Automatic driving vehicle intersection passing method, device and equipment

Abstract

The embodiment of the specification discloses an automatic driving vehicle intersection passing method, device and equipment, the method comprises: acquiring the driving speed of the automatic driving vehicle and the lane distance of the automatic driving vehicle from the stop line of the intersection in real time; determining the first distance and the second distance according to the driving speed; the first distance is positively correlated with the driving speed, and the second distance is positively correlated with the driving speed; the first distance is greater than the second distance; when the lane distance is less than the first distance and greater than or equal to the second distance, it is judged whether the automatic driving vehicle needs to be decelerated; if yes, the automatic driving vehicle is controlled to be decelerated; when the lane distance is less than the second distance, if the automatic driving vehicle meets the preset parking condition, the automatic driving vehicle is controlled to be parked. In this way, when the automatic driving vehicle needs to be parked subsequently, the situation of emergency braking is avoided, and the driving safety of the automatic driving vehicle is improved.

Description

Technical Field

[0001] This application relates to the field of autonomous driving technology, and in particular to a method, apparatus and equipment for autonomous vehicles to pass through intersections. Background Technology

[0002] Currently, in scenarios where autonomous vehicles pass through intersections (i.e., road intersections) equipped with traffic lights, when an autonomous vehicle is close to the intersection, if the traffic light at the intersection is green, the autonomous vehicle needs to determine whether it can reach the intersection within the remaining time of the green light based on its speed and distance from the intersection. If it is determined that it cannot reach the intersection within the remaining time of the green light, the autonomous vehicle will be stopped.

[0003] However, in related technologies, because autonomous vehicles often travel at high speeds, they are prone to sudden braking when parking, which leads to lower driving safety. Summary of the Invention

[0004] The embodiments of this specification provide a method, apparatus, and device for autonomous vehicles to pass through intersections, which can avoid sudden braking when autonomous vehicles pass through intersections and improve the driving safety of autonomous vehicles.

[0005] To solve the above-mentioned technical problems, the embodiments in this specification are implemented as follows:

[0006] This specification provides an embodiment of a method for autonomous vehicles to pass through intersections, including:

[0007] The driving speed of the autonomous vehicle and the distance between the autonomous vehicle and the stop line at the intersection are obtained in real time.

[0008] A first distance and a second distance are determined based on the driving speed; the first distance is positively correlated with the driving speed, and the second distance is also positively correlated with the driving speed; the first distance is greater than the second distance.

[0009] When the distance between the vehicles is less than the first distance and greater than or equal to the second distance, the autonomous vehicle is judged whether it needs to decelerate based on the traffic light data at the intersection, the driving speed, and the distance between the vehicles.

[0010] If so, then control the autonomous vehicle to decelerate;

[0011] When the distance between the vehicle and the lane is less than the second distance, if the autonomous vehicle meets the preset parking conditions, then the autonomous vehicle is controlled to park.

[0012] This specification provides an embodiment of an autonomous vehicle intersection passage device, comprising:

[0013] The vehicle driving data acquisition module is used to acquire the driving speed of the autonomous vehicle and the distance between the autonomous vehicle and the stop line at the intersection in real time.

[0014] A distance threshold determination module is used to determine a first distance and a second distance based on the driving speed; the first distance is positively correlated with the driving speed, and the second distance is positively correlated with the driving speed; the first distance is greater than the second distance;

[0015] The deceleration decision module is used to determine whether the autonomous vehicle needs to decelerate when the distance between the vehicle lanes is less than the first distance and greater than or equal to the second distance, based on traffic light data at the intersection, the driving speed, and the distance between the vehicle lanes.

[0016] A deceleration module is used to control the autonomous vehicle to decelerate if the autonomous vehicle needs to decelerate.

[0017] The parking decision module is used to control the autonomous vehicle to park if the distance between the vehicle and the lane is less than the second distance and the autonomous vehicle meets the preset parking conditions.

[0018] This specification provides an embodiment of an autonomous vehicle intersection passage device, comprising:

[0019] At least one processor; and,

[0020] A memory communicatively connected to the at least one processor; wherein,

[0021] The memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enable the at least one processor to:

[0022] The driving speed of the autonomous vehicle and the distance between the autonomous vehicle and the stop line at the intersection are obtained in real time.

[0023] A first distance and a second distance are determined based on the driving speed; the first distance is positively correlated with the driving speed, and the second distance is also positively correlated with the driving speed; the first distance is greater than the second distance.

[0024] When the distance between the vehicles is less than the first distance and greater than or equal to the second distance, the autonomous vehicle is judged whether it needs to decelerate based on the traffic light data at the intersection, the driving speed, and the distance between the vehicles.

[0025] If so, then control the autonomous vehicle to decelerate;

[0026] When the distance between the vehicle and the lane is less than the second distance, if the autonomous vehicle meets the preset parking conditions, then the autonomous vehicle is controlled to park.

[0027] At least one embodiment provided in this specification can achieve the following beneficial effects: When the distance between the autonomous vehicle and the lane is less than a first distance but greater than or equal to a second distance, if the autonomous vehicle meets a preset deceleration condition, it is controlled to decelerate; when the distance between the autonomous vehicle and the lane is less than the second distance, if the autonomous vehicle meets a preset stopping condition, it is controlled to stop. By decelerating the autonomous vehicle before the stopping phase, sudden braking is avoided when the autonomous vehicle needs to stop later, thus improving the driving safety of the autonomous vehicle. Furthermore, since the first and second distances are determined based on the driving speed of the autonomous vehicle, and the higher the driving speed, the larger the corresponding first and second distances, the autonomous vehicle traveling at a higher speed has sufficient distance to decelerate, further preventing sudden braking and improving the driving safety of the autonomous vehicle. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a schematic diagram illustrating the switching of intersection passage decision states for an autonomous vehicle, as provided in the embodiments of this specification.

[0030] Figure 2 A flowchart illustrating an autonomous vehicle's method for navigating intersections, provided as an embodiment of this specification;

[0031] Figure 3 This is a schematic diagram of the structure of an autonomous vehicle intersection passage device provided in the embodiments of this specification;

[0032] Figure 4 This is a structural schematic diagram of an autonomous vehicle intersection passage device provided as an embodiment of this specification. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of one or more embodiments of this specification clearer, the technical solutions of one or more embodiments of this specification will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of them. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of one or more embodiments of this specification.

[0034] The technical solutions provided in the various embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0035] Figure 1 This is a schematic diagram illustrating the switching of intersection passage decision states for an autonomous vehicle, as provided in an embodiment of this specification. Figure 1 As shown, during the process of the autonomous vehicle moving towards the intersection, the system collects the vehicle's speed and distance from the stop line at a preset data collection frequency. Then, after each speed data collection, a first distance and a second distance are determined based on that speed. The first distance is positively correlated with the speed, and the second distance is also positively correlated with the speed; the first distance is greater than the second distance.

[0036] Furthermore, when the distance between the autonomous vehicle and its lane is greater than or equal to a first distance, the autonomous vehicle's intersection passage decision state switches to normal driving state 101. In normal driving state 101, it is not necessary to determine whether the autonomous vehicle can pass through the intersection when the traffic light is green, and the autonomous vehicle is controlled to decelerate or stop based on the determination result. The autonomous vehicle continues driving, and when the distance between the autonomous vehicle and its lane is less than the first distance but greater than or equal to a second distance, the autonomous vehicle's intersection passage decision state switches to deceleration decision state 102. In deceleration decision state 102, it is determined whether the autonomous vehicle can pass through the intersection when the traffic light is green. If it is determined that the autonomous vehicle cannot pass through the intersection when the traffic light is green, the autonomous vehicle is controlled to decelerate. The autonomous vehicle continues driving, and when the distance between the autonomous vehicle and its lane is less than the second distance, the autonomous vehicle's intersection passage decision state switches to stopping decision state 103. In parking decision state 103, it is determined whether the autonomous vehicle can pass through the intersection when the traffic light is green. If it is determined that the autonomous vehicle can pass through the intersection when the traffic light is green, the autonomous vehicle enters the intersection in parking decision state 103. After entering the intersection, its intersection passage decision state switches to normal driving state 101. If it is determined that the autonomous vehicle cannot pass through the intersection when the traffic light is green, the autonomous vehicle's intersection passage decision state switches to parking waiting state 104. In parking waiting state 104, the autonomous vehicle is controlled to stop. Then, when the preset start condition is met, the autonomous vehicle's intersection passage decision state switches to normal driving state 101, and it passes through the intersection in normal driving state 101. The preset start condition can be that the traffic light is green.

[0037] This description describes an embodiment employing the above-described technical solution. When the distance between the autonomous vehicle and the lane markings is less than a first distance but greater than or equal to a second distance, if the autonomous vehicle meets a preset deceleration condition, it is controlled to decelerate. When the distance between the autonomous vehicle and the lane markings is less than the second distance, if the autonomous vehicle meets a preset stopping condition, it is controlled to stop. This deceleration before the stopping phase prevents sudden braking when a stop is required later, improving the driving safety of the autonomous vehicle. Furthermore, since the first and second distances are determined based on the autonomous vehicle's speed, and the higher the speed, the larger the corresponding first and second distances, autonomous vehicles traveling at higher speeds have sufficient distance to decelerate, further preventing sudden braking and improving driving safety.

[0038] Next, with reference to the accompanying drawings, a method for autonomous vehicles to pass through intersections, as provided in the embodiments of the specification, will be described in detail:

[0039] Figure 2 This is a flowchart illustrating a method for autonomous vehicles to pass through intersections, provided as an embodiment of this specification. From a programming perspective, the entity executing this process can be a server, or an application program for an autonomous vehicle intersection passage device mounted on the server. Figure 2 As shown, the process includes the following steps:

[0040] Step 201: Real-time acquisition of the driving speed of the autonomous vehicle and the distance between the autonomous vehicle and the stop line at the intersection.

[0041] Specifically, the acquisition of the autonomous vehicle's speed and distance from the lane can begin when the autonomous vehicle enters the road it is on, or it can begin when the autonomous vehicle is at a preset distance from the stop line at an intersection. The preset distance can be set by those skilled in the art according to actual needs. For example, the preset distance can be equal to the distance the autonomous vehicle needs to travel to decelerate from the speed limit of the road it is on to zero with a first preset acceleration. The first preset acceleration is the acceleration used to determine the first distance, as described below.

[0042] In addition, the data collection frequency for the driving speed and distance between the autonomous vehicle and the lane can be once per second or at other frequencies.

[0043] Step 202: Determine a first distance and a second distance based on the driving speed; the first distance is positively correlated with the driving speed, and the second distance is positively correlated with the driving speed; the first distance is greater than the second distance.

[0044] Specifically, the first and second distances can be updated based on the speed of the autonomous vehicle each time it is acquired. Alternatively, after acquiring the speed of the autonomous vehicle each time, the current speed is compared with the previously acquired speed. If it is determined that the current speed has changed compared to the previously acquired speed, the first and second distances are updated based on the current speed. If it is determined that the current speed has not changed compared to the previously acquired speed, the first and second distances are not updated.

[0045] The first distance can be equal to the distance the autonomous vehicle needs to travel to decelerate from its initial speed to zero using a first preset acceleration; the second distance can be equal to the distance the autonomous vehicle needs to travel to decelerate from its initial speed to zero using a second preset acceleration; the first preset acceleration is greater than the second preset acceleration. In a specific example, the first preset acceleration can be set to -1.5 m / s². 2 The second preset acceleration can be set to -3m / s². 2 .

[0046] Alternatively, the first distance and the second distance can be determined in other ways, as long as the first distance is positively correlated with the driving speed, the second distance is positively correlated with the driving speed, and the first distance is greater than the second distance. For example, the first distance can be equal to the distance the autonomous vehicle needs to travel to decelerate from its driving speed to 0.1 m / s with a first preset acceleration; the second distance can be equal to the distance the autonomous vehicle needs to travel to decelerate from its driving speed to 0.1 m / s with a second preset acceleration.

[0047] Step 203: When the distance between the vehicles and the lane is less than the first distance and greater than or equal to the second distance, determine whether the autonomous vehicle needs to decelerate based on the traffic light data at the intersection, the driving speed, and the distance between the vehicles and the lane.

[0048] Specifically, when an autonomous vehicle is traveling towards an intersection, if the distance between the autonomous vehicle and the roadway is less than a first distance but greater than or equal to a second distance, the autonomous vehicle enters a deceleration decision state. In this state, if the traffic light at the intersection is not green, the autonomous vehicle is determined to need to decelerate. If the traffic light is green, the autonomous vehicle's deceleration needs to be determined based on the remaining time of the green light, its speed, and the distance between the vehicle and the roadway. For example, the ratio of the distance between the vehicle and the roadway to the speed can be calculated to obtain the time it would take for the autonomous vehicle to travel from its current location to the stop line at the intersection at that speed. If this time is greater than the remaining time of the green light, the autonomous vehicle is determined to need to decelerate.

[0049] Step 204: If yes, then control the autonomous vehicle to decelerate.

[0050] In practical applications, during the deceleration process of an autonomous vehicle, there may be other vehicles traveling within a preset distance ahead. Therefore, when controlling the autonomous vehicle to decelerate, if there are other vehicles traveling within the preset distance ahead, it is necessary to control the autonomous vehicle to maintain a safe distance from the nearest vehicle (also known as the vehicle in front).

[0051] Based on this, controlling the deceleration of autonomous vehicles can specifically include:

[0052] Determine whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle.

[0053] If there is a road vehicle traveling within a preset distance ahead of the autonomous vehicle, the autonomous vehicle is controlled to decelerate according to the minimum acceleration between the fifth and sixth accelerations; the fifth acceleration is used to adjust the speed of the autonomous vehicle to the second speed; the sixth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle; the second speed is less than or equal to the preset safe speed.

[0054] If there are no road vehicles traveling within a preset distance range ahead of the autonomous vehicle, the autonomous vehicle is controlled to decelerate based on the fifth acceleration.

[0055] In the embodiments of this specification, the preset distance range can be within 5 meters of the autonomous vehicle, or it can be any other distance range. The preset safe speed can be a speed that ensures the autonomous vehicle can brake with a small braking acceleration when emergency braking is required; for example, the preset safe speed can be set to 30 km / h.

[0056] In a specific example, if there are no road vehicles traveling within a preset distance range ahead of the autonomous vehicle, the fifth acceleration can be calculated according to the following formula:

[0057]

[0058] Among them, a speedLimit This is the speed-limiting acceleration, also known as the fifth acceleration mentioned earlier, with units of m / s². 2 ;v final In this embodiment, v represents the adjusted driving speed of the autonomous vehicle. final The second velocity is expressed in m / s; v veh τ represents the speed of the autonomous vehicle, measured in m / s. v The constant for calculating the first acceleration can be 2, and its unit is seconds.

[0059] Then, based on the calculated fifth acceleration, the autonomous vehicle is controlled to decelerate, so that the speed of the autonomous vehicle is adjusted to the second speed.

[0060] In another specific example, if there are road vehicles traveling within a preset distance range ahead of the autonomous vehicle, the sixth acceleration can be calculated according to the following formula:

[0061]

[0062] Among them, a acc This refers to the following acceleration, also known as the sixth acceleration mentioned earlier, with units of m / s². 2 ;v rel The difference between the speed of the vehicle in front and the speed of the autonomous vehicle is expressed in m / s; d is the distance between the autonomous vehicle and the vehicle in front; t is the distance between the autonomous vehicle and the vehicle in front. re τ is the reaction time constant, which can be set to 2, with units of seconds; d This is the constant for calculating the second acceleration, and its value can be set to 5, with the unit being seconds.

[0063] Then, compare the magnitudes of the fifth and sixth accelerations, assuming the fifth acceleration is -1 m / s². 2 The sixth acceleration is 1 m / s². 2 It can be determined that the fifth acceleration is less than the sixth acceleration. Therefore, based on the fifth acceleration, the autonomous vehicle is controlled to decelerate.

[0064] Step 205: When the distance between the vehicle and the lane is less than the second distance, if the autonomous vehicle meets the preset parking conditions, then control the autonomous vehicle to park.

[0065] Specifically, when the distance between the vehicles and the lane is less than the second distance, the autonomous vehicle is controlled to enter a parking decision state, and the autonomous vehicle is judged whether it needs to stop based on the traffic light data at the intersection, the driving speed and the distance between the vehicles and the lane.

[0066] If the autonomous vehicle needs to stop, then control the autonomous vehicle to stop at the intersection.

[0067] More specifically, during the process of an autonomous vehicle moving towards an intersection in a deceleration decision state, if the distance between the autonomous vehicle and the roadway is less than a second distance, the autonomous vehicle is controlled to enter a stop decision state. In the stop decision state, if the traffic light at the intersection is not green, it is determined that the autonomous vehicle needs to stop; and if the traffic light at the intersection is green, it can be determined whether the autonomous vehicle needs to stop based on the remaining time corresponding to the green light state, the driving speed, and the distance between the vehicle and the roadway. For example, the ratio of the distance between the vehicle and the roadway to the driving speed can be calculated to obtain the time it takes for the autonomous vehicle to travel from its current position to the stop line at the intersection at the stated speed. If this time is greater than the remaining time corresponding to the green light state, it is determined that the autonomous vehicle needs to stop.

[0068] If the autonomous vehicle needs to stop, the system controls it to enter a stop-and-wait state and then stops. During the stopping process, the autonomous vehicle must maintain a safe distance from the vehicle in front. Therefore, controlling the autonomous vehicle to stop at the intersection can specifically include:

[0069] Determine whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle.

[0070] If so, the autonomous vehicle is controlled to stop based on the minimum acceleration between the first acceleration and the second acceleration; the first acceleration is used to reduce the speed of the autonomous vehicle from the driving speed to 0 when the autonomous vehicle reaches the intersection; the second acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle.

[0071] If not, then based on the first acceleration, control the autonomous vehicle to stop.

[0072] Specifically, the second acceleration can be calculated according to formula (2). The first acceleration can be used to reduce the speed of the autonomous vehicle from the driving speed to 0 when the autonomous vehicle reaches the stop line at the intersection. More specifically, the first acceleration can be calculated using the following formula:

[0073]

[0074] Among them, a dec The first acceleration is expressed in m / s². 2 ;d veh2stopline The distance between the vehicle and the lane for autonomous vehicles is in meters. Other parameters are given in formulas (1) and (2).

[0075] Optionally, the method of this embodiment may further include the following steps:

[0076] If the autonomous vehicle does not need to stop, then determine whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle.

[0077] If so, the autonomous vehicle is controlled to pass through the intersection based on the minimum acceleration between the third and fourth accelerations; the third acceleration is used to adjust the speed of the autonomous vehicle to a first speed; the fourth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle; the first speed is less than or equal to the speed limit of the road where the autonomous vehicle is located, and greater than the preset safe speed.

[0078] If not, then based on the third acceleration, control the autonomous vehicle to pass through the intersection.

[0079] Specifically, the third acceleration can be calculated using formula (1), at which point V final The first velocity is given. The fourth acceleration can be calculated using formula (2).

[0080] Optionally, the method in this embodiment may further include:

[0081] If the autonomous vehicle does not need to slow down, then determine whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle.

[0082] If so, the autonomous vehicle is controlled to continue driving based on the minimum acceleration between the seventh and eighth accelerations; the seventh acceleration is used to adjust the speed of the autonomous vehicle to a first speed; the eighth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle; the first speed is less than or equal to the speed limit of the road where the autonomous vehicle is located, and greater than the preset safe speed.

[0083] If not, then based on the seventh acceleration, control the autonomous vehicle to continue driving.

[0084] Specifically, the seventh acceleration can be calculated using formula (1), at which point v final The first velocity is given. The eighth acceleration can be calculated using formula (2).

[0085] Optionally, after step 202, the method of this embodiment may further include:

[0086] When the distance between the vehicle lanes is greater than or equal to the first distance, it is determined whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle.

[0087] If so, the autonomous vehicle is controlled to continue driving based on the minimum acceleration between the ninth and tenth accelerations; the ninth acceleration is used to adjust the speed of the autonomous vehicle to a first speed; the tenth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle; the first speed is less than or equal to the speed limit of the road where the autonomous vehicle is located, and greater than the preset safe speed.

[0088] If not, then the autonomous vehicle is controlled to continue driving according to the ninth acceleration.

[0089] Specifically, if the distance between the autonomous vehicle and the lane is greater than or equal to the first distance, the autonomous vehicle is controlled to enter normal driving mode. In normal driving mode, the driving state of the autonomous vehicle is controlled using the above method. The ninth acceleration can be calculated according to formula (1), where V... final The first speed is given. The tenth acceleration can be calculated using formula (2). This allows the autonomous vehicle to maintain a preset first speed while keeping a safe distance from the vehicle in front during normal driving.

[0090] Based on a general inventive concept, embodiments of this specification also provide an autonomous vehicle intersection passage device corresponding to the above method. Figure 3 This is a schematic diagram of the structure of an autonomous vehicle intersection passage device provided in the embodiments of this specification. Figure 3 As shown, the device may include:

[0091] The vehicle driving data acquisition module 31 is used to acquire the driving speed of the autonomous vehicle and the distance between the autonomous vehicle and the stop line at the intersection in real time.

[0092] The distance threshold determination module 32 is used to determine a first distance and a second distance based on the driving speed; the first distance is positively correlated with the driving speed, and the second distance is positively correlated with the driving speed; the first distance is greater than the second distance.

[0093] The first judgment module 33 is used to determine whether the distance between the vehicle lines is less than the first distance and greater than or equal to the second distance, and to obtain a first judgment result.

[0094] The deceleration decision module 34 is used to determine whether the autonomous vehicle needs to decelerate if the first judgment result indicates that the distance between the vehicle lanes is less than the first distance and greater than or equal to the second distance, based on the traffic light data at the intersection, the driving speed, and the distance between the vehicle lanes.

[0095] The deceleration module 35 is used to control the autonomous vehicle to decelerate if the autonomous vehicle needs to decelerate.

[0096] Optionally, the apparatus of this embodiment may further include:

[0097] The parking decision module is used to determine whether the autonomous vehicle needs to stop if the first judgment result indicates that the distance between the vehicle lines is less than the second distance, based on the traffic light data at the intersection, the driving speed, and the distance between the vehicle lines.

[0098] The parking module is used to control the autonomous vehicle to stop at the intersection if it needs to stop.

[0099] Optionally, the parking module can be used specifically for:

[0100] A second determination result is obtained by determining whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle.

[0101] If the second determination result indicates that there is a road vehicle traveling within a preset distance range ahead of the autonomous vehicle, then the autonomous vehicle is controlled to stop according to the minimum acceleration between the first acceleration and the second acceleration; the first acceleration is used to reduce the speed of the autonomous vehicle from the driving speed to 0 when the autonomous vehicle reaches the intersection; the second acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle.

[0102] If the second determination result indicates that there are no road vehicles traveling within a preset distance range ahead of the autonomous vehicle, then the autonomous vehicle is controlled to stop based on the first acceleration.

[0103] Optionally, the apparatus of this embodiment may further include a first intersection access module, used for:

[0104] If the autonomous vehicle does not need to stop, then it is determined whether there are any road vehicles traveling within a preset distance range in front of the autonomous vehicle, and a third determination result is obtained.

[0105] If the third determination result indicates that there is a road vehicle traveling within a preset distance range ahead of the autonomous vehicle, then the autonomous vehicle is controlled to pass through the intersection based on the minimum acceleration between the third acceleration and the fourth acceleration; the third acceleration is used to adjust the speed of the autonomous vehicle to a first speed; the fourth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle; the first speed is less than or equal to the speed limit of the road where the autonomous vehicle is located, and greater than the preset safe speed.

[0106] If the third determination result indicates that there are no road vehicles traveling within a preset distance range ahead of the autonomous vehicle, then based on the third acceleration, the autonomous vehicle is controlled to pass through the intersection.

[0107] Optionally, the reduction module 35 can be used specifically for:

[0108] The system determines whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle, thus obtaining a fourth determination result.

[0109] If the fourth determination result indicates that there is a road vehicle traveling within a preset distance range ahead of the autonomous vehicle, then the autonomous vehicle is controlled to decelerate according to the minimum acceleration between the fifth and sixth accelerations; the fifth acceleration is used to adjust the speed of the autonomous vehicle to the second speed; the sixth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle; the second speed is less than or equal to the preset safe speed.

[0110] If the fourth determination result indicates that there are no road vehicles traveling within a preset distance range ahead of the autonomous vehicle, then the autonomous vehicle is controlled to decelerate based on the fifth acceleration.

[0111] Optionally, the apparatus of this embodiment may further include a second intersection module, used for:

[0112] If the autonomous vehicle does not need to decelerate, then it is determined whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle, and a fifth determination result is obtained.

[0113] If the fifth determination result indicates that there is a road vehicle traveling within a preset distance range ahead of the autonomous vehicle, then the autonomous vehicle is controlled to continue traveling according to the minimum acceleration between the seventh acceleration and the eighth acceleration; the seventh acceleration is used to adjust the speed of the autonomous vehicle to a first speed; the eighth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while traveling; the vehicle in front is the road vehicle closest to the autonomous vehicle; the first speed is less than or equal to the speed limit of the road where the autonomous vehicle is located, and greater than the preset safe speed.

[0114] If the fifth determination result indicates that there are no road vehicles traveling within a preset distance range ahead of the autonomous vehicle, then based on the seventh acceleration, the autonomous vehicle is controlled to continue driving.

[0115] Optionally, the first distance is equal to the distance the autonomous vehicle needs to travel to decelerate from the driving speed to 0 with a first preset acceleration; the second distance is equal to the distance the autonomous vehicle needs to travel to decelerate from the driving speed to 0 with a second preset acceleration; and the first preset acceleration is greater than the second preset acceleration.

[0116] Optionally, the device in this embodiment may further include a normal driving module for:

[0117] Determine whether the distance between the vehicle lines is greater than or equal to the first distance.

[0118] If the distance between the vehicle lanes is greater than or equal to the first distance, then it is determined whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle, and a sixth determination result is obtained.

[0119] If the sixth determination result indicates that there is a road vehicle traveling within a preset distance range ahead of the autonomous vehicle, then the autonomous vehicle is controlled to continue traveling according to the minimum acceleration between the ninth and tenth accelerations; the ninth acceleration is used to adjust the speed of the autonomous vehicle to a first speed; the tenth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while traveling; the vehicle in front is the road vehicle closest to the autonomous vehicle; the first speed is less than or equal to the speed limit of the road where the autonomous vehicle is located, and greater than the preset safe speed.

[0120] If the sixth determination result indicates that there are no road vehicles traveling within a preset distance range ahead of the autonomous vehicle, then the autonomous vehicle is controlled to continue driving according to the ninth acceleration.

[0121] Based on the same idea, embodiments of this specification also provide a device corresponding to the above method. Specifically, this device may be a computer device installed in an autonomous vehicle.

[0122] Figure 4 This is a structural schematic diagram of an autonomous vehicle intersection passage device provided as an embodiment of this specification. Figure 4 As shown, device 400 may include:

[0123] At least one processor 410; and,

[0124] Memory 430 communicatively connected to the at least one processor; wherein,

[0125] The memory 430 stores instructions 420 that can be executed by the at least one processor 410, the instructions being executed by the at least one processor 410 to enable the at least one processor 410 to:

[0126] The driving speed of the autonomous vehicle and the distance between the autonomous vehicle and the stop line at the intersection are obtained in real time.

[0127] A first distance and a second distance are determined based on the driving speed; the first distance is positively correlated with the driving speed, and the second distance is positively correlated with the driving speed; the first distance is greater than the second distance.

[0128] Determine whether the distance between the vehicle lines is less than the first distance and greater than or equal to the second distance to obtain a first determination result.

[0129] If the first determination result indicates that the distance between the vehicles is less than the first distance and greater than or equal to the second distance, then based on the traffic light data at the intersection, the driving speed, and the distance between the vehicles, it is determined whether the autonomous vehicle needs to decelerate.

[0130] If the autonomous vehicle needs to decelerate, then control the autonomous vehicle to decelerate.

[0131] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, for... Figure 4 As the device shown is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0132] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program a digital system themselves to "integrate" it onto a PLD, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must also be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0133] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 635D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F420. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, ASICs, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0134] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0135] For ease of description, the above devices are described separately by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0136] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0137] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0138] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0139] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0140] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0141] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0142] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital character versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0143] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0144] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0145] This application can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0146] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for autonomous vehicles to pass through intersections, characterized in that, include: The driving speed of the autonomous vehicle and the distance between the autonomous vehicle and the stop line at the intersection are obtained in real time. A first distance and a second distance are determined based on the driving speed; the first distance is positively correlated with the driving speed, and the second distance is also positively correlated with the driving speed; the first distance is greater than the second distance. When the distance between the vehicles is less than the first distance and greater than or equal to the second distance, the autonomous vehicle is judged whether it needs to decelerate based on the traffic light data at the intersection, the driving speed, and the distance between the vehicles. If so, then control the autonomous vehicle to decelerate; When the distance between the vehicle and the lane is less than the second distance, if the autonomous vehicle meets the preset parking conditions, then the autonomous vehicle is controlled to park. When the distance between the autonomous vehicle and the lane is greater than or equal to the first distance, the autonomous vehicle’s intersection passage decision state switches to normal driving state. In normal driving state, it is not necessary to determine whether the autonomous vehicle can pass through the intersection when the traffic light is green. The control of the autonomous vehicle to decelerate specifically includes: Determine whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle; If so, the autonomous vehicle is controlled to decelerate according to the minimum acceleration between the fifth and sixth accelerations; the fifth acceleration is used to adjust the speed of the autonomous vehicle to the second speed; the sixth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle; the second speed is less than or equal to the preset safe speed. If not, then based on the fifth acceleration, control the autonomous vehicle to decelerate.

2. The method according to claim 1, characterized in that, If the autonomous vehicle meets the preset parking conditions, then controlling the autonomous vehicle to park specifically includes: Based on the traffic light data at the intersection, the driving speed, and the distance between the vehicles, it is determined whether the autonomous vehicle needs to stop. If the autonomous vehicle needs to stop, then control the autonomous vehicle to stop at the intersection.

3. The method according to claim 2, characterized in that, The control of the autonomous vehicle to stop at the intersection specifically includes: Determine whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle; If so, the autonomous vehicle is controlled to stop based on the minimum acceleration between the first acceleration and the second acceleration; the first acceleration is used to reduce the speed of the autonomous vehicle from the driving speed to 0 when the autonomous vehicle reaches the intersection; the second acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle. If not, then based on the first acceleration, control the autonomous vehicle to stop.

4. The method according to claim 2, characterized in that, Also includes: If the autonomous vehicle does not need to stop, then determine whether there are any road vehicles traveling within a preset distance range in front of the autonomous vehicle. If so, the autonomous vehicle is controlled to pass through the intersection based on the minimum acceleration between the third and fourth accelerations; the third acceleration is used to adjust the speed of the autonomous vehicle to a first speed; the fourth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle; the first speed is less than or equal to the speed limit of the road where the autonomous vehicle is located, and greater than the preset safe speed. If not, then based on the third acceleration, control the autonomous vehicle to pass through the intersection.

5. The method according to claim 1, characterized in that, Also includes: If the autonomous vehicle does not need to decelerate, then determine whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle. If so, the autonomous vehicle is controlled to continue driving based on the minimum acceleration between the seventh and eighth accelerations; the seventh acceleration is used to adjust the speed of the autonomous vehicle to a first speed; the eighth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle; the first speed is less than or equal to the speed limit of the road where the autonomous vehicle is located, and greater than the preset safe speed. If not, then based on the seventh acceleration, control the autonomous vehicle to continue driving.

6. The method according to claim 1, characterized in that, The first distance is equal to the distance the autonomous vehicle needs to travel to decelerate from the driving speed to 0 with a first preset acceleration; The second distance is equal to the distance the autonomous vehicle needs to travel to decelerate from the driving speed to 0 with a second preset acceleration; The first preset acceleration is greater than the second preset acceleration.

7. The method according to claim 1, characterized in that, After determining the first distance and the second distance based on the driving speed, the method further includes: When the distance between the vehicle lanes is greater than or equal to the first distance, it is determined whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle. If so, the autonomous vehicle is controlled to continue driving based on the minimum acceleration between the ninth and tenth accelerations; the ninth acceleration is used to adjust the speed of the autonomous vehicle to a first speed; the tenth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle; the first speed is less than or equal to the speed limit of the road where the autonomous vehicle is located, and greater than the preset safe speed. If not, then the autonomous vehicle is controlled to continue driving according to the ninth acceleration.

8. An autonomous vehicle intersection passage device, characterized in that, include: The vehicle driving data acquisition module is used to acquire the driving speed of the autonomous vehicle and the distance between the autonomous vehicle and the stop line at the intersection in real time. A distance threshold determination module is used to determine a first distance and a second distance based on the driving speed; the first distance is positively correlated with the driving speed, and the second distance is positively correlated with the driving speed; the first distance is greater than the second distance. The deceleration decision module is used to determine whether the autonomous vehicle needs to decelerate when the distance between the vehicle lanes is less than the first distance and greater than or equal to the second distance, based on traffic light data at the intersection, the driving speed, and the distance between the vehicle lanes. A deceleration module is used to control the autonomous vehicle to decelerate if the autonomous vehicle needs to decelerate. The parking decision module is used to control the autonomous vehicle to park if the distance between the vehicle lines is less than the second distance and the autonomous vehicle meets the preset parking conditions. The device is also used for: When the distance between the autonomous vehicle and the lane is greater than or equal to the first distance, the autonomous vehicle’s intersection passage decision state switches to normal driving state. In normal driving state, it is not necessary to determine whether the autonomous vehicle can pass through the intersection when the traffic light is green. The deceleration module is specifically used for: Determine whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle; If so, the autonomous vehicle is controlled to decelerate according to the minimum acceleration between the fifth and sixth accelerations; the fifth acceleration is used to adjust the speed of the autonomous vehicle to the second speed; the sixth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle; the second speed is less than or equal to the preset safe speed. If not, then based on the fifth acceleration, control the autonomous vehicle to decelerate.

9. An intersection passage device for autonomous vehicles, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enable the at least one processor to: The driving speed of the autonomous vehicle and the distance between the autonomous vehicle and the stop line at the intersection are obtained in real time. A first distance and a second distance are determined based on the driving speed; the first distance is positively correlated with the driving speed, and the second distance is also positively correlated with the driving speed; the first distance is greater than the second distance. When the distance between the vehicles is less than the first distance and greater than or equal to the second distance, the autonomous vehicle is judged whether it needs to decelerate based on the traffic light data at the intersection, the driving speed, and the distance between the vehicles. If so, then control the autonomous vehicle to decelerate; When the distance between the vehicle and the lane is less than the second distance, if the autonomous vehicle meets the preset parking conditions, then the autonomous vehicle is controlled to park. When the distance between the autonomous vehicle and the lane is greater than or equal to the first distance, the autonomous vehicle’s intersection passage decision state switches to normal driving state. In normal driving state, it is not necessary to determine whether the autonomous vehicle can pass through the intersection when the traffic light is green. The control of the autonomous vehicle to decelerate specifically includes: Determine whether there are any road vehicles traveling within a preset distance range ahead of the autonomous vehicle; If so, the autonomous vehicle is controlled to decelerate according to the minimum acceleration between the fifth and sixth accelerations; the fifth acceleration is used to adjust the speed of the autonomous vehicle to the second speed; the sixth acceleration is used to maintain a preset safe distance between the autonomous vehicle and the vehicle in front while driving; the vehicle in front is the road vehicle closest to the autonomous vehicle; the second speed is less than or equal to the preset safe speed. If not, then based on the fifth acceleration, control the autonomous vehicle to decelerate.

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