle V is normally predicted as the predicted travel road.

[0027] In addition, the cruise control task is designed to perform an adaptive cruise control task that (i) specifying or determining as a target vehicle one of other vehicles that exist near or adjacent to the vehicle(s) V, ie traveling if one of the other vehicles satisfies at least one target vehicle selection condition (ii) when the target vehicle enters the predicted route ahead of the vehicle V, maintains a distance from the vehicle V to the target vehicle at least approximately equal to a predetermined target distance.

[0028] More specifically, with reference to Fig. 1A, the driving support system 1 includes a predicted road condition detector 3, a vehicle condition detector 10, a vehicle control system 20, and a driving support control device, ie, a driving support ECU (Electronic Control Unit) 40.

[0029] The predictive road condition detector 3 is configured to acquire information indicating the conditions of a predicted travel road; this information is referred to as predictive road condition information. For example, the predictive road condition detector 3 is equipped with a radar sensor 5 and an image pickup unit 7.

[0030] The radar sensor 5 is mounted, for example, at the center portion of the front end of the vehicle V and is operable to transmit scanning waves such as radar waves or laser waves and receive echoes based on the transmitted scanning waves. Based on the received echoes, the radar sensor 5 is operable to detect the positions of target objects that reflect the scanning waves as echoes.

[0031] For example, the radar sensor 5 according to this embodiment is configured as a laser radar. The radar sensor 5 has a laser output point with a center axis CA extending toward the front of the vehicle V. The radar sensor 5 emits laser waves, i.e., laser beams, as the scanning waves from the laser output point toward the front of the vehicle V to scan a sector area SA with a predetermined center angle θC in a horizontal direction, i.e., a vehicle width direction, in front of the vehicle 1. The sector area SA has a predetermined vertical width in the height direction of the vehicle V.

[0032] The radar sensor 5 receives echoes produced by reflection of at least some of the laser waves by target objects; each echo has a corresponding scanning angle θ with respect to the central axis CA of the radar sensor 5 within the central angle θC of the scanned area SA.

[0033] For example, the radar sensor 5 stores a first time at which each of the laser waves is emitted and a second time at which an echo corresponding to at least some of the laser waves is received. Based on the information stored in the radar sensor 5, the radar sensor 5 measures an interval between the first time and the second time for each of the echoes. Then, based on the interval measured for each of the echoes, the radar sensor 5 determines the distance, i.e., the minimum distance, d, of a corresponding target object with respect to the vehicle V and the orientation, i.e., the scanning angle θ, of a corresponding target object with respect to the center axis CA of the radar sensor 5 of the vehicle V.

[0034] That is, the distance d and the orientation (scanning angle) θ of each target object corresponding to one of the echoes, which represents positional information about a corresponding target object, are obtained. The distance d and the orientation (scanning angle) θ are referred to as target position data of a corresponding target object. The radar sensor 5 outputs the target position data of each target object as some of the predicted road information to the driving support ECU 40. It is noted that, because the target position data of each target object includes the distance d and the orientation (scanning angle) θ, the target position data of each target object has a polar coordinate (d, θ) in a polar coordinate system. For example, a target object OB0 with a polar coordinate (d0, θ0) in Fig. 1B.

[0035] Note that the radar sensor 5 is not limited to a laser radar for emitting laser beams as scanning waves. Specifically, the radar sensor 5 may be configured as a millimeter-wave radar for emitting millimeter waves as scanning waves or as a sonar for emitting ultrasonic waves as scanning waves.

[0036] The image pickup unit 7 is configured as, for example, a known camera device, and is mounted, for example, at the center portion of the front end of the vehicle V. The image pickup unit 7 is operable to capture images of a sector area SA1 having a predetermined center angle θc1 in the horizontal direction, i.e., the vehicle width direction, in front of the vehicle V. The sector area SA1 has a predetermined vertical width in the height direction of the vehicle V.

[0037] For example, the central angle θc1 and the vertical width of the sector area SA1 are determined to monitor: (1) a predicted route on which the vehicle V is predicted to travel (2) Traffic signs for vehicles predicted to travel on the predicted route.

[0038] Specifically, the image pickup unit 7 is operable to capture an image of the sector area SA1 on and around the predicted travel road in front of the vehicle V at unit times or at uniform time intervals, and to obtain the captured images as some of the predicted road condition information. Then, the image pickup unit 7 outputs the obtained predicted road information to the driving support ECU 40.

[0039] The vehicle condition detector 10 is configured to detect various types of information representing the behavior of the vehicle V. For example, the vehicle condition detector 10 is equipped with a yaw rate sensor 12, wheel speed sensors 14, and a steering angle sensor 16.

[0040] The yaw rate sensor 12 is operable to output to the driving support ECU 40 a signal indicative of an angular velocity around a vertical axis of the vehicle as a yaw rate γ of the vehicle V.

[0041] The wheel speed sensors 14 are respectively mounted on the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel of the vehicle V. Each of the wheel speed sensors 14 is operable to output a pulse whose leading or trailing edge occurs each time the axle of a corresponding wheel is rotated by a predetermined angle. In other words, each of the wheel speed sensors 14 outputs a train of pulses, whose widths are defined based on the rotational speed of the axle of a corresponding wheel, as a pulse signal.

[0042] The steering angle sensor 16 is operable to output to the driving support ECU 40 a signal comprising at least one of: (i) a relative angle of a steering wheel of the vehicle V, ie a change in the steering angle of the steering wheel (ii) an absolute angle of the steering wheel with respect to the straight-ahead position of the steering wheel when the vehicle V is traveling straight ahead.

[0043] The signals output by the vehicle condition detector 10 are referred to as vehicle condition signals.

[0044] The vehicle control system 20 includes electronic control units (ECUs) for controlling various devices installed in the vehicle V. The vehicle control system 20 according to this embodiment includes at least an engine ECU 22, a brake ECU 24, and a meter ECU 26.

[0045] The engine ECU 22 is designed to control the operating sequences of a multi-cylinder internal combustion engine EN of the vehicle V, which for the sake of simplicity is referred to as an engine EN. The engine EN includes a throttle valve TV and a throttle actuator TA. The throttle actuator TA is communicatively connected to the engine ECU 22 and coupled to a driver-operated accelerator pedal AP of the vehicle V.

[0046] The throttle valve TV and the throttle actuator TA serve as a device or means for controlling the amount of air entering from the intake pipe, an intake manifold (or intake port) just before each cylinder of the engine EN.

[0047] The vehicle control system 20 further includes various types or kinds of sensors required to control the operations of the engine EN and / or the vehicle V.

[0048] More specifically, the sensors include an acceleration sensor S1 and a brake sensor S2.

[0049] The acceleration sensor S1 is operable to measure a driver-set (depressed) position or stroke of a driver-operated accelerator pedal AP of the vehicle V, which is coupled to the throttle valve TV, and to output a signal to the engine ECU 22 indicating the measured driver-operated position or such stroke of the accelerator pedal AP.

[0050] The brake sensor S2 is operable to measure a driver-set (depressed) position or stroke of a brake pedal BP of the vehicle V and to output a signal to the brake ECU 24 indicating the measured driver-operated position or such stroke of the brake pedal BP.

[0051] The engine ECU 22 is configured as, for example, a computer circuit having a central processing unit (CPU), a storage unit such as a read-only memory (ROM) and a random access memory (RAM), etc. The engine ECU 22 is operable to perform: (i) a first task of starting and stopping the engine EN, (ii) a second task of controlling a correct quantity of fuel to be injected from an injector provided for each cylinder of the engine EN, (iii) a third task of controlling a correct ignition timing for an ignition device provided for each cylinder of the engine EN (iv) a fourth task of controlling the speed of the engine EN to thereby control the speed of the vehicle V.

[0052] More specifically, as the fourth task, the engine ECU 22 controls the throttle actuator TA based on the signal output from the acceleration sensor S1 to thereby control how the throttle valve TV opens the air passage inside the intake pipe to each cylinder to adjust the amount of intake air reaching each cylinder.

[0053] Furthermore, the engine ECU 22 is communicatively connected to the driving support ECU 40 and operable to control the throttle actuator TA in accordance with instructions sent from the driving support ECU 40 to thereby change a torque generated by the engine EN.

[0054] The brake ECU 24 is configured as, for example, a computer circuit including a central processing unit (CPU), a storage unit such as a read-only memory (ROM) and a random access memory (RAM), etc. The brake ECU 24 is operable to control a brake control system BC having an ABS (anti-lock brake system). The brake control system BC includes a hydraulic circuit HC equipped with at least a first hydraulic valve HV1 and a second hydraulic valve HV2. The brake control system BC further includes at least first and second actuators AN1 and AN2 coupled to the respective first and second hydraulic valves HV1 and HV2 and communicatively connected to the brake ECU 24.

[0055] The first and second hydraulic valves HV1 and HV2 and the first and second actuators AN1 and AN2 serve as means for individually controlling a hydraulic pressure to be applied to a brake for each of the wheels.

[0056] More specifically, the brake ECU 24 is operable to receive the signals output from the brake sensors S2 and to receive the pulse signals output from the wheel speed sensors 14.

[0057] The brake ECU 24 is operable to determine, based on the received pulse signals from the wheel speed sensors 14, whether a condition of each wheel exists that indicates impending wheel lock.

[0058] If it is determined that a wheel condition exists that indicates imminent wheel lock, the brake ECU 24 is operable to cause the first actuator AN1 to control the first hydraulic valve HV1 based on the signal output from the corresponding brake sensor S2. This reduces the hydraulic pressure applied to a brake corresponding to the affected wheel, and consequently reduces the braking force on the affected wheel from a normal level to a predetermined low level.

[0059] If it is determined that the condition of the wheel has returned to a correct state after the hydraulic pressure has been reduced, the brake ECU 24 is operable to cause the second actuator AN2 to control the second hydraulic valve HV2 based on the signal output from the corresponding brake sensor S2. This increases the hydraulic pressure applied to the brake corresponding to the affected wheel, and consequently returns the braking force on the affected wheel from the predetermined low level to the normal level.

[0060] The brake ECU 24 is communicatively connected to the driving support ECU 40 and operable to control at least one of the actuators AN1 and AN2 in accordance with instructions sent from the driving support ECU 40 to thereby change the hydraulic pressure applied to the brakes for each wheel.

[0061] The meter ECU 26 is configured as, for example, a computer circuit including a central processing unit (CPU), a storage unit such as a read-only memory (ROM) and a random access memory (RAM), etc. The meter ECU 26 is communicatively connected to the driving support ECU 40 and other devices installed in the vehicle V. The meter ECU 26 is operable to receive various pieces of information sent from the driving support ECU 26 and the other devices and to control how the pieces of information are to be displayed on one or more displays, such as one or more meter displays MD, installed in the vehicle V.

[0062] For example, the meter ECU 26 is operable to display the speed of the vehicle V and a rotational speed of the engine EN on the one or more meter displays MD. The meter ECU 26 is further operable to display how the drive support ECU 40 is performing a drive support task for the vehicle V and to display certain steps of the drive support task on the corresponding one or more meter displays MD.

[0063] The driving assistance ECU 40 is configured, for example, as a computer circuit with at least a ROM 41, a RAM 42, a CPU 43, an analog-to-digital (A / D) converter 44, an input / output (I / O) interface 45, a communication circuit 45, etc.; the components 41 to 45 are communicatively connected to one another via, for example, a bus line. The driving assistance ECU 40 is operable to perform various tasks, including the driving assistance task.

[0064] Data and programs that need to be retained even when the drive support ECU 40 is turned off are stored in the ROM 41. The CPU 43 is configured to temporarily store programs and data in the RAM 42.

[0065] The A / D converter 44 is operable to receive the predictive road condition information output by the predictive road condition detector 3 and the vehicle condition signals output by the vehicle condition detector 10. The A / D converter 44 is operable to convert the predictive road condition information and the vehicle condition signals into digital data. The I / O interface 45 is operable to supply the digital data to the CPU 43. The communication circuit 46 serves to enable the CPU 43 to communicate with the vehicle control system 20.

[0066] More specifically, for example, a driving assistance program consisting of instructions is stored in the ROM 41; the driving assistance program causes the CPU 43 to execute the driving assistance task. For example, the driving assistance task is configured to recognize the shape of a predicted driving road on which the vehicle V is predicted to travel, and to perform driving assistance control of the vehicle V based on the recognized shape of the predicted driving road.

[0067] The driving support control of the vehicle V according to this embodiment includes selecting, ie, determining, based on at least one predetermined target vehicle selection condition, one of other vehicles traveling adjacent to, ie, in the surroundings of, the vehicle V as a target vehicle that the vehicle V tracks, ie, follows.

[0068] Next, the driving support task executed by the CPU 43 of the driving support ECU 40 will be described below.

[0069] It is noted that the CPU 43 starts the driving support program stored in the ROM 41 cyclically at every preset interval, such as every 100 ms, and thus performs the driving support task based on the driving support program at every preset interval.

[0070] When the driving assistance program is started, the CPU 43, in step S110, reads digital data indicating the predictive road information sent from the predictive road condition detector 3 via the A / D converter 44 and the I / O interface 45. For example, in step S110, according to this embodiment, the CPU 43 reads the target position data of each target object existing ahead of the vehicle V from the radar sensor 5. That is, the target position data of each target object includes the distance d and the scanning angle θ of a corresponding target object.

[0071] Next, in step S120, the CPU 43 converts the distance d and the scanning angle θ of each target object, i.e., the polar coordinate (d, θ) of the target position data of each target object in the polar coordinate system, into a Cartesian coordinate (X, Z) in a Cartesian, i.e., XZ, coordinate system. The XZ coordinate system has a Z axis that coincides with the center axis CA of the radar sensor 5 and an X axis that coincides with the vehicle width direction passing through the radar output point of the radar sensor 5. For example, an origin coordinate in the XZ coordinate system coincides with the laser output point of the radar sensor 5 of the vehicle V.

[0072] For example, the CPU 43 converts the polar coordinate (d0, θ0) of the target object OB0 in the polar coordinate system into a Cartesian coordinate (X0, Z0) in the XZ coordinate system (conversion process P1).

[0073] In step S120, the CPU 43 further performs a target object detection process P2 based on the Cartesian coordinate (X, Z) of each target object existing in front of the vehicle V.

[0074] For example, in step S120, the CPU 43 classifies data items, each of which has the Cartesian coordinates (X, Z), into clusters CL1...CLn (n is an integer equal to or greater than 2); the distances between the data items included in each of the clusters CL1 to CLn are close to each other, i.e., are smaller than a predetermined threshold. In step S120, the CPU 43 recognizes that the data items included in each of the clusters CL1 to CLn are data items obtained from a corresponding one of target objects TO1 to TOn. Then, in step S120, the CPU 43 determines a center position coordinate of each of the clusters CL1 to CLn, i.e., of each of the target objects TO1 to TOn, in the XZ coordinate system. In step S120, the CPU 120 determines a size such as an area, a lateral width in the vehicle width direction, or the like of each of the clusters CL1 to CLn, that is, each of the target objects TO1 to TOn.

[0075] Furthermore, in step S120, the CPU 43 determines a relative speed of each of the target objects TO1 to TOn relative to the vehicle V. For example, the CPU 43 tracks the center position coordinate of each of the clusters CL1 to CLn, i.e., each of the target objects TO1 to TOn, in steps S120 of several cycles of the driving support task. Then, based on the tracking results, i.e., the changes in the center position coordinate of each of the clusters CL1 to CLn over time, the CPU 43 determines the relative speed of each of the target objects TO1 to TOn relative to the vehicle V.

[0076] In step S120, the CPU 43 determines the type of a corresponding one of the target objects TO1 to TOn based on the size and relative speed of each of the target objects TO1 to TOn. Note that the type of each of the target objects TO1 to TOn represents a corresponding one of the target objects TO1 to TOn. For example, the CPU 43 determines one of the target objects TO1 to TOn as a roadside object such as a guardrail if the corresponding object is a guardrail, and determines another one of the target objects TO1 to TOn as a leading vehicle if the corresponding target object is a leading vehicle.

[0077] Following step S120, in step S130, the CPU 43 recognizes, based on the digital data indicating the predictive road information(s) sent from the predictive road condition detector 3, the surroundings of a predicted travel road on which the vehicle V is predicted to travel. In step S130, the CPU 43 may read the digital data of the vehicle condition signals output from the vehicle condition detector 10 and recognize, based on the digital data of the vehicle condition signals, the surroundings of the predicted travel road on which the vehicle V is predicted to travel.

[0078] For example, according to this embodiment, in step S130, the CPU 43 recognizes at least the shape of the predicted road as the surroundings of the predicted road. Furthermore, in step S130, the CPU 43 recognizes at least the number of lanes included in the predicted road and the lane type of the predicted road.

[0079] The CPU 43 in accordance with this embodiment is programmed to estimate the shape of the predicted road using the known estimation methods.

[0080] As a first known method, the CPU 43 estimates the planar shape of the predicted road as the shape of the predicted travel road based on the arrangement of the roadside objects, ie, guardrails, detected in step S120. The planar shape of the predicted travel road is a curved shape with a curvature radius R. Then, the CPU 43 recognizes the curved shape with the curvature radius R as the shape of the predicted travel road.

[0081] As a second known method, the CPU 43 estimates the shape of the predicted road based on the images captured by the image pickup unit 7. As a third known method, the CPU 43 estimates the shape of the predicted road based on the vehicle condition signals measured by the vehicle condition detector 10.

[0082] In the second known method, the CPU 43 performs a known image recognition process to recognize a lane line, such as a colored lane line, painted on the predicted travel road using the images captured by the image pickup unit 7. Then, based on the detected lane lines, the CPU 43 estimates the planar shape of the predicted travel road as the shape of the predicted travel road.

[0083] In the third known method, the CPU 43 detects the rotational speed of the axle of each wheel based on the pulse signal output from each of the wheel speed sensors 14 and calculates the speed of the vehicle V based on the rotational speed of the axle of each wheel.

[0084] The CPU detects the yaw rate γ of the vehicle V based on the signal output from the yaw rate sensor 12. Then, the CPU 43 divides the speed of the vehicle V by the yaw rate γ of the vehicle V and thereby calculates the curve radius R of the predicted road as the shape of the predicted road.

[0085] The CPU 43 may be configured to estimate the curve radius R of the predicted road using the combination of at least two of the first to third known methods as the shape of the predicted road. In this case, the CPU 43 may calculate an arithmetic mean or a weighted average of values ​​of the curve radius R of the predicted road calculated using at least two of the first to third known methods, and may estimate the arithmetic mean or the weighted average as the curve radius R of the predicted road.

[0086] For example, lane types of predicted routes in accordance with this embodiment include: (i) a first lane type which is a combination of a predicted travel lane on which the vehicle V is predicted to travel and a merging lane merging into the predicted travel lane (cf. Fig. 3A), (ii) a second lane type which is a combination of a predicted travel lane in which the vehicle V is predicted to travel and an adjacent lane from which a vehicle adjacent to the vehicle V can legally and physically make a lane change to the predicted travel lane (cf. Fig. 3B) (iii) a third lane type, which is a combination of a predicted travel lane in which the vehicle V is predicted to travel and an adjacent lane from which a vehicle adjacent to the vehicle V cannot legally and physically make a lane change to the predicted travel lane (cf. Fig. 3C).

[0087] It is noted that a predicted travel lane for the vehicle V is a forward side of a current travel lane of the vehicle V.

[0088] In step S130, for example, the CPU 43 performs the known image recognition process for recognizing a lane line, such as a colored lane line or lane marking, painted on the predicted travel road using the images captured by the image pickup unit 7. Then, the CPU 43 determines the lane type of the predicted travel road based on the type of the recognized lane marking. That is, if it is determined that the type of the recognized lane marking is a broken line (see FIG. Fig. 3A or Fig. 3B), the CPU 43 detects that it is possible for an adjacent vehicle to perform a lane change into the predicted travel road. Otherwise, if it is determined that the type of the detected lane marking is a solid line (see Fig. 3C), the CPU 43 detects that a neighboring vehicle is unable to change lanes into the predicted travel road.

[0089] In step S130, the CPU 43 may determine the lane type of the predicted travel road using another known method. For example, the ROM 41 and / or the RAM 42 store many template images of many road signs. The CPU 43 compares the images on and around the predicted travel road ahead of the vehicle V, captured by the image pickup unit 7, with the template images, and thereby recognizes the descriptions of the traffic signs included in the captured images. Then, the CPU 43 determines that the lane type of the predicted travel road is the third lane type if the description of any of the traffic signs indicates "NO OVERTAKE OR PASS" or "KEEP CURRENT LANE."

[0090] Following step S130, the CPU 43 determines in step S140 whether the predicted travel road allows lane changes using the surroundings of the predicted travel road.

[0091] If it is determined that lane changes are permitted on the predicted travel road (YES in step S140), the CPU 43 changes, i.e., relaxes, the at least one target vehicle selection condition in step S150 such that other vehicles traveling in the vicinity of the vehicle V are more easily selected as a target vehicle that the vehicle V is tracking. In other words, the CPU 43 changes the at least one target vehicle selection condition in step S150 to thereby increase the probability that other vehicles traveling in the vicinity of the vehicle V are selected as a target vehicle that the vehicle V is tracking or following.

[0092] The at least one target vehicle selection condition is at least one condition, in other words at least one rule, required for selecting, i.e., determining, one of other vehicles traveling around the vehicle V as a target vehicle tracking the vehicle V. In other words, a selected one of the vehicles traveling around the vehicle V satisfies the at least one target vehicle selection condition.

[0093] The at least one target vehicle selection condition may typically include, for example, a condition in which: (1) one of the other vehicles in the vicinity of vehicle V is moving in the direction of movement of vehicle V (2) the inter-vehicle distance between vehicle V and any of the other vehicles in the vicinity of vehicle V is the shortest among all the inter-vehicle resistances between vehicle V and the other vehicles.

[0094] Specifically, the at least one target vehicle selection condition according to this embodiment includes a condition that a same-lane probability of another vehicle traveling ahead of the vehicle V in a converging or adjacent lane adjacent to the predicted travel path of the vehicle V, or in the same predicted travel path, is equal to or higher than a threshold probability. The same-lane probability of another vehicle is defined as a probability that the other vehicle is traveling ahead of the vehicle V on the predicted travel path of the vehicle V.

[0095] That is, when it is determined that the same-lane probability of one of the other vehicles is equal to or higher than the threshold probability, the CPU 43 selects the one of the other vehicles as a target vehicle that the vehicle V tracks.

[0096] More specifically, a value of the same-lane probability of each of the other vehicles traveling around vehicle V can be calculated based on, for example, the relative relationships between: (i) the position, for example, of the origin coordinate of the XZ coordinate system of the vehicle V, (ii) the surroundings of the predicted travel route detected in step S130 (iii) the position, ie the XZ coordinate (X, Z) of each of the other vehicles.

[0097] In this embodiment, the CPU 43 is programmed to calculate a value of the same-lane probability of a neighboring vehicle traveling in a lane adjacent to the predicted travel road of the vehicle V such that the value of the same-lane probability of the neighboring vehicle is increased with an increment of at least one of: (1) the distance of the movement of the neighboring vehicle close to the predicted travel route of the vehicle V in the vehicle width direction (2) the lateral speed of movement of the neighboring vehicle near the predicted travel road of the vehicle V is increased in the vehicle width direction.

[0098] In this embodiment, the CPU 43 is programmed to calculate a value of the same-lane probability of an entering vehicle traveling on an merging lane adjacent to the predicted travel road of the vehicle V such that the value of the same-lane probability of the entering vehicle is increased with an increment of at least one of: (3) the distance of the movement of the incoming vehicle close to the predicted travel route of the vehicle V in the vehicle width direction (4) the lateral speed of movement of the incoming vehicle close to the predicted travel route of the vehicle V is increased in the vehicle width direction.

[0099] Similarly, the CPU 43 is programmed to calculate a value of the same-lane probability of a preceding vehicle traveling ahead of the vehicle V on the predicted travel road such that the value of the same-lane probability of the preceding vehicle is increased by an increment of at least one of: 1. the distance of the preceding vehicle's movement close to an adjacent lane adjacent to the predicted travel road in the vehicle width direction 2. the lateral speed of movement of the preceding vehicle close to the adjacent lane in the vehicle width direction is reduced.

[0100] More specifically, in step S150, the CPU 43 may decrease a value of the threshold probability to thereby make other vehicles, such as neighboring vehicles or incoming vehicles traveling in front of the vehicle V, more easily selectable as the target vehicle tracking the vehicle V. In step S150, the CPU 43 may decrease a value of the threshold probability by a predetermined value.

[0101] After completion of the operation in step S150, the driving support task proceeds to step S170.

[0102] Otherwise, if it is determined that the predicted travel road does not allow lane changes (NO in step S140), the CPU 43 changes, i.e., tightens, in step S160, the at least one target vehicle selection condition such that other vehicles traveling in the vicinity of the vehicle V are less or more difficult to select than the target vehicle that the vehicle V is tracking. In other words, the CPU 43 changes the at least one target vehicle selection condition to thereby make it more difficult for other vehicles to be selected as a target vehicle that the vehicle V is tracking or following.

[0103] More specifically, in step S160, the CPU 43 may increase a value of the threshold probability to thereby make other vehicles, such as neighboring vehicles or incoming vehicles traveling in front of the vehicle V, less likely to be selected as the target vehicle tracking the vehicle V. In step S160, the CPU 43 may increase a value of the threshold probability by a predetermined value.

[0104] After completion of the operation in step S160, the driving support task proceeds to step S170.

[0105] In step S170, the CPU 43 detects environmental conditions, ie, conditions of the surrounding traffic, around the predicted travel route, using, for example: (1) the results of the operations in the above-described steps S110 to S150 or steps S110 to S114 and S160, (2) digital data indicating the predictive road information sent from the predictive road condition detector 3, and / or (3) digital data of the vehicle condition signals output from the vehicle condition detector 10.

[0106] Then, if necessary, in step S170, the CPU 43 corrects the at least one target vehicle selection condition for at least one of other vehicles traveling in the vicinity of the vehicle V based on the recognized environmental conditions around the predicted traveling road.

[0107] The environmental conditions around the vehicle V according to this embodiment include the conditions of the predicted travel road and the travel conditions of other vehicles traveling around the vehicle V. More specifically, the environmental conditions around the vehicle V include, for example, tracking histories, travel environments, and behaviors of surrounding vehicles.

[0108] For example, the tracking history for each of other vehicles traveling around vehicle V represents information indicating whether a corresponding one of the other vehicles has been selected as a target vehicle that vehicle V is tracking.

[0109] The travel environments include, for example, the lane type of the predicted travel road detected in step S130.

[0110] For example, the behaviors of surrounding vehicles include at least one of: 1. the behaviour of at least one preceding vehicle moving along the predicted route of vehicle V, 2. the behavior of at least one neighboring vehicle moving in lanes adjacent to the predicted route of vehicle V, 3. the behavior of at least one incoming vehicle moving along an incoming lane that merges into the predicted route of travel of vehicle V.

[0111] The CPU 43 according to this embodiment detects the other vehicles traveling around the vehicle V using the images captured by the image pickup unit 7. Then, the CPU 43 monitors motion information associated with the movements of the detected other vehicles, and, based on the monitored motion information about the detected other vehicles, detects the behaviors of one or more preceding vehicles, one or more adjacent vehicles, and / or one or more incoming vehicles.

[0112] It is noted that the movement information associated with the movements of each of the detected other vehicles around vehicle V includes at least: (1) the orientations of the movements of a corresponding one of the other vehicles in the vehicle width direction, (2) the distances of the movements of a corresponding one of the other vehicles in the vehicle width direction (3) the changes in the lateral velocity of a corresponding one of the other vehicles in the vehicle width direction.

[0113] That is, the motion information associated with the movements of each of the detected other vehicles around vehicle V includes the changes in the same-lane probability of a corresponding one of the detected other vehicles.

[0114] Next, how the CPU 43 corrects the at least one target vehicle selection condition for at least one of other vehicles traveling around the vehicle V in step S170 will be described below.

[0115] Specifically, as the correction in step S170, the CPU 43 increases the probability that at least one of the other vehicles is selected as a target vehicle tracking the vehicle V, which at least one of the other vehicles has been selected as a target vehicle at least once. This is because another vehicle that has been selected as a target vehicle at least once can easily be selected again as a target vehicle tracking the vehicle V.

[0116] In addition, in step S170, when it is determined that the predicted travel road has a curved shape and the predicted travel road allows lane changes (see Fig. 4A), the CPU 43 sets at least one target vehicle selection condition for neighboring vehicles included in the other vehicles to thereby make it difficult for the neighboring vehicles to be selected as a target vehicle that the vehicle V tracks.

[0117] In step S170, assume the situation that the vehicle V is traveling along an edge, i.e., a curve, of the predicted curved travel lane, while the preceding vehicle traveling along the edge of the predicted curved travel lane in front of the vehicle V is selected as a target vehicle that the vehicle V tracks (cf. Fig. 4B). In this situation, the CPU 43 corrects the at least one target vehicle selection condition for the preceding vehicle in step S170, thereby increasing the probability that the preceding vehicle traveling ahead of the vehicle V is continuously selected as a target vehicle tracking the vehicle V. Specifically, even if it is determined that the predicted traveling road does not allow lane changes, the CPU 43 corrects the at least one target vehicle selection condition for the preceding vehicle in step S170, thereby increasing the probability that the preceding vehicle traveling ahead of the vehicle V is continuously selected as a target vehicle tracking the vehicle V.

[0118] Note that according to this embodiment, the CPU 43 is configured to perform the correction of the at least one target vehicle selection condition for at least one of other vehicles traveling around the vehicle V in accordance with the environmental conditions around the vehicle V after the operation in step S150 or S160. However, the present disclosure is not limited to this configuration.

[0119] More specifically, the CPU 43 may be configured to perform the correction of the at least one target vehicle selection condition for at least one of other vehicles without executing the operation in step S150 or S160.

[0120] Next, specific examples of how the CPU 43 changes the at least one target vehicle selection condition in step S150 or S160, or corrects the at least one target vehicle selection condition in step S170, will be described below with reference to Fig. 5A to 5C are described in more detail.

[0121] In each of the Fig. In Figures 5A to 5C, the vertical axis shows the in-lane probability of each of the other vehicles traveling around vehicle V, and the horizontal axis shows time. As described above, the in-lane probability of each of the other vehicles traveling around vehicle V depends on at least: (1) the distance of movement of a corresponding one of the other vehicles close to the predicted travel lane of the vehicle V in the vehicle width direction (2) the lateral speed of movement of a corresponding one of the other vehicles close to the predicted travel lane of the vehicle V in the vehicle width direction.

[0122] Furthermore, the same-lane probability of a preceding vehicle moving in the predicted travel lane in front of vehicle V depends on at least 1. the distance of the preceding vehicle's movement close to an adjacent lane adjacent to the predicted travel lane in the vehicle width direction 2. the lateral speed of movement of the preceding vehicle close to the adjacent lane in the vehicle width direction.

[0123] Fig. 5A illustrates a predetermined standard change curve of the same-lane probability of an adjacent vehicle traveling in an adjacent lane adjacent to a predicted traveling lane of the vehicle V while the adjacent vehicle is swerving in the vehicle width direction (cf. Fig. 3C).

[0124] The standard change curve of the same-lane probability of a neighboring vehicle, shown in Fig. 3C, substantially matches a predetermined standard change curve of the same-lane probability of an adjacent vehicle traveling on a predicted curved travel road (cf. Fig. 4A).

[0125] More precisely, Fig. 4A, the vehicle V is traveling along an edge of an inner predicted curved travel lane of the predicted curved travel road, while an adjacent vehicle is traveling along an edge of an outer adjacent lane of the predicted curved travel road in front of the vehicle V. Information representing the predetermined standard change curve of the same-lane probability of an adjacent vehicle, shown in Fig. 5A, is stored, for example, in the ROM 41.

[0126] Fig. 5B illustrates a predetermined standard change curve of the same-lane probability of a preceding vehicle traveling in a predicted travel lane of the vehicle V ahead of the vehicle V when the predicted travel lane is a curved lane (cf. Fig. 4B).

[0127] More precisely, Fig. 4B, the vehicle V advances at an edge of the predicted curved travel lane while the preceding vehicle advances at the edge of the predicted curved travel lane in front of the vehicle V, so that the preceding vehicle is selected as a target vehicle that the vehicle V tracks. Information that represents the predetermined standard change curve of the same-lane probability of a preceding vehicle shown in Fig. 5B, is stored, for example, in the ROM 41.

[0128] Fig. Figure 5C illustrates a predetermined standard change curve of the same-lane probability of an entering vehicle traveling in an merging lane that merges into a predicted travel lane of vehicle V when the merging lane attempts to merge into the predicted travel lane (cf. Fig. 3A).

[0129] The predetermined standard change curve of the same-lane probability of an entering vehicle substantially agrees with a predetermined standard change curve of the same-lane probability of an adjacent vehicle traveling in an adjacent lane of a predicted travel lane of the vehicle V when the adjacent vehicle attempts to cut into the predicted travel lane (cf. Fig. 3B).

[0130] Information representing the predetermined standard change curve of the same-lane probability of each of an entering vehicle and an adjacent vehicle shown in Fig. 5B, is stored, for example, in the ROM 41.

[0131] In each of the Fig. 5A to 5C, a reference symbol TH represents a current value of the threshold probability.

[0132] As in Fig. 5C, because an incoming vehicle or a neighboring vehicle (cf. Fig. 3A or Fig. 3B) attempts to enter the predicted travel lane of the vehicle V in front of the vehicle V, the same-lane probability of the entering vehicle or the neighboring vehicle increases linearly. Consequently, if the same-lane probability of the entering vehicle or the neighboring vehicle (cf. Fig. 3A or Fig. 3B) is equal to or greater than the current value TH of the threshold probability at a time t1, the entering vehicle of the neighboring vehicle can be selected as a target vehicle that tracks the vehicle V.

[0133] In contrast, as in Fig. 3C, when a neighboring vehicle swerves in the vehicle width direction, the standard change curve of the same-lane probability of a swerving neighboring vehicle has a positive peak at which the swerving neighboring vehicle is closest to the predicted travel lane of the vehicle V (cf. tp in Fig. 5A).

[0134] Consequently, if the current value TH of the threshold probability for the Fig. 5C, the pulling-out neighboring vehicle would be erroneously selected as a target vehicle tracking vehicle V at a time t2, even though the pulling-out neighboring vehicle should be legally prevented from entering the predicted travel lane of vehicle V (cf. Fig. 5A).

[0135] To solve such a problem, the CPU 43 in accordance with this embodiment is programmed to, for example, in step S160, set the threshold probability to a value TH1 higher than the positive peak of the predetermined standard change curve of the same-lane probability of such a swerving vehicle shown in Fig. 5A. This makes it difficult for the neighboring vehicle pulling out to be selected as a target vehicle for tracking vehicle V.

[0136] Similarly, as in Fig. 4A, if the neighboring vehicle is traveling at the edge of the outer adjacent lane of the predicted curved road, the same-lane probability of the neighboring vehicle is likely to increase. This results in the standard change curve of the same-lane probability of such a neighboring vehicle having a positive peak at which the neighboring vehicle is traveling at the edge of the outer adjacent lane of the predicted curved road (cf. tp in Fig. 5A).

[0137] Consequently, if the current value TH of the threshold probability for the Fig. 5C, the neighboring vehicle would be erroneously selected as a target vehicle tracking the vehicle V at a time t2, even though the neighboring vehicle does not attempt to enter the predicted travel lane of the vehicle V (cf. Fig. 5A).

[0138] To solve such a problem, the CPU 43 in accordance with this embodiment is programmed to, for example, in step S160 or S170, set the threshold probability to a value TH1 higher than the positive peak of the predetermined standard change curve of the same-lane probability of such an adjacent vehicle shown in Fig. 5A. This makes it difficult for the neighboring vehicle to be selected as a target vehicle that vehicle V is tracking.

[0139] As in Fig. As shown in Figure 4B, when the preceding vehicle travels along the edge of the predicted curved travel lane in front of vehicle V, the in-lane probability of the preceding vehicle is likely to decrease. This results in the standard change curve of the in-lane probability of such a preceding vehicle having a negative peak at which the preceding vehicle travels along the edge of the predicted curved travel lane (cf. tp in Fig. 5B).

[0140] Consequently, if the current value TH of the threshold probability for the Fig. 5C, the preceding vehicle would be erroneously deselected as a target vehicle tracking the vehicle V at a time t3, even though the preceding vehicle does not attempt to perform a lane change from the predicted travel lane of the vehicle V to an adjacent lane that is adjacent to the predicted travel lane (cf. Fig. 5B).

[0141] To solve such a problem, the CPU 43 according to this embodiment is programmed to, for example, in step S160 or S170, set the threshold probability to a value TH2 lower than the negative peak of the predetermined standard change curve of the same-lane probability of such a preceding vehicle shown in Fig. 5B. This allows the preceding vehicle to be continuously selected as a target vehicle for tracking vehicle V.

[0142] On the other hand, in order to prevent a neighboring vehicle from being selected as a target vehicle tracking the vehicle V, a value THA of the threshold probability may be set to a relatively high value (cf. Fig. 5D). However, in this case, the time at which the same lane probability of an entering vehicle or a neighboring vehicle, shown in Fig. 3A or Fig. 3B, equal to or higher than the value THA of the threshold probability at time t1, compared to the aforementioned, in Fig. 5C. This may cause a driver of vehicle V to feel uncomfortable.

[0143] To solve such a problem, the CPU 43 according to this embodiment is programmed to, for example, in step S170, reduce the threshold probability to a value TH3 lower than the value THA. This allows the time at which the same-lane probability of an entering vehicle or an adjacent vehicle, shown in Fig. 3A or Fig. 3B, becomes equal to or higher than the value THA of the threshold probability, before time t1A. This prevents the driver of vehicle V from feeling uncomfortable.

[0144] Following step S170, the CPU 43 performs one of: (1) a first determination as to whether any of the other vehicles traveling around the vehicle V satisfies the at least one target vehicle selection condition if the vehicle V is not tracking any other vehicle (step 180a) (2) a second determination as to whether a preceding vehicle continuously satisfies the at least one target vehicle selection condition if the vehicle V is tracking the preceding vehicle (step S180b).

[0145] When it is determined that one of the other vehicles traveling around the vehicle V satisfies the at least one target vehicle selection condition if the vehicle V is not tracking another vehicle (YES in step S180a), the CPU 43 selects one of the other vehicles as a target vehicle that the vehicle V is tracking in step S180c.

[0146] Otherwise, if it is determined that none of the other vehicles traveling around the vehicle V satisfies the at least one target vehicle selection condition when the vehicle V is not tracking another vehicle (NO in step S180a), the CPU ends the driving support task in step S180d.

[0147] On the other hand, if it is determined that the preceding vehicle continuously satisfies the at least one target vehicle selection condition, if the vehicle V is tracking the preceding vehicle (YES in step S180b), the CPU continuously selects the preceding vehicle as the target vehicle that the vehicle V is tracking in step S180e.

[0148] Otherwise, if it is determined that the preceding vehicle does not continuously satisfy the at least one target vehicle selection condition when the vehicle V is tracking the preceding vehicle (NO in step S180b), the CPU 43 performs the above-mentioned first determination, ie, the operations in steps S180a, S180b and S180d.

[0149] Next, in step S190, as an example of driving support control, the CPU 43 performs adaptive cruise control included in the driving support task for the target vehicle tracking the vehicle V.

[0150] If no other vehicles satisfy the at least one target vehicle selection condition in step S190, the CPU 43 may perform cruise control that automatically controls the speed of the vehicle V such that the speed of the vehicle V is maintained at a constant speed set by a driver of the vehicle V.

[0151] More specifically, according to this embodiment, the CPU 43 outputs instructions for performing adaptive cruise control to the engine ECU 22 and / or the brake ECU 24. The instructions cause the engine ECU 22 to control the throttle actuator TA and / or cause the brake ECU 24 to control the first and second actuators AN1 and AN2, thereby maintaining the distance from the vehicle V to the target vehicle at approximately a predetermined target distance.

[0152] If no other vehicles satisfy the at least one target vehicle selection condition in step S290, the CPU 43 issues instructions to perform cruise control to the engine ECU 22 and / or the brake ECU 24. The instructions cause the engine ECU 22 to control the throttle actuator TA and / or cause the brake ECU 24 to control the first and second actuators AN1 and AN2, thereby maintaining the speed of the vehicle V at a constant speed specified by the driver of the vehicle V.

[0153] Furthermore, while executing the adaptive cruise control or the cruise control, the CPU 43 outputs various pieces of information about the executed adaptive cruise control or the cruise control to the meter ECU 26 in step S190. Upon receiving the various pieces of information about the adaptive cruise control or the cruise control, the meter ECU 26 displays the pieces of information about the executed adaptive cruise control or the cruise control on the one or more meter displays MD. In step S190, the CPU 43 outputs instructions to the meter ECU 26 for visually and / or audibly generating a warning when one or more predetermined conditions for generating a warning are met. Upon receiving the instructions, the meter ECU 26 outputs a visually and / or audibly warning on the one or more meter displays MD.

[0154] After the operation in step S190, the CPU 43 ends the current cycle of the driving support task and waits until the next start time for the next cycle of the driving support task is reached.

[0155] As described above, the driving support ECU 40, which serves as a device for controlling the vehicle V to track another vehicle V according to this embodiment, is configured to recognize the surroundings of a predicted travel road of the vehicle V (refer to steps S110 to S130) using at least one of (1) the digital data indicating the predictive road information sent from the predictive road condition detector 3 (2) the digital data of the vehicle condition signals output from the vehicle condition detector 10.

[0156] The driving support ECU 40 is further configured to determine whether lane changes are possible in the predicted travel road using the surroundings of the predicted travel road (see step S140).

[0157] The driving support ECU 40 is further configured to set the at least one target vehicle selection condition based on a result of the determination (see step S150 or S160).

[0158] More specifically, when it is determined that lane changes are possible in the predicted travel road (YES in step S140), the drive support ECU 40 is configured to change the at least one target vehicle selection condition such that other vehicles traveling in the vicinity of the vehicle V are more easily selectable as a target vehicle that the vehicle V is tracking (see step S150).

[0159] Otherwise, when it is determined that lane changes are not possible in the predicted travel road (NO in step S140), the drive support ECU 40 is configured to change the at least one target vehicle selection condition such that other vehicles traveling in the vicinity of the vehicle V are more difficult to select than a target vehicle that the vehicle V is tracking (see step S160).

[0160] Furthermore, the driving support ECU 40 is configured to detect the environmental conditions around the predicted travel road and correct the at least one target vehicle selection condition based on the detected environmental conditions around the predicted travel road (see step S170).

[0161] Thereafter, the driving support ECU 40 is configured to select one of the other vehicles traveling around the vehicle V as a target vehicle to track the vehicle V, provided the selected one of the other vehicles satisfies the at least one target vehicle selection condition (see step S180). After determining the target vehicle, the driving support ECU 40 is configured to perform adaptive cruise control for the target vehicle (step S190).

[0162] More precisely, when the surroundings of the predicted travel route of the vehicle V detect the first lane type of the combination of the predicted travel lane and the merging lane (cf. Fig. 3A), the driving support ECU 40 determines that it is possible for an incoming vehicle moving on the merging lane to perform a lane change (see steps S130 and S140 in Fig. 2). Then, the driving support ECU 40 changes, ie, relaxes, the at least one target vehicle selection condition such that the entering vehicle is more easily selectable as a target vehicle that the vehicle V is tracking (see step S150).

[0163] Similarly, when the surroundings of the predicted travel road of the vehicle V detect the second lane type of the combination of the predicted travel lane and an adjacent lane from which a vehicle adjacent to the vehicle V can legally and physically perform a lane change to the predicted travel lane (cf. Fig. 3B), the driving support ECU 40 determines that it is possible for a neighboring vehicle traveling in the adjacent lane to perform a lane change (see steps S130 and S140 in Fig. 2). Then, the driving support ECU 40 changes, ie, relaxes, the at least one target vehicle selection condition such that the neighboring vehicle is more easily selectable as a target vehicle that the vehicle V is tracking (see step S150).

[0164] On the other hand, when the surroundings of the predicted travel road of the vehicle V show the third lane type of the combination of the predicted travel lane and an adjacent lane from which a vehicle adjacent to the vehicle V is legally or physically prevented from making a lane change (cf. Fig. 3C), the driving support ECU 40 determines that a neighboring vehicle traveling in the adjacent lane is unable to perform a lane change (see steps S130 and S140 in Fig. 2). Then, the at least one target vehicle selection condition is changed, ie, tightened, such that the neighboring vehicle is more difficult to select than a target vehicle that the vehicle V is tracking (see step S160).

[0165] That is, the driving support ECU 40 changes the at least one target vehicle selection condition to thereby increase the probability that other vehicles traveling in the vicinity of the vehicle V are selected as a target vehicle that the vehicle V tracks when it is determined that the surroundings of the predicted travel road allow lane changes. Furthermore, the driving support ECU 40 changes the at least one target vehicle selection condition to thereby decrease the probability that other vehicles traveling in the vicinity of the vehicle V are selected as a target vehicle that the vehicle V tracks when it is determined that the surroundings of the predicted travel road do not allow lane changes.

[0166] When an adjacent vehicle or an entering vehicle is traveling on an adjacent lane or a merging lane in the predicted traveling road on which lane changes are permitted, and attempts to merge in front of the vehicle V, the driving support ECU 40 causes the adjacent vehicle or the entering vehicle to be selected as a target vehicle that the vehicle V tracks as early as possible.

[0167] On the other hand, when an adjacent vehicle is traveling on an adjacent lane in the predicted traveling road on which lane changes are prohibited, the driving support ECU 40 prevents the adjacent vehicle or the entering vehicle from being selected as a target vehicle that the vehicle V tracks even if the adjacent vehicle swerves out.

[0168] Consequently, the driving support ECU 40 improves the accuracy of detecting a vehicle other than a target vehicle that the vehicle V is tracking, and thus provides appropriate driving support to drivers without causing discomfort to the drivers due to inappropriate selection of a vehicle other than a target vehicle that the vehicle V is tracking.

[0169] Furthermore, the driving support ECU 40 is configured to correct the at least one target vehicle selection condition based on the detected environmental conditions around the predicted travel road of the vehicle V. Specifically, the driving support ECU 40 corrects the at least one target vehicle selection condition in accordance with the tracking histories for other vehicles traveling around the vehicle V, the traveling environments including the lane type of the predicted travel road and the behaviors of the surrounding vehicles. Consequently, the corrected at least one target vehicle selection condition is correctly determined in accordance with the tracking histories for other vehicles traveling around the vehicle V, the traveling environments including the lane type of the predicted travel road and the behaviors of the surrounding vehicles.

[0170] More specifically, it corrects when it is determined that the predicted travel road has a curved shape and when the predicted travel road allows lane changes (cf. Fig. 4), the driving support ECU 40 sets the at least one target vehicle selection condition to thereby make it difficult for neighboring vehicles to be selected as a target vehicle tracking the vehicle V. This prevents the neighboring vehicle traveling on the edge of the outer adjacent lane of the predicted curved road from being erroneously selected as a target vehicle tracking the vehicle V.

[0171] Furthermore, when it is determined that the vehicle V is traveling along an edge of the predicted curved traveling lane, while the preceding vehicle traveling along the edge of the predicted curved traveling lane in front of the vehicle V is selected as a target vehicle tracking the vehicle V, the driving support ECU 40 corrects the at least one target vehicle selection condition. This correction allows the preceding vehicle to be continuously selected as a target vehicle tracking the vehicle V. This provides appropriate driving assistance to drivers without causing discomfort due to the absence of the preceding vehicle as a vehicle tracking the vehicle V.

[0172] As described above, the driving support ECU 40 correctly determines the at least one target vehicle selection condition in accordance with the environmental conditions around the predicted travel road of the vehicle V.

[0173] This embodiment of the present disclosure and invention has been described, but the present disclosure and invention are not limited to the aforementioned embodiment. The embodiment can be modified within the scope of the present disclosure and invention.

[0174] For example, in step S170, the CPU 43 increases the probability that at least one of the other vehicles is selected as a target vehicle tracking the vehicle V; the at least one of the other vehicles has been selected as a target vehicle at least once. However, the present disclosure is not limited to the above-described correction.

[0175] More specifically, in step S170, the CPU 43 may maintain the probability that at least one of the other vehicles is selected as a target vehicle tracking the vehicle V in accordance with the environmental conditions around the predicted travel road of the vehicle V.

[0176] In step S170, the CPU 43 increases the probability that at least one of the other vehicles is selected as a target vehicle tracking the vehicle V; the behavior of the at least one of the other vehicles indicates an attempt to perform a lane change to the predicted travel lane of the vehicle V. However, the present disclosure is not limited to the above-described correction.

[0177] More specifically, in step S170, the CPU 43 may maintain the probability that at least one of the other vehicles is selected as a target vehicle tracking the vehicle V in accordance with the environmental conditions around the predicted travel road of the vehicle V.

[0178] In step S170, if it is determined that the predicted travel road has a curved shape and if the predicted travel road allows lane changes (see Fig. 4A), the CPU 43 adjusts the at least one target vehicle selection condition to thereby make it difficult for vehicles other than a target vehicle to be selected for tracking the vehicle V. However, the present disclosure is not limited to the above-described correction.

[0179] More specifically, in step S170, when it is determined that the predicted travel road has a curved shape and when the predicted travel road allows lane changes (see Fig. 4A), the CPU 43 performs the maintenance of the at least one target vehicle selection condition in accordance with the environmental conditions around the predicted travel route of the vehicle V.

[0180] In step S170, in the situation where the vehicle V is traveling on an edge of the predicted curved traveling lane, while the preceding vehicle traveling on the edge of the predicted curved traveling lane in front of the vehicle V is currently selected as a target vehicle tracking the vehicle V (see FIG. Fig. 4B), the CPU 43 continuously calculates the probability that the preceding vehicle traveling ahead of the vehicle V is selected as a target vehicle tracking the vehicle V. However, the present disclosure is not limited to the above-described correction.

[0181] More precisely, in the Fig. 4B, the CPU 43 maintains the probability that the preceding vehicle traveling in front of the vehicle V is continuously selected as a target vehicle tracking the vehicle V in accordance with the environmental conditions around the predicted traveling road of the vehicle V.

[0182] In step S190, the CPU 43 performs adaptive cruise control included in the driving support task for the target vehicle tracking the vehicle V as an example of driving support control, but the present disclosure is not limited to the above-described correction.

[0183] More specifically, in step S190, the CPU 43 of a driving support system according to a modification of the present disclosure may perform, as an example of driving support control, a modified adaptive cruise control included in the driving support task for the target vehicle tracking the vehicle V.

[0184] Fig. 6 schematically illustrates a routine showing the modified adaptive cruise control executed in step S190a by the CPU 43 after the operation in step S180.

[0185] More specifically, following step S180, the CPU 43 determines in step S310 whether the predicted travel road allows lane changes using the surroundings of the predicted travel road; the surroundings of the predicted travel road were detected in step S130.

[0186] If it is determined that lane changes on the predicted travel road are difficult (NO in step S310), the CPU 43 executes the processing determined in step S190 of Fig. 2 and terminates the driving support task after the termination of the operation sequence in step S190.

[0187] Otherwise, if it is determined that the predicted travel road allows lane changes (YES in step S310), the CPU 43 determines in step S320 whether the behaviors of at least one neighboring vehicle detected in step S170 show that the at least one neighboring vehicle is traveling via both the predicted travel lane and an adjacent lane.

[0188] If it is determined that the behaviors of at least one neighboring vehicle detected in step S170 do not show that the at least one neighboring vehicle is traveling across both the predicted traveling lane and an adjacent lane (NO in step S320), the CPU 43 executes the processing detected in step S190 of Fig. 2. Then, the CPU 43 terminates the driving support task after completing the operation in step S190.

[0189] Otherwise, if it is determined that the behaviors of at least one neighboring vehicle detected in step S170 show that the at least one neighboring vehicle is traveling along both the predicted traveling road and an adjacent traveling lane (YES in step S320), the CPU 43 restricts the acceleration of the vehicle V in step S330. For example, the acceleration limiting control executed in step S330 is configured to control, for example, the throttle actuator TA via the engine ECU 22 and thereby limit or prohibit the acceleration of the vehicle V. More specifically, the CPU 43 may execute the control executed in step S190 of Fig. 2 while performing the acceleration limit control in step S330.

[0190] After completing the operation in step S330, the CPU 43 terminates the driving support task.

[0191] As described above, according to the modification, the driving support ECU 40 is configured to perform the acceleration limiting task to limit or prohibit the acceleration of the vehicle V when it is determined that the predicted traveling road permits lane changes. This leads to an improvement in the driving safety of the vehicle V.

[0192] More specifically, if it is determined that the predicted travel road allows lane changes, there is a possibility that another vehicle traveling in a lane adjacent to the predicted travel lane of vehicle V will perform a lane change from the adjacent lane to the predicted travel lane in front of vehicle V. Consequently, if another vehicle traveling in the adjacent lane were to merge in front of vehicle V from the adjacent lane while vehicle V was accelerating, the driving safety of vehicle V and the other vehicle would be compromised.

[0193] In view of the circumstances, the driving support ECU 40 is configured in accordance with the modification to perform the acceleration limiting control to limit or prevent acceleration of the vehicle V, which leads to improvement in driving safety of the vehicle V and that of the merging vehicle.

[0194] Preferably, in accordance with the modification, the driving support ECU is configured to perform the acceleration limiting task to limit or prevent the acceleration of the vehicle V when it is determined that the predicted travel road allows lane changes and the at least one adjacent vehicle travels across both the predicted travel lane and an adjacent lane.

[0195] That is, if another vehicle is moving across the predicted travel lane of vehicle V and a lane adjacent to the predicted travel lane, there is a high possibility or probability that the other vehicle will perform a lane change from the adjacent lane to the predicted travel lane.

[0196] Consequently, according to the modification, the driving support ECU is capable of performing the acceleration limiting task to limit or prevent the acceleration of the vehicle V when it detects that at least one adjacent vehicle is traveling across both the predicted travel lane and the adjacent lane. This improves the driving safety of the vehicle V and the merging vehicle while satisfying the driver's intention to accelerate the vehicle V as much as possible.

[0197] The driving support ECU according to the modification is configured to perform the acceleration limit control in step S330 when it is determined that the predicted travel road allows lane changes and the at least one adjacent vehicle is traveling across both the predicted travel lane and an adjacent lane. However, the present disclosure is not limited to this configuration.

[0198] Specifically, according to the modification in step S330, the CPU 43 of the driving support system may perform deceleration control to decelerate the vehicle V when it is determined that the predicted travel road permits lane changes and the at least one adjacent vehicle is traveling across both the predicted travel lane and an adjacent lane. For example, the CPU 43 controls the first and second hydraulic actuators AN1 and AN2 via the brake ECU 24, thereby decelerating the vehicle V.

[0199] In step S330, the CPU 43 of the driving support system may advance or retard the acceleration timing of the vehicle V according to the modification to prevent the adjacent vehicle merging into the predicted travel road from having any adverse effect on the vehicle V. In step S330, the CPU 43 may advance or retard the deceleration timing of the vehicle V to prevent the adjacent vehicle merging into the predicted travel road from having any adverse effect on the vehicle V.

[0200] In step S330, the CPU 43 of the driving support system may output visual and / or audible warnings via the meter displays MD and the meter ECU 26 in accordance with the modification; the visible and / or audible warnings indicate that an adjacent vehicle is likely to merge in front of the vehicle V. In step S330, the CPU 43 may advance or delay the output timing of the visible and / or audible warnings to prevent the vehicle merging into the predicted travel road from having any effect on the vehicle V.

[0201] In step S330, the driving support ECU 40 according to the modification may be configured to, in accordance with the environmental conditions around the predicted traveling road, one of (1) the acceleration limit control (2) the delay control (3) the control of changing the acceleration or deceleration time (4) controlling the issuance of visible and / or audible warnings (5) the control of changing the timing of the output of the visible and / or audible warnings.

[0202] Furthermore, according to the embodiment and the modification, the driving support ECU 40 is configured to separately perform the change of the at least one target vehicle selection condition and the correction of the at least one target vehicle selection condition, but the present disclosure is not limited thereto.

[0203] More precisely, Fig. 7 schematically illustrates a part of a modified driving support task executed by the CPU 43 of the driving support ECU 40 in accordance with another modification.

[0204] As in Fig. 7, the CPU 43, after the operation in step S130, detects in step S140a environmental conditions, ie, conditions of the surrounding traffic, around the predicted travel route (cf. step S170 in Fig. 2).

[0205] Following step S140a, the CPU 43 determines in step S140b whether the predicted travel road allows lane changes using the surroundings of the predicted travel road (see step S140 in Fig. 2).

[0206] Next, in step S200, the CPU 43 sets the at least one target vehicle selection condition based on the detected environmental conditions and the result of the determination in step S140b.

[0207] For example, as described above, the CPU 43 changes, ie, tightens, the at least one target vehicle selection condition such that other vehicles traveling in the vicinity of the vehicle V are more difficult to select as a target vehicle that the vehicle is tracking, if it is determined that (1) the predicted route does not allow lane changes (2) vehicle V is not tracking any other vehicle.

[0208] As another example, as described above, the CPU 43 changes, ie, relaxes, the at least one target vehicle selection condition for a preceding vehicle traveling ahead of the vehicle V in the same lane to facilitate the preceding vehicle being continuously selected as the target vehicle tracking the vehicle V when it is determined that (1) the predicted route does not allow lane changes (2) the vehicle V is currently tracking the vehicle in front.

[0209] The driving support system according to each of the embodiment and the modification is configured to change or correct the threshold probability to thereby change or correct the at least one target vehicle selection condition, but the present disclosure is not limited to this configuration.

[0210] More specifically, the driving support system according to the embodiment and each of the modifications may be configured to change or correct a value of the same-lane probability of each of the other vehicles traveling around the vehicle V, to thereby change or correct the at least one target vehicle selection condition of a corresponding one of the other vehicles.

[0211] Furthermore, according to the embodiment and any of the modifications, the driving assistance system may be configured to change or correct the target vehicle selection condition in any of several methods. Specifically, the methods allow the driving assistance system to change or correct the at least one target vehicle selection condition such that other vehicles traveling in the vicinity of the vehicle V that are less likely or heavier than a target vehicle tracking the vehicle V are selectable when it is determined that the predicted travel road does not allow lane changes.

[0212] The driving assistance system according to the embodiment is configured to perform adaptive cruise control or cruise control as an example of driving assistance control, but the present disclosure is not limited thereto. Specifically, the driving assistance system according to the embodiment and the modification may be configured to perform lane departure prevention assistance control.

[0213] The lane departure prevention support control is configured to (1) to recognize the shape of a predicted travel lane on which the vehicle V is predicted to travel, which corresponds to a current travel lane of the vehicle V (see, for example, step S130 of Fig. 2) (2) to keep the vehicle V moving within the predicted travel lane, and thereby prevent the vehicle V from leaving the predicted travel lane.

[0214] The vehicle condition detector 10 is equipped with the yaw rate sensor 12, the wheel speed sensors 14, and the steering angle sensor 16, but the present disclosure is not limited to this structure. Specifically, the vehicle condition detector 10 may be equipped with the yaw rate sensor 12 and the wheel speed sensors 14, thereby omitting the steering angle sensor 16, or may be equipped with the wheel speed sensors 14 and the steering angle sensor 16, thereby omitting the yaw rate sensor 12. Specifically, the vehicle condition detector 10 according to the present disclosure is preferably equipped with at least a first sensor for measuring the steering angle of the vehicle V and a second sensor for measuring the speed of the vehicle V.

[0215] From the driving support system according to the embodiment and each of the modifications, the vehicle state detector may be eliminated.

[0216] While the illustrative embodiment of the present disclosure or invention has been described herein, the present disclosure or invention is not limited to the embodiment described herein, but includes any and all embodiments with modifications, omissions, combinations (e.g., of aspects across different embodiments), adaptations, and / or alternations as may be apparent to one of ordinary skill in the art based on the present disclosure. The limitations in the claims are to be interpreted broadly based on the language used in the claims and are not limited to examples described in the present specification or during the probation phase of the application, which examples are to be construed as non-exclusive.

Claims

[1] Device (1) for controlling a vehicle (V) to track another vehicle, comprising: a detector (3) that detects other vehicles that exist in the vicinity of the controlled vehicle; a target vehicle tracking initiating device (40, S180a, S180b, S190) arranged to cause the controlled vehicle to track one of the other vehicles as a target vehicle if one of the other vehicles satisfies a predetermined target vehicle selection condition, the predetermined target vehicle selection condition being necessary for selecting one of the other vehicles as a target vehicle; a travel road environment recognition device (40, S110 to S130) arranged to recognize an environment of a predicted travel road on which the controlled vehicle is predicted to travel using conditions of the predicted travel road; a lane change permission determining device (40, S140, S140b) arranged to determine whether the predicted road permits lane changes on the basis of the detected surroundings of the predicted road; and a target vehicle selection condition setting device (40; S150, S160, S200) arranged to set the target vehicle selection condition based on a result of the determination, wherein the target vehicle selection condition setting device is configured to: detect the surrounding traffic conditions around the predicted route; correct the target vehicle selection condition based on the detected surrounding traffic conditions; to have stored therein a tracking history for each of the other vehicles, the tracking history of each of the other vehicles representing whether a corresponding one of the other vehicles has been selected as the target vehicle; the tracking history for each of the vehicles other than the surrounding traffic conditions to identify the predicted route; and correct the target vehicle selection condition for each of the other vehicles based on the tracking history for a corresponding one of the other vehicles. [2] The apparatus according to claim 1, wherein the target vehicle selection condition setting means is configured to change the target vehicle selection condition so as to make it difficult to select the other vehicles as the target vehicle when it is determined that the predicted travel road does not allow lane changes. [3] The apparatus according to claim 1 or 2, wherein the target vehicle selection condition setting means is configured to change the target vehicle selection condition to increase a possibility that each of the other vehicles is selected as a target vehicle when it is determined that the predicted travel road allows lane changes. [4] The apparatus according to claim 1, wherein the environment of the predicted travel road includes a shape of the predicted travel road, and the target vehicle selection condition setting means is configured to: the shape of the predicted route as the ambient traffic conditions around the predicted route; and to correct the target vehicle selection condition based on the shape of the predicted road. [5] The apparatus according to claim 1, wherein the target vehicle selection condition setting means is configured to: detecting the behavior of each of the other vehicles as the surrounding traffic conditions around the predicted route; and correct the target vehicle selection condition for each of the other vehicles based on the behavior of a corresponding one of the other vehicles. [6] Device according to one of claims 1 to 5, further comprising: an acceleration limiting device (40, S310 to S330) arranged to limit the acceleration of the controlled vehicle when it is determined that the predicted road allows lane changes. [7] The apparatus according to claim 6, wherein, when the controlled vehicle is predicted to travel on a predicted travel lane included in the predicted travel road, the acceleration limiting means is configured to: to recognize the behavior of each of the other vehicles; determine, based on the behavior of each of the other vehicles, whether at least one of the other vehicles is traveling across both the predicted travel lane and a lane adjacent to the predicted travel lane; and to limit the acceleration of the controlled vehicle if it is determined that: the predicted route allows lane changes, and at least one of the other vehicles is moving across both the predicted travel lane and a lane adjacent to the predicted travel lane. [8] The apparatus according to any one of claims 1 to 7, wherein, when the controlled vehicle is predicted to travel on a predicted travel lane included in the predicted travel road, the at least one target vehicle selection condition includes a condition that a same-lane probability of each of the other vehicles is equal to or higher than a threshold probability, wherein the same-lane probability of each of the other vehicles is defined as a probability that a corresponding one of the other vehicles is moving ahead of the controlled vehicle in the predicted travel lane of the controlled vehicle; and the target vehicle selection condition setting means is configured to increase the threshold probability such that selecting the other vehicles as the target vehicle is made more difficult when it is determined that the predicted travel road does not allow lane changes. [9] Apparatus according to claim 8, wherein: the target vehicle selection condition setting means is configured to decrease the threshold probability to increase a possibility that each of the other vehicles is selected as a target vehicle when it is determined that the predicted travel road allows lane changes. [10] Apparatus according to claim 8, wherein: the detector is configured to detect a position of each of the other vehicles; and the lane change permission detection device is configured to: detect, based on the position of each of the other vehicles, a distance of movement of each of the other vehicles near the predicted travel lane in a width direction of the controlled vehicle; and a lateral speed of movement of each of the other vehicles near the predicted travel lane in the width direction of the controlled vehicle; and calculate a value of the same-lane probability of each of the other vehicles based on the detected distance of movement and the detected lateral speed of movement of a corresponding one of the other vehicles. [11] Computer program product for a device (1) for controlling a vehicle (V) to track another vehicle, the device including a detector (3) that detects other vehicles that exist adjacent to the controlled vehicle, and the computer program product including: a computer-readable storage medium (41, 42); and a set of computer program instructions embedded in the computer-readable storage medium, the instructions causing a computer (43): causing the controlled vehicle to track one of the other vehicles as a target vehicle if one of the other vehicles satisfies a predetermined target vehicle selection condition, the predetermined target vehicle selection condition being necessary for selecting one of the other vehicles as a target vehicle; Detecting an environment of a predicted route for which the controlled vehicle is predicted to travel using conditions of the predicted route; Determine whether the predicted route allows lane changes based on the detected environment of the predicted route; and Setting the target vehicle selection condition based on a result of the determination, wherein setting the target vehicle selection condition comprises: Detecting the ambient traffic conditions around the predicted route; Correcting the target vehicle selection condition based on the detected surrounding traffic conditions; to have stored a tracking history for each of the other vehicles, the tracking history of each of the other vehicles representing whether a corresponding one of the other vehicles was selected as the target vehicle; Recognizing the tracking history for each of the vehicles other than the ambient traffic conditions around the predicted route; and Correcting the target vehicle selection condition for each of the other vehicles based on the tracking history for a corresponding one of the other vehicles. [12] The computer program product of claim 11, wherein the instructions cause a computer to change the target vehicle selection condition such that selecting the other vehicles as the target vehicle is made more difficult when it is determined that the predicted road does not allow lane changes. [13] The computer program product of claim 12, wherein the instructions cause a computer to change the target vehicle selection condition such that a possibility of selecting the other vehicles as the target vehicle is increased when it is determined that the predicted travel road allows lane changes.

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