Automatic driving method and device and carrier

Abstract

The invention discloses an automatic driving method and device and a carrier, and relates to the technical field of carrier driving. The method comprises the following steps: determining a conflict area; respectively calculating the residual braking decision time when the automatic driving vehicle runs at the maximum deceleration speed and the residual acceleration decision time when the automatic driving vehicle runs at the maximum acceleration speed; according to the residual braking decision time and the residual acceleration decision time, the probability that the automatic driving vehicle passes through the conflict area is calculated; and according to the probability that the automatic driving vehicle passes through the conflict area, controlling the automatic driving vehicle to decelerate at the maximum deceleration so as to safely stop in front of the conflict area or to accelerate at the maximum acceleration so as to safely pass through the conflict area. According to the embodiment, the technical problem of frequent sudden braking of the automatic driving vehicle at the intersection can be solved.

Description

Technical Field

[0001] The present invention relates to the field of vehicle driving technology, and in particular to an automatic driving method, device and vehicle. Background Art

[0002] When autonomous driving vehicles are driving on urban roads, they will inevitably conflict with the driving trajectories of social vehicles driven by human drivers. Especially at intersections, the driving trajectories of turning vehicles and straight-moving vehicles often conflict, and straight-moving vehicles need to decide whether to give way to avoid conflicts.

[0003] For low-speed autonomous driving vehicles, the handling of these dynamic obstacle vehicles is currently mainly based on the speed, direction, and road structure of the obstacle vehicle to predict the movement trend in the next few seconds, and the predicted trajectory to determine whether the autonomous driving vehicle and the obstacle vehicle will conflict in the future. Once the predicted trajectory intersects with the trajectory of the autonomous driving vehicle, it will trigger the emergency braking of the autonomous driving vehicle. However, this strategy is relatively conservative, resulting in frequent emergency braking of autonomous driving vehicles at intersections. If there are vehicles following closely, it often causes a series of rear-end collisions due to insufficient reaction time, which will also reduce the overall efficiency of the autonomous driving vehicle. Summary of the invention

[0004] In view of this, an embodiment of the present invention provides an autonomous driving method, device and vehicle to solve the technical problem of frequent sudden braking of autonomous driving vehicles at intersections.

[0005] To achieve the above objective, according to one aspect of an embodiment of the present invention, an automatic driving method is provided, including:

[0006] Identify conflict areas;

[0007] Calculate the remaining braking decision time when the autonomous driving vehicle is decelerating at the maximum deceleration and the remaining acceleration decision time when it is accelerating at the maximum acceleration;

[0008] Calculate the probability of the autonomous driving vehicle passing through the conflict area according to the remaining braking decision time and the remaining acceleration decision time;

[0009] According to the probability of the autonomous driving vehicle passing through the conflict area, the autonomous driving vehicle is controlled to decelerate at the maximum deceleration so as to stop safely before the conflict area or to accelerate at the maximum acceleration so as to pass safely through the conflict area.

[0010] Optionally, respectively calculating the remaining braking decision time for the autonomous driving vehicle to decelerate at the maximum deceleration and the remaining acceleration decision time for the autonomous driving vehicle to accelerate at the maximum acceleration includes:

[0011] Calculate the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area;

[0012] Calculate the remaining braking decision time for the autonomous driving vehicle to decelerate at the maximum deceleration according to the obstacle travel time, the first safety distance between the autonomous driving vehicle and the stop boundary of the conflict area, the initial speed and the maximum deceleration of the autonomous driving vehicle;

[0013] Based on the obstacle travel time, the second safety distance between the autonomous driving vehicle and the passing boundary of the conflict area, the initial speed and maximum acceleration of the autonomous driving vehicle, the remaining acceleration decision time for the autonomous driving vehicle to accelerate at the maximum acceleration is calculated.

[0014] Optionally, the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area is calculated, including:

[0015] Calculate the travel distance between the obstacle vehicle and the center point of the conflict area;

[0016] The travel distance is divided by the travel speed of the obstacle vehicle to obtain the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area.

[0017] Optionally, calculating the probability of the autonomous driving vehicle passing through the conflict area according to the remaining braking decision time and the remaining acceleration decision time includes:

[0018] The probability of the autonomous driving vehicle passing through the conflict area is calculated based on the remaining braking decision time and the remaining acceleration decision time by using a probability calculation model.

[0019] Optionally, the probability calculation model is described as:

[0020] If the remaining braking decision time is smaller and the remaining acceleration decision time is larger, the probability of the autonomous driving vehicle passing through the conflict area is greater; if the remaining braking decision time is larger and the remaining acceleration decision time is smaller, the probability of the autonomous driving vehicle passing through the conflict area is smaller.

[0021] Optionally, according to the probability of the autonomous driving vehicle passing through the conflict area, controlling the autonomous driving vehicle to decelerate at a maximum deceleration so as to stop safely before the conflict area or to accelerate at a maximum acceleration so as to pass safely through the conflict area includes:

[0022] Determining whether the probability of the autonomous driving vehicle passing through the conflict area is greater than or equal to a probability threshold;

[0023] If yes, controlling the autonomous driving vehicle to accelerate at the maximum acceleration so as to safely pass through the conflict area;

[0024] If not, the autonomous driving vehicle is controlled to decelerate at the maximum deceleration so as to stop safely before the conflict area.

[0025] In addition, according to another aspect of an embodiment of the present invention, an automatic driving device is provided, including:

[0026] A determination module, for determining a conflict area;

[0027] The first calculation module is used to calculate the remaining braking decision time of the autonomous driving vehicle when decelerating at the maximum deceleration and the remaining acceleration decision time when accelerating at the maximum acceleration;

[0028] A second calculation module is used to calculate the probability of the autonomous driving vehicle passing through the conflict area according to the remaining braking decision time and the remaining acceleration decision time;

[0029] A control module is used to control the autonomous driving vehicle to decelerate at a maximum deceleration so as to stop safely before the conflict area or to accelerate at a maximum acceleration so as to pass safely through the conflict area according to the probability of the autonomous driving vehicle passing through the conflict area.

[0030] Optionally, the first calculation module is further used for:

[0031] Calculate the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area;

[0032] Calculate the remaining braking decision time for the autonomous driving vehicle to decelerate at the maximum deceleration according to the obstacle travel time, the first safety distance between the autonomous driving vehicle and the stop boundary of the conflict area, the initial speed and the maximum deceleration of the autonomous driving vehicle;

[0033] Based on the obstacle travel time, the second safety distance between the autonomous driving vehicle and the passing boundary of the conflict area, the initial speed and maximum acceleration of the autonomous driving vehicle, the remaining acceleration decision time for the autonomous driving vehicle to accelerate at the maximum acceleration is calculated.

[0034] Optionally, the first calculation module is further used for:

[0035] Calculate the travel distance between the obstacle vehicle and the center point of the conflict area;

[0036] The travel distance is divided by the travel speed of the obstacle vehicle to obtain the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area.

[0037] Optionally, the second calculation module is further used for:

[0038] The probability of the autonomous driving vehicle passing through the conflict area is calculated based on the remaining braking decision time and the remaining acceleration decision time by using a probability calculation model.

[0039] Optionally, the probability calculation model is described as:

[0040] If the remaining braking decision time is smaller and the remaining acceleration decision time is larger, the probability of the autonomous driving vehicle passing through the conflict area is greater; if the remaining braking decision time is larger and the remaining acceleration decision time is smaller, the probability of the autonomous driving vehicle passing through the conflict area is smaller.

[0041] Optionally, the control module is further used for:

[0042] Determining whether the probability of the autonomous driving vehicle passing through the conflict area is greater than or equal to a probability threshold;

[0043] If yes, controlling the autonomous driving vehicle to accelerate at the maximum acceleration so as to safely pass through the conflict area;

[0044] If not, the autonomous driving vehicle is controlled to decelerate at the maximum deceleration so as to stop safely before the conflict area.

[0045] In addition, according to another aspect of an embodiment of the present invention, a vehicle is provided, comprising the automatic driving device described in any of the above embodiments.

[0046] In addition, according to another aspect of the embodiment of the present invention, there is also provided an electronic device, including:

[0047] one or more processors;

[0048] a storage device for storing one or more programs,

[0049] When the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any one of the above embodiments.

[0050] According to another aspect of an embodiment of the present invention, a computer-readable medium is provided, on which a computer program is stored. When the program is executed by a processor, the method described in any one of the above embodiments is implemented.

[0051] One embodiment of the above invention has the following advantages or beneficial effects: because the remaining braking decision time of the autonomous driving vehicle decelerating at the maximum deceleration and the remaining acceleration decision time of the autonomous driving vehicle accelerating at the maximum acceleration are calculated respectively, and then the probability of the autonomous driving vehicle passing through the conflict area is calculated according to the remaining braking decision time and the remaining acceleration decision time, and finally the decision of continuing to pass or stopping to give way is made according to the probability, so the technical problem of frequent sudden braking of the autonomous driving vehicle at the intersection in the prior art is overcome. The embodiment of the present invention comprehensively considers the remaining decision time of the autonomous driving vehicle in the two modes of sudden braking and constant speed driving according to the motion state of the autonomous driving vehicle and the obstacle vehicle, and uses the remaining decision time to construct a passing probability calculation model to assist in judging whether the autonomous driving vehicle needs to brake and give way when it conflicts with the obstacle vehicle at the intersection, so as to more reasonably judge whether the autonomous driving vehicle and the obstacle vehicle have a collision risk, and finally improve the traffic efficiency under the premise of ensuring the safety of autonomous driving, so that the autonomous driving vehicle can take into account the safety and efficiency of autonomous driving in a complex intersection environment.

[0052] The further effects of the above-mentioned non-conventional optional manner will be described below in conjunction with the specific implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0054] Figure 1 is a flowchart of an automatic driving method according to an embodiment of the present invention;

[0055] Figure 2 is a schematic diagram of an autonomous driving vehicle encountering a right-turn obstacle at an intersection according to an embodiment of the present invention;

[0056] Figure 3 is a flowchart of an automatic driving method according to a reference embodiment of the present invention;

[0057] Figure 4 is a schematic diagram of an automatic driving device according to an embodiment of the present invention;

[0058] Figure 5 is an exemplary vehicle system architecture diagram to which embodiments of the present invention may be applied;

[0059] Figure 6 It is a schematic diagram of the structure of a computer system of a terminal device or a server suitable for implementing an embodiment of the present invention. DETAILED DESCRIPTION

[0060] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0061] It should be noted that the collection, collection, updating, analysis, processing, use, transmission, storage and other aspects of user personal information involved in the technical solution of this disclosure are in compliance with the provisions of relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. Necessary measures are taken for user personal information to prevent illegal access to user personal information data and maintain the security of user personal information, network security and national security.

[0062] Figure 1 is a flow chart of an automatic driving method according to an embodiment of the present invention. As an embodiment of the present invention, Figure 1 As shown, the automatic driving method may include:

[0063] Step 101, determining the conflict area.

[0064] Step 102, respectively calculates the remaining braking decision time for the autonomous driving vehicle to decelerate at the maximum deceleration and the remaining acceleration decision time for the autonomous driving vehicle to accelerate at the maximum acceleration.

[0065] Intersection interaction scenarios such as Figure 2 As shown, the autonomous driving vehicle (ego) is going straight, and the obstacle vehicle (obs) is about to turn right. The conflict area refers to the area where the two vehicles conflict. The autonomous driving vehicle and the obstacle vehicle need to take measures to avoid appearing in the conflict area at the same time. Among them, the obstacle vehicle can be a social vehicle driven by a human driver or an autonomous driving vehicle, and the embodiment of the present invention does not limit this.

[0066] When encountering an obstacle vehicle, in terms of speed, the behavioral decisions of the autonomous driving vehicle mainly include two modes: continue to pass and stop to give way. That is, the autonomous driving vehicle needs to make a decision to pass or stop to give way based on the status of the two vehicles. Among them, the status of the autonomous driving vehicle includes path, speed, acceleration and deceleration, etc. The path of the autonomous driving vehicle can be obtained through the upstream global navigation and path planning, the speed of the autonomous driving vehicle can be obtained through sensors, and the acceleration and deceleration of the autonomous driving vehicle can be given according to the performance parameters of the vehicle, which will not be elaborated in the embodiments of the present invention. Among them, the state of the obstacle vehicle includes predicted trajectory, speed, etc. The predicted trajectory and speed of the obstacle vehicle can be given by the upstream module based on observation data, road structure and other information, which will not be elaborated in the embodiments of the present invention. It should be noted that in the embodiments of the present invention, the obstacle vehicle can be considered to be traveling at a uniform speed.

[0067] like Figure 2 As shown, the remaining braking decision time for the autonomous driving vehicle to decelerate at the maximum deceleration so as to stop safely before the conflict area (stop before the boundary of the conflict area closest to the autonomous driving vehicle) and the remaining acceleration decision time for the autonomous driving vehicle to accelerate at the maximum acceleration so as to safely pass through the conflict area (pass through the boundary of the conflict area far away from the autonomous driving vehicle) are calculated respectively.

[0068] Optionally, step 102 may include: calculating the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area; calculating the remaining braking decision time for the autonomous driving vehicle to decelerate at the maximum deceleration according to the obstacle travel time, the first safety distance between the autonomous driving vehicle and the stop boundary of the conflict area, the initial speed and the maximum deceleration of the autonomous driving vehicle; calculating the remaining acceleration decision time for the autonomous driving vehicle to accelerate at the maximum acceleration according to the obstacle travel time, the second safety distance between the autonomous driving vehicle and the passing boundary of the conflict area, the initial speed and the maximum acceleration of the autonomous driving vehicle. First, calculate the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area, and then calculate the remaining acceleration decision time according to the obstacle travel time, the first safety distance (S) between the autonomous driving vehicle and the stop boundary of the conflict area. stop ), the initial speed and maximum deceleration of the autonomous driving vehicle, and the remaining braking decision time for the autonomous driving vehicle to decelerate at the maximum deceleration and stop safely before the conflict area, and the second safety distance (S cross ), the initial speed and maximum acceleration of the autonomous driving vehicle, and calculate the remaining acceleration decision time for the autonomous driving vehicle to accelerate at the maximum acceleration and safely pass through the conflict area.

[0069] Step 103, calculating the probability of the autonomous driving vehicle passing through the conflict area based on the remaining braking decision time and the remaining acceleration decision time.

[0070] Optionally, step 102 may include: calculating the probability of the autonomous driving vehicle passing through the conflict area based on the remaining braking decision time and the remaining acceleration decision time, and using a probability calculation model. The embodiment of the present invention first calculates the remaining braking decision time for the autonomous driving vehicle to decelerate at the maximum deceleration and stop safely before the conflict area, and the remaining acceleration decision time for the autonomous driving vehicle to accelerate at the maximum acceleration and pass the conflict area safely, and then uses a probability calculation model to calculate the probability of the autonomous driving vehicle passing through the conflict area, which helps to accurately make decisions on whether to continue to pass or stop to give way based on the calculated probability in subsequent steps.

[0071] Optionally, the passing probability calculation model is described as: if the remaining braking decision time is smaller and the remaining acceleration decision time is larger, the probability of the autonomous driving vehicle passing the conflict area is larger; if the remaining braking decision time is larger and the remaining acceleration decision time is smaller, the probability of the autonomous driving vehicle passing the conflict area is small.

[0072] Step 104, based on the probability of the autonomous driving vehicle passing through the conflict area, control the autonomous driving vehicle to decelerate at a maximum deceleration so as to stop safely before the conflict area or to accelerate at a maximum acceleration so as to pass safely through the conflict area.

[0073] The closer the autonomous driving vehicle is to the conflict area, the shorter the remaining braking decision time and the longer the remaining acceleration decision time, the greater the passing probability; if the autonomous driving vehicle is farther away from the conflict area, the longer the remaining braking decision time and the shorter the remaining acceleration decision time, the smaller the passing probability; if the obstacle vehicle is closer to the conflict area, the remaining braking decision time and the remaining acceleration decision time of the autonomous driving vehicle are both relatively short, and the passing probability will also be smaller.

[0074] Optionally, step 104 may include: determining whether the probability of the autonomous driving vehicle passing through the conflict area is greater than or equal to a probability threshold; if so, controlling the autonomous driving vehicle to accelerate at maximum acceleration so as to safely pass through the conflict area; if not, controlling the autonomous driving vehicle to decelerate at maximum deceleration so as to safely stop before the conflict area. In an embodiment of the present invention, a probability threshold may be pre-set. If the probability calculated in step 103 is greater than or equal to the probability threshold, it is considered that the probability that the autonomous driving vehicle can accelerate at maximum acceleration to safely pass through the conflict area is high, that is, the autonomous driving vehicle is controlled to accelerate at maximum acceleration to safely pass through the conflict area; if the probability calculated in step 103 is less than the probability threshold, it is considered that the probability that the autonomous driving vehicle decelerates at maximum deceleration to safely stop before the conflict area is high, and the autonomous driving vehicle is controlled to decelerate at maximum deceleration to safely stop before the conflict area.

[0075] According to the various embodiments described above, it can be seen that the embodiments of the present invention respectively calculate the remaining braking decision time of the autonomous driving vehicle decelerating at the maximum deceleration and the remaining acceleration decision time of the autonomous driving vehicle accelerating at the maximum acceleration, and then calculate the probability of the autonomous driving vehicle passing through the conflict area according to the remaining braking decision time and the remaining acceleration decision time, and finally make a decision on whether to continue to pass or stop to give way according to the probability, thereby solving the technical problem of frequent sudden braking of the autonomous driving vehicle at the intersection in the prior art. The embodiments of the present invention comprehensively consider the remaining decision time of the autonomous driving vehicle in the two modes of sudden braking and constant speed driving according to the motion state of the autonomous driving vehicle and the obstacle vehicle, and use the remaining decision time to construct a passing probability calculation model to assist in judging whether the autonomous driving vehicle needs to brake and give way when it conflicts with the obstacle vehicle at the intersection, so as to more reasonably judge whether the autonomous driving vehicle and the obstacle vehicle have a collision risk, and finally improve the traffic efficiency under the premise of ensuring the safety of autonomous driving, so that the autonomous driving vehicle can take into account the safety and efficiency of autonomous driving in a complex intersection environment.

[0076] Figure 3 is a flow chart of an automatic driving method according to a reference embodiment of the present invention. As another embodiment of the present invention, Figure 3 As shown, the automatic driving method may include:

[0077] Step 301, determining the conflict area.

[0078] Step 302, calculating the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area.

[0079] Optionally, step 302 may include: calculating the travel distance between the obstacle vehicle and the center point of the conflict area; dividing the travel distance by the travel speed of the obstacle vehicle, thereby obtaining the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area. Optionally, the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area may be calculated using formula (1):

[0080]

[0081] Among them, S obs is the driving distance between the obstacle vehicle and the center point of the conflict area, v obs is the speed of the obstacle vehicle.

[0082] Step 303, calculates the remaining braking decision time for the autonomous driving vehicle to decelerate at the maximum deceleration based on the obstacle travel time, the first safety distance between the autonomous driving vehicle and the stopping boundary of the conflict area, the initial speed and the maximum deceleration of the autonomous driving vehicle.

[0083] Step 304, calculates the remaining acceleration decision time for the autonomous driving vehicle to accelerate at the maximum acceleration based on the obstacle travel time, the second safety distance between the autonomous driving vehicle and the passing boundary of the conflict area, the initial speed and the maximum acceleration of the autonomous driving vehicle.

[0084] There is no restriction on the execution order of step 303 and step 304. Step 303 may be executed first and then step 304, or step 304 may be executed first and then step 303, or step 303 and step 304 may be executed simultaneously.

[0085] In an embodiment of the present invention, the remaining decision time includes the remaining braking decision time: T stop , and the remaining acceleration decision time: T cross . T dtop That is, assuming that the autonomous driving vehicle selects the deceleration mode, starting from the current moment, the latest execution time for the autonomous driving vehicle to stop safely before the conflict area; T cross That is, assuming that the autonomous driving vehicle selects the acceleration mode, starting from the current moment, the latest execution time that allows the autonomous driving vehicle to safely pass through the conflict area. The specific calculation process is as follows:

[0086]

[0087] in,

[0088] T obs =T stop + t dec =T cross + tacc (4) Combining equation (2), equation (3) and equation (4), we can get:

[0089]

[0090] Among them, v ego is the initial speed of the autonomous vehicle, v obs is the speed of the obstacle vehicle, S stop is the first safe distance between the autonomous vehicle and the stopping boundary of the conflict area, S cross S is the second safe distance between the autonomous driving vehicle and the passing boundary of the conflict area; obs is the driving distance between the obstacle vehicle and the center point of the conflict area, T obs is the obstacle travel time required for the obstacle vehicle to reach the center of the conflict area, that is, the autonomous driving vehicle needs to travel within T obs Complete all decisions within the time limit (deceleration ensures that it does not exceed S stop , or continue passing S cross ) to ensure that the autonomous driving vehicle does not intersect with the conflict area; a max is the maximum acceleration of the autonomous driving vehicle, t acc is the acceleration time in acceleration mode; d max is the maximum deceleration of the autonomous driving vehicle, t dec It is the deceleration time in deceleration mode.

[0091] Step 305, based on the remaining braking decision time and the remaining acceleration decision time, and using a probability calculation model, calculate the probability of the autonomous driving vehicle passing through the conflict area.

[0092] Optionally, the passing probability calculation model is described as: if the remaining braking decision time is smaller and the remaining acceleration decision time is larger, the probability of the autonomous driving vehicle passing the conflict area is larger; if the remaining braking decision time is larger and the remaining acceleration decision time is smaller, the probability of the autonomous driving vehicle passing the conflict area is small.

[0093] Optionally, the probability calculation model is described as:

[0094]

[0095] Where P is the probability of the autonomous driving vehicle passing through the conflict area, T stop is the remaining braking decision time, T cross Remaining acceleration decision time, a, b, w are all preset parameters.

[0096] Optionally, a>0, b<0, w>0, a, b, w are all empirical parameters, and those skilled in the art may set them according to actual needs, which is not limited in the embodiment of the present invention.

[0097] Step 306, determine whether the probability of the autonomous driving vehicle passing through the conflict area is greater than or equal to a probability threshold; if so, execute step 307; if not, execute step 308.

[0098] Step 307, controlling the autonomous driving vehicle to accelerate at the maximum acceleration so as to safely pass through the conflict area.

[0099] Step 308, controlling the autonomous driving vehicle to decelerate at the maximum deceleration so as to stop safely before the conflict area.

[0100] by Figure 2 Taking the scenario shown as an example, the empirical parameters a, b, and w are set to: a=1.67, b=-1.69, and w=0.57, respectively.

[0101] Example 1: The speed v of the obstacle vehicle obs =5m / s, S obs =10m, the initial speed v of the autonomous vehicle ego =3m / s, S stop =2m, S cross =7m; the maximum acceleration of the autonomous vehicle a max =1m / s 2 , maximum deceleration d max =5m / s 2 ;

[0102] According to formula (1), we can get: T obs =2s; According to formula (5) (6), we can get: T stop =0.74s, T cros =0.59s; According to formula (7), the passing probability is: P1=0.51.

[0103] Example 2: Initial velocity v of the obstacle vehicle obs =5m / s, S obs =10m, the initial speed v of the autonomous vehicle ego =3m / s, S stop =5m, S cross =10m; the maximum acceleration of the autonomous vehicle a max =1m / s 2 , maximum deceleration d max =5m / s 2 ;

[0104] According to formula (1), we can get: T obs=2s; According to formula (5) (6), we can get: T stop =1.37s, T cros =-0.83s; According to formula (7), the passing probability is: P2 = 0.15.

[0105] From the above two examples, we can see that under the same conditions, the closer the autonomous driving vehicle is to the conflict area, the greater the probability of passing, and vice versa, which is consistent with the results of theoretical analysis.

[0106] In addition, the specific implementation content of the autonomous driving method in a reference embodiment of the present invention has been described in detail in the autonomous driving method described above, so the repeated content will not be described here.

[0107] Figure 4 Schematic diagram of an automatic driving device according to an embodiment of the present invention. Figure 4 As shown, the automatic driving device 400 includes a determination module 401, a first calculation module 402, a second calculation module 403 and a control module 404; wherein the determination module 401 is used to determine the conflict area; the first calculation module 402 is used to respectively calculate the remaining braking decision time for the automatic driving vehicle to decelerate at the maximum deceleration and the remaining acceleration decision time for accelerating at the maximum acceleration; the second calculation module 403 is used to calculate the probability of the automatic driving vehicle passing through the conflict area according to the remaining braking decision time and the remaining acceleration decision time; the control module 404 is used to control the automatic driving vehicle to decelerate at the maximum deceleration so as to stop safely before the conflict area or to accelerate at the maximum acceleration so as to pass through the conflict area safely according to the probability of the automatic driving vehicle passing through the conflict area.

[0108] Optionally, the first calculation module 402 is further configured to:

[0109] Calculate the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area;

[0110] Calculate the remaining braking decision time for the autonomous driving vehicle to decelerate at the maximum deceleration according to the obstacle travel time, the first safety distance between the autonomous driving vehicle and the stop boundary of the conflict area, the initial speed and the maximum deceleration of the autonomous driving vehicle;

[0111] Based on the obstacle travel time, the second safety distance between the autonomous driving vehicle and the passing boundary of the conflict area, the initial speed and maximum acceleration of the autonomous driving vehicle, the remaining acceleration decision time for the autonomous driving vehicle to accelerate at the maximum acceleration is calculated.

[0112] Optionally, the first calculation module 402 is further configured to:

[0113] Calculate the travel distance between the obstacle vehicle and the center point of the conflict area;

[0114] The travel distance is divided by the travel speed of the obstacle vehicle to obtain the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area.

[0115] Optionally, the second calculation module 403 is further used for:

[0116] The probability of the autonomous driving vehicle passing through the conflict area is calculated based on the remaining braking decision time and the remaining acceleration decision time by using a probability calculation model.

[0117] Optionally, the probability calculation model is described as:

[0118] If the remaining braking decision time is smaller and the remaining acceleration decision time is larger, the probability of the autonomous driving vehicle passing through the conflict area is greater; if the remaining braking decision time is larger and the remaining acceleration decision time is smaller, the probability of the autonomous driving vehicle passing through the conflict area is smaller.

[0119] Optionally, the control module 404 is further configured to:

[0120] Determining whether the probability of the autonomous driving vehicle passing through the conflict area is greater than or equal to a probability threshold;

[0121] If yes, controlling the autonomous driving vehicle to accelerate at the maximum acceleration so as to safely pass through the conflict area;

[0122] If not, the autonomous driving vehicle is controlled to decelerate at the maximum deceleration so as to stop safely before the conflict area.

[0123] It should be noted that the specific implementation content of the automatic driving device described in the present invention has been described in detail in the automatic driving method described above, so the repeated content will not be described here.

[0124] An embodiment of the present invention provides a vehicle, which may include the automatic driving device provided by each of the above embodiments.

[0125] Figure 5 An exemplary vehicle system architecture 500 is shown to which a vehicle driving method or a vehicle driving device according to an embodiment of the present invention may be applied.

[0126] like Figure 5As shown, the vehicle system architecture 500 may include various systems, such as an autonomous driving system 501, a power system 502, a sensor system 503, a control system 504, one or more peripheral devices 505, a power supply 506, a computer system 507, and a user interface 508. Optionally, the vehicle system architecture 500 may include more or fewer systems, and each system may include multiple elements. In addition, each system and element of the vehicle system architecture 500 may be interconnected by wire or wirelessly.

[0127] Among them, the vehicle system architecture 500 includes an automatic driving system 501, and the automatic driving system 501 can be in a full or partial automatic driving mode. For example, the automatic driving system 501 can automatically control the vehicle to drive without interacting with a person; the automatic driving system 501 can also control the automatic driving of the vehicle in the automatic driving mode, and can also adjust the automatic driving behavior of the automatic driving system 501 by interacting with a person. Specifically, the automatic driving system 501 can determine the conflict area; calculate the remaining braking decision time for the automatic driving vehicle to decelerate at the maximum deceleration and the remaining acceleration decision time for the automatic driving vehicle to accelerate at the maximum acceleration; calculate the probability of the automatic driving vehicle passing through the conflict area according to the remaining braking decision time and the remaining acceleration decision time; according to the probability of the automatic driving vehicle passing through the conflict area, control the automatic driving vehicle to decelerate at the maximum deceleration so as to stop safely before the conflict area or accelerate at the maximum acceleration so as to pass through the conflict area safely.

[0128] The power system 502 may include components that provide power movement for the vehicle. For example, the power system 502 may include an engine, an energy source, a transmission, wheels, tires, etc. Among them, the engine may be an internal combustion engine, an electric motor, an air compression engine, or other types of engine combinations, such as a hybrid engine consisting of a gasoline engine and an electric motor, and a hybrid engine consisting of an internal combustion engine and an air compression engine. The engine converts the energy source into mechanical energy and provides it to the transmission. Examples of energy sources may include gasoline, diesel, other petroleum-based fuels, propane, other compressed gas-based fuels, ethanol, solar panels, batteries, and other sources of electricity. The energy source may also provide energy for other systems of the vehicle. In addition, the transmission may include a gearbox, a differential, a drive shaft, a clutch, etc.

[0129] The sensor system 503 may include sensors for sensing the surrounding environment of the vehicle. For example, a positioning system (the positioning system may be a global positioning system (GPS) system, or a Beidou system or other positioning systems), a radar, a laser rangefinder, an inertial measurement unit (IMU), and a camera. The positioning system may be used to locate the geographic location of the vehicle. The IMU is used to sense the position and orientation changes of the vehicle based on inertial acceleration. In one embodiment, the IMU may be a combination of an accelerometer and a gyroscope. The radar may use radio signals to sense objects in the surrounding environment of the vehicle. In some embodiments, in addition to sensing objects, the radar may also be used to sense the speed and / or direction of travel of the object, etc.

[0130] Among them, in order to detect environmental information, objects, etc. located in front, rear or side of the vehicle, radars, cameras, etc. can be configured at appropriate locations outside the vehicle. For example, in order to obtain an image in front of the vehicle, the camera can be configured in the interior of the vehicle close to the front windshield. Alternatively, the camera can be configured around the front bumper or radiator grille. For example, in order to obtain an image behind the vehicle, the camera can be configured in the interior of the vehicle close to the rear window glass. Alternatively, the camera can be configured around the rear bumper, trunk or tailgate. In order to obtain an image on the side of the vehicle, the camera can be configured in the interior of the vehicle close to at least one of the side windows. Alternatively, the camera can be configured around the side mirrors, fenders or doors, etc.

[0131] Laser rangefinders use lasers to sense objects in the vehicle's environment.

[0132] The camera can be used to capture multiple images of the vehicle's surroundings. The camera can be a still or video camera.

[0133] The control system 504 includes a software system for implementing autonomous driving, such as a system for route planning, an obstacle avoidance system, a visual system for image analysis, etc. The control system 504 may also include hardware systems such as a throttle and a steering wheel system. In addition, the control system 504 may include additional or alternative components other than those shown and described. Alternatively, some of the components shown above may be reduced.

[0134] The control system 504 interacts with external sensors, other autonomous driving devices, other computer systems, or users through the peripheral devices 505. The peripheral devices 505 may include a wireless communication system, an onboard computer, a microphone, and / or a speaker.

[0135] In some embodiments, peripheral devices 505 provide a means for a user of control system 504 to interact with user interface 508. For example, an onboard computer can provide information to a user of the vehicle. The user interface can also operate the onboard computer to receive input from the user. The onboard computer can be operated via a touch screen. In other cases, peripheral devices can provide a means for communicating with other devices located in the vehicle. For example, a microphone can receive audio (e.g., voice commands or other audio input) from a user of control system 504. Similarly, a speaker can output audio to a user of control system 504.

[0136] The wireless communication system can communicate with one or more devices wirelessly directly or via a communication network. For example, the wireless communication system can communicate with a network such as a cellular network, WiFi, and a wireless local area network (WLAN), or can communicate directly with a device using an infrared link, Bluetooth, or ZigBee. Other wireless protocols, such as various autonomous driving communication systems, etc.

[0137] The power source 506 can provide power to various components of the vehicle. The power source 506 can be a rechargeable lithium-ion or lead-acid battery.

[0138] Some or all functions of implementing autonomous driving are controlled by computer system 507. Computer system 507 may include at least one processor that executes instructions stored in a non-transitory computer-readable medium such as a memory. Computer system 507 provides the above-mentioned autonomous driving system with execution code for implementing autonomous driving.

[0139] The processor can be any conventional processor, such as a commercially available central processing unit (CPU). Alternatively, the processor can be a dedicated device such as an application specific integrated circuit (ASIC) or other hardware-based processor. Those of ordinary skill in the art will appreciate that the processor, computer, or memory can actually include multiple processors, computers, or memories that may or may not be stored in the same physical housing. For example, the memory can be a hard disk drive or other storage media that is located in a housing different from the computer. Therefore, references to processors or computers will be understood to include references to a collection of processors or computers or memories that may or may not operate in parallel. Different from using a single processor to perform the steps described herein, some components such as steering components and deceleration components can each have their own processors that only perform calculations related to the functions specific to the components.

[0140] The user interface 508 is used to provide information to or receive information from a user of the vehicle. Optionally, the user interface 508 may include one or more input / output devices within the set of peripheral devices 505, such as a wireless communication system, an onboard computer, a microphone, and a speaker.

[0141] It should be understood that the above components are only examples. In actual applications, the components in the above modules or systems may be added or deleted according to actual needs. Figure 5 It should not be understood as limiting the embodiments of the present application.

[0142] Reference below Figure 6 , which shows a schematic diagram of the structure of a computer system 600 of a terminal device suitable for implementing an embodiment of the present invention. Figure 6 The terminal device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0143] like Figure 6 As shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 into a random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the system 600 are also stored. The CPU 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0144] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage section 608 as needed.

[0145] In particular, according to the embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the central processing unit (CPU) 601, the above-mentioned functions defined in the system of the present invention are executed.

[0146] It should be noted that the computer-readable medium shown in the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0147] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0148] The modules involved in the embodiments of the present invention may be implemented by software or hardware. The modules described may also be set in a processor, for example, it may be described as: a processor includes a first computing module, a second computing module and a control module, wherein the names of these modules do not constitute a limitation on the modules themselves in some cases.

[0149] As another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiment; or it may exist independently without being assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by a device, the device implements the following method: determining a conflict area; respectively calculating the remaining braking decision time for the autonomous driving vehicle to decelerate at the maximum deceleration and the remaining acceleration decision time for the autonomous driving vehicle to accelerate at the maximum acceleration; calculating the probability of the autonomous driving vehicle passing through the conflict area based on the remaining braking decision time and the remaining acceleration decision time; and controlling the autonomous driving vehicle to decelerate at the maximum deceleration so as to stop safely before the conflict area or to accelerate at the maximum acceleration so as to pass safely through the conflict area based on the probability of the autonomous driving vehicle passing through the conflict area.

[0150] According to the technical solution of the embodiment of the present invention, the remaining braking decision time of the autonomous driving vehicle decelerating at the maximum deceleration and the remaining acceleration decision time of the autonomous driving vehicle accelerating at the maximum acceleration are calculated respectively, and then the probability of the autonomous driving vehicle passing through the conflict area is calculated according to the remaining braking decision time and the remaining acceleration decision time, and finally the decision of continuing to pass or stopping to give way is made according to the probability. Therefore, the technical problem of frequent sudden braking of the autonomous driving vehicle at the intersection in the prior art is overcome. The embodiment of the present invention comprehensively considers the remaining decision time of the autonomous driving vehicle in the two modes of sudden braking and constant speed driving according to the motion state of the autonomous driving vehicle and the obstacle vehicle, and uses the remaining decision time to construct a passing probability calculation model to assist in judging whether the autonomous driving vehicle needs to brake and give way when it conflicts with the obstacle vehicle at the intersection, so as to more reasonably judge whether the autonomous driving vehicle and the obstacle vehicle have a collision risk, and finally improve the traffic efficiency under the premise of ensuring the safety of autonomous driving, so that the autonomous driving vehicle can take into account the safety and efficiency of autonomous driving in a complex intersection environment.

[0151] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An automatic driving method, characterized in that: include: Identify conflict areas; Calculate the remaining braking decision time when the autonomous driving vehicle is decelerating at the maximum deceleration and the remaining acceleration decision time when it is accelerating at the maximum acceleration; Calculate the probability of the autonomous driving vehicle passing through the conflict area according to the remaining braking decision time and the remaining acceleration decision time; According to the probability of the autonomous driving vehicle passing through the conflict area, the autonomous driving vehicle is controlled to decelerate at the maximum deceleration so as to stop safely before the conflict area or to accelerate at the maximum acceleration so as to pass safely through the conflict area.

2. The method according to claim 1, characterized in that The remaining braking decision time for the autonomous driving vehicle to decelerate at the maximum deceleration and the remaining acceleration decision time for the autonomous driving vehicle to accelerate at the maximum acceleration are calculated respectively, including: Calculate the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area; Calculate the remaining braking decision time for the autonomous driving vehicle to decelerate at the maximum deceleration according to the obstacle travel time, the first safety distance between the autonomous driving vehicle and the stop boundary of the conflict area, the initial speed and the maximum deceleration of the autonomous driving vehicle; Based on the obstacle travel time, the second safety distance between the autonomous driving vehicle and the passing boundary of the conflict area, the initial speed and maximum acceleration of the autonomous driving vehicle, the remaining acceleration decision time for the autonomous driving vehicle to accelerate at the maximum acceleration is calculated.

3. The method according to claim 2, characterized in that Calculate the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area, including: Calculate the travel distance between the obstacle vehicle and the center point of the conflict area; The travel distance is divided by the travel speed of the obstacle vehicle to obtain the obstacle travel time required for the obstacle vehicle to reach the center point of the conflict area.

4. The method according to claim 1, characterized in that Calculating the probability of the autonomous driving vehicle passing through the conflict area according to the remaining braking decision time and the remaining acceleration decision time includes: The probability of the autonomous driving vehicle passing through the conflict area is calculated based on the remaining braking decision time and the remaining acceleration decision time by using a probability calculation model.

5. The method according to claim 4, characterized in that The pass probability calculation model is described as: If the remaining braking decision time is smaller and the remaining acceleration decision time is larger, the probability of the autonomous driving vehicle passing through the conflict area is greater; if the remaining braking decision time is larger and the remaining acceleration decision time is smaller, the probability of the autonomous driving vehicle passing through the conflict area is smaller.

6. The method according to claim 1, characterized in that According to the probability of the autonomous driving vehicle passing through the conflict area, controlling the autonomous driving vehicle to decelerate at a maximum deceleration so as to stop safely before the conflict area or to accelerate at a maximum acceleration so as to pass safely through the conflict area, including: Determining whether the probability of the autonomous driving vehicle passing through the conflict area is greater than or equal to a probability threshold; If yes, controlling the autonomous driving vehicle to accelerate at the maximum acceleration so as to safely pass through the conflict area; If not, the autonomous driving vehicle is controlled to decelerate at the maximum deceleration so as to stop safely before the conflict area.

7. An automatic driving device, characterized in that: include: A determination module, for determining a conflict area; The first calculation module is used to calculate the remaining braking decision time when the autonomous driving vehicle decelerates at the maximum deceleration and the remaining acceleration decision time when the autonomous driving vehicle accelerates at the maximum acceleration; A second calculation module is used to calculate the probability of the autonomous driving vehicle passing through the conflict area according to the remaining braking decision time and the remaining acceleration decision time; A control module is used to control the autonomous driving vehicle to decelerate at a maximum deceleration so as to stop safely before the conflict area or to accelerate at a maximum acceleration so as to pass safely through the conflict area according to the probability of the autonomous driving vehicle passing through the conflict area.

8. A carrier, characterized in that: Comprising an automatic driving device as described in claim 7.

9. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

10. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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