CN118597193A - Vehicle speed smoothness optimization method - Google Patents

Abstract

The present application discloses a method for optimizing vehicle speed smoothness, which includes: based on the vehicle automatic driving, after the planning of the primary path planning and speed planning, secondary planning is performed; wherein, path planning is performed based on the spatiotemporal information of obstacles appearing on the driving route of the vehicle; speed planning is performed based on time synchronization, the spatial interference between the dynamic trajectory of the obstacle and the driving route of the vehicle; and the decision of the driving route of the vehicle is made based on path planning and speed planning. Through the above scheme, an obstacle ST diagram is drawn, and through the spatial diagram of multiple blocks, a tunnel that the vehicle can pass is found, so that the secondary planning has multiple alternatives, so that the executable guidance trajectory is optimized after the secondary planning. Dynamic obstacles and static obstacles are mixedly processed, and the optimal guidance trajectory is planned in combination with the vehicle's own dynamic boundaries, so that the passability of the vehicle is improved and the probability of planning failure is reduced.

Description

Vehicle speed ride optimization method

Technical Field

The application relates to the field of automatic driving, in particular to a vehicle speed smoothness optimization method, electronic equipment, a storage medium and a vehicle.

Background

In the existing self-defined driving planning algorithm, a horizontal-longitudinal decoupling method is a popular method, and is mainly divided into two parts of path planning and speed planning;

1. Path planning

Path planning is an important component in autopilot, the main task of which is to find an optimal path between a given start point and end point. For example, in hundred-degree Apollo, a graph-based search method is used for path planning, and an a-star algorithm is used to find an optimal path. The algorithm finds a path of least cost by evaluating the cost of each possible path. In evaluating the path, factors such as dynamics of the vehicle, driving environment, traffic rules, and the like need to be considered. In addition, the hundred-degree Apollo also adopts a quadratic programming method to smooth the found path so as to ensure the comfort and the safety of the vehicle in the running process.

2. Speed planning

The speed planning is performed on the basis of the path planning, and the main task is to calculate the speed and acceleration of the vehicle at each time point according to the path planning and the dynamics of the vehicle. For example, in hundred-degree Apollo, a method based on an optimization algorithm is adopted for speed planning, firstly, an available space is searched on an ST graph through a dynamic planning method, and then a speed track is output smoothly through a quadratic planning algorithm. The algorithm calculates optimal speed and acceleration by minimizing the travel time and energy consumption of the vehicle. In calculating the speed and acceleration, it is necessary to consider the limitation condition of the vehicle and the running environment to ensure the safety and comfort of the vehicle during running.

In the method, the problem that longitudinal smoothness is poor due to longitudinal planning failure exists. The failure of longitudinal planning is mainly because when dynamic planning is performed, a planning track is sent after limiting conditions (acceleration and speed boundaries) are added, and in the follow-up secondary planning, the track is taken as input, so that a result cannot be optimized, the secondary planning is failed, further, longitudinal irregularity is caused, and the driving control is finished through the sudden braking of the vehicle; through data analysis, the poor longitudinal smoothness is caused by overlarge speed change of the vehicle due to overlarge gap between adjacent frame speed planning output results, longitudinal somatosensory is poor, and subsequent running control cannot be continued.

Therefore, a solution for optimizing the smoothness of the vehicle speed is needed, a programmable space is found through planning, a tunnel is planned in the planned space, and the speed is optimized through quadratic programming, so that an executable guiding track is obtained.

Disclosure of Invention

The invention aims to provide a vehicle speed smoothness optimization method, electronic equipment, a storage medium and a vehicle, and at least solves the technical problem of poor vehicle speed smoothness.

The invention provides the following scheme:

According to an aspect of the present invention, there is provided a vehicle speed ride optimization method including:

performing secondary planning after planning based on primary path planning and speed planning based on automatic driving of the vehicle;

wherein, based on the space-time information that the obstacle appears on the route of the self-vehicle, make the route planning;

based on time synchronization, the dynamic track of the obstacle interferes with the space of the self-vehicle driving route to make speed planning;

Based on the path planning and the speed planning, a decision of the self-vehicle driving route is made.

Further, the planning a path based on the space-time information of the obstacle on the self-vehicle driving path includes:

drawing an occlusion region of the obstacle based on time deduction;

Drawing a speed track of the shielding area for avoiding the obstacle by the own vehicle according to the shielding area for drawing the obstacle;

wherein, based on the shielding area of the obstacle comprises a plurality of shielding areas, the space between the shielding areas of the obstacle is planned and drawn;

and marking a speed track strategy for crossing the space between the shielding intervals of the obstacle for speed planning.

Further, based on the time synchronization, the spatial interference between the dynamic track of the obstacle and the self-vehicle driving route, the speed planning comprises:

Acquiring vehicle dynamics boundary information;

Deducing a speed track of the mark crossing the space between the shielding sections of the obstacle according to the vehicle dynamics boundary information;

according to the deduction result, the screening speed track strategy comprises,

Giving up a speed track strategy of a shielding area which can not realize the avoidance of the obstacle, and judging whether the speed track strategy of the shielding area which can realize the avoidance of the obstacle is remained;

if the speed track strategy for avoiding the shielding area of the obstacle is available, controlling the longitudinal and transverse movement of the vehicle according to the speed track strategy for avoiding the shielding area of the obstacle.

Further, based on the time synchronization, the spatial interference between the dynamic track of the obstacle and the self-vehicle driving route, the speed planning further includes:

If the speed track strategy of the shielding area for avoiding the obstacle is not realized at present, introducing acceleration control;

And correcting a speed track strategy of a shielding area which cannot realize the avoidance of the obstacle at present according to the introduced acceleration control, and generating the speed track strategy of the shielding area which can realize the avoidance of the obstacle.

Further, the screening speed trajectory strategy further includes:

Obtaining a calculation formula:

Cost＝Cost _{Road speed limit} +Cost _{Desired speed} +Cost _{acceleration and deceleration rate} +Cost_jerk+Cost _{Historical trajectories} ；

screening a speed track strategy according to the road speed limit, the expected speed, the acceleration and deceleration speed, jerk and the historical track;

The method comprises the steps of taking a speed track strategy corresponding to a minimum Cost value as a currently executed speed track strategy according to a plurality of speed track strategies.

Further, the speed track strategy is selected according to the road speed limit, the expected speed, the acceleration and deceleration speed, jerk and the history track, and includes:

Obtaining a calculation formula:

delta＝max(v _{planning speed} -v _{Road speed limit} ，0)；

Cost _{Road speed limit} ＝e^delta*w；

Wherein w is a weight and a standard amount.

Further, according to the road speed limit, the expected speed, the acceleration and deceleration speed, jerk and the historical track, the screening speed trajectory strategy further comprises:

Obtaining a calculation formula:

v _{Desired speed} ＝min(v _{Cruise speed} ,v _{Road speed limit} ,v _{Initial velocity} +a _{desired acceleration} *t)；

delta＝abs(v _{planning speed} -v _{Desired speed} )；

Cost _{Desired speed} ＝delta*w1；

Wherein v _{Cruise speed} 、v _{Road speed limit} and a _{desired acceleration} are the calibration amounts, v _{Initial velocity} is the initial speed of the vehicle, and w1 is the weight.

Further, according to the road speed limit, the expected speed, the acceleration and deceleration speed, jerk and the historical track, the screening speed trajectory strategy further comprises:

Setting a boundary for limiting acceleration according to the vehicle dynamics boundary information;

Judging whether the planned acceleration based on the speed track strategy exceeds the boundary of the set limiting acceleration or not;

if the planned acceleration is greater than the upper acceleration boundary,

Obtaining a calculation formula: a _delta＝a _{Planning acceleration} -a _{Upper boundary of acceleration} ;

if the planned acceleration is less than the lower acceleration boundary,

Obtaining a calculation formula: a _delta＝a _{Lower boundary of acceleration} -a _{Planning acceleration} ;

According to the formula: cost _{acceleration and deceleration rate} ＝a_delta x w2, obtain Cost _{acceleration and deceleration rate} ;

Wherein a _{Upper boundary of acceleration} 、a _{Lower boundary of acceleration} is a standard amount; w2 is the weight and the standard quantity.

Further, according to the road speed limit, the expected speed, the acceleration and deceleration speed, jerk and the historical track, the screening speed trajectory strategy further comprises:

Setting a boundary of a limit jerk according to the vehicle dynamics boundary information;

determining whether the speed trajectory strategy based plan jerk exceeds the boundary of the set limit jerk;

If the plan jerk is greater than the jerk upper boundary,

Obtaining a calculation formula: a _delta＝a_jerk-a_{jerk Upper boundary of} ;

if the plan jerk is less than the jerk lower boundary,

Obtaining a calculation formula: a _delta＝a_{jerk Lower boundary of} -a_jerk;

According to the formula: cost _jerk＝a_delta x w3, obtain Cost _{acceleration and deceleration rate} ;

wherein ajerk _{Upper boundary of} 、a_{jerk Lower boundary of} is a standard amount; w3 is the weight and the standard quantity.

Further, according to the road speed limit, the expected speed, the acceleration and deceleration speed, jerk and the historical track, the screening speed trajectory strategy further comprises:

acquiring the variation of the speed track planned in the current period and the previous period based on the speed track planned in the adjacent previous period;

Comprising the formula: s _delta＝abs(s _{Historical planning speed trajectory} -s _{Current planned speed trajectory} );

Cost _{Historical trajectories} ＝s_delta*w4；

Wherein w4 is weight, a standard amount; s _{Historical planning speed trajectory} is the speed track planned in the adjacent previous cycle, and s _{Historical planning speed trajectory} is the speed track planned in the current cycle.

According to two aspects of the present invention, there is provided a vehicle speed ride optimization apparatus including:

the driving planning module is used for carrying out secondary planning after planning based on primary path planning and speed planning based on automatic driving of the vehicle;

The path planning module is used for planning a path based on space-time information of the obstacle on the self-vehicle running route;

the speed planning module is used for carrying out speed planning based on the spatial interference of the dynamic track of the obstacle and the self-vehicle driving route in time synchronization;

And the driving decision module is used for making decisions of the driving route of the bicycle based on the path planning and the speed planning.

According to three aspects of the present invention, there is provided an electronic apparatus including: the device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;

the memory stores a computer program that, when executed by the processor, causes the processor to perform the steps of the vehicle speed ride optimization method.

According to four aspects of the present invention, there is provided a computer-readable storage medium comprising: the method comprises the steps of storing a computer program executable by the electronic device, and enabling the electronic device to execute the vehicle speed ride optimization method when the computer program runs on the electronic device.

According to five aspects of the present invention, there is provided a vehicle including:

the electronic equipment is used for realizing the vehicle speed smoothness optimization method;

a processor that runs a program, and executes the steps of the vehicle speed ride optimization method from data output from the electronic device when the program is running;

a storage medium for storing a program that, when executed, performs the steps of the vehicle speed ride optimization method on data output from the electronic device.

Through the scheme, the following beneficial technical effects are obtained:

According to the application, through drawing an obstacle ST diagram and space diagrams of a plurality of blocks, a tunnel which can be passed through by the vehicle is found, so that the secondary planning has a plurality of alternative schemes, and the executable guide track is optimized after the secondary planning.

According to the application, the optimal guiding track is planned by combining dynamic barriers and static barriers with the dynamic boundary of the vehicle, so that the trafficability of the vehicle is improved, and the probability of planning failure is reduced.

According to the application, the speed control is introduced into the secondary planning, and the guiding track is optimized through the acceleration and deceleration control, so that the probability of success of obstacle avoidance of the vehicle is increased.

The application deletes the alternative scheme by combining the information of road speed limit, expected speed limit, history track and the like, so that the output track scheme has higher executable performance.

Drawings

FIG. 1 is a flow chart of a vehicle speed ride optimization method provided by one or more embodiments of the present invention.

FIG. 2 is a block diagram of a vehicle speed ride optimization apparatus according to one or more embodiments of the present invention.

Fig. 3 is a schematic diagram of an ST view of an embodiment of the present invention.

Fig. 4 is a schematic diagram of an ST view of three obstacles in accordance with an embodiment of the present invention.

FIG. 5 is a schematic illustration of the interference of a host vehicle trajectory with two obstacle vehicle trajectories according to one embodiment of the invention.

Fig. 6 is a schematic diagram of an ST view of a two-obstacle vehicle according to an embodiment of the invention.

FIG. 7 is a schematic illustration of a host vehicle track punctuation in accordance with one embodiment of the invention.

Fig. 8 is a schematic illustration of a vehicle trajectory trace of an embodiment of the present invention.

Fig. 9 is a schematic diagram of a road speed limit Cost according to an embodiment of the invention.

Fig. 10 is a schematic illustration of acceleration/deceleration jerk Cost of one embodiment of the present invention.

FIG. 11 is a schematic diagram of a historical track Cost of an embodiment of the invention.

FIG. 12 is a block diagram of an electronic device configured to implement a method for optimizing vehicle speed ride quality in accordance with one or more embodiments of the present invention.

Detailed Description

The following description of the embodiments of the present invention will be made apparent and fully in view of the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

FIG. 1 is a flow chart of a vehicle speed ride optimization method provided by one or more embodiments of the present invention.

The vehicle speed ride optimization method as shown in fig. 1 includes:

step S1, performing secondary planning after planning based on primary path planning and speed planning based on automatic driving of a vehicle;

Step S2, path planning is conducted based on space-time information of the obstacle on the self-vehicle running route;

step S3, based on time synchronization, the dynamic track of the obstacle interferes with the space of the self-vehicle driving route to make speed planning;

And S4, making a decision of the self-vehicle driving route based on the path planning and the speed planning.

Specifically, in one embodiment, based on the function module that generates the ST map, one hatched block is drawn to represent an obstacle on a two-dimensional map of the time axis and the position axis as time passes and the vehicle moves. The curve formed by the P points of the shadow patterns is bypassed and used as the guiding track of the vehicle to avoid the obstacle, in the embodiment, the guiding track of the vehicle is based on the space-time information of the obstacle on the self-vehicle driving route, the path planning is performed, the time synchronization is based on the space interference of the dynamic track of the obstacle and the self-vehicle driving route, the speed planning is performed, so that the guiding track is perfectly avoided from the guiding track of the shadow patterns, and the dynamics limiting rule is not violated in the speed planning. When the secondary planning is carried out, and the first path planning is needed, an accurate and reasonable passing tunnel space is obtained, and sufficient space areas exist among a plurality of shadow image blocks, so that the speed planning can have dynamics rationality. And selecting an optimal track for controlling steering from the transverse direction and controlling the vehicle speed from the longitudinal direction through screening.

In this embodiment, making a path plan based on the spatio-temporal information that the obstacle appears on the own-vehicle travel route includes:

drawing an occlusion region of the obstacle based on time deduction;

Drawing a speed track of the shielding area for avoiding the obstacle by the vehicle according to the shielding area for drawing the obstacle;

Wherein the shielding areas based on the barriers comprise a plurality of shielding areas, and the spaces between the shielding areas of the barriers are planned and drawn;

A velocity trajectory strategy marking the space between the occlusion regions across the obstacle is used for velocity planning.

Specifically, in one embodiment, the vehicle passing obstacles include static and dynamic obstacles, e.g., stones on the road are static obstacles and other moving vehicles are dynamic obstacles. The obstacles may include a plurality and a plurality with respect to the advancing direction of the host vehicle, and the host vehicle needs to penetrate and detour between the respective obstacles. Based on the time deduction, an occlusion region (shadow pattern) of the obstacle is drawn, and a space between the shadow patterns is described as a tunnel to be passed through by the shadow patterns. Considering the outline of the vehicle itself in the space of the passing tunnel, only the relatively centered position is most suitable, and the reference point can be marked roughly first. By means of speed planning, the reference points are connected into a continuous smooth line, which represents the track of the guided vehicle. The smoother the line, the more gentle the control, the softer the motion and the better the comfort.

In this embodiment, based on time synchronization, the performing speed planning includes:

Acquiring vehicle dynamics boundary information;

Deducing a speed track of a space between shielding sections of the mark crossing the obstacle according to the vehicle dynamics boundary information;

according to the deduction result, the screening speed track strategy comprises,

Giving up a speed track strategy of an occlusion area incapable of realizing obstacle avoidance, and judging whether the speed track strategy of the occlusion area capable of realizing obstacle avoidance is remained;

If the speed track strategy of the shielding area capable of avoiding the obstacle exists, controlling the longitudinal and transverse movement of the vehicle according to the speed track strategy of the shielding area capable of avoiding the obstacle.

Specifically, there are a plurality of tunnels as traffic in the space between the plurality of shaded tiles, but not all are suitable as currently selected tunnels, and physical laws of the vehicle itself, such as grip, steering torque, etc., need to be considered, so that the traffic tunnels (blank areas between shaded tiles) are selected within the capability that the vehicle can achieve. The longitudinal and transverse movements actually achievable by the vehicle are controlled based on the range of capabilities that the vehicle can achieve including achieving a speed trajectory strategy for the occlusion region that avoids the obstacle.

In this embodiment, based on time synchronization, the spatial interference between the dynamic track of the obstacle and the travelling path of the vehicle, the speed planning further includes:

If the speed track strategy of the shielding area capable of avoiding the obstacle is not realized at present, introducing acceleration control;

And correcting the speed track strategy of the shielding area which can not realize the avoidance of the obstacle at present according to the introduced acceleration control, and generating the speed track strategy of the shielding area which can realize the avoidance of the obstacle.

Specifically, in one embodiment, although a tunnel is selected to pass through a blank area between the shadow tiles, other vehicles are not stable and motionless like a static obstacle, the relative position changes slightly, and the vehicle cannot travel at a uniform speed along a straight line without changing during movement. And the vehicle acceleration is adjusted through the early rough mark reference points, so that the vehicle tracks the rough mark reference points to form a fine curve track, and obstacle avoidance is realized. Where speed or acceleration, both magnitude and direction are covered.

In this embodiment, the screening speed trajectory strategy further includes:

Obtaining a calculation formula:

Cost＝Cost _{Road speed limit} +Cost _{Desired speed} +Cost _{acceleration and deceleration rate} +Cost_jerk+Cost _{Historical trajectories} ；

screening a speed track strategy according to the road speed limit, the expected speed, the acceleration and deceleration speed, jerk and the historical track;

The method comprises the steps of taking a speed track strategy corresponding to a minimum Cost value as a currently executed speed track strategy according to a plurality of speed track strategies.

Specifically, in one embodiment, the trajectory is filtered by sorting the trajectory according to road speed limit, desired speed, acceleration and deceleration, jerk, historical trajectory conditions.

And calculating the Cost of the weights, and taking the trace with the minimum value as the result of outputting the trace after adding the Cost.

The calculation formula of the Cost value is as follows:

Cost＝Cost _{Road speed limit} +Cost _{Desired speed} +Cost _{acceleration and deceleration rate} +Cost_jerk+Cost _{Historical trajectories}

The single Cost calculation method comprises the following steps of:

delta＝max(v _{planning speed} -v _{Road speed limit} ，0)；

Cost _{Road speed limit} ＝e^delta*w；

Wherein w is a weight and a standard amount.

In this embodiment, the speed track policy is selected according to the road speed limit, the expected speed, the acceleration/deceleration speed, jerk and the history track, including:

Obtaining a calculation formula:

delta＝max(v _{planning speed} -v _{Road speed limit} ，0)；

Cost _{Road speed limit} ＝e^delta*w；

Wherein w is a weight and a standard amount.

Specifically, in one embodiment, the single Cost calculation method uses a road speed limit value as a reference value, and the vehicle speed is adjusted around the reference value in an up-down feedback manner, so as to reduce the increase. Delta is the offset value used for exponential amplification to obtain the Cost value.

In this embodiment, based on the road speed limit, the desired speed, the acceleration/deceleration, jerk and the history track, the screening speed trajectory strategy further comprises:

Obtaining a calculation formula:

v _{Desired speed} ＝min(v _{Cruise speed} ,v _{Road speed limit} ,v _{Initial velocity} +a _{desired acceleration} *t)；

delta＝abs(v _{planning speed} -v _{Desired speed} )；

Cost _{Desired speed} ＝delta*w1；

Wherein v _{Cruise speed} 、v _{Road speed limit} and a _{desired acceleration} are the calibration amounts, v _{Initial velocity} is the initial speed of the vehicle, and w1 is the weight.

Specifically, in one embodiment, the single-item Cost calculation method includes a desired speed Cost:

v _{Desired speed} ＝min(v _{Cruise speed} ,v _{Road speed limit} ,v _{Initial velocity} +a _{desired acceleration} *t)；

delta＝abs(v _{planning speed} -v _{Desired speed} )；

Cost _{Desired speed} ＝delta*w1；

Wherein v _{Cruise speed} 、v _{Road speed limit} and a _{desired acceleration} are the calibration amounts, v _{Initial velocity} is the initial speed of the vehicle, and w1 is the weight. The speed of the vehicle is fed back up and down around a reference value by taking a desired speed value as the reference value, so that the speed is increased and decreased.

In this embodiment, based on the road speed limit, the desired speed, the acceleration/deceleration, jerk and the history track, the screening speed trajectory strategy further comprises:

setting a boundary for limiting acceleration according to the vehicle dynamics boundary information;

Judging whether the planned acceleration based on the speed track strategy exceeds the boundary of the set limiting acceleration or not;

if the planned acceleration is greater than the upper acceleration boundary,

Obtaining a calculation formula: a _delta＝a _{Planning acceleration} -a _{Upper boundary of acceleration} ;

if the planned acceleration is less than the lower acceleration boundary,

Obtaining a calculation formula: a _delta＝a _{Lower boundary of acceleration} -a _{Planning acceleration} ;

According to the formula: cost _{acceleration and deceleration rate} ＝a_delta x w2, obtain Cost _{acceleration and deceleration rate} ;

Wherein a _{Upper boundary of acceleration} 、a _{Lower boundary of acceleration} is a standard amount; w2 is the weight and the standard quantity.

Specifically, in one embodiment, the single-item Cost calculation method includes an acceleration/deceleration Cost:

Whether the acceleration of the planned trajectory is within a limited acceleration range.

A _delta＝a _{Planning acceleration} -a _{Upper boundary of acceleration} when the planned acceleration is greater than the upper acceleration boundary;

A _delta＝a _{Lower boundary of acceleration} -a _{Planning acceleration} when the planned acceleration is less than the upper acceleration boundary;

Cost _{acceleration and deceleration rate} ＝a_delta*w2；

Wherein a _{Upper boundary of acceleration} 、a _{Lower boundary of acceleration} is a standard amount; w2 is the weight and the standard quantity.

In this embodiment, based on the road speed limit, the desired speed, the acceleration/deceleration, jerk and the history track, the screening speed trajectory strategy further comprises:

Setting a boundary of a limit jerk according to the vehicle dynamics boundary information;

determining whether the speed trajectory strategy based plan jerk exceeds the boundary of the set limit jerk;

If the plan jerk is greater than the jerk upper boundary,

Obtaining a calculation formula: a _delta＝a_jerk-a_{jerk Upper boundary of} ;

if the plan jerk is less than the jerk lower boundary,

Obtaining a calculation formula: a _delta＝a_{jerk Lower boundary of} -a_jerk;

According to the formula: cost _jerk＝a_delta x w3, obtain Cost _{acceleration and deceleration rate} ;

wherein ajerk _{Upper boundary of} 、a_{jerk Lower boundary of} is a standard amount; w3 is the weight and the standard quantity.

Specifically, the single Cost calculation method includes jerk Cost:

A _delta＝a _{Planning acceleration} -a_{jerk Upper boundary of} when the plan jerk is greater than the jerk upper boundary;

Jerk _delta＝jerk _{Lower boundary of} -jerk _{Planning jerk} when the plan jerk is less than the jerk upper boundary;

Cost_jerk＝jerk_delta*w3；

wherein a _{jerk Upper boundary of} 、a_{jerk Lower boundary of} is a standard amount; w3 is the weight and the standard quantity.

In this embodiment jerk is the derivative of acceleration with respect to time, i.e. jerk. Cost jerk is the penalty weight for jerk.

In this embodiment, based on the road speed limit, the desired speed, the acceleration/deceleration, jerk and the history track, the screening speed trajectory strategy further comprises:

acquiring the variation of the speed track planned in the current period and the previous period based on the speed track planned in the adjacent previous period;

Comprising the formula: s _delta＝abs(s _{Historical planning speed trajectory} -s _{Current planned speed trajectory} );

Cost _{Historical trajectories} ＝s_delta*w4；

Wherein w4 is weight, a standard amount; s _{Historical planning speed trajectory} is the speed track planned in the adjacent previous cycle, and s _{Historical planning speed trajectory} is the speed track planned in the current cycle.

Specifically, the variation of the planned track and the previous periodic track is used as a Cost calculation basis.

s_delta＝abs(s _{Historical planning speed trajectory} -s _{Current planned speed trajectory} )；

Cost _{Historical trajectories} ＝s_delta*w4；

FIG. 2 is a block diagram of a vehicle speed ride optimization apparatus according to one or more embodiments of the present invention.

The vehicle speed ride optimization apparatus as shown in fig. 2 includes: the system comprises a driving planning module, a path planning module, a speed planning module and a driving decision module;

the driving planning module is used for carrying out secondary planning after planning based on primary path planning and speed planning based on automatic driving of the vehicle;

The path planning module is used for planning a path based on space-time information of the obstacle on the self-vehicle running route;

the speed planning module is used for carrying out speed planning based on the spatial interference of the dynamic track of the obstacle and the self-vehicle driving route in time synchronization;

And the driving decision module is used for making decisions of the driving route of the bicycle based on the path planning and the speed planning.

It should be noted that, although the present system discloses only the driving planning module, the path planning module, the speed planning module and the driving decision module, the present device is not meant to be limited to the above basic functional modules, but rather, the present invention is meant to be expressed in that, based on the above basic functional modules, one or more functional modules can be added arbitrarily by a person skilled in the art in combination with the prior art to form infinite embodiments or technical solutions, that is, the present system is open rather than closed, and the scope of protection of the claims of the present invention is not limited to the above disclosed basic functional modules because the present embodiment discloses only individual basic functional modules.

Through the scheme, the following beneficial technical effects are obtained:

According to the application, through drawing an obstacle ST diagram and space diagrams of a plurality of blocks, a tunnel which can be passed through by the vehicle is found, so that the secondary planning has a plurality of alternative schemes, and the executable guide track is optimized after the secondary planning.

According to the application, the optimal guiding track is planned by combining dynamic barriers and static barriers with the dynamic boundary of the vehicle, so that the trafficability of the vehicle is improved, and the probability of planning failure is reduced.

According to the application, the speed control is introduced into the secondary planning, and the guiding track is optimized through the acceleration and deceleration control, so that the probability of success of obstacle avoidance of the vehicle is increased.

The application deletes the alternative scheme by combining the information of road speed limit, expected speed limit, history track and the like, so that the output track scheme has higher executable performance.

Fig. 3 is a schematic diagram of an ST view of an embodiment of the present invention.

Fig. 4 is a schematic diagram of an ST view of three obstacles in accordance with an embodiment of the present invention.

FIG. 5 is a schematic illustration of the interference of a host vehicle trajectory with two obstacle vehicle trajectories according to one embodiment of the invention.

Fig. 6 is a schematic diagram of an ST view of a two-obstacle vehicle according to an embodiment of the invention.

FIG. 7 is a schematic illustration of a host vehicle track punctuation in accordance with one embodiment of the invention.

Fig. 8 is a schematic illustration of a vehicle trajectory trace of an embodiment of the present invention.

Fig. 9 is a schematic diagram of a road speed limit Cost according to an embodiment of the invention.

Fig. 10 is a schematic illustration of acceleration/deceleration jerk Cost of one embodiment of the present invention.

FIG. 11 is a schematic diagram of a historical track Cost of an embodiment of the invention.

In one embodiment, the vehicle path planning track and the obstacle vehicle prediction track are input and output as the speed planning track. Therefore, a proper speed planning track which accords with vehicle dynamics and has vehicle smoothness is found in a plurality of planning spaces among the multiple obstacles and is used as a basis for subsequent track planning.

As shown in fig. 3, the input data is an ST chart including obstacle information. The ST chart shows time information of an obstacle vehicle and an obstacle on a travel route of the own vehicle, that is, the obstacle appears on a planned travel route of the own vehicle for a certain period of time.

The obstacle vehicles in the figure are on the future driving track of the vehicle in the time period from t ₁ to t ₂. At time t ₁, the distance from the head of the obstacle vehicle to the current position of the vehicle is S ₁, and the distance from the tail of the obstacle vehicle to the current position of the vehicle is S ₀; at time t ₂, the distance from the head of the obstacle vehicle to the current position of the vehicle is S ₃, and the distance from the tail of the obstacle vehicle to the current position of the vehicle is S ₂.

For track traj, the larger the slope, the greater the vehicle planning speed. On traj ₁, point P is a point on the vehicle speed map, and indicates that the vehicle is traveling a distance from the front of the vehicle S ₁ at time t ₀. Therefore, when the vehicle speed planning trajectory is traj ₁, it is decided to go beyond the vehicle, and when it is decided to traj ₂, it is decided to give way to the vehicle.

With respect to the dynamic planning and the quadratic planning, the self-vehicle velocity planning trajectory traj is calculated from the dynamic planning and the quadratic planning.

In another embodiment, as shown in fig. 4, assuming that three obstacles constitute the ST map, it can be seen on the map that four planning spaces are divided by the three obstacles for planning a route.

In another embodiment, as shown in fig. 5, veh_o is an algorithm (i.e. the vehicle speed smoothness optimization method in the present application) in the present embodiment carried by the own vehicle, veh_a is an obstacle vehicle a, veh_b is an obstacle vehicle b, the predicted trajectories of the two obstacle vehicles respectively pass through the path planning trajectories of the own vehicle, veh_a starts to enter the own vehicle trajectory at 20m at 5s, leaves at 30m at 7s, veh_b starts to enter the own vehicle trajectory at 30m at 2s, and leaves at 40m at 4 s. Whereby the operating mode is represented in combination with the ST chart as the pattern of fig. 6.

From fig. 4, further transformation is to fig. 7, the spaces D1, D4 cannot be planned successfully due to dynamics limitations, and D2, D3 are viable spaces. The trajectory is allowed to go on the obstacle decision above and is overridden on the decision below. For example, the T1 trajectory is to clear the upper obstacle beyond the lower two obstacles. The existing algorithm directly calculates only one so-called optimal planning track through dynamic planning. The application will send out the optimal speed planning track of each feasible space, and provide more choices for the subsequent optimization.

Optimizing the speed planning track by secondary planning comprises determining the boundary of each space D and performing primary secondary planning. As shown in fig. 8, in combination with the speed acceleration limitation, a preliminary quadratic programming is performed, and continuous tracks T1, T2 are obtained from the marked P points, and this operation is performed for each feasible space of the previous step. Thus obtaining a plurality of self-vehicle speed planning tracks.

Code logic corresponding to the functional module includes generating a barrier decision corresponding to a DP (graphical representation of a combination of space D and labeled P points representing dynamic programming) output trajectory; adding a boundary according to the obstacle decision; and performing preliminary optimization on the DP output track by using a quadratic programming tool, and storing the output track.

In another embodiment, the several planned trajectories that have been obtained are screened.

As shown in fig. 9, 10, and 11, the trajectory is screened according to road speed limit, desired speed, acceleration/deceleration, jerk, and history.

And calculating the Cost of the weights, wherein the track with the smallest sum of the Cost is the output track.

The calculation formula is as follows:

Cost＝Cost _{Road speed limit} +Cost _{Desired speed} +Cost _{acceleration and deceleration rate} +Cost_jerk+Cost _{Historical trajectories}

The single Cost calculation method comprises the following steps of:

delta＝max(v _{planning speed} -v _{Road speed limit} ，0)；

Cost _{Road speed limit} ＝e^delta*w；

Wherein w is a weight and a standard amount.

The single-item Cost calculation method comprises the following steps of:

v _{Desired speed} ＝min(v _{Cruise speed} ,v _{Road speed limit} ,v _{Initial velocity} +a _{desired acceleration} *t)；

delta＝abs(v _{planning speed} -v _{Desired speed} )；

Cost _{Desired speed} ＝delta*w1；

Wherein v _{Cruise speed} 、v _{Road speed limit} and a _{desired acceleration} are the calibration amounts, v _{Initial velocity} is the initial speed of the vehicle, and w1 is the weight.

The single Cost calculation method comprises the steps of adding and subtracting speed/jerk Cost:

Whether the acceleration of the planned trajectory is within a limited acceleration range.

When the planned acceleration is greater than the upper acceleration boundary,

a^d _e ¹ _ta＝a _{Planning acceleration} -a _{Upper boundary of}

When the planned acceleration is less than the upper acceleration boundary,

a^d _e ^l _ta＝a _{Lower boundary of} -a _{Planning acceleration}

Cost _{acceleration and deceleration rate} ＝a_delta*w2

Similarly, when the plan jerk is greater than the jerk upper boundary,

a^d _e ^l _ta＝a _{Planning acceleration} -a _{Upper boundary of}

When the plan jerk is less than the jerk upper boundary,

jerk_delta＝jerk _{Lower boundary of} -jerk _{Planning jerk}

Cost_jerk＝jerk_delta*w3

Wherein a _{Upper boundary of} (acceleration), a _{Lower boundary of} (acceleration) and a _{Upper boundary of} (jerk)、a _{Lower boundary of} (jerk) are calibrated quantities; w2 and w3 are weights and standard amounts.

The single-item Cost calculation method comprises the steps of:

And the variation of the planned track and the track of the previous period is used as a Cost calculation basis.

s_delta＝abs(s _{Historical trajectories} -s _{Planning trajectories} )；

Cost _{Historical trajectories} ＝s_delta*w4；

Wherein w4 is weight, a standard amount; s _{Historical trajectories} is the output planning track of the last period module.

In the code logic in the corresponding functional module, the selected track speed is as fast as possible; speed limit Cost penalizes exponentially (i.e., increases exponentially); selecting a track similar to the historical track; and adopting the track point square difference sum calculation.

FIG. 12 is a block diagram of an electronic device configured to implement a method for optimizing vehicle speed ride quality in accordance with one or more embodiments of the present invention.

As shown in fig. 12, the present application provides an electronic apparatus including: the device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;

The memory stores a computer program that, when executed by the processor, causes the processor to perform the steps of a vehicle speed ride optimization method.

The present application also provides a computer-readable storage medium storing a computer program executable by an electronic device, which when run on the electronic device causes the electronic device to perform the steps of a vehicle speed ride optimization method.

The present application also provides a vehicle including:

The electronic equipment is used for realizing the vehicle speed smoothness optimization method;

a processor that runs a program, and executes a vehicle speed ride optimization method from data output from the electronic device when the program runs;

a storage medium storing a program that, when executed, performs the steps of the vehicle speed ride optimization method on data output from the electronic device.

The communication bus mentioned above for the electronic device may be a peripheral component interconnect standard (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, etc. The communication bus may be classified as an address bus, a data bus, a control bus, or the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.

The electronic device includes a hardware layer, an operating system layer running on top of the hardware layer, and an application layer running on top of the operating system. The hardware layer includes hardware such as a central processing unit (CPU, central Processing Unit), a memory management unit (MMU, memory Management Unit), and a memory. The operating system may be any one or more computer operating systems that implement electronic device control via processes (processes), such as a Linux operating system, a Unix operating system, an Android operating system, an iOS operating system, or a windows operating system, etc. In addition, in the embodiment of the present invention, the electronic device may be a handheld device such as a smart phone, a tablet computer, or an electronic device such as a desktop computer, a portable computer, which is not particularly limited in the embodiment of the present invention.

The execution body controlled by the electronic device in the embodiment of the invention can be the electronic device or a functional module in the electronic device, which can call a program and execute the program. The electronic device may obtain firmware corresponding to the storage medium, where the firmware corresponding to the storage medium is provided by the vendor, and the firmware corresponding to different storage media may be the same or different, which is not limited herein. After the electronic device obtains the firmware corresponding to the storage medium, the firmware corresponding to the storage medium can be written into the storage medium, specifically, the firmware corresponding to the storage medium is burned into the storage medium. The process of burning the firmware into the storage medium may be implemented by using the prior art, and will not be described in detail in the embodiment of the present invention.

The electronic device may further obtain a reset command corresponding to the storage medium, where the reset command corresponding to the storage medium is provided by the provider, and the reset commands corresponding to different storage media may be the same or different, which is not limited herein.

At this time, the storage medium of the electronic device is a storage medium in which the corresponding firmware is written, and the electronic device may respond to a reset command corresponding to the storage medium in which the corresponding firmware is written, so that the electronic device resets the storage medium in which the corresponding firmware is written according to the reset command corresponding to the storage medium. The process of resetting the storage medium according to the reset command may be implemented in the prior art, and will not be described in detail in the embodiments of the present invention.

For convenience of description, the above devices are described as being functionally divided into various units and modules. Of course, the functions of the units, modules may be implemented in one or more pieces of software and/or hardware when implementing the application.

It will be understood by those skilled in the art that all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs unless defined otherwise. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

For the purposes of simplicity of explanation, the methodologies are shown and described as a series of acts, it is to be understood and appreciated by one of ordinary skill in the art that the methodologies are not limited by the order of acts, as some acts may, in accordance with the methodologies, take place in other order or concurrently. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred embodiments, and that the acts are not necessarily required by the embodiments of the invention.

From the above description of embodiments, it will be apparent to those skilled in the art that the present application may be implemented in software plus a necessary general hardware platform. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a storage medium, such as a ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform the method according to the embodiments or some parts of the embodiments of the present application.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.

Claims (10)

1. The vehicle speed ride optimization method is characterized by comprising the following steps of:

performing secondary planning after planning based on primary path planning and speed planning based on automatic driving of the vehicle;

wherein, based on the space-time information that the obstacle appears on the route of the self-vehicle, make the route planning;

based on time synchronization, the dynamic track of the obstacle interferes with the space of the self-vehicle driving route to make speed planning;

Based on the path planning and the speed planning, a decision of the self-vehicle driving route is made.

2. The vehicle speed ride optimization method according to claim 1, wherein the planning a path based on the spatio-temporal information of the obstacle present on the own vehicle travel route comprises:

drawing an occlusion region of the obstacle based on time deduction;

Drawing a speed track of the shielding area for avoiding the obstacle by the own vehicle according to the shielding area for drawing the obstacle;

wherein, based on the shielding area of the obstacle comprises a plurality of shielding areas, the space between the shielding areas of the obstacle is planned and drawn;

and marking a speed track strategy for crossing the space between the shielding intervals of the obstacle for speed planning.

3. The vehicle speed ride optimization method according to claim 2, wherein the performing speed planning based on the spatial interference between the dynamic trajectory of the obstacle and the self-vehicle driving route based on the time synchronization includes:

Acquiring vehicle dynamics boundary information;

Deducing a speed track of the mark crossing the space between the shielding sections of the obstacle according to the vehicle dynamics boundary information;

according to the deduction result, the screening speed track strategy comprises,

Giving up a speed track strategy of a shielding area which can not realize the avoidance of the obstacle, and judging whether the speed track strategy of the shielding area which can realize the avoidance of the obstacle is remained;

if the speed track strategy for avoiding the shielding area of the obstacle is available, controlling the longitudinal and transverse movement of the vehicle according to the speed track strategy for avoiding the shielding area of the obstacle.

4. The vehicle speed ride optimization method of claim 3, wherein the performing the speed planning based on the spatial interference of the dynamic trajectory of the obstacle and the self-vehicle driving route based on the time synchronization further comprises:

If the speed track strategy of the shielding area for avoiding the obstacle is not realized at present, introducing acceleration control;

And correcting a speed track strategy of a shielding area which cannot realize the avoidance of the obstacle at present according to the introduced acceleration control, and generating the speed track strategy of the shielding area which can realize the avoidance of the obstacle.

5. The vehicle speed ride optimization method of claim 4, wherein the screening speed trajectory strategy further comprises:

Obtaining a calculation formula:

Cost＝Cost _{Road speed limit} +Cost _{Desired speed} +Cost _{acceleration and deceleration rate} +Cost_jerk+Cost _{Historical trajectories} ；

screening a speed track strategy according to the road speed limit, the expected speed, the acceleration and deceleration speed, jerk and the historical track;

The method comprises the steps of taking a speed track strategy corresponding to a minimum Cost value as a currently executed speed track strategy according to a plurality of speed track strategies.

6. The vehicle speed ride optimization method according to claim 5, wherein the screening the speed trajectory strategy according to the road speed limit, the expected speed, the acceleration/deceleration, jerk, and the history trajectory comprises:

Obtaining a calculation formula:

delta＝max(v _{planning speed} -v _{Road speed limit} ，0)；

Cost _{Road speed limit} ＝e^delta*w；

Wherein w is a weight and a standard amount.

7. The vehicle speed ride optimization method according to claim 6, wherein the screening the speed trajectory strategy according to the road speed limit, the expected speed, the acceleration/deceleration, jerk, and the history trajectory further comprises:

Obtaining a calculation formula:

v _{Desired speed} ＝min(v _{Cruise speed} ,v _{Road speed limit} ,v _{Initial velocity} +a _{desired acceleration} *t)；

delta＝abs(v _{planning speed} -v _{Desired speed} )；

Cost _{Desired speed} ＝delta*w1；

Wherein v _{Cruise speed} 、v _{Road speed limit} and a _{desired acceleration} are the calibration amounts, v _{Initial velocity} is the initial speed of the vehicle, and w1 is the weight.

8. The vehicle speed ride optimization method of claim 7, wherein the screening the speed trajectory strategy according to the road speed limit, the desired speed, the acceleration/deceleration, jerk, and the historical trajectory further comprises:

Setting a boundary for limiting acceleration according to the vehicle dynamics boundary information;

Judging whether the planned acceleration based on the speed track strategy exceeds the boundary of the set limiting acceleration or not;

if the planned acceleration is greater than the upper acceleration boundary,

Obtaining a calculation formula: a _delta＝a _{Planning acceleration} -a _{Upper boundary of acceleration} ;

if the planned acceleration is less than the lower acceleration boundary,

Obtaining a calculation formula: a _delta＝a _{Lower boundary of acceleration} -a _{Planning acceleration} ;

According to the formula: cost _{acceleration and deceleration rate} ＝a_delta x w2, obtain Cost _{acceleration and deceleration rate} ;

Wherein a _{Upper boundary of acceleration} 、a _{Lower boundary of acceleration} is a standard amount; w2 is the weight and the standard quantity.

9. The vehicle speed ride optimization method of claim 8, wherein the screening the speed trajectory strategy according to the road speed limit, the desired speed, the acceleration/deceleration, jerk, and the historical trajectory further comprises:

Setting a boundary of a limit jerk according to the vehicle dynamics boundary information;

determining whether the speed trajectory strategy based plan jerk exceeds the boundary of the set limit jerk;

If the plan jerk is greater than the jerk upper boundary,

Obtaining a calculation formula: a _delta＝a_jerk-a_{jerk Upper boundary of} ;

if the plan jerk is less than the jerk lower boundary,

Obtaining a calculation formula: a _delta＝a_{jerk Lower boundary of} -a_jerk;

According to the formula: cost _jerk＝a_delta x w3, obtain Cost _{acceleration and deceleration rate} ;

wherein ajerk _{Upper boundary of} 、a_{jerk Lower boundary of} is a standard amount; w3 is the weight and the standard quantity.

10. The vehicle speed ride optimization method of claim 9, wherein the screening the speed trajectory strategy according to the road speed limit, the desired speed, the acceleration/deceleration, jerk, and the historical trajectory further comprises:

acquiring the variation of the speed track planned in the current period and the previous period based on the speed track planned in the adjacent previous period;

Comprising the formula: s _delta＝abs(s _{Historical planning speed trajectory} -s _{Current planned speed trajectory} );

Cost _{Historical trajectories} ＝s_delta*w4；

Wherein w4 is weight, a standard amount; s _{Historical planning speed trajectory} is the speed track planned in the adjacent previous cycle, and s _{Historical planning speed trajectory} is the speed track planned in the current cycle.