CN113515038B

CN113515038B - Vehicle lane changing method, device, equipment and readable storage medium

Info

Publication number: CN113515038B
Application number: CN202111041182.3A
Authority: CN
Inventors: 郑芳芳; 侯康宁; 刘晓波; 唐优华; 陆良; 白霖涵; 周韬
Original assignee: Chengdu Jiaoda Big Data Technology Co ltd; Southwest Jiaotong University
Current assignee: Chengdu Jiaoda Big Data Technology Co ltd; Southwest Jiaotong University
Priority date: 2021-09-07
Filing date: 2021-09-07
Publication date: 2021-11-26
Anticipated expiration: 2041-09-07
Also published as: CN113515038A

Abstract

The invention provides a vehicle lane changing method, a device, equipment and a readable storage medium, wherein the method comprises the following steps: acquiring first information and second information; determining vehicles in front of the lane changing vehicles and vehicles behind the lane changing vehicles after the lane changing vehicles join the vehicle queue according to the first information; judging whether a lane change condition is met or not according to the current position information of the front vehicle and the current position information of the rear vehicle, if so, planning an expected lane change track of the lane change vehicle and calculating an expected yaw angle and a front wheel corner of the lane change vehicle; and sending a control command based on the yaw angle expected by the lane changing vehicle, the front wheel rotating angle expected by the lane changing vehicle and the vehicle configuration information of the lane changing vehicle, wherein the control command is used for controlling the command of the lane changing vehicle to join the vehicle queue. The invention provides a novel dynamic collaborative lane changing model, which can update the lane changing diameter in real time along with the change of the speed of a vehicle in front, thereby not only ensuring the lane changing safety, but also improving the lane changing flexibility.

Description

Vehicle lane changing method, device, equipment and readable storage medium

Technical Field

The invention relates to the technical field of traffic, in particular to a vehicle lane changing method, a vehicle lane changing device, vehicle lane changing equipment and a readable storage medium.

Background

At present, most of domestic and foreign researches on automatic vehicle queue control are biased to the longitudinal control aspect of the queue, and the researches on cooperative lane changing and dynamic lane changing in the transverse control aspect and the combined control algorithm of the two aspects are lacked. Meanwhile, the existing driving research of the automatic formation of vehicles is difficult to adapt to complex traffic environment, and the research of module integration algorithms such as decision, planning, control and the like on a microscopic level is lacked.

Disclosure of Invention

The invention aims to provide a vehicle lane changing method, a vehicle lane changing device, a vehicle lane changing equipment and a readable storage medium, so as to improve the problems.

In order to achieve the above object, the embodiments of the present application provide the following technical solutions:

in one aspect, an embodiment of the present application provides a vehicle lane changing method, where the method includes:

acquiring first information and second information, wherein the first information comprises a request for joining a vehicle queue, which is sent by a lane-changing vehicle; the second information comprises current running state information of the lane changing vehicle and vehicle configuration information of the lane changing vehicle;

determining a vehicle positioned in front of the lane changing vehicle and a vehicle positioned behind the lane changing vehicle after the lane changing vehicle joins the vehicle queue according to the first information, defining the front vehicle as a front vehicle, defining the rear vehicle as a rear vehicle, and acquiring current position information of the front vehicle and the current position information of the rear vehicle;

judging whether a lane change condition is met or not according to the current position information of the front vehicle and the current position information of the rear vehicle, and calculating by using a dynamic collaborative lane change model to obtain a yaw angle and a front wheel rotation angle expected by the lane change vehicle based on the current position information of the front vehicle and the current running state information of the lane change vehicle if the lane change condition is met;

and sending a control command based on the yaw angle expected by the lane changing vehicle, the front wheel rotating angle expected by the lane changing vehicle and the vehicle configuration information of the lane changing vehicle, wherein the control command is used for controlling the command of the lane changing vehicle to join the vehicle queue.

Optionally, the determining, according to the first information, that the lane change vehicle joins the vehicle queue and then is located at a vehicle in front of the lane change vehicle and a vehicle behind the lane change vehicle includes:

obtaining a first result based on a request query of joining the vehicle queue sent by the lane change vehicle, wherein the first result comprises the sequence of each vehicle leaving the vehicle queue in the vehicle queue to which the lane change vehicle is to be joined and the sequence of the lane change vehicle leaving the vehicle queue after the lane change vehicle joins the vehicle queue;

and determining the relative position in the vehicle queue after the lane changing vehicle is added into the vehicle queue based on the first result, and determining the vehicle positioned in front of the lane changing vehicle after the lane changing vehicle is added into the vehicle queue and the vehicle positioned behind the lane changing vehicle after the lane changing vehicle is added into the vehicle queue according to the relative position.

Optionally, the determining whether the lane change condition is met according to the current position information of the front vehicle and the current position information of the rear vehicle includes:

acquiring an expected safety distance and a minimum safety distance;

and calculating a first distance between the front most part of the lane changing vehicle and the rear most part of the front vehicle and a second distance between the rear most part of the lane changing vehicle and the front most part of the rear vehicle according to the current running state information of the lane changing vehicle, the current position information of the front vehicle and the current position information of the rear vehicle, wherein if the first distance is equal to the expected safe distance and the second distance is greater than or equal to the minimum safe distance, the lane changing condition is met.

Optionally, the obtaining, by using a dynamic collaborative lane change model, an expected yaw angle and a front wheel rotation angle of the lane change vehicle based on the current position information of the front vehicle and the current running state information of the lane change vehicle includes:

combining the distributed cascade PID control algorithm with a sine function to construct the dynamic collaborative lane changing model;

obtaining an expected lane changing track of the lane changing vehicle based on the dynamic collaborative lane changing model, the current position information of the front vehicle and the current running state information of the lane changing vehicle, wherein the current running state information of the lane changing vehicle comprises the current position, speed and acceleration of the lane changing vehicle;

and obtaining the expected yaw angle and the expected front wheel rotation angle of the lane changing vehicle based on the expected lane changing track of the lane changing vehicle.

Optionally, the sending a control command based on the desired yaw angle of the lane change vehicle, the desired front wheel rotation angle of the lane change vehicle, and the vehicle configuration information of the lane change vehicle, where the control command is used to control a command that the lane change vehicle joins the vehicle queue, includes:

calculating to obtain an increment of a front wheel corner of the lane changing vehicle at present by utilizing a model predictive control algorithm based on vehicle configuration information of the lane changing vehicle, a yaw angle expected by the lane changing vehicle and a front wheel corner expected by the lane changing vehicle;

and controlling the lane changing vehicle to be added into the vehicle queue based on the increment of the front wheel turning angle of the current lane changing vehicle.

Optionally, the controlling the lane change vehicle to join in the vehicle queue based on the increase of the front wheel rotation angle of the current lane change vehicle includes:

controlling the lane changing vehicle to move towards the vehicle queue direction based on the increment of the front wheel turning angle of the lane changing vehicle to obtain a second result, wherein the second result comprises the running state information of the lane changing vehicle after the lane changing vehicle moves and the position information of the front vehicle after the lane changing vehicle moves;

updating an expected lane changing track of the lane changing vehicle according to the second result and the dynamic collaborative lane changing model, and updating the increment of the front wheel corner of the lane changing vehicle based on the updated lane changing track;

and controlling the lane changing vehicle to continuously move towards the vehicle queue direction based on the updated increment amount of the front wheel turning angle until the lane changing vehicle joins the vehicle queue, wherein when the center line of the lane changing vehicle towards the advancing direction of the vehicle queue is coincident with the center line of the vehicle queue, the lane changing vehicle is determined to have joined the vehicle queue.

Optionally, when the first information and the second information are obtained, the method further includes:

acquiring third information, wherein the third information comprises current running state information of each vehicle in the vehicle queue, and the current running state information of each vehicle comprises current position information of each vehicle, current speed of each vehicle and current acceleration of each vehicle;

based on the current running state information of each vehicle, calculating the acceleration of each vehicle at the next moment by utilizing a distributed cascade PID longitudinal control algorithm;

calculating the position information and the speed of each vehicle at the next moment according to the current running state information of each vehicle and the acceleration of each vehicle at the next moment;

and controlling the position and the speed of each vehicle at the next moment based on the position information and the speed of each vehicle at the next moment.

Optionally, the calculating, based on the current running state information of each vehicle, the acceleration of each vehicle at the next time by using a distributed cascade PID longitudinal control algorithm includes:

calculating the acceleration of each vehicle at the next moment by the formulas (1) to (10), wherein the formulas (1) to (10) are sequentially as follows:

d_i(k)＝x_i-1(k)-x_i(k)-l_i-1 (1)

in formula (1), k represents the number of sampling cycles; l_i-1Represents the length of the (i-1) th vehicle; d_iRepresents the measured distance between the front bumper of the ith vehicle and the rear bumper of the ith-1 vehicle; x is the number of_i(k) Indicating the position of the ith vehicle at the kth sampling time; x is the number of_i-1(k) Indicating the position of the (i-1) th vehicle at the kth sampling moment, wherein the (i) th vehicle is adjacent to the (i-1) th vehicle, and the (i-1) th vehicle is positioned in front of the (i) th vehicle;

S_i(k)＝d₀+v_i(k)h_t (2)

in the formula (2), S_iRepresenting a desired separation of the ith vehicle from the (i-1) th vehicle; d₀Representing the minimum safe distance between the ith vehicle and the (i-1) th vehicle; h is_tRepresenting a constant headway; suppose all subsystems have the same d₀And h_t；v_i(k) Representing the speed of the ith vehicle at the kth sampling instant;

pitch error e_xiAnd speed error

Is used for measurement controlA target, defined as:

in formula (3), k represents the number of sampling cycles; e.g. of the type_xi(k) Represents P_i,i-1The pitch error of the subsystem at the kth sampling instant, where P_i,i-1A subsystem representing the i-th vehicle and the i-1 st vehicle;

represents P_i,i-1The speed error of the subsystem at the kth sampling moment; d_iRepresents the measured distance between the front bumper of the ith vehicle and the rear bumper of the ith-1 vehicle; v. of_i-1(k) Representing the speed of the (i-1) th vehicle at the kth sampling moment; v. of_i(k) Representing the speed of the ith vehicle at the kth sampling instant; s_iRepresenting a desired separation of the ith vehicle from the (i-1) th vehicle;

P_i,i-1the outer ring PID control algorithm equation of the subsystem is as follows:

e_xi(k)＝d_i(k)-S_i(k) (5)

in the formulae (4) to (5),

represents P_i,i-1The output of the outer ring PID of the subsystem at the kth sampling moment;

represents P_i,i-1Proportional coefficient of subsystem outer ring PID;

represents P_i,i-1Integral coefficient of subsystem outer ring PID;

represents P_i,i-1Differential coefficient of outer loop PID of subsystem, e_xi(k) Represents P_i,i-1The distance error of the subsystem at the kth sampling moment; e.g. of the type_xi(k-1) represents P_i,i-1The distance error of the subsystem at the k-1 sampling moment, j ∈ {0,1, k };

P_i,i-1the inner ring PID control algorithm equation of the subsystem is as follows:

in the formulae (6) to (8),

represents P_i,i-1The speed error of the subsystem at the kth sampling moment; e.g. of the type_vi(k) Represents P_i,i-1Inputting an inner ring PID of the subsystem at the kth sampling moment; u. of_i(k) Represents P_i,i-1The output of an inner ring PID of the subsystem at the kth sampling moment;

represents P_i,i-1Proportional coefficient of subsystem inner ring PID;

represents P_i,i-1Integral coefficient of subsystem inner ring PID;

represents P_i,i-1Differential coefficient of inner ring PID of the subsystem; j is an element of 0,1, k.

T_sRepresenting the sampling time, the acceleration calculation formula of the (k +1) th sampling moment of each subsystem is as follows:

in formula (9), a_i(k +1) represents the acceleration of the ith vehicle at the (k +1) th sampling time; a is_i(k) Representing the acceleration of the ith vehicle at the kth sampling moment; u. of_i(k) Represents P_i,i-1The output of an inner ring PID of the subsystem at the kth sampling moment; tau is_iRepresenting the longitudinal dynamic inertial lag of the ith vehicle;

meanwhile, each subsystem is constrained, and the constraint conditions are as follows:

in the formula (10), u_minRepresents the minimum value of the control output; u. of_maxRepresents the maximum value of the control output; u. of_i(k) Represents P_i,i-1The output of an inner ring PID of the subsystem at the kth sampling moment; a is_minRepresents a minimum acceleration; a is_maxRepresents the maximum acceleration; v. of_minIs the minimum speed allowed on the road; v. of_maxIs the maximum speed allowed on the road.

Optionally, the calculating, according to the current operation state information of each vehicle and the acceleration of each vehicle at the next time, to obtain the position information and the speed of each vehicle at the next time includes:

calculating the position information and the speed of each vehicle at the next moment by formulas (11) and (12), wherein the formulas (11) and (12) are as follows:

v_i(k+1)＝a_i(k+1)*T_s (11)

in formulae (11) to (12), T_sRepresents a sampling time; a is_i(k +1) represents the acceleration of the ith vehicle at the (k +1) th sampling time; v. of_i(k) Representing the speed of the ith vehicle at the kth sampling instant; v. of_i(k +1) represents the speed of the ith vehicle at the (k +1) th sampling time; x is the number of_i(k +1) represents the position of the ith vehicle at the (k +1) th sampling instant.

Optionally, the obtaining of the desired yaw angle and the desired front wheel rotation angle of the lane change vehicle by using the dynamic collaborative lane change model includes:

calculating a desired yaw angle and a desired front wheel rotation angle of the lane-change vehicle by equations (13) to (18), which are, in order:

in the formula (13), the first and second groups,

indicating the transverse position of the lane change vehicle at the lane change starting time;

indicating the longitudinal position of the lane change vehicle at the lane change starting time;

indicating a position of the preceding vehicle on a lane change start time target lane;

indicating the lateral distance at the beginning of the lane change; a is_LRepresents a planned acceleration; (x)_r,y_r) Indicating a desired position of the lane-change vehicle; t is t₀Indicating a lane change start time; t is t_eIndicating the track changing end time; v. of_SV(t) represents the speed of the lane-change vehicle at time t; v. of_SV(t+T_s) Indicating that the lane-changing vehicle is at T + T_sThe speed of the moment; a is_SV(t+T_s) Indicating that the lane-changing vehicle is at T + T_sAcceleration of time of day；

In formulae (14) to (16), x_rIndicating a desired longitudinal position of the lane-change vehicle; y is_rIndicating a desired lateral position of the lane-change vehicle;

indicating the lateral distance at the beginning of the lane change; a is_LRepresents a planned acceleration; v. of_SV(t) represents the speed of the lane-change vehicle at time t;

indicating the transverse position of the lane change vehicle at the lane change starting time; y is_r' represents y_rThe first derivative of (a); y is_r"denotes y_rThe second derivative of (a); k represents y_rThe curvature of (a);

δ_fr＝tan^-1(L*K) (18)

in the formulae (17) to (18),

indicating a desired yaw angle of the lane-change vehicle; delta_frIndicating a desired front wheel steering angle of the lane-change vehicle;

and delta_frBoth are arcsDegree system, L represents the distance between the front and rear axles of the vehicle; y is_r' represents y_rThe first derivative of (a).

Optionally, calculating, by using a model predictive control algorithm, an increase of a front wheel steering angle of the lane change vehicle based on vehicle configuration information of the lane change vehicle, the yaw angle expected by the lane change vehicle, and the front wheel steering angle expected by the lane change vehicle, and including:

calculating the increment of the front wheel turning angle of the current lane changing vehicle through formulas (19) to (24), wherein the formulas (19) to (24) are as follows:

the vehicle state is described by a kinematic model with three degrees of freedom, and the formula is as follows:

in formula (19), (x, y) represents the vehicle rear axle center coordinates;

representing a vehicle yaw angle; delta_fIndicating a vehicle front wheel steering angle; l represents a vehicle front-rear axle distance; v represents a vehicle speed;

in the formulae (20) to (21),

representing a current state of the vehicle; u ═ v δ_f]^TRepresenting the current control variable of the vehicle, where v represents the speed of the lane-change vehicle, δ_fIndicating a front wheel steering angle of the lane-change vehicle;

representing a desired state obtained from a reference trajectory; u. of_r＝[v_r δ_fr]^TRepresenting a desired control variable obtained from a reference trajectory; x is the number of_rIndicating a desired longitudinal position of the lane-change vehicle; y is_rIndicating a desired lateral position of the lane-change vehicle;

indicating a desired yaw angle of the lane-change vehicle; delta_frIndicating a desired front wheel steering angle of the lane-change vehicle; v. of_rIndicating a desired speed of the lane-change vehicle;

the minimum cost function of the model predictive control algorithm is described as:

min J(k)＝[ΔU(k)^T,ε]^TH(k)[ΔU(k)^T,ε]+f^T(k)[ΔU(k)^T,ε] (22)

the constraint conditions are as follows:

in equations (22) to (24), k represents the number of sampling cycles; j (k) represents a cost function for the kth sampling instant; Δ u (k) represents the increment of the control variable at the kth sampling time; u shape_minA minimum constraint representing a control variable; u shape_maxA maximum constraint representing a control variable; delta U_minA minimum constraint value representing a control variable increment; delta U_maxA maximum constraint value representing a control variable increment; ε represents the relaxation factor; ρ represents a weight coefficient;

a weight matrix representing the input state quantity;

a weight matrix representing control variable increments;

a prediction matrix representing an input state quantity;

a prediction matrix representing control variable increments; a represents a coefficient matrix of a constraint equation; h (k) and f (k) both represent coefficient matrices in the standard form of a quadratic optimization problem.

In a second aspect, an embodiment of the present application provides a vehicle lane changing device, which includes a first obtaining module, a first calculating module, a second calculating module, and a first control module.

The system comprises a first acquisition module, a second acquisition module and a control module, wherein the first acquisition module is used for acquiring first information and second information, and the first information comprises a request for joining a vehicle queue, which is sent by a lane-changing vehicle; the second information comprises current running state information of the lane changing vehicle and vehicle configuration information of the lane changing vehicle;

the first calculation module is used for determining a vehicle positioned in front of the lane changing vehicle and a vehicle positioned behind the lane changing vehicle after the lane changing vehicle is added into the vehicle queue according to the first information, defining the front vehicle as a front vehicle, defining the rear vehicle as a rear vehicle, and acquiring the current position information of the front vehicle and the current position information of the rear vehicle;

the second calculation module is used for judging whether a lane change condition is met or not according to the current position information of the front vehicle and the current position information of the rear vehicle, and calculating by using a dynamic collaborative lane change model to obtain a yaw angle and a front wheel rotation angle expected by the lane change vehicle based on the current position information of the front vehicle and the current running state information of the lane change vehicle if the lane change condition is met;

the lane changing vehicle control system comprises a first control module and a second control module, wherein the first control module is used for sending a control command based on a yaw angle expected by the lane changing vehicle, a front wheel rotating angle expected by the lane changing vehicle and vehicle configuration information of the lane changing vehicle, and the control command is used for controlling a command of the lane changing vehicle to join the vehicle queue.

Optionally, the first computing module includes:

the query unit is used for querying to obtain a first result based on a request of joining the vehicle queue sent by the lane changing vehicle, wherein the first result comprises the sequence of each vehicle leaving the vehicle queue in the vehicle queue to which the lane changing vehicle is to be joined and the sequence of the lane changing vehicle leaving the vehicle queue after the lane changing vehicle is joined in the vehicle queue;

and the determining unit is used for determining a vehicle positioned in front of the lane changing vehicle after the lane changing vehicle is added into the vehicle queue and a vehicle positioned behind the lane changing vehicle after the lane changing vehicle is added into the vehicle queue according to the relative position in the vehicle queue after the lane changing vehicle is determined to be added into the vehicle queue based on the first result.

Optionally, the second computing module includes:

an acquisition unit configured to acquire a desired safety distance and a minimum safety distance;

and the first calculation unit is used for calculating a first distance between the most front part of the lane changing vehicle and the most rear part of the front vehicle and a second distance between the most rear part of the lane changing vehicle and the most front part of the rear vehicle according to the current running state information of the lane changing vehicle, the current position information of the front vehicle and the current position information of the rear vehicle, and if the first distance is equal to the expected safe distance and the second distance is greater than or equal to the minimum safe distance, the lane changing condition is met.

Optionally, the second computing module includes:

the building unit is used for combining the distributed cascade PID control algorithm with a sine function to build the dynamic collaborative channel changing model;

a second calculation unit, configured to obtain an expected lane change track of the lane change vehicle based on the dynamic collaborative lane change model, current position information of the front vehicle, and current running state information of the lane change vehicle, where the current running state information of the lane change vehicle includes a current position, a current speed, and an acceleration of the lane change vehicle;

and the third calculation unit is used for obtaining the expected yaw angle and the expected front wheel rotating angle of the lane changing vehicle based on the expected lane changing track of the lane changing vehicle.

Optionally, the first control module includes:

a fourth calculating unit, configured to calculate, based on vehicle configuration information of the lane change vehicle, an expected yaw angle of the lane change vehicle, and an expected front wheel steering angle of the lane change vehicle, an increase amount of a front wheel steering angle of the current lane change vehicle by using a model predictive control algorithm;

and the control unit is used for controlling the lane changing vehicle to be added into the vehicle queue based on the increment of the front wheel rotation angle of the current lane changing vehicle.

Optionally, the control unit includes:

the first control subunit is used for controlling the lane changing vehicle to move towards the vehicle queue direction based on the increment of the front wheel turning angle of the lane changing vehicle to obtain a second result, and the second result comprises the running state information of the lane changing vehicle after the lane changing vehicle moves and the position information of the front vehicle after the lane changing vehicle moves;

the updating subunit is used for updating the expected lane changing track of the lane changing vehicle according to the second result and the dynamic collaborative lane changing model, and updating the increment of the front wheel turning angle of the lane changing vehicle based on the updated lane changing track;

and the second control subunit is used for controlling the lane changing vehicle to continuously move towards the vehicle queue direction based on the updated increment amount of the front wheel rotation angle until the lane changing vehicle is added into the vehicle queue, wherein when the center line of the lane changing vehicle towards the advancing direction of the vehicle queue is coincident with the center line of the vehicle queue, the lane changing vehicle is determined to be added into the vehicle queue.

Optionally, the apparatus further includes:

a second obtaining module, configured to obtain third information, where the third information includes current operation state information of each vehicle in the vehicle queue, and the current operation state information of each vehicle includes current position information of each vehicle, current speed of each vehicle, and current acceleration of each vehicle;

the third calculation module is used for calculating the acceleration of each vehicle at the next moment by utilizing a distributed cascade PID longitudinal control algorithm based on the current running state information of each vehicle;

the fourth calculation module is used for calculating the position information and the speed of each vehicle at the next moment according to the current running state information of each vehicle and the acceleration of each vehicle at the next moment;

and the second control module is used for controlling the position and the speed of each vehicle at the next moment based on the position information and the speed of each vehicle at the next moment.

Optionally, the third computing module includes:

a fifth calculating unit, configured to calculate an acceleration of each vehicle at the next time through equations (1) - (10), where the equations (1) - (10) are:

d_i(k)＝x_i-1(k)-x_i(k)-l_i-1 (1)

S_i(k)＝d₀+v_i(k)h_t (2)

in the formula (2), S_iRepresenting a desired separation of the ith vehicle from the (i-1) th vehicle; d₀Representing the minimum safe distance between the ith vehicle and the (i-1) th vehicle; h is_tRepresenting a constant headway; suppose all subsystems have the same d₀And h_t；v_i(k) To representThe speed of the ith vehicle at the kth sampling instant;

pitch error e_xiAnd speed error

Is used to measure the control target, which is defined as:

e_xi(k)＝d_i(k)-S_i(k) (5)

in the formulae (4) to (5),

represents P_i,i-1Outer ring of subsystemThe proportionality coefficient of PID;

represents P_i,i-1Integral coefficient of subsystem outer ring PID;

represents P_i，i-1Differential coefficient of outer loop PID of subsystem, e_xi(k) Represents P_i,i-1The distance error of the subsystem at the kth sampling moment; e.g. of the type_xi(k-1) represents P_i,i-1The distance error of the subsystem at the k-1 sampling moment, j ∈ {0,1, k };

in the formulae (6) to (8),

represents P_i,i-1Proportional coefficient of subsystem inner ring PID;

represents P_i,i-1Integral coefficient of subsystem inner ring PID;

represents P_i,i-1Differential coefficient of inner ring PID of the subsystem; j ∈ {0,1, k };

Optionally, the fourth calculating module includes:

a sixth calculating unit for calculating the position information and the speed of each vehicle at the next time by equations (11) and (12), wherein the equations (11) and (12) are:

v_i(k+1)＝a_i(k+1)*T_s (11)

Optionally, the second computing module includes:

a seventh calculation unit configured to calculate a desired yaw angle and a desired front wheel rotation angle of the lane-change vehicle by equations (13) to (18), the equations (13) to (18) being, in order:

in the formula (13), the first and second groups,

indicating the lateral distance at the beginning of the lane change; a is_LRepresents a planned acceleration; (x)_r,y_r) Indicating a desired position of the lane-change vehicle; t is t₀Indicating a lane change start time; t is t_eIndicating the track changing end time; v. of_SV(t) represents the speed of the lane-change vehicle at time t; v. of_SV(t+T_s) Indicating that the lane-changing vehicle is at T + T_sThe speed of the moment; a is_SV(t+T_s) Indicating that the lane-changing vehicle is at T + T_sAcceleration at a moment;

δ_fr＝tan^-1(L*K) (18)

in the formulae (17) to (18),

and delta_frBoth are in radian system, and L represents the distance between the front axle and the rear axle of the vehicle; y is_r' represents y_rThe first derivative of (a).

Optionally, the fourth calculating unit includes:

a calculating subunit, configured to calculate, through equations (19) - (24), an amount of increase of a front wheel steering angle of the current lane-changing vehicle, where equations (19) - (24) are:

in formula (19), (x, y) represents the vehicle rear axle center coordinates;

in the formulae (20) to (21),

min J(k)＝[ΔU(k)^T,ε]^TH(k)[ΔU(k)^T,ε]+f^T(k)[ΔU(k)^T,ε] (22)

the constraint conditions are as follows:

a weight matrix representing the input state quantity;

a weight matrix representing control variable increments;

a prediction matrix representing an input state quantity;

In a third aspect, an embodiment of the present application provides a lane changing device for a vehicle, where the device includes a memory and a processor. The memory is used for storing a computer program; the processor is used for realizing the steps of the vehicle lane changing method when executing the computer program.

In a fourth aspect, the present application provides a readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the vehicle lane changing method described above.

The invention has the beneficial effects that:

1. the invention provides a distributed cascade PID control algorithm, which comprises an inner ring PID for controlling a speed error and an outer ring PID for controlling a distance error so as to execute longitudinal control of vehicle formation. The algorithm definitely considers the correlation and the coupling of the two types of errors and has stronger anti-interference capability.

2. The invention provides a dynamic cooperative lane changing model consisting of a distributed cascade PID control algorithm and an improved sinusoidal path planning method. And the speed of the lane changing vehicle is calculated according to a distributed cascade PID control algorithm, so that the lane changing safety is ensured. The continuous path is then planned based on a modified sinusoidal function that takes into account passenger discomfort that may be caused by lateral acceleration. Furthermore, the range of possible planned accelerations is determined using the yaw rate of the vehicle, which is an important parameter of the modified sinusoidal function, the parameters of which have a physical significance.

3. The dynamic collaborative lane changing model provided by the invention explicitly considers the heterogeneity of the CAV of the intelligent internet vehicle in the aspect of inertial lag. Lane change uncertainty caused by a change in the speed of a preceding vehicle in the target lane is also considered, as well as coordinated maneuvers between the lane change vehicle and the fleet of vehicles in the target lane.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.

FIG. 1 is a schematic flow chart of a lane change method for a vehicle according to an embodiment of the present invention;

FIG. 2 is a schematic structural diagram of a lane-changing device of a vehicle according to an embodiment of the present invention;

FIG. 3 is a schematic structural diagram of a lane-changing device for a vehicle according to an embodiment of the present invention;

fig. 4 is a schematic diagram of a cascade PID control structure of each distributed subsystem in the embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that: like reference numbers or letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined or explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.

Example 1

As shown in fig. 1, the present embodiment provides a lane change method for a vehicle, which includes step S1, step S2, step S3, and step S4.

Step S1, acquiring first information and second information, wherein the first information comprises a request for joining a vehicle queue sent by a lane-changing vehicle; the second information comprises current running state information of the lane changing vehicle and vehicle configuration information of the lane changing vehicle;

step S2, determining a vehicle positioned in front of the lane changing vehicle and a vehicle positioned behind the lane changing vehicle after the lane changing vehicle joins the vehicle queue according to the first information, defining the front vehicle as a front vehicle, defining the rear vehicle as a rear vehicle, and acquiring the current position information of the front vehicle and the current position information of the rear vehicle;

step S3, judging whether a lane change condition is met or not according to the current position information of the front vehicle and the current position information of the rear vehicle, and if the lane change condition is met, calculating by using a dynamic collaborative lane change model to obtain a yaw angle and a front wheel rotation angle expected by the lane change vehicle based on the current position information of the front vehicle and the current running state information of the lane change vehicle;

and step S4, sending a control command based on the yaw angle expected by the lane changing vehicle, the front wheel rotation angle expected by the lane changing vehicle and the vehicle configuration information of the lane changing vehicle, wherein the control command is used for controlling the command of the lane changing vehicle to join the vehicle queue.

In this embodiment, the current operating state information of the lane-changing vehicle includes the current position, speed and acceleration of the lane-changing vehicle, and the vehicle configuration information of the lane-changing vehicle includes the vehicle yaw angle, front wheel rotation angle, front-rear axle distance and speed of the lane-changing vehicle; the embodiment provides a dynamic cooperative lane change model consisting of a distributed cascade PID control algorithm and an improved sinusoidal function trajectory planning method, wherein the distributed cascade PID control algorithm in the model considers the fluctuation of the speed of a vehicle in front of a target lane and determines the longitudinal acceleration and the speed of a vehicle with a proper lane change so as to ensure the lane change safety; the modified sinusoidal function accounts for passenger discomfort that may be caused by lateral acceleration, plans a reference trajectory, and updates the amount of increase in the front wheel angle of the lane-change vehicle in real time to avoid a potential collision until the lane change is complete. Furthermore, the important parameters of the modified sinusoidal function, the feasible range of which the acceleration is planned, are determined using the yaw rate of the vehicle, the parameters of the modified sinusoidal function having physical significance and being easier to interpret.

In an embodiment of the present disclosure, the method may further include step S5, step S6, step S7, and step S8.

Step S5, acquiring third information, wherein the third information comprises current running state information of each vehicle in the vehicle queue, and the current running state information of each vehicle comprises current position information of each vehicle, current speed of each vehicle and current acceleration of each vehicle;

step S6, based on the current running state information of each vehicle, calculating the acceleration of each vehicle at the next moment by using a distributed cascade PID longitudinal control algorithm;

step S7, calculating the position information and the speed of each vehicle at the next moment according to the current running state information of each vehicle and the acceleration of each vehicle at the next moment;

and step S8, controlling the position and the speed of each vehicle at the next moment based on the position information and the speed of each vehicle at the next moment.

In this embodiment, while the first information and the second information are obtained, step S5 to step S8 are also executed, the method in this embodiment can calculate the position and speed of the vehicle at the next time in real time, and control the vehicle to be located at the calculated position and reach the calculated speed at the next time through the calculated position and speed, so as to ensure that the vehicles in the fleet always keep a safe driving state; meanwhile, the expected yaw angle and the expected front wheel rotation angle of the lane changing vehicle at each moment can be updated through the position and the running speed of the vehicle in the fleet which are updated in real time.

In a specific embodiment of the present disclosure, the step S2 may further include a step S21 and a step S22.

Step S21, obtaining a first result based on a request query of joining the vehicle queue sent by the lane change vehicle, wherein the first result comprises the sequence of each vehicle leaving the vehicle queue in the vehicle queue to which the lane change vehicle is to be joined and the sequence of the lane change vehicle leaving the vehicle queue after the lane change vehicle is joined in the vehicle queue;

and step S22, determining the relative position in the vehicle queue after the lane changing vehicle is added into the vehicle queue based on the first result, and determining the vehicle positioned in front of the lane changing vehicle after the lane changing vehicle is added into the vehicle queue and the vehicle positioned behind the lane changing vehicle after the lane changing vehicle is added into the vehicle queue according to the relative position.

In this embodiment, the position order of each vehicle in the queue is determined by the following rule: the position of each vehicle on the expressway, which leaves the expressway, can be obtained in advance, and the relative position of each vehicle in the queue is determined according to the distance between the leaving position and the current position, wherein the vehicle with the smallest distance is at the tail end of the queue, and the vehicle with the largest distance is at the front end of the queue. By the aid of the sorting rule, the last vehicle in the queue can always leave the queue first, and accordingly the influence on the stability of the whole queue system is reduced.

In this embodiment, the position of each vehicle in the queue may be obtained in advance, and the position where the lane change vehicle is to be inserted and the vehicle located in front of and behind the lane change vehicle after the lane change vehicle is inserted may be determined according to the position of the lane change vehicle in the queue.

In a specific embodiment of the present disclosure, the step S3 may further include a step S31 and a step S32.

Step S31, acquiring an expected safety distance and a minimum safety distance;

step S32, calculating a first distance between the front of the lane change vehicle and the rear of the front vehicle and a second distance between the rear of the lane change vehicle and the front of the rear vehicle according to the current operating state information of the lane change vehicle, the current position information of the front vehicle and the current position information of the rear vehicle, and if the first distance is equal to the expected safe distance and the second distance is greater than or equal to the minimum safe distance, the lane change condition is met.

In this embodiment, when the lane change condition is met, the position of the lane change vehicle is defined as the starting point of the lane change vehicle, and at this time, the rear vehicle and the lane change vehicle cooperate with the maneuver to meet the lane change condition, specifically: (1) the lane changing vehicle needs to be accelerated properly when the lane changing vehicle is behind the lane changing starting point, and needs to be decelerated properly when the lane changing vehicle is in front of the lane changing starting point; (2) the rear vehicle decelerates to provide a safe lane changing space for the lane changing vehicle. Meanwhile, when the lane change condition is met, the lane change is triggered, the rear vehicle and the lane change vehicle form a new subsystem, the front vehicle and the lane change vehicle form another subsystem, and the safety of longitudinal driving can be ensured through the execution of the steps S5 to S8. And then, performing a lane changing maneuver through the dynamic collaborative lane changing model until the whole lane changing process is completed, wherein the whole lane changing process can be completed on the premise of ensuring the safety of longitudinal driving in the lane changing process.

In a specific embodiment of the present disclosure, the step S3 may further include a step S33, a step S34 and a step S35.

Step S33, combining the distributed cascade PID control algorithm with a sine function to construct the dynamic collaborative lane changing model;

step S34, obtaining an expected lane changing track of the lane changing vehicle based on the dynamic collaborative lane changing model, the current position information of the front vehicle and the current running state information of the lane changing vehicle, wherein the current running state information of the lane changing vehicle comprises the current position, speed and acceleration of the lane changing vehicle;

and step S35, obtaining the desired yaw angle and the desired front wheel rotation angle of the lane changing vehicle based on the desired lane changing track of the lane changing vehicle.

In a specific embodiment of the present disclosure, the step S4 may further include a step S41 and a step S42.

Step S41, calculating to obtain the increment of the front wheel steering angle of the lane changing vehicle by utilizing a model predictive control algorithm based on the vehicle configuration information of the lane changing vehicle, the yaw angle expected by the lane changing vehicle and the front wheel steering angle expected by the lane changing vehicle;

and step S42, controlling the lane changing vehicle to be added into the vehicle queue based on the increment of the front wheel turning angle of the current lane changing vehicle.

In a specific embodiment of the present disclosure, the step S42 may further include a step S421, a step S422, and a step S423.

Step S421, controlling the lane-changing vehicle to move towards the vehicle queue direction based on the increment of the front wheel turning angle of the lane-changing vehicle, so as to obtain a second result, wherein the second result comprises the running state information of the lane-changing vehicle after the lane-changing vehicle moves and the position information of the front vehicle after the lane-changing vehicle moves;

step S422, an expected lane change track of the lane change vehicle is updated according to the second result and the dynamic collaborative lane change model, and the increment of the front wheel rotation angle of the lane change vehicle is updated based on the updated lane change track;

step S423, controlling the lane-change vehicle to continue moving toward the vehicle queue based on the updated increase amount of the front wheel turning angle until the lane-change vehicle joins the vehicle queue, wherein when a center line of the lane-change vehicle in the advancing direction of the vehicle queue coincides with a center line of the vehicle queue, it is determined that the lane-change vehicle has joined the vehicle queue.

In this embodiment, when the current increase of the front wheel angle of the lane changing vehicle is calculated, the lane changing vehicle is controlled to move towards the vehicle queue direction, after the lane changing vehicle moves, the position and the speed of each vehicle at the next moment are calculated by using the method from step S5 to step S8, the increase of the front wheel angle of the lane changing vehicle is updated, the increase of the front wheel angle of the lane changing vehicle is continuously updated, the lane changing vehicle gradually approaches the vehicle fleet, and when the vertical center line (towards the advancing direction of the vehicle fleet) of the lane changing vehicle is overlapped with the vertical center line (towards the advancing direction of the vehicle fleet) of the vehicle fleet, the lane changing is completed. By updating the increment of the front wheel corner of the lane changing vehicle in real time (equivalent to updating the lane changing path), the lane changing safety is ensured, and the lane changing flexibility is improved.

In a specific embodiment of the present disclosure, the step S6 may further include a step S61.

Considering a queue consisting of N intelligent internet vehicles (CAVs) in this embodiment, we define any two adjacent vehicles on the same lane as subsystems. Let P_i,i-1Showing the subsystem consisting of the i-1 st vehicle and the i-th vehicle. P_i,i-1The change in speed of the rear vehicle (i.e., the i-1 st vehicle) in the subsystem is controlled by a control algorithm. We assume that each vehicle in the queue can measure the distance between two adjacent vehicles and the front speed, while setting x_i(t),v_i(t),a_i(t) represents the position, velocity and acceleration of the ith vehicle at time t, i ∈ {1,2, N }.

The embodiment provides a distributed cascade PID control algorithm for longitudinally controlling a vehicle queue. In effect, the distributed cascade PID is a two-level control structure with an inner loop and an outer loop. The outer loop PID controls the spacing between adjacent vehicles, and the inner loop PID controls the speed of the vehicle. The output of the outer ring is used as the input of the inner ring, and compared with the feedback value of the inner ring to form the whole inner and outer ring double-layer control, and the cascade PID control structure of each distributed subsystem is shown in FIG. 4.

Step S61, calculating the acceleration of each vehicle at the next moment through formulas (1) - (10), wherein the formulas (1) - (10) are as follows:

d_i(k)＝x_i-1(k)-x_i(k)-l_i-1 (1)

S_i(k)＝d₀+v_i(k)h_t (2)

in the formula (2), S_iRepresenting a desired separation of the ith vehicle from the (i-1) th vehicle; d₀Representing the minimum safe distance between the ith vehicle and the (i-1) th vehicle; h is_tRepresenting a constant headway; to simplify the problem, it is assumed that all subsystems have the same d₀And h_t；v_i(k) Representing the speed of the ith vehicle at the kth sampling instant;

the goal of the distributed cascade PID control algorithm is to maintain the desired spacing and uniform speed of the subsystems and to respond quickly to any vehicle disturbances, thereby ensuring overall fleet stability, with a spacing error e_xiAnd speed error

Is used to measure the control target, which is defined as:

e_xi(k)＝d_i(k)-S_i(k) (5)

in the formulae (4) to (5),

represents P_i,i-1Proportional coefficient of subsystem outer ring PID;

represents P_i,i-1Integral coefficient of subsystem outer ring PID;

represents P_i,i-1Differential coefficient of outer loop PID of subsystem, e_xi(k) Represents P_i,i-1Subsystem at kThe spacing error at the sampling time; e.g. of the type_xi(k-1) represents P_i,i-1The distance error of the subsystem at the k-1 sampling moment, j ∈ {0,1, k };

in the formulae (6) to (8),

represents P_i,i-1Proportional coefficient of subsystem inner ring PID;

represents P_i,i-1Integral coefficient of subsystem inner ring PID;

Wherein the first constraint in equation (10) takes into account vehicle performance limitations, the second constraint is related to passenger comfort, and the third constraint reflects road conditions. The present embodiment considers the heterogeneity of intelligent networked vehicles, where different networked vehicles have different values of inertial lag.

In a specific embodiment of the present disclosure, the step S7 may further include a step S71.

Step S71, calculating the position information and speed of each vehicle at the next time by equations (11) and (12), where equations (11) and (12) are:

v_i(k+1)＝a_i(k+1)*T_s (11)

In a specific embodiment of the present disclosure, the step S3 may further include a step S36.

In the embodiment, a distributed cascade PID control algorithm is combined with a sine function, and a novel dynamic collaborative channel changing model is provided. After lane changing is started, the lane changing vehicle and the front vehicle are regarded as a new subsystem and controlled by a distributed cascade PID control algorithm. Under the premise of avoiding the collision of two vehicles, the distributed cascade PID control algorithm calculates the acceleration of the lane-changing vehicle by considering the relative speed and the distance of the two vehicles and updates the vehicle speed in real time. The velocity is then passed in real time to a sinusoidal function model to plan a dynamic lane change trajectory. In the lane changing process, the dynamic collaborative lane changing model can update the lane changing diameter in real time along with the change of the speed of the front vehicle, so that the lane changing safety is ensured, and the lane changing flexibility is improved.

Step S36, calculating a desired yaw angle and a desired front wheel steering angle of the lane-change vehicle by equations (13) to (18), which are in turn:

in the formula (13), the first and second groups,

δ_fr＝tan^-1(L*K) (18)

in the formulae (17) to (18),

In a specific embodiment of the present disclosure, the step S41 may further include step S411.

In this embodiment, the model predictive control algorithm is used to calculate the increment of the front wheel rotation angle at each sampling time, so as to complete the track changing process of the transverse control.

Step S411, calculating and obtaining the increment of the front wheel turning angle of the current lane changing vehicle through formulas (19) - (24), wherein the formulas (19) - (24) are as follows:

to simplify microscopic vehicle control, we describe the vehicle state using a three-degree-of-freedom kinematic model. The vehicle state is described by a kinematic model with three degrees of freedom, as formula (19):

in formula (19), (x, y) represents the vehicle rear axle center coordinates;

and (3) carrying out real-time tracking control on the expected track by adopting a model predictive control algorithm, wherein a tracking control system of the model predictive control algorithm is described as formulas (20) to (21):

in the formulae (20) to (21),

representing a current state of the vehicle; u-v δ_f]^TRepresenting the current control variable of the vehicle, where v represents the speed of the lane-change vehicle, δ_fIndicating a front wheel steering angle of the lane-change vehicle;

min J(k)＝[ΔU(k)^T,ε]^TH(k)[ΔU(k)^T,ε]+f^T(k)[ΔU(k)^T,ε] (22)

the constraint conditions are as follows:

in equations (22) to (24), k represents the number of sampling cycles; j (k) represents a cost function for the kth sampling instant; Δ u (k) represents the increment of the control variable at the kth sampling time (where the increment of the control variable includes the speed increment of the lane-change vehicle and the front wheel steering angle increment of the lane-change vehicle); u shape_minA minimum constraint representing a control variable; u shape_maxA maximum constraint representing a control variable; delta U_minA minimum constraint value representing a control variable increment; delta U_maxA maximum constraint value representing a control variable increment; ε represents the relaxation factor; ρ represents a weight coefficient;

a weight matrix representing the input state quantity;

a weight matrix representing control variable increments;

a prediction matrix representing an input state quantity;

a prediction matrix representing control variable increments; a represents a coefficient matrix of a constraint equation; h (k) and f (k) both represent coefficient matrices in the standard form of the quadratic optimization problem, that is to say h (k) represents one coefficient matrix in the standard form of the quadratic optimization problem and f (k) represents the other coefficient matrix in the standard form of the quadratic optimization problem;

example 2

As shown in fig. 2, the present embodiment provides a lane-changing device for a vehicle, which includes a first obtaining module 701, a first calculating module 702, a second calculating module 703 and a first control module 704.

The first obtaining module 701 is configured to obtain first information and second information, where the first information includes a request for joining a vehicle queue sent by a lane change vehicle; the second information comprises current running state information of the lane changing vehicle and vehicle configuration information of the lane changing vehicle;

the first calculation module 702 is configured to determine, according to the first information, a vehicle located in front of the lane change vehicle and a vehicle located behind the lane change vehicle after the lane change vehicle joins the vehicle queue, define the vehicle in front as a front vehicle, define the vehicle behind as a rear vehicle, and obtain current position information of the front vehicle and current position information of the rear vehicle;

the second calculating module 703 is configured to determine whether a lane change condition is met according to the current position information of the front vehicle and the current position information of the rear vehicle, and if the lane change condition is met, calculate, by using a dynamic collaborative lane change model, an expected yaw angle and a front wheel rotation angle of the lane change vehicle based on the current position information of the front vehicle and the current operating state information of the lane change vehicle;

the first control module 704 is configured to send a control command based on a yaw angle desired by the lane-change vehicle, a front wheel rotation angle desired by the lane-change vehicle, and vehicle configuration information of the lane-change vehicle, where the control command is used to control a command for the lane-change vehicle to join the vehicle queue.

In a specific embodiment of the present disclosure, the apparatus further includes a second obtaining module 705, a third calculating module 706, a fourth calculating module 707, and a second controlling module 708.

The second obtaining module 705 is configured to obtain third information, where the third information includes current running state information of each vehicle in the vehicle queue, and the current running state information of each vehicle includes current position information of each vehicle, current speed of each vehicle, and current acceleration of each vehicle;

the third calculating module 706 is configured to calculate, based on the current running state information of each vehicle, an acceleration of each vehicle at the next time by using a distributed cascade PID longitudinal control algorithm;

the fourth calculating module 707 is configured to calculate, according to the current operation state information of each vehicle and the acceleration of each vehicle at the next time, position information and speed of each vehicle at the next time;

the second control module 708 is configured to control the position and the speed of each vehicle at the next time based on the position information and the speed of each vehicle at the next time.

In a specific embodiment of the present disclosure, the first calculating module 702 further includes a querying unit 7021 and a determining unit 7022.

The querying unit 7021 is configured to obtain a first result based on a query of a request to join the vehicle queue sent by the lane change vehicle, where the first result includes an order in which each vehicle leaves the vehicle queue in the vehicle queue to which the lane change vehicle is to join and an order in which the lane change vehicle leaves the vehicle queue after the lane change vehicle joins the vehicle queue;

the determining unit 7022 is configured to determine, based on the first result, a vehicle located in front of the lane change vehicle after the lane change vehicle joins the vehicle queue and a vehicle located behind the lane change vehicle after the lane change vehicle joins the vehicle queue according to the relative position in the vehicle queue after the lane change vehicle is determined to join the vehicle queue.

In a specific embodiment of the present disclosure, the second calculating module 703 further includes an obtaining unit 7031 and a first calculating unit 7032.

The acquiring unit 7031 is configured to acquire the expected safe distance and the minimum safe distance;

the first calculating unit 7032 is configured to calculate, according to the current operating state information of the lane change vehicle, the current position information of the front vehicle, and the current position information of the rear vehicle, a first distance between the foremost part of the lane change vehicle and the rearmost part of the front vehicle, and a second distance between the rearmost part of the lane change vehicle and the foremost part of the rear vehicle, where if the first distance is equal to the expected safe distance and the second distance is greater than or equal to a minimum safe distance, a lane change condition is met.

In a specific embodiment of the present disclosure, the second computing module 703 further includes a constructing unit 7033, a second computing unit 7034, and a third computing unit 7035.

The constructing unit 7033 is configured to combine the distributed cascade PID control algorithm with a sinusoidal function to construct the dynamic collaborative lane change model;

the second calculating unit 7034 is configured to obtain an expected lane change track of the lane change vehicle based on the dynamic collaborative lane change model, the current position information of the front vehicle, and the current operating state information of the lane change vehicle, where the current operating state information of the lane change vehicle includes a current position, a current speed, and a current acceleration of the lane change vehicle;

the third calculating unit 7035 is configured to obtain a desired yaw angle and a desired front wheel rotation angle of the lane change vehicle based on a desired lane change trajectory of the lane change vehicle.

In a specific embodiment of the present disclosure, the first control module 704 further includes a fourth calculating unit 7041 and a control unit 7042.

The fourth calculating unit 7041 is configured to calculate, based on the vehicle configuration information of the lane change vehicle, the yaw angle expected by the lane change vehicle, and the front wheel rotation angle expected by the lane change vehicle, an increment of the front wheel rotation angle of the current lane change vehicle by using a model predictive control algorithm;

the control unit 7042 is configured to control the lane change vehicle to join the vehicle queue based on an increment of a front wheel rotation angle of the current lane change vehicle.

In a specific embodiment of the present disclosure, the control unit 7042 further includes a first control subunit 70421, an update subunit 70422, and a second control subunit 70423.

The first control subunit 70421 is configured to control, based on the increment of the current vehicle front wheel rotation angle, the lane change vehicle to move toward the vehicle queue direction, so as to obtain a second result, where the second result includes operation state information of the lane change vehicle after the lane change vehicle moves and position information of the vehicle ahead after the lane change vehicle moves;

the updating subunit 70422, configured to update the expected lane change trajectory of the lane change vehicle according to the second result and the dynamic collaborative lane change model, and update the increment of the front wheel steering angle of the lane change vehicle based on the updated lane change trajectory;

the second control subunit 70423 is configured to control, based on the updated increase amount of the front wheel rotation angle, the lane-change vehicle to continue moving toward the vehicle queue until the lane-change vehicle joins the vehicle queue, where when a center line of the lane-change vehicle in the forward direction of the vehicle queue coincides with a center line of the vehicle queue, it is determined that the lane-change vehicle has joined the vehicle queue.

In a specific embodiment of the present disclosure, the third computing module 706 further includes a fifth computing unit 7061.

The fifth calculating unit 7061 is configured to calculate the acceleration of each vehicle at the next time according to equations (1) - (10), where the equations (1) - (10) sequentially include:

d_i(k)＝x_i-1(k)-x_i(k)-l_i-1 (1)

S_i(k)＝d₀+v_i(k)h_t (2)

in the formula (2), S_iRepresenting a desired separation of the ith vehicle from the (i-1) th vehicle; d₀Representing the minimum safe distance between the ith vehicle and the (i-1) th vehicle; h is_tIndicating constant vehicleHead time interval; suppose all subsystems have the same d₀And h_t；v_i(k) Representing the speed of the ith vehicle at the kth sampling instant;

pitch error e_xiAnd speed error

Is used to measure the control target, which is defined as:

e_xi(k)＝d_i(k)-S_i(k) (5)

in the formulae (4) to (5),

represents P_i,i-1Proportional coefficient of subsystem outer ring PID;

represents P_i,i-1Integral coefficient of subsystem outer ring PID;

in the formulae (6) to (8),

represents P_i,i-1Proportional coefficient of subsystem inner ring PID;

represents P_i,i-1Integral coefficient of subsystem inner ring PID;

In a specific embodiment of the present disclosure, the fourth calculating module 707 further includes a sixth calculating unit 7071.

The sixth calculating unit 7071 is configured to calculate the position information and the speed of each vehicle at the next time by equations (11) and (12), where the equations (11) and (12) are:

v_i(k+1)＝a_i(k+1)*T_s a11)

In a specific embodiment of the present disclosure, the second calculating module 703 further includes a seventh calculating unit 7036.

The seventh calculating unit 7036 is configured to calculate a desired yaw angle and a desired front wheel rotation angle of the lane-change vehicle by equations (13) to (18), where equations (13) to (18) are:

in the formula (13), the first and second groups,

δ_fr＝tan^-1(L*K) (18)

in the formulae (17) to (18),

In a specific embodiment of the present disclosure, the fourth computing unit 7041 further includes a computing subunit 70411.

The calculating subunit 70411 is configured to calculate, through equations (19) - (24), an increase amount of the current front wheel steering angle of the lane-changing vehicle, where equations (19) - (24) are:

in formula (19), (x, y) represents the vehicle rear axle center coordinates;

in the formulae (20) to (21),

min J(k)＝[ΔU(k)^T,ε]^T H(k)[ΔU(k)^T,ε]+f^T(k)[ΔU(k)^T,ε] (22)

the constraint conditions are as follows:

a weight matrix representing the input state quantity;

a weight matrix representing control variable increments;

a prediction matrix representing an input state quantity;

It should be noted that, regarding the apparatus in the above embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated herein.

Example 3

Corresponding to the above method embodiments, the embodiments of the present disclosure also provide a vehicle lane change device, and the vehicle lane change device described below and the vehicle lane change method described above may be referred to in correspondence with each other.

Fig. 3 is a block diagram illustrating a vehicle lane-change device 800 according to an exemplary embodiment. As shown in fig. 3, the vehicle lane change apparatus 800 may include: a processor 801, a memory 802. The vehicle lane-change device 800 may also include one or more of a multimedia component 803, an input/output (I/O) interface 804, and a communication component 805.

The processor 801 is configured to control the overall operation of the vehicle lane-changing apparatus 800 to complete all or part of the steps of the vehicle lane-changing method. The memory 802 is used to store various types of data to support operation of the vehicle lane-changing device 800, such as instructions for any application or method operating on the vehicle lane-changing device 800, as well as application-related data, such as contact data, messaging, pictures, audio, video, and the like. The Memory 802 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk or optical disk. The multimedia components 803 may include screen and audio components. Wherein the screen may be, for example, a touch screen and the audio component is used for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may further be stored in the memory 802 or transmitted through the communication component 805. The audio assembly also includes at least one speaker for outputting audio signals. The I/O interface 804 provides an interface between the processor 801 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the vehicle lane-changing device 800 and other devices. Wireless communication, such as Wi-Fi, bluetooth, Near Field Communication (NFC), 2G, 3G, or 4G, or a combination of one or more of them, so that the corresponding communication component 805 may include: Wi-Fi module, bluetooth module, NFC module.

In an exemplary embodiment, the vehicle lane-changing Device 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the vehicle lane-changing methods described above.

In another exemplary embodiment, a computer readable storage medium comprising program instructions which, when executed by a processor, implement the steps of the vehicle lane-change method described above is also provided. For example, the computer readable storage medium may be the memory 802 described above that includes program instructions executable by the processor 801 of the vehicle lane-change device 800 to perform the vehicle lane-change method described above.

Example 4

Corresponding to the above method embodiment, the embodiment of the present disclosure further provides a readable storage medium, and a readable storage medium described below and the above described vehicle lane changing method may be referred to correspondingly.

A readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the vehicle lane changing method of the above-mentioned method embodiment.

The readable storage medium may be a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and various other readable storage media capable of storing program codes.

The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method of changing lanes of a vehicle, comprising:

sending a control command based on the yaw angle expected by the lane changing vehicle, the front wheel rotation angle expected by the lane changing vehicle and the vehicle configuration information of the lane changing vehicle, wherein the control command is used for controlling a command of the lane changing vehicle to join the vehicle queue;

wherein the desired yaw angle and front wheel steering angle of the lane-change vehicle are calculated by equations (13) - (18), which in turn are:

in the formula (13), the first and second groups,

δ_fr＝tan^-1(L*K) (18)

in the formulae (17) to (18),

2. The vehicle lane-changing method according to claim 1, wherein the determining, based on the first information, that the lane-changing vehicle is a vehicle ahead of the lane-changing vehicle and a vehicle behind the lane-changing vehicle after joining the vehicle queue comprises:

3. The vehicle lane change method according to claim 1, wherein the determining whether a lane change condition is met according to the current position information of the front vehicle and the current position information of the rear vehicle comprises:

acquiring an expected safety distance and a minimum safety distance;

4. The method of claim 1, wherein the calculating a desired yaw angle and a desired front wheel rotation angle of the lane-change vehicle using a dynamic collaborative lane-change model based on the current position information of the leading vehicle and the current operating state information of the lane-change vehicle comprises:

combining a distributed cascade PID control algorithm with a sine function to construct the dynamic cooperative lane change model;

5. The vehicle lane-change method of claim 1, wherein the sending a control command based on a desired yaw angle of the lane-change vehicle, a desired front wheel angle of the lane-change vehicle, and vehicle configuration information of the lane-change vehicle, the control command for controlling the command for the lane-change vehicle to join the vehicle queue comprises:

6. The vehicle lane-change method of claim 5, wherein the controlling the lane-change vehicle to join the vehicle queue based on an amount of increase in a front wheel steering angle of the current lane-change vehicle comprises:

7. The method of changing lanes for a vehicle according to claim 1, wherein the obtaining the first information and the second information further comprises:

8. A vehicle lane-changing device, comprising:

the lane changing vehicle comprises a first control module, a second control module and a control module, wherein the first control module is used for sending a control command based on a yaw angle expected by the lane changing vehicle, a front wheel rotating angle expected by the lane changing vehicle and vehicle configuration information of the lane changing vehicle, and the control command is used for controlling a command of the lane changing vehicle to join the vehicle queue;

in the formula (13), the first and second groups,

indicating the lateral distance at the beginning of the lane change; a is_LRepresents a planned acceleration; (x)_r，y_r) Indicating a desired position of the lane-change vehicle; t is t₀Indicating a lane change start time; t is t_eIndicating the track changing end time; v. of_SV(t) represents the speed of the lane-change vehicle at time t; v. of_SV(t+T_s) Indicating that the lane-changing vehicle is at T + T_sThe speed of the moment; a is_SV(t+T_s) Indicating that the lane-changing vehicle is at T + T_sAcceleration at a moment;

indicating the transverse position of the lane change vehicle at the lane change starting time; y is_j' represents y_rThe first derivative of (a); y is_r"denotes y_rThe second derivative of (a); k represents y_rThe curvature of (a);

δ_fr＝tan^-1(L*K) (18)

in the formulae (17) to (18),

9. A vehicle lane-change apparatus, comprising:

a memory for storing a computer program;

a processor for implementing the steps of the vehicle lane-change method according to any one of claims 1 to 7 when executing said computer program.

10. A readable storage medium, characterized by: the readable storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the vehicle lane-changing method according to any one of claims 1 to 7.