CN111158372B - Electric automobile automatic driving method based on fuzzy controller - Google Patents
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Abstract
The invention discloses an automatic driving method of an electric automobile based on a fuzzy controller, which is characterized in that on the basis of installing a front side radar set on a head of the automobile, another two sets of radars and the fuzzy controller are added, the two groups of radars are respectively a left side radar group and a right side radar group, each group is provided with two radars which are arranged on the automobile body above four wheels of the automobile, the added radar groups are beneficial to quickly identifying lane states and restoring driving environments under various severe driving environments, the safety of the automobile and other running vehicles is ensured, and the adopted fuzzy controller is a mathematical model preset according to driving experiences, the fuzzy control method has the advantages that driving habits of drivers can be well simulated by fuzzifying all driving environments, meanwhile, the fuzzy controller is low in requirement on the operation speed of the central controller, rapidity of a system can be improved, and quick response of control decision is facilitated. The method can improve the rapidity of restoring the driving environment and reduce the danger, thereby improving the road traffic safety performance.
Description
Technical Field
The invention relates to the technical field of electric automobiles, in particular to an automatic driving method of an electric automobile based on a fuzzy controller.
Background
The electric automobile is one of the important directions of the current vehicle development, and the motor has the advantages of high response speed, good controllability and the like, and is becoming an important choice for replacing the traditional gasoline engine and diesel engine. In order to reduce human error in driving, automated driving is one of the important development directions of vehicle technology. The automatic driving aims to calculate an expected track through navigation and track the expected track, and control a vehicle through a tracked point to realize automatic driving so as to reduce errors caused by manual operation as much as possible. The complexity and variability of the driving environment require operations such as acceleration and deceleration, left-right parallel adjustment, etc. to be performed on an expected path of the controlled vehicle during the driving process.
The automatic driving system based on vision or images has poor working performance under dark or certain conditions and limited performance of restoring driving environment, and meanwhile, the quality of an image processing algorithm is also one of important reasons influencing the automatic driving system, so that the response speed of the control system is easily reduced. Since the performance of the radar is less affected by the environment, it has good performance in detecting objects that are stationary or moving on the travel path. The automatic driving system aims to safely drive on an expected track, driving modes are generally divided into straight driving, left turning, right turning and reverse driving, safety is a fuzzy concept, for example, driving distance is controlled at a proper distance, and an accurate speed tracking system is not suitable for driving environments.
Disclosure of Invention
The invention aims to overcome the defects and shortcomings of the prior art, and provides an automatic driving method of an electric automobile based on a fuzzy controller, which is beneficial to quickly identifying lane states and restoring driving environments under various severe driving environments through an additional radar set, ensures the safety of vehicles and other driving vehicles, and is low in requirement on the calculation speed of a central controller based on the fuzzy controller, capable of improving the rapidity of the system, beneficial to quick response of control decisions, reducing the danger in a manual driving mode and improving the road traffic safety performance.
In order to achieve the purpose, the technical scheme provided by the invention is as follows: a fuzzy controller based automatic driving method for an electric vehicle comprises the steps that firstly, a front side radar group is installed on a vehicle head and consists of two radars which are respectively arranged beside a left front lamp and a right front lamp, the detected vehicle distance is Fd, Fd is min { Fd1(k), Fd2(k) }, Fd1(k) and Fd2(k) are respectively the vehicle distance detected by the two radars of the front side radar group in the k-th period, in addition, two groups of radars and a fuzzy controller are additionally arranged, the two groups of radars are respectively a left side radar group and a right side radar group, each group of radar group is respectively provided with two radars, the two groups of radars are installed on the vehicle body above four wheels of the electric vehicle, and Ld1(k), Ld2(k), Rd1(k) and Rd2(k) are respectively the obstacle distances detected by the left side radar group and the right side radar group in the k-th period; the fuzzy controller fuzzifies each driving environment according to a preset mathematical model of driving experience; the automatic driving method of the electric automobile comprises the following steps:
1) after a driver sets a destination, a navigation system gives an expected running track, lane conditions and road speed limit of a controlled vehicle, then a fuzzy controller tracks the expected track, and the controlled vehicle carries out vehicle following, line combining and overtaking, left-right turning and turning operations according to a driving environment in the track tracking process;
2) the fuzzy controller preferentially executes following operation, fuzzifies the vehicle distance into five conditions of no vehicle running ahead, large vehicle distance, proper vehicle distance, small vehicle distance and too small vehicle distance according to the vehicle distance and the running speed detected by the front side radar group and driving experience, fuzzifies control signals of a motor and a steering gear of the electric vehicle into five conditions of speed limit running along a road, speed increase, vehicle speed stabilization, light braking and heavy braking, carries out following running operation according to the running environment, executes step 3) when an expected track prompts that a controlled vehicle needs to be subjected to left doubling or left turning, and executes step 4) when the expected track prompts that the controlled vehicle needs to be subjected to right doubling or right turning;
3) when the controlled vehicle realizes stable following running, if the running speed v and the speed limit vmaxWhen the difference is greater than a specified threshold value, the fuzzy controller judges that the passing efficiency of the controlled vehicle running along with the vehicle is poor, if the left side radar group identifies that the left side lane state is good, the fuzzy controller realizes merging and overtaking by using the steering gear, meanwhile, the controlled vehicle continues to run along with the vehicle after overtaking is finished, and the step 2 is executed), otherwise, the controlled vehicle stops merging, keeps running on the original lane, and executes the step 2);
4) when the expected track needs to turn right or stop at the side, the controlled vehicle is merged to the right, the fuzzy controller realizes the merging function according to the state of the right lane, if the radar group on the right side identifies that the state of the right lane is good, the right turning or the side-approaching parking operation is executed, the controlled vehicle continues to execute the following running after completing the right merging, the step 2) is executed, otherwise, the controlled vehicle stops merging, the original lane running is kept, and the step 2) is executed again.
In step 1), the expected trajectory is a control target for the controlled vehicle to travel, the lane condition is used for judging whether the controlled vehicle can be in a parallel line state or a left-right turning state, and the road speed limit is the maximum speed at which the controlled vehicle travels and is an expected travel speed at which the controlled vehicle travels without a vehicle in front.
In step 2), the fuzzy controller fuzzifies into five conditions according to the vehicle distance Fd and the running speed v, Fd/v>5s is the forward no-vehicle running condition, 3.5s<Fd/v<5s is the case of a large vehicle distance, 2.5s<Fd/v<3.5s is the proper distance, 1.5s<Fd/v<2.5s is the case of small vehicle distance, Fd/v<1.5s is the situation that the distance is too small; the vehicle with controlled automatic driving requirement can realize the following driving function according to the driving environment, the actuator of the system is an electric motor, the fuzzy controller fuzzes the control signal of the electric motor into five conditions, and the current driving speed is set as vdWith an expected vehicle speed ve：ve>2*vdThe vehicle runs along the road at a limited speed; 1.1 vd<ve<2*vdThe speed of the controlled vehicle is increased; 0.9 vd<ve<1.1*vdThe controlled vehicle stabilizes the speed; 0.5 vd<ve<0.9*vdThe controlled vehicle is lightly braked; v. ofe<0.2*vdEmergency braking of the controlled vehicle;
wherein, the control rule of the fuzzy controller is described as follows:
defining the distance error e of traveldComprises the following steps: e.g. of the typedAnd Fd/v-3, the following vehicle running control rule is as follows: when e isd>When 0, the controlled vehicle accelerates by using an accelerator pedal, edThe larger the propulsion is, the stronger the propulsion is; when e isd<At 0, the controlled vehicle is decelerated by the brake pedal and the motor, edThe smaller the braking force, the stronger the necessary safety distance is ensured.
In the step 2), when the vehicle distance Fd and the running speed v detected by the front side radar group meet Fd/v >5s, the fuzzy controller judges that the controlled vehicle is in a front vehicle-free running condition, the road speed limit is used as the input of a vehicle speed control system, the controlled vehicle runs along the road speed limit, and the road passing efficiency is effectively improved on the premise of ensuring safe running.
In step 3), after the controlled vehicle realizes stable following driving, if the driving speed v and the road speed limit vmaxSatisfy v/vmax<70%, the efficiency of the road running with the following vehicle is poor, let Ld1(k), Ld2(k), Ld1(k-1), Ld2(k-1) be the obstacle distance detected by the left radar group at the k and k-1 sampling period respectively, T is the sampling period, DL is the necessary transverse distance generated by lane change, defined as the lane width, if the left lane state satisfies the following condition:
Ld1(k)＞DL
Ld2(k)＞DL
the fuzzy controller judges that the left lane of the controlled vehicle is in good state, can be subjected to line doubling, realizes line doubling and overtaking by using a steering gear of the vehicle, continues to execute following driving after overtaking is finished, and executes the step 2); if the condition is not met, the controlled vehicles stop merging, the original lane is kept to run, and the step 2) is continuously executed.
In step 4), when the controlled vehicle needs to stop or turn right according to the given track of the navigation system to change lanes to the right, let Rd1(k), Rd2(k), Rd1(k-1) and Rd2(k-1) be the obstacle distances detected by the right radar group in the k-th and k-1-th sampling periods respectively, T be the sampling period, DL be the necessary transverse distance for lane change, defined as the lane width, if the right lane state satisfies the following conditions:
Rd1(k)＞DL
Rd2(k)＞DL
the fuzzy controller judges that the right lane of the controlled vehicle is in good state and can be doubled, the doubling operation is realized by using a steering gear of the vehicle, the following driving is continuously executed after the right doubling is finished, and the step 2) is executed; if the condition is not met, the controlled vehicles stop merging, the original lane is kept to run, and the step 2) is continuously executed.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. two groups of radars are added, the frequency is high, the driving environment is easily and quickly restored, and the safety of a controlled vehicle and other running vehicles is guaranteed.
2. The radar is easy to assemble and apply in engineering, and meanwhile, the software performance requirement is low, a large number of algorithms do not need to be developed, and the radar can be integrated in a vehicle-mounted system.
3. The radar is little influenced by the conditions such as lighting condition, contrast ratio and the like, can work under various severe driving environments, and can identify the lane state.
4. The fuzzy controller is used for meeting the requirement on the operation speed of the central processing unit, only the distance value returned by the radar group in a period of sampling period needs to be processed, the image does not need to be processed, the rapidity of the system can be improved, and the quick response of control decision is facilitated.
5. The fuzzy controller is designed, parameters are preset according to driving experience, and the driving habit of a driver can be well simulated without learning a large number of samples.
Drawings
Fig. 1 is a schematic view of the assembly of an autonomous radar set, in which the Wheel Base is the vehicle Wheel Base, the Tread is the vehicle Wheel Base, and the Width is the vehicle Width.
FIG. 2 is a schematic diagram of an expected trajectory of an autopilot output.
Fig. 3 is a fuzzification schematic of a fuzzy controller.
Fig. 4 is a schematic diagram of a control strategy when no vehicle is driving ahead during autonomous driving.
Fig. 5 is a schematic diagram of a control strategy for performing a parallel overtaking operation during automatic driving.
Fig. 6 is a schematic diagram of left/right lane state detection in automatic driving.
Detailed Description
The present invention will be further described with reference to the following specific examples.
The assembly diagram of the autonomous driving radar set shown in fig. 1 shows that a front side radar set is installed at the vehicle head, and consists of two radars Fd1 and Fd2 respectively arranged beside the left and right front lamps, and two sets of radars are additionally arranged, namely a left side radar set (comprising two radars Ld1 and Ld2) and a right side radar set (comprising two radars Rd1 and Rd2) respectively, and are installed on the vehicle body above four wheels of the electric vehicle, the vehicle distance detected by the front side radar set is Fd, Fd min { Fd1(k), Fd2(k) }, Fd1(k) and Fd2(k) are respectively the vehicle distance detected by the two radars of the front side radar set in the k-th period.
Let Ld1(k), Ld2(k), Ld1(k-1), Ld2(k-1) be the obstacle distance detected by the left radar group at the k and k-1 sampling periods, respectively, T be the sampling period, DL be the necessary lateral distance generated by lane change, defined as the lane width, and the conditions of the left lane safe lane change are as follows:
Ld1(k)＞DL
Ld2(k)＞DL
let Rd1(k), Rd2(k), Rd1(k-1) and Rd2(k-1) be the obstacle distances detected by the right radar group at the k and k-1 sampling periods, respectively, T be the sampling period, DL be the necessary transverse distance for lane change, defined as the lane width, and the conditions for safe lane change of the right lane are as follows:
Rd1(k)＞DL
Rd2(k)＞DL
when a controlled vehicle runs according to an expected track given by navigation, a radar group starts to detect the distances between obstacles in front and on the left and right sides, and at this time, the method for automatically driving the electric vehicle based on the fuzzy controller provided by the embodiment specifically comprises the following steps:
1) after a driver sets a destination, a navigation system gives an expected running track, lane conditions and road speed limit of a controlled vehicle, then a fuzzy controller tracks the expected track, and the controlled vehicle carries out vehicle following, line combining and overtaking, left-right turning and turning operations according to a driving environment in the track tracking process.
2) The fuzzy controller preferentially executes following operation, fuzzifies the vehicle distance into five conditions of no vehicle running ahead, large vehicle distance, proper vehicle distance, small vehicle distance and undersize vehicle distance according to the vehicle distance and the running speed detected by the front side radar group and according to the driving experience, and fuzzifies control signals of a differential motor and a steering gear of the electric vehicle into five conditions of speed limiting running along a road, speed increasing, vehicle speed stabilizing, light braking and heavy braking. And the fuzzy controller carries out vehicle following running operation according to the running environment. When the expected track indicates that the controlled vehicle needs to be left-jointed or turned left, executing the step 3); step 4) is executed when the expected track indicates that the controlled vehicle needs to be right-handed and parallel or right-handed.
3) When the controlled vehicle realizes stable following running, if the running speed v and the speed limit vmaxWhen the difference is greater than a specified threshold value, the fuzzy controller judges that the passing efficiency of the controlled vehicle for following the vehicle is poor, if the left side radar identifies that the left side lane state is good, the fuzzy controller realizes the parallel line overtaking by using the steering gear, and meanwhile, the following vehicle is continuously driven after the overtaking is finished, and the step 2 is executed); otherwise, the controlled vehicles stop merging, keep the original lane to run, and then execute the step 2).
4) When the expected track needs to turn right or stop along the side, the controlled vehicle is merged to the right, the controller realizes the merging function according to the state of the right lane, if the right radar identifies that the state of the right lane is good, the controller executes the operation of turning right or stopping along the side, and the controlled vehicle continues to execute the following running after completing the rightward merging, and the step 2 is executed); otherwise, the controlled vehicles stop merging, keep the original lane to run, and then execute the step 2).
Specifically, after the driver sets the destination, the navigation system gives the expected track, lane condition and road speed limit of the controlled vehicle, as shown in fig. 2, and then the fuzzy controller tracks the expected track, the expected track is composed of a plurality of points (x [ n ], y [ n ]) of a two-dimensional plane determined by positioning, and in the track tracking process, the controlled vehicle performs following, merging and overtaking, left-right turning and turning around operations according to the driving environment.
After the driver sets the destination and the expected track is given by the navigation system, the controlled vehicle executes step 2), in the step 2), as shown in fig. 3, the fuzzy controller fuzzes into five conditions according to the distance Fd returned by the front radar group and the running speed v, a: fd/v>5s is the front vehicle-free running condition, B: 3.5s<Fd/v<5s is the larger vehicle distance, C: 2.5s<Fd/v<3.5s is the appropriate vehicle distance, D: 1.5s<Fd/v<2.5s is the case of small vehicle distance, E: fd/v<And 1.5s is the case of the undersized vehicle distance. The automatic driving request controlled vehicle can realize the following driving function according to the driving environment, the actuator of the system is an electric motor, the controller fuzzes the control signal of the electric motor into five conditions, and the current driving speed is assumed as vdWith an expected vehicle speed ve：I、ve>2*vdThe controlled vehicle runs along the road at a limited speed; II. 1.1 vd<ve<2*vdThe speed of the controlled vehicle is increased; III, 0.9 vd<ve<1.1*vdThe controlled vehicle stabilizes the speed; IV, 0.5 vd<ve<0.9*vdThe controlled vehicle is lightly braked; v, ve<0.2*vdAnd the controlled vehicle is emergently braked.
The control rules of the fuzzy controller are described as follows: defining the distance error of the running as edAnd Fd/v-3, the following vehicle running control rule is as follows: when e isd>When 0, the controlled vehicle accelerates by using an accelerator pedal, edThe larger the propulsion force. When e isd<At 0, the controlled vehicle is decelerated by the brake pedal and the motor, edThe smaller the braking force, the stronger the necessary safety distance is ensured.
The fuzzy controller carries out weighted summation on the expected speed and the current running speed according to a preset membership function according to a control rule to complete defuzzification, so that the motor and the steering gear are controlled.
In the step 2), if Fd/v is the case a, the expected speed meets the case I, the controlled vehicle drives along the road at the speed limit, and the speed tracks the road speed limit, so as to improve the road traffic efficiency on the premise of ensuring the safety, as shown in fig. 4.
In the step 3), after the controlled vehicle realizes stable following running, if the running speed v and the road speed limit v are reachedmaxSatisfy v/vmax<70%, the efficiency of the road running with the vehicle is poor, and at the same time, the navigation system recognizes that the left lane can run and the current road can be merged, as shown in fig. 5, let Ld1(k), Ld2(k), Ld1(k-1), Ld2(k-1) be the obstacle distance detected by the left radar group in the k and k-1 sampling periods, T be the sampling period, DL be the necessary lateral distance generated by lane change, defined as the lane width, if the left lane state satisfies the following conditions:
Ld1(k)＞DL
Ld2(k)＞DL
the fuzzy controller judges that the left lane of the controlled vehicle is in good condition, and can merge to realize the merging overtaking by using the steering gear, as shown in fig. 5.
In the step 4), taking right merging as an example, when the controlled vehicle needs to stop or turn right according to the given track of the navigation system, and the navigation system recognizes that the right lane can be driven, and the current road can be merged to change lanes to the right, if the right lane state satisfies the following conditions:
Rd1(k)＞DL
Rd2(k)＞DL
the fuzzy controller judges that the right lane of the controlled vehicle is in good condition, and can perform merging operation by using the steering gear, as shown in fig. 6, DL is a necessary lateral distance for lane change and is defined as a lane width.
The above-mentioned embodiments are merely preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, so that the changes in the shape and principle of the present invention should be covered within the protection scope of the present invention.
Claims (5)
1. An electric automobile automatic driving method based on a fuzzy controller is characterized in that: firstly, a front side radar group is installed on a vehicle head and consists of two radars which are respectively arranged beside a left front lamp and a right front lamp, the detected vehicle distance is Fd, wherein Fd is min { Fd1(k), Fd2(k) }, Fd1(k) and Fd2(k) are respectively the vehicle distance detected by the two radars of the front side radar group in the k-th period, in addition, two groups of radars and a fuzzy controller are additionally arranged, the two groups of radars are respectively a left side radar group and a right side radar group, each group of radar group is respectively provided with two radars, the two radars are installed on the vehicle body above four wheels of the electric vehicle, and Ld1(k), Ld2(k), 1(k) and Rd2(k) are respectively the obstacle distances detected by the left side radar group and the right side radar group in the k-th period; the fuzzy controller fuzzifies each driving environment according to a preset mathematical model of driving experience; the automatic driving method of the electric automobile comprises the following steps:
1) after a driver sets a destination, a navigation system gives an expected running track, lane conditions and road speed limit of a controlled vehicle, then a fuzzy controller tracks the expected track, and the controlled vehicle carries out vehicle following, line combining and overtaking, left-right turning and turning operations according to a driving environment in the track tracking process;
2) the fuzzy controller preferentially executes following operation, fuzzifies the vehicle distance into five conditions of no vehicle running ahead, large vehicle distance, proper vehicle distance, small vehicle distance and too small vehicle distance according to the vehicle distance and the running speed detected by the front side radar group and driving experience, fuzzifies control signals of a motor and a steering gear of the electric vehicle into five conditions of speed limit running along a road, speed increase, vehicle speed stabilization, light braking and heavy braking, carries out following running operation according to the running environment, executes step 3) when an expected track prompts that a controlled vehicle needs to be subjected to left doubling or left turning, and executes step 4) when the expected track prompts that the controlled vehicle needs to be subjected to right doubling or right turning;
3) when the controlled vehicle is stableAfter following the vehicle, if the driving speed v and the speed limit vmaxWhen the difference is greater than a specified threshold value, the fuzzy controller judges that the passing efficiency of the controlled vehicle running along with the vehicle is poor, if the left side radar group identifies that the left side lane state is good, the fuzzy controller realizes merging and overtaking by using the steering gear, meanwhile, the controlled vehicle continues to run along with the vehicle after overtaking is finished, and the step 2 is executed), otherwise, the controlled vehicle stops merging, keeps running on the original lane, and executes the step 2);
when the controlled vehicle realizes stable following running, if the running speed v and the road speed limit vmaxSatisfy v/vmax<70%, the efficiency of the road running with the following vehicle is poor, let Ld1(k), Ld2(k), Ld1(k-1), Ld2(k-1) be the obstacle distance detected by the left radar group at the k and k-1 sampling period respectively, T is the sampling period, DL is the necessary transverse distance generated by lane change, defined as the lane width, if the left lane state satisfies the following condition:
Ld1(k)＞DL
Ld2(k)＞DL
the fuzzy controller judges that the left lane of the controlled vehicle is in good state, can be subjected to line doubling, realizes line doubling and overtaking by using a steering gear of the vehicle, continues to execute following driving after overtaking is finished, and executes the step 2); if the condition is not met, the controlled vehicles stop merging, the original lane is kept to run, and the step 2) is continuously executed;
4) when the expected track needs to turn right or stop at the side, the controlled vehicle is merged to the right, the fuzzy controller realizes the merging function according to the state of the right lane, if the radar group on the right side identifies that the state of the right lane is good, the right turning or the side-approaching parking operation is executed, the controlled vehicle continues to execute the following running after completing the right merging, the step 2) is executed, otherwise, the controlled vehicle stops merging, the original lane running is kept, and the step 2) is executed again.
2. The fuzzy controller-based automatic driving method for the electric vehicle according to claim 1, wherein: in step 1), the expected trajectory is a control target for the controlled vehicle to travel, the lane condition is used for judging whether the controlled vehicle can be in a parallel line state or a left-right turning state, and the road speed limit is the maximum speed at which the controlled vehicle travels and is an expected travel speed at which the controlled vehicle travels without a vehicle in front.
3. The fuzzy controller-based automatic driving method for the electric vehicle according to claim 1, wherein: in step 2), the fuzzy controller fuzzifies into five conditions according to the vehicle distance Fd and the running speed v, Fd/v>5s is the forward no-vehicle running condition, 3.5s<Fd/v<5s is the case of a large vehicle distance, 2.5s<Fd/v<3.5s is the proper distance, 1.5s<Fd/v<2.5s is the case of small vehicle distance, Fd/v<1.5s is the situation that the distance is too small; the vehicle with controlled automatic driving requirement can realize the following driving function according to the driving environment, the actuator of the system is an electric motor, the fuzzy controller fuzzes the control signal of the electric motor into five conditions, and the current driving speed is set as vdWith an expected vehicle speed ve：ve>2*vdThe vehicle runs along the road at a limited speed; 1.1 vd<ve<2*vdThe speed of the controlled vehicle is increased; 0.9 vd<ve<1.1*vdThe controlled vehicle stabilizes the speed; 0.5 vd<ve<0.9*vdThe controlled vehicle is lightly braked; v. ofe<0.2*vdEmergency braking of the controlled vehicle;
wherein, the control rule of the fuzzy controller is described as follows:
defining the distance error e of traveldComprises the following steps: e.g. of the typedAnd Fd/v-3, the following vehicle running control rule is as follows: when e isd>When 0, the controlled vehicle accelerates by using an accelerator pedal, edThe larger the propulsion is, the stronger the propulsion is; when e isd<At 0, the controlled vehicle is decelerated by the brake pedal and the motor, edThe smaller the braking force, the stronger the necessary safety distance is ensured.
4. The fuzzy controller-based automatic driving method for the electric vehicle according to claim 1, wherein: in the step 2), when the vehicle distance Fd and the running speed v detected by the front side radar group meet Fd/v >5s, the fuzzy controller judges that the controlled vehicle is in a front vehicle-free running condition, the road speed limit is used as the input of a vehicle speed control system, the controlled vehicle runs along the road speed limit, and the road passing efficiency is effectively improved on the premise of ensuring safe running.
5. The fuzzy controller-based automatic driving method for the electric vehicle according to claim 1, wherein: in step 4), when the controlled vehicle needs to stop or turn right according to the given track of the navigation system to change lanes to the right, let Rd1(k), Rd2(k), Rd1(k-1) and Rd2(k-1) be the obstacle distances detected by the right radar group in the k-th and k-1-th sampling periods respectively, T be the sampling period, DL be the necessary transverse distance for lane change, defined as the lane width, if the right lane state satisfies the following conditions:
Rd1(k)＞DL
Rd2(k)＞DL
the fuzzy controller judges that the right lane of the controlled vehicle is in good state and can be doubled, the doubling operation is realized by using a steering gear of the vehicle, the following driving is continuously executed after the right doubling is finished, and the step 2) is executed; if the condition is not met, the controlled vehicles stop merging, the original lane is kept to run, and the step 2) is continuously executed.
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