Vehicle driving control method and device, electronic equipment and vehicle

Abstract

The invention relates to the technical field of intelligent driving, in particular to a vehicle driving control method and device, electronic equipment and a vehicle. Obtaining current road information corresponding to a current road where the vehicle is located; identifying the current road information, and determining whether the current road is a continuous plane road section; if the vehicle is in the continuous plane road section, detecting whether abnormal traffic flow exists in each front vehicle in a preset range in front of the vehicle based on at least two types of sensors; therefore, the problems that a traditional traffic flow monitoring system often depends on a single sensor and cannot comprehensively and accurately obtain traffic flow information, so that the judgment on the abnormal condition of the traffic flow is inaccurate and the response is not timely are solved, and the accurate judgment on the abnormal traffic flow is realized. And if the abnormal traffic flow exists, the vehicle is controlled according to the relationship between the abnormal traffic flow and the vehicle, so that the control accuracy of the vehicle is ensured, and the driving safety of the vehicle can be ensured.

Description

Technical Field

[0001] The present invention relates to the field of intelligent driving technology, and in particular to a vehicle driving control method, device, electronic equipment and vehicle. Background Art

[0002] With the rapid development of intelligent transportation systems (ITS), accurate acquisition and timely response to road traffic flow information have become key links in improving road safety and traffic efficiency.

[0003] However, traditional traffic flow monitoring systems are often unable to obtain traffic flow information comprehensively and accurately, resulting in inaccurate judgments on traffic flow anomalies and untimely responses.

[0004] Therefore, how to accurately judge the abnormal traffic flow and control it according to the abnormal traffic flow has become an urgent problem to be solved. Summary of the invention

[0005] In view of this, the present invention provides a vehicle driving control method, device, electronic device and vehicle to solve the problem of how to accurately judge abnormal traffic flow and control according to the abnormal traffic flow, which has become an urgent problem to be solved.

[0006] In a first aspect, the present invention provides a vehicle driving control method, the method comprising:

[0007] Obtain the current road information corresponding to the current road where the vehicle is located;

[0008] Identify the current road information and determine whether the current road is a continuous flat road section;

[0009] If the vehicle is on a continuous flat road section, at least two types of sensors are used to detect whether there is an abnormal traffic flow among the front vehicles within a preset range in front of the vehicle; the abnormal traffic flow is composed of at least two abnormal front vehicles in abnormal conditions among the front vehicles;

[0010] If there is abnormal traffic flow, the vehicle is controlled based on the relationship between the abnormal traffic flow and the vehicle.

[0011] The vehicle driving control method provided by the embodiment of the present application obtains the current road information corresponding to the current road where the vehicle is located; identifies the current road information and determines whether the current road is a continuous plane section, thereby ensuring the accuracy of the result of determining whether the current road is a continuous plane section. If the vehicle is in a continuous plane section, then based on at least two types of sensors, it is detected whether there is abnormal traffic flow in each front vehicle within a preset range in front of the vehicle, thereby ensuring the accuracy of the detected abnormal traffic flow in the front vehicle. Therefore, it solves the problem that the traditional traffic flow monitoring system often relies on a single sensor and cannot fully and accurately obtain traffic flow information, resulting in inaccurate judgment of abnormal traffic flow conditions and untimely response, and realizes accurate judgment of abnormal traffic flow. If there is abnormal traffic flow, the vehicle is controlled according to the relationship between the abnormal traffic flow and the vehicle, ensuring the accuracy of controlling the vehicle, and then ensuring the driving safety of the vehicle.

[0012] In an optional implementation, identifying the current road information and determining whether the current road is a continuous plane section includes:

[0013] Identify the current road information and detect whether the current road is a fork or intersection;

[0014] If the current road is not a fork and is not an intersection, then obtain the road slope corresponding to the current road;

[0015] If the road slope is less than the preset slope threshold, the curve radius corresponding to the current road is obtained;

[0016] If the curve radius is greater than the preset curve radius, it is determined that the current road is a continuous flat road section.

[0017] In an optional implementation, detecting whether there is abnormal traffic flow in each front vehicle within a preset range in front of the vehicle based on at least two types of sensors includes:

[0018] Acquire current position information and / or current speed information of each front vehicle detected by at least two types of sensors;

[0019] Tracking the current position information and / or current speed information of each front vehicle detected by each sensor;

[0020] For each front vehicle, if the current position information and / or current speed information of the front vehicle detected by at least two types of sensors is continuously lost for a time period exceeding the disappearance judgment time threshold, the front vehicle whose current position information and / or current speed information is continuously lost is determined to be an abnormal front vehicle;

[0021] Based on each abnormal front vehicle, an abnormal traffic flow is determined.

[0022] The vehicle driving control method provided in the embodiment of the present application obtains the current position information and / or current speed information of each front vehicle detected by at least two types of sensors; tracks the current position information and / or current speed information of each front vehicle detected by each sensor; if the current position information and / or current speed information of the front vehicle detected by at least two types of sensors is continuously lost for a time period exceeding the disappearance judgment time threshold, the front vehicle whose current position information and / or current speed information is continuously lost is determined to be an abnormal front vehicle; based on each abnormal front vehicle, the abnormal traffic flow is determined, thereby ensuring the accuracy of the determination that the front vehicle whose current position information and / or current speed information is continuously lost is an abnormal front vehicle, and further ensuring the accuracy of the determined abnormal traffic flow. Therefore, the problem that the traditional traffic flow monitoring system often relies on a single sensor and cannot fully and accurately obtain traffic flow information, resulting in inaccurate judgment of abnormal traffic flow conditions and untimely response, is solved.

[0023] In an optional implementation, detecting whether there is abnormal traffic flow in each front vehicle within a preset range in front of the vehicle based on at least two types of sensors includes:

[0024] Identify the current road information and determine the current lane width;

[0025] Acquire the driving trajectory of each front vehicle detected by at least two types of sensors;

[0026] For each vehicle ahead, the driving trajectory detected by each sensor is compared with the corresponding lane trajectory in the target lane where the vehicle ahead was located a preset time ago;

[0027] If the lateral deviation between the driving trajectory of the front vehicle detected by at least two types of sensors and the lane trajectory is greater than the current lane width, the front vehicle is determined as an abnormal front vehicle; based on each abnormal front vehicle, an abnormal traffic flow is determined.

[0028] The vehicle driving control method provided in the embodiment of the present application identifies the current road information, determines the current lane width, and ensures the accuracy of the determined current lane width. The driving trajectory of each front vehicle detected by at least two types of sensors is obtained; for each front vehicle, the driving trajectory detected by each sensor is compared with the corresponding lane trajectory in the target lane where the front vehicle was located before a preset time, ensuring the accuracy of the comparison result. If there is a lateral deviation between the driving trajectory of the front vehicle detected by at least two types of sensors and the lane trajectory that is greater than the current lane width, the front vehicle is determined as an abnormal front vehicle; based on each abnormal front vehicle, the abnormal traffic flow is determined to ensure the accuracy of the determined abnormal traffic flow. Therefore, it solves the problem that the traditional traffic flow monitoring system often relies on a single sensor and cannot fully and accurately obtain traffic flow information, resulting in inaccurate judgment of abnormal traffic flow conditions and untimely response.

[0029] In an optional implementation, detecting whether there is abnormal traffic flow in each front vehicle within a preset range in front of the vehicle based on at least two types of sensors includes:

[0030] Detect whether the future driving section of each front vehicle within a future preset time period meets the preset conditions;

[0031] If the future driving section of each front vehicle within the future preset time period meets the preset conditions, then obtaining the current speed of each front vehicle transmitted by at least two types of sensors;

[0032] For each front vehicle, the current speed of the front vehicle detected by each sensor is compared with the current speed of the adjacent vehicle corresponding to the front vehicle to obtain the speed difference between the current vehicle corresponding to each sensor and the adjacent vehicle;

[0033] For each vehicle ahead, the speed difference between the vehicle ahead and the adjacent vehicles is obtained according to the detection of each sensor, and it is determined whether there is abnormal traffic flow in the vehicle ahead.

[0034] The vehicle driving control method provided by the embodiment of the present application detects whether the future driving section of each front vehicle in the future preset time period meets the preset conditions, thereby ensuring the accuracy of the obtained detection results. If the future driving section of each front vehicle in the future preset time period meets the preset conditions, the current speed of each front vehicle transmitted by at least two types of sensors is obtained, so that the current speed of each front vehicle can be obtained in multiple directions. For each front vehicle, the current speed of the front vehicle detected by each sensor is compared with the current speed of the adjacent vehicle corresponding to the front vehicle, and the speed difference between the current vehicle corresponding to each sensor and the adjacent vehicle is obtained, thereby ensuring the accuracy of the speed difference between the current vehicle corresponding to each sensor and the adjacent vehicle. For each front vehicle, according to the speed difference between the front vehicle and the adjacent vehicle detected by each sensor, it is judged whether there is an abnormal traffic flow in the front vehicle, thereby ensuring the accuracy of the result of judging whether there is an abnormal traffic flow in the front vehicle. Therefore, the problem that the traditional traffic flow monitoring system often relies on a single sensor and cannot fully and accurately obtain traffic flow information, resulting in inaccurate judgment of abnormal traffic flow and untimely response is solved.

[0035] In an optional implementation, for each front vehicle, according to the speed difference between the front vehicle and the adjacent vehicle detected by each sensor, determining whether there is an abnormal traffic flow in the front vehicle includes:

[0036] For each vehicle ahead, the speed difference detected by each sensor is compared with a preset speed difference;

[0037] If there are at least two sensors whose speed difference is greater than the preset speed difference, and the speed difference is greater than the preset speed difference for a duration greater than the preset duration, the front vehicle is determined as an abnormal front vehicle;

[0038] Based on each abnormal front vehicle, an abnormal traffic flow is determined.

[0039] The vehicle driving control method provided by the embodiment of the present application compares the speed difference detected by each sensor with the preset speed difference for each front vehicle; if there are at least two speed differences detected by the sensors that are greater than the preset speed difference, and the speed difference is greater than the preset speed difference for a duration greater than the preset duration, the front vehicle is determined as an abnormal front vehicle; based on each abnormal front vehicle, an abnormal traffic flow is determined, thereby ensuring the accuracy of the determined abnormal traffic flow.

[0040] In an optional implementation, detecting whether the future driving section of each front vehicle within a future preset time period meets a preset condition includes:

[0041] Acquire the driving trajectory and current position information corresponding to each front vehicle detected by at least two types of sensors;

[0042] Predict the future position information of each vehicle ahead within a preset time period in the future based on the driving trajectory and current position information of each vehicle ahead;

[0043] For each vehicle ahead, determine the future driving section based on the future position information;

[0044] Identify the future driving section and detect whether the future driving section is a continuous flat section;

[0045] If the future driving section is a continuous flat section, the road length of the future driving section is obtained;

[0046] If the road length is less than or equal to a preset road length threshold, it is determined that the future driving section of each front vehicle within a future preset time period meets the preset condition.

[0047] The vehicle driving control method provided by the embodiment of the present application obtains the driving trajectory and current position information corresponding to each front vehicle detected by at least two types of sensors; predicts the future position information of each front vehicle in a future preset time period according to the driving trajectory and current position information corresponding to each front vehicle, thereby ensuring the accuracy of the predicted future position information of each front vehicle in a future preset time period. For each front vehicle, the future driving section is determined according to the future position information, thereby ensuring the accuracy of the determined future driving section. The future driving section is identified, and it is detected whether the future driving section is a continuous plane section, thereby ensuring the accuracy of the obtained detection result. If the future driving section is a continuous plane section, the road length of the future driving section is obtained. If the road length is less than or equal to the preset road length threshold, it is determined that the future driving section of each front vehicle in the future preset time period meets the preset conditions. It is ensured that the future driving section of each front vehicle in the future preset time period meets the accuracy of the preset conditions.

[0048] In an optional implementation, if there is an abnormal traffic flow, the vehicle is controlled according to the relationship between the abnormal traffic flow and the vehicle, including:

[0049] Obtaining current abnormal position information corresponding to each abnormal front vehicle in each abnormal traffic flow;

[0050] According to each current abnormal position information, determine the target abnormal front vehicle closest to the vehicle from each abnormal front vehicle;

[0051] Obtain the longitudinal distance between the target abnormal front vehicle and the vehicle;

[0052] Divide the longitudinal distance by the current speed of the vehicle to obtain the longitudinal time distance between the vehicle and the abnormal vehicle ahead of the target.

[0053] The vehicle is controlled according to the longitudinal time distance.

[0054] The vehicle driving control method provided in the embodiment of the present application obtains the current abnormal position information corresponding to each abnormal front vehicle in each abnormal traffic flow; according to each current abnormal position information, the target abnormal front vehicle closest to the vehicle is determined from each abnormal front vehicle, thereby ensuring the accuracy of the determined target abnormal front vehicle. The longitudinal distance between the target abnormal front vehicle and the vehicle is obtained; the longitudinal distance is divided by the current speed corresponding to the vehicle to obtain the longitudinal time distance of the vehicle equivalent to the target abnormal front vehicle, thereby ensuring the accuracy of the calculated longitudinal time distance. According to the longitudinal time distance, the vehicle is controlled to ensure the accuracy of the control of the vehicle, thereby ensuring the driving safety of the vehicle.

[0055] In an optional implementation, controlling the vehicle according to the longitudinal time distance includes:

[0056] Compare the longitudinal time interval with the preset alarm time interval; the preset alarm time interval is calculated based on the current vehicle speed corresponding to the vehicle, the minimum deceleration value of the vehicle for risk avoidance, the shortest time required for the driver to react and the driver's takeover reaction time threshold;

[0057] If the longitudinal time distance is less than the preset alarm time distance, the vehicle is controlled to output the current state information and current abnormal position information of the target abnormal front vehicle, and output alarm prompt information to the driver;

[0058] Compare the longitudinal time distance with the preset emergency avoidance time distance; the preset emergency avoidance time distance is calculated based on the current vehicle speed corresponding to the vehicle, the minimum deceleration value of the vehicle for avoidance, and the tolerance threshold from the issuance of the driving control signal to the realization of control; the preset emergency avoidance time distance is less than the preset alarm time distance;

[0059] If the longitudinal time distance is less than the preset emergency avoidance time distance, the vehicle will be controlled to slow down and stop.

[0060] The vehicle driving control method provided in the embodiment of the present application compares the longitudinal time distance with the preset alarm time distance; if the longitudinal time distance is less than the preset alarm time distance, the vehicle is controlled to output the current state information and current abnormal position information of the target abnormal vehicle ahead, and outputs the alarm prompt information to the driver, thereby ensuring the accuracy of the output current state information and current abnormal position information of the target abnormal vehicle ahead, and the accuracy of the alarm prompt information output to the driver. The longitudinal time distance is compared with the preset emergency avoidance time distance; if the longitudinal time distance is less than the preset emergency avoidance time distance, the vehicle is controlled to slow down and stop, ensuring the accuracy of controlling the vehicle to slow down and stop, and thus ensuring the driving safety of the vehicle.

[0061] In a second aspect, the present invention provides a vehicle driving control device, the device comprising:

[0062] An acquisition module is used to obtain current road information corresponding to the current road where the vehicle is located;

[0063] A determination module is used to identify the current road information and determine whether the current road is a continuous plane section;

[0064] A detection module, for detecting, if the vehicle is on a continuous flat road section, whether there is an abnormal traffic flow among the front vehicles within a preset range in front of the vehicle based on at least two types of sensors; the abnormal traffic flow is composed of at least two abnormal front vehicles in abnormal state among the front vehicles;

[0065] The control module is used to control the vehicle according to the relationship between the abnormal traffic flow and the vehicle if there is abnormal traffic flow.

[0066] The vehicle driving control method provided by the embodiment of the present application obtains the current road information corresponding to the current road where the vehicle is located; identifies the current road information and determines whether the current road is a continuous plane section, thereby ensuring the accuracy of the result of determining whether the current road is a continuous plane section. If the vehicle is in a continuous plane section, then based on at least two types of sensors, it is detected whether there is abnormal traffic flow in each front vehicle within a preset range in front of the vehicle, thereby ensuring the accuracy of the detected abnormal traffic flow in the front vehicle. Therefore, it solves the problem that the traditional traffic flow monitoring system often relies on a single sensor and cannot fully and accurately obtain traffic flow information, resulting in inaccurate judgment of abnormal traffic flow conditions and untimely response, and realizes accurate judgment of abnormal traffic flow. If there is abnormal traffic flow, the vehicle is controlled according to the relationship between the abnormal traffic flow and the vehicle, ensuring the accuracy of controlling the vehicle, and then ensuring the driving safety of the vehicle.

[0067] In a third aspect, the present invention provides an electronic device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the vehicle driving control method of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0068] In a fourth aspect, the present invention provides a vehicle comprising an electronic device, a vehicle body and at least two types of sensors, wherein the electronic device is used to execute the vehicle driving control method of the first aspect or any corresponding embodiment thereof.

[0069] In a fifth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the vehicle driving control method of the first aspect or any corresponding embodiment thereof.

[0070] In a sixth aspect, the present invention provides a computer program product, comprising computer instructions for causing a computer to execute the vehicle driving control method of the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0072] Figure 1 is a flow chart of a vehicle driving control method according to an embodiment of the present invention;

[0073] Figure 2 is a flow chart of another vehicle driving control method according to an embodiment of the present invention;

[0074] Figure 3 is a flow chart of another vehicle driving control method according to an embodiment of the present invention;

[0075] Figure 4 is a flow chart of another vehicle driving control method according to an embodiment of the present invention;

[0076] Figure 5 is a schematic structural diagram of the vehicle according to an embodiment of the present invention;

[0077] Figure 6 is a structural block diagram of a vehicle driving control device according to an embodiment of the present invention;

[0078] Figure 7 It is a schematic diagram of the hardware structure of the electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0079] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0080] With the rapid development of intelligent transportation systems (ITS), accurate acquisition and timely response to road traffic flow information have become key links in improving road safety and traffic efficiency.

[0081] However, traditional traffic flow monitoring systems are often unable to obtain traffic flow information comprehensively and accurately, resulting in inaccurate judgments on traffic flow anomalies and untimely responses.

[0082] Therefore, how to accurately judge the abnormal traffic flow and control it according to the abnormal traffic flow has become an urgent problem to be solved.

[0083] It should be noted that the execution subject of the vehicle driving control method provided in the embodiment of the present application may be a vehicle driving control device, and the vehicle driving control device may be implemented as part or all of an electronic device through software, hardware, or a combination of software and hardware, wherein the electronic device may be a control device in a vehicle. Among them, the vehicle may include an electronic device, a vehicle body, and at least two types of sensors. Specifically, the vehicle may include at least two types of sensors such as a forward-sensing laser radar, a forward-sensing camera, a forward-sensing millimeter-wave radar, a navigation map device, and a combined positioning device composed of a GNSS+RTK+IMU+wheel speed sensor.

[0084] Among them, the forward sensing laser radar provides road information of the road on which the vehicle is traveling and information about the vehicle ahead. The road information includes the position, type, shape, and road surface bump position and depth of fixed road elements such as lane lines, curbs, guardrails, traffic light poles, street light poles, traffic signs, and traffic platforms relative to the vehicle, and also includes the position, type, shape, and other attribute information of movable road elements such as road cones and temporary signs relative to the vehicle, including lane line position, lane line type, lane line trajectory, lane line start and end points, curb position, curb height, curb trajectory, curb start and end points, guardrail position, guardrail type, guardrail trajectory, guardrail start and end points, traffic light pole position, street light number and position, traffic sign type, traffic sign position, traffic platform type, traffic platform position, road surface bump position and depth, road cone type, road cone position, temporary sign type, temporary sign position, and other information. The front vehicle information includes the type of vehicle, the vehicle ID number, the real-time position of the vehicle relative to the vehicle, and the real-time speed of the vehicle relative to the vehicle.

[0085] The forward perception camera provides information about the road on which the vehicle is traveling and the vehicle ahead. The information type and attributes are the same as those provided by the forward perception lidar.

[0086] The forward-sensing millimeter-wave radar provides information about the road the vehicle is traveling on and the vehicle ahead. The information type and attributes are the same as those provided by the forward-sensing lidar.

[0087] The navigation map device provides road-level road information, including the location of the road section where the vehicle is located, whether it is an intersection, roundabout, fork section, merging, curve radius, uphill / downhill.

[0088] The combined positioning device consisting of GNSS+RTK+IMU+wheel speed sensor integrates the information of satellite positioning system, differential positioning base station, vehicle inertial navigation system and vehicle wheel speed sensor to provide road-level absolute positioning coordinate information of the vehicle, including longitude, latitude, elevation, time and other information.

[0089] In the following method embodiments, the description is made by taking the execution subject as an electronic device as an example.

[0090] According to an embodiment of the present invention, a vehicle driving control method embodiment is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0091] In this embodiment, a vehicle driving control method is provided, which can be used in the above-mentioned electronic device. Figure 1is a flow chart of a vehicle driving control method according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0092] Step S101, obtaining current road information corresponding to the current road where the vehicle is located.

[0093] Specifically, the electronic device can obtain the current location information corresponding to the vehicle based on the positioning device. Then, according to the navigation map device and sensors such as laser radar, perception camera, millimeter wave radar, etc., the current road corresponding to the current location information is determined, thereby determining the section position corresponding to the current road, whether it is an intersection, roundabout, fork section, confluence, curve radius, uphill / downhill and other information. In addition, the electronic device can also obtain the position, type, shape, and road surface bump position and depth of fixed road elements such as lane lines, curbs, guardrails, traffic light poles, street light poles, traffic signs, and traffic platforms relative to the vehicle based on the forward sensing laser radar, forward sensing camera, and forward sensing millimeter wave radar, and also obtain the position, type, shape, and other attribute information of movable road elements such as road cones and temporary signs relative to the vehicle, including the lane line position, lane line type, lane line trajectory, lane line start and end points, curb position, curb height, curb trajectory, curb start and end points, guardrail position, guardrail type, guardrail trajectory, guardrail start and end points, traffic light pole position, street light number and position, traffic sign type, traffic sign position, traffic platform type, traffic platform position, road surface bump position and depth, road cone type, road cone position, temporary sign type, temporary sign position, and other information. Thus, the current road information corresponding to the current road where the vehicle is located is generated.

[0094] The positioning device may be a combined positioning device based on at least one of GNSS+RTK+IMU+wheel speed sensor.

[0095] Among them, the current road information may include the position, type, shape, and the position and depth of the fixed road elements such as lane lines, curbs, guardrails, traffic light poles, street light poles, traffic signs, and traffic stations relative to the vehicle, and also include the position, type, shape, and other attribute information of movable road elements such as road cones and temporary signs relative to the vehicle, including the position of lane lines, lane line types, lane line tracks, lane line start and end points, curb positions, curb heights, curb tracks, curb start and end points, guardrail positions, guardrail types, guardrail tracks, guardrail start and end points, traffic light pole positions, street light numbers and positions, traffic sign types, traffic sign positions, traffic station types, traffic station positions, road concave and convex positions and depths, road cone types, road cone positions, temporary sign types, and temporary sign positions. It also includes the position of the road section where the vehicle is located, whether it is an intersection, a roundabout, a forked section, a merge, a curve radius, uphill / downhill, and other information.

[0096] Step S102, identifying the current road information to determine whether the current road is a continuous plane section.

[0097] Specifically, the electronic device may identify the current road information and determine whether the current road information meets the road requirements of a continuous plane road section.

[0098] Among them, the road requirements for the continuous plane section may include at least one of the current road being a non-fork, the current road being a non-intersection, the road slope of the current road being less than a certain threshold, and the curve radius of the current road being greater than a certain threshold. This embodiment does not make specific limitations on the road requirements for the continuous plane section.

[0099] This step will be described in detail below.

[0100] Step S103: if the vehicle is on a continuous flat road section, then based on at least two types of sensors, detect whether there is abnormal traffic flow in each vehicle in front of the vehicle within a preset range in front of the vehicle.

[0101] The abnormal traffic flow is composed of at least two abnormal front vehicles in abnormal state among the front vehicles.

[0102] Specifically, if the vehicle is on a continuous flat road section, the electronic device obtains information about each vehicle in a preset range ahead of the vehicle detected by at least two types of sensors. Then, the information about the vehicles ahead detected by each sensor is identified to determine whether there is an abnormal vehicle ahead among the vehicles ahead, and then each abnormal vehicle ahead is determined as an abnormal traffic flow.

[0103] The front vehicle information includes the type of vehicle, the vehicle ID number, the real-time position of the vehicle relative to the vehicle, and the real-time speed of the vehicle relative to the vehicle.

[0104] If the detection results corresponding to at least two types of sensors both indicate that abnormal traffic flow exists in the vehicle ahead, the electronic device determines that abnormal traffic flow exists in the vehicle ahead.

[0105] This step will be described in detail below.

[0106] Step S104: If there is abnormal traffic flow, the vehicle is controlled according to the relationship between the abnormal traffic flow and the vehicle.

[0107] Specifically, if there is an abnormal traffic flow in the front vehicle, the electronic device determines the positional relationship between the abnormal traffic flow and the vehicle according to the position information of the abnormal traffic flow, and then controls the vehicle according to the positional relationship between the abnormal traffic flow and the vehicle.

[0108] The vehicle driving control method provided by the embodiment of the present application obtains the current road information corresponding to the current road where the vehicle is located; identifies the current road information and determines whether the current road is a continuous plane section, thereby ensuring the accuracy of the result of determining whether the current road is a continuous plane section. If the vehicle is in a continuous plane section, then based on at least two types of sensors, it is detected whether there is abnormal traffic flow in each front vehicle within a preset range in front of the vehicle, thereby ensuring the accuracy of the detected abnormal traffic flow in the front vehicle. Therefore, it solves the problem that the traditional traffic flow monitoring system often relies on a single sensor and cannot fully and accurately obtain traffic flow information, resulting in inaccurate judgment of abnormal traffic flow conditions and untimely response, and realizes accurate judgment of abnormal traffic flow. If there is abnormal traffic flow, the vehicle is controlled according to the relationship between the abnormal traffic flow and the vehicle, ensuring the accuracy of controlling the vehicle, and then ensuring the driving safety of the vehicle.

[0109] In this embodiment, a vehicle driving control method is provided, which can be used in the above-mentioned electronic device. Figure 2 is a flow chart of a vehicle driving control method according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps:

[0110] Step S201, obtaining current road information corresponding to the current road where the vehicle is located.

[0111] For details about this step, please refer to the above description of step S101, which will not be elaborated here.

[0112] Step S202, identifying the current road information to determine whether the current road is a continuous plane section.

[0113] Specifically, the above step S202 may include the following steps:

[0114] Step S2021, identifying the current road information and detecting whether the current road is a fork or an intersection.

[0115] Optionally, the electronic device may detect whether the current road is a fork or an intersection based on the road information of the current road sent by the navigation map device.

[0116] Optionally, the electronic device may also receive a road image corresponding to the current road sent by a forward sensing camera, recognize the road image, and detect whether the current road is a fork or an intersection based on the recognition result.

[0117] Step S2022: If the current road is not a fork and is not an intersection, then the road slope corresponding to the current road is obtained.

[0118] If the current road is not a fork and is not an intersection, the electronic device can optionally obtain the road slope corresponding to the current road based on the positioning device. Optionally, the electronic device can also obtain the road slope corresponding to the current road based on the navigation map device.

[0119] Optionally, the electronic device can receive a preset slope threshold input by a user, or a preset slope threshold sent by other devices, or set a preset slope threshold based on attribute information of the vehicle, etc. The embodiment of the present application does not specifically limit the manner in which the electronic device obtains the preset slope threshold.

[0120] Then, the electronic device compares the road slope corresponding to the current road with a preset slope threshold.

[0121] Step S2023, if the road slope is less than the preset slope threshold, obtain the curve radius corresponding to the current road.

[0122] Specifically, if the road slope is less than a preset slope threshold, the electronic device can obtain the curve radius corresponding to the current road based on the positioning device, or obtain the curve radius corresponding to the current road through the navigation map device. The electronic device can also detect the surrounding environment through sensors such as forward sensing laser radar, forward sensing camera, and forward sensing millimeter wave radar, so as to obtain the curve radius corresponding to the current road.

[0123] Optionally, the electronic device may receive a preset turning radius input by a user, or may receive a preset turning radius sent by other devices, or may set a preset turning radius based on attribute information of the vehicle, etc. The embodiment of the present application does not specifically limit the manner in which the electronic device obtains the preset turning radius.

[0124] Then, the electronic device compares the curve radius corresponding to the current road with the preset turning radius.

[0125] Step S2024: If the curve radius is greater than the preset curve radius, it is determined that the current road is a continuous plane section.

[0126] Specifically, if the curve radius is greater than a preset curve radius, the electronic device may determine that the current road is a continuous flat road section.

[0127] Step S203: if the vehicle is on a continuous flat road section, then based on at least two types of sensors, detect whether there is abnormal traffic flow in each vehicle in front of the vehicle within a preset range in front of the vehicle.

[0128] Specifically, the above-mentioned step S203 of “detecting whether there is abnormal traffic flow in each vehicle ahead within a preset range ahead of the vehicle based on at least two types of sensors” may include the following steps:

[0129] Step S2031: If the vehicle is on a continuous flat road section, the current position information and / or current speed information of each front vehicle detected by at least two types of sensors is obtained.

[0130] Specifically, if the vehicle is on a continuous flat road section, the electronic device obtains current position information and / or current speed information of each front vehicle detected by at least two types of sensors.

[0131] Step S2032: Track the current position information and / or current speed information of each front vehicle detected by each sensor.

[0132] Specifically, the electronic device may track the current position information and / or current speed information of each front vehicle detected by each sensor.

[0133] Step S2033, for each vehicle ahead, if the current position information and / or current speed information of the vehicle ahead detected by at least two types of sensors is continuously lost for a period exceeding the disappearance judgment time threshold, the vehicle ahead whose current position information and / or current speed information is continuously lost is determined to be an abnormal vehicle ahead.

[0134] Specifically, for a target front vehicle among the front vehicles, if the current position information and / or current speed information of the target front vehicle detected by a certain sensor is lost, then timing starts from the moment when the current position information and / or current speed information of the target front vehicle is found to be lost; if the current position information and / or current speed information of the target front vehicle is continuously lost for more than a disappearance judgment time threshold, then it is determined that the front vehicle detected by the sensor is an abnormal front vehicle;.

[0135] If there are detection results corresponding to at least two types of sensors, and both indicate that the vehicle ahead is an abnormal vehicle ahead, the electronic device will determine the vehicle ahead as an abnormal vehicle ahead, thereby ensuring the accuracy of determining the abnormal vehicle ahead, avoiding the situation where a single sensor can only provide limited information, such as the number, speed or occupancy of vehicles, but cannot simultaneously obtain multi-dimensional data, such as vehicle type, driver behavior, etc., and avoiding the situation where a single sensor usually can only cover a specific area and has poor effect on monitoring large-scale traffic flows.

[0136] The disappearance judgment time threshold is greater than or equal to 2 sensor detection cycles.

[0137] Step S2034, determining abnormal traffic flow based on each abnormal front vehicle.

[0138] Specifically, the electronic device may determine abnormal traffic flow based on each abnormal front vehicle.

[0139] Step S204: If there is abnormal traffic flow, the vehicle is controlled according to the relationship between the abnormal traffic flow and the vehicle.

[0140] For details about this step, please refer to the above description of step S104, which will not be elaborated here.

[0141] The vehicle driving control method provided in the embodiment of the present application identifies the current road information and detects whether the current road is a fork or an intersection, thereby ensuring the accuracy of the detection result. If the current road is not a fork and not an intersection, the road slope corresponding to the current road is obtained; if the road slope is less than the preset slope threshold, the curve radius corresponding to the current road is obtained; if the curve radius is greater than the preset curve radius, the current road is determined to be a continuous flat section, thereby ensuring the accuracy of the current road being determined to be a continuous flat section.

[0142] If the vehicle is on a continuous flat road section, the current position information and / or current speed information of each vehicle ahead detected by at least two types of sensors is obtained; the current position information and / or current speed information of each vehicle ahead detected by each sensor is tracked; if the current position information and / or current speed information of the vehicle ahead detected by at least two types of sensors is continuously lost for a time period exceeding the disappearance judgment time threshold, the vehicle ahead whose current position information and / or current speed information is continuously lost is determined to be an abnormal vehicle ahead; based on each abnormal vehicle ahead, the abnormal traffic flow is determined, thereby ensuring the accuracy of determining that the vehicle ahead whose current position information and / or current speed information is continuously lost is an abnormal vehicle ahead, and further ensuring the accuracy of the abnormal traffic flow. Therefore, the problem that the traditional traffic flow monitoring system often relies on a single sensor and cannot fully and accurately obtain traffic flow information is solved, resulting in inaccurate judgment of abnormal traffic flow conditions and untimely response.

[0143] In this embodiment, a vehicle driving control method is provided, which can be used in the above-mentioned electronic device. Figure 3 is a flow chart of a vehicle driving control method according to an embodiment of the present invention. Figure 3 As shown, the process includes the following steps:

[0144] Step S301, obtaining current road information corresponding to the current road where the vehicle is located.

[0145] For details about this step, please refer to the above description of step S201, which will not be elaborated here.

[0146] Step S302: Identify the current road information to determine whether the current road is a continuous plane section.

[0147] For details about this step, please refer to the above description of step S202, which will not be elaborated here.

[0148] Step S303: If the vehicle is on a continuous flat road section, then based on at least two types of sensors, detect whether there is abnormal traffic flow in each vehicle in front of the vehicle within a preset range in front of the vehicle.

[0149] Specifically, the above step S303 may include the following steps:

[0150] Step S3031: If the vehicle is on a continuous flat road section, the current road information is identified to determine the current lane width.

[0151] The current road information may include lane line information. Exemplarily, the electronic device may obtain a road image corresponding to the current road based on a forward sensing camera, and then recognize the road image to determine the lane line information in the road image.

[0152] Specifically, if the vehicle is on a continuous flat road section, the electronic device can identify the lane line information in the current road information, determine the distance between two adjacent lane lines, and thus determine the distance between the two adjacent lane lines as the current lane width.

[0153] Step S3032, obtaining the driving tracks of each front vehicle detected by at least two types of sensors.

[0154] Optionally, the electronic device can obtain the position information and speed information corresponding to each front vehicle based on the forward sensing laser radar, and then generate the driving trajectory of each front vehicle based on the position information and speed information corresponding to each front vehicle.

[0155] Optionally, the electronic device can obtain the corresponding vehicle image of each front vehicle based on the forward sensing camera, identify each front vehicle image based on the image recognition algorithm, and provide the position, size and movement trajectory of each front vehicle, thereby determining the corresponding driving trajectory of each front vehicle.

[0156] Optionally, the electronic device can obtain the position information and speed information corresponding to each front vehicle based on the forward sensing millimeter wave radar, and then generate the driving trajectory of each front vehicle based on the position information and speed information corresponding to each front vehicle.

[0157] Step S3033: for each front vehicle, the driving trajectory detected by each sensor is compared with the corresponding lane trajectory in the target lane where the front vehicle was located before a preset time.

[0158] Specifically, for each front vehicle, the electronic device can also determine the target lane where each front vehicle was located before the preset time length according to the driving track of each front vehicle detected by each sensor. The preset time length can be 0.3s, 0.2s, or 0.1s, and the embodiment of the present application does not specifically limit the preset time length.

[0159] Then, the electronic device determines the lane trajectory corresponding to the target lane, and compares the driving trajectory detected by each sensor with the corresponding lane trajectory in the target lane.

[0160] Step S3034: If the lateral deviation between the driving trajectory of the front vehicle detected by at least two types of sensors and the lane trajectory is greater than the current lane width, the front vehicle is determined as an abnormal front vehicle.

[0161] Specifically, if there is a lateral deviation between the driving trajectory of the front vehicle and the lane trajectory detected by at least two types of sensors that is greater than the current lane width, the electronic device will determine the front vehicle whose driving trajectory has a lateral deviation between the driving trajectory and the lane trajectory that is greater than the current lane width as an abnormal front vehicle.

[0162] Step S3035, determining abnormal traffic flow based on each abnormal front vehicle.

[0163] Specifically, each abnormal front vehicle constitutes an abnormal traffic flow, so the electronic device determines the abnormal traffic flow based on each abnormal front vehicle.

[0164] Step S304: If there is abnormal traffic flow, the vehicle is controlled according to the relationship between the abnormal traffic flow and the vehicle.

[0165] For details about this step, please refer to the above description of step S204, which will not be elaborated here.

[0166] The vehicle driving control method provided in the embodiment of the present application identifies the current road information, determines the current lane width, and ensures the accuracy of the determined current lane width. The driving trajectory of each front vehicle detected by at least two types of sensors is obtained; for each front vehicle, the driving trajectory detected by each sensor is compared with the corresponding lane trajectory in the target lane where the front vehicle was located before a preset time, to ensure the accuracy of the comparison result. If there is a lateral deviation between the driving trajectory of the front vehicle detected by at least two types of sensors and the lane trajectory that is greater than the current lane width, the front vehicle is determined as an abnormal front vehicle; based on each abnormal front vehicle, an abnormal traffic flow is determined. The accuracy of the determined abnormal traffic flow is guaranteed. Therefore, it solves the problem that the traditional traffic flow monitoring system often relies on a single sensor and cannot fully and accurately obtain traffic flow information, resulting in inaccurate judgment of abnormal traffic flow conditions and untimely response.

[0167] In this embodiment, a vehicle driving control method is provided, which can be used in the above-mentioned electronic device. Figure 4 is a flow chart of a vehicle driving control method according to an embodiment of the present invention. Figure 4 As shown, the process includes the following steps:

[0168] Step S401, obtaining current road information corresponding to the current road where the vehicle is located.

[0169] For details about this step, please refer to the above description of step S301, which will not be elaborated here.

[0170] Step S402: Identify the current road information to determine whether the current road is a continuous plane section.

[0171] For details about this step, please refer to the above description of step S302, which will not be repeated here.

[0172] Step S403: If the vehicle is on a continuous flat road section, then based on at least two types of sensors, detect whether there is abnormal traffic flow in each vehicle in front of the vehicle within a preset range in front of the vehicle.

[0173] Specifically, the above step S403 may include the following steps:

[0174] Step S4031, if the vehicle is on a continuous flat road section, then detect whether the future driving section of each front vehicle within a future preset time period meets the preset conditions.

[0175] In an optional implementation manner of the present application, the above step S4031 may include the following steps:

[0176] Step a1, obtaining the driving track and current position information corresponding to each front vehicle detected by at least two types of sensors.

[0177] Optionally, the electronic device can obtain the position information and speed information corresponding to each front vehicle based on the forward sensing laser radar, and then generate the driving trajectory of each front vehicle based on the position information and speed information corresponding to each front vehicle, thereby obtaining the driving trajectory and current position information corresponding to each front vehicle.

[0178] Optionally, the electronic device can obtain the corresponding vehicle image of each front vehicle based on the forward sensing camera, identify each front vehicle image based on the image recognition algorithm, and provide the position, size and movement trajectory of each front vehicle, thereby determining the corresponding driving trajectory and current position information of each front vehicle.

[0179] Optionally, the electronic device can obtain the position information and speed information corresponding to each front vehicle based on the forward sensing millimeter wave radar, and then determine the driving trajectory and current position information corresponding to each front vehicle based on the position information and speed information corresponding to each front vehicle.

[0180] Step a2, predicting the future position information of each front vehicle within a preset time period in the future according to the driving trajectory and current position information corresponding to each front vehicle.

[0181] Specifically, the electronic device can input the driving trajectory and current position information corresponding to each front vehicle into the prediction model, and the prediction model extracts features from the driving trajectory and current position information corresponding to each front vehicle, and outputs the future position information of the front vehicle within a preset time period in the future.

[0182] Among them, the prediction model can be a linear regression model (such as ARIMA, SARIMA, etc.), or a machine learning model (such as random forest, support vector machine, neural network, etc.), or a deep learning model (such as recurrent neural network RNN, long short-term memory network LSTM, gated recurrent unit GRU, etc.). The embodiment of the present application does not specifically limit the prediction model.

[0183] It should be noted that the prediction model is obtained by training with historical data and adjusting the model parameters.

[0184] Step a3, for each vehicle ahead, determine the future driving section based on the future position information.

[0185] Specifically, for each front vehicle, the electronic device may determine the future driving section corresponding to each front vehicle according to the future position information corresponding to each front vehicle.

[0186] Step a4, identifying the future driving section and detecting whether the future driving section is a continuous plane section.

[0187] Specifically, the electronic device determines the section position corresponding to the future driving section based on the navigation map device, whether it is an intersection, roundabout, fork section, confluence, curve radius, uphill / downhill and other information of the future driving section.

[0188] Specifically, the electronic device can identify the future driving section information, and if it is determined that the future driving section is not a fork and is not an intersection, and the road slope is less than a preset slope threshold, and the curve radius is greater than a preset curve radius, then the future driving section is determined to be a continuous flat section. Otherwise, it is determined that the future driving section is not a continuous flat section.

[0189] Step a5: If the future driving section is a continuous plane section, the road length of the future driving section is obtained.

[0190] Specifically, if the future driving section is a continuous plane section, the electronic device obtains the road length of the future driving section based on the navigation map device.

[0191] Then, the electronic device compares the road length of the future driving section with a preset road length threshold, wherein the preset road length threshold may be 50 m, 45 m, or 55 m, and the embodiment of the present application does not specifically limit the preset road length threshold.

[0192] Step a6: If the road length is less than or equal to the preset road length threshold, it is determined that the future driving section of each front vehicle within the future preset time period meets the preset condition.

[0193] Specifically, if the road length is less than or equal to a preset road length threshold, the electronic device determines that the future driving section of each front vehicle within a future preset time period meets the preset condition.

[0194] In another optional implementation of the present application, the driving tracks and current position information corresponding to each front vehicle detected by at least two types of sensors are obtained. Based on the driving tracks and current position information corresponding to each front vehicle, the future position information of each front vehicle in a future preset time period is predicted. For each front vehicle, the future driving section is determined based on the future position information. The future driving section is identified to detect whether the future driving section is a continuous flat section. If the future driving section is a continuous flat section, it is determined that the future driving section of each front vehicle in the future preset time period meets the preset conditions.

[0195] Step S4032: If the future driving section of each front vehicle within the future preset time period meets the preset conditions, the current speed of each front vehicle transmitted by at least two types of sensors is obtained.

[0196] Specifically, if the future driving section of each front vehicle within a future preset time period meets a preset condition, the electronic device can obtain the current vehicle speed of each front vehicle transmitted by at least two types of sensors.

[0197] Exemplarily, the electronic device may receive the current speed of each vehicle ahead transmitted by at least two types of sensors including a forward-perceiving lidar, a forward-perceiving camera, and a forward-perceiving millimeter-wave radar.

[0198] Step S4033, for each front vehicle, compare the current speed of the front vehicle detected by each sensor with the current speed of the adjacent vehicle corresponding to the front vehicle to obtain the speed difference between the current vehicle corresponding to each sensor and the adjacent vehicle.

[0199] For each front vehicle, the electronic device can determine the adjacent vehicle corresponding to each front vehicle according to the current position information of each front vehicle.

[0200] The electronic device may compare the current speed of the front vehicle detected by each sensor with the current speed of an adjacent vehicle corresponding to the front vehicle.

[0201] That is, the current speed of the vehicle in front of this lane is compared with the current speed of the vehicles in front of the adjacent left and right lanes, the current speed of the vehicle in front of the left lane is compared with the current speed of the vehicle in front of the left-left lane, and the current speed of the vehicle in front of the right lane is compared with the current speed of the vehicle in front of the right-right lane.

[0202] In addition, the electronic device calculates a speed difference between a current vehicle speed of the leading vehicle and a current vehicle speed of an adjacent vehicle corresponding to the leading vehicle.

[0203] Step S4034: for each front vehicle, determine whether there is abnormal traffic flow among the front vehicles by obtaining the speed difference between the front vehicle and the adjacent vehicles according to the detection of each sensor.

[0204] Specifically, the above step S4034 may include the following steps:

[0205] Step b1, for each vehicle ahead, comparing the speed difference detected by each sensor with a preset speed difference.

[0206] Specifically, the electronic device can receive the preset speed difference value input by the user, and can receive the preset speed difference value sent by other devices. The electronic device can also set the preset speed difference value according to the current speed of the vehicle. The higher the current speed of the vehicle, the greater the preset speed difference value.

[0207] Exemplarily, the preset speed difference may be calculated according to the following formula:

[0208] The preset speed difference = Max [the maximum speed difference between the speed limits of adjacent lanes on this road section in the road traffic rules, the set speed threshold], where the set speed threshold can be 30km / h or 34km / h. The embodiment of the present application does not specifically limit the set speed threshold.

[0209] Then, the electronic device compares the speed difference between the front vehicle and the adjacent vehicle detected by each sensor with the preset speed difference.

[0210] Step b2: if there are at least two sensors whose speed difference is greater than a preset speed difference, and the speed difference is greater than the preset speed difference for a duration greater than a preset duration, the front vehicle is determined as an abnormal front vehicle;

[0211] Specifically, if there are at least two sensors whose speed difference detected is greater than the preset speed difference, the electronic device counts from the moment when the speed difference is greater than the preset speed difference to obtain the duration of time that the speed difference is greater than the preset speed difference. Then the duration of time that the speed difference is greater than the preset speed difference is compared with the preset duration. If the duration of time that the speed difference is greater than the preset speed difference is greater than the preset duration, the electronic device determines the front vehicle, whose speed difference with the adjacent vehicle is greater than the preset speed difference and whose duration of time that the speed difference is greater than the preset speed difference is greater than the preset duration, as an abnormal front vehicle.

[0212] The preset time length may be 2 sensor detection cycles, or 3 sensor detection cycles. The embodiment of the present application does not specifically limit the preset time length.

[0213] Step b3, determining abnormal traffic flow based on each abnormal front vehicle.

[0214] Specifically, each abnormal front vehicle constitutes an abnormal traffic flow, so the electronic device determines the abnormal traffic flow based on each abnormal front vehicle.

[0215] Step S404: If there is abnormal traffic flow, the vehicle is controlled according to the relationship between the abnormal traffic flow and the vehicle.

[0216] Specifically, the above step S404 may include the following steps:

[0217] Step S4041, obtaining current abnormal position information corresponding to each abnormal front vehicle in each abnormal traffic flow.

[0218] Specifically, after the electronic device determines the abnormal traffic flow, it can obtain the current abnormal position information corresponding to each abnormal front vehicle in each abnormal traffic flow based on at least two types of sensors.

[0219] Step S4042: According to each current abnormal position information, determine the target abnormal front vehicle closest to the vehicle from among the abnormal front vehicles.

[0220] Specifically, the electronic device may compare the current abnormal position information of each abnormal front vehicle, and determine the target abnormal front vehicle closest to the vehicle from among the abnormal front vehicles.

[0221] Step S4043, obtaining the longitudinal distance between the target abnormal front vehicle and the vehicle.

[0222] Specifically, the electronic device may calculate the longitudinal distance between the target abnormal front vehicle and the vehicle according to the current position information of the vehicle and the current abnormal position information of the target abnormal front vehicle.

[0223] Step S4044, divide the longitudinal distance by the current vehicle speed corresponding to the vehicle to obtain the longitudinal time distance between the vehicle and the target abnormal front vehicle.

[0224] Specifically, the electronic device may divide the longitudinal distance by the current vehicle speed corresponding to the own vehicle to obtain the longitudinal time distance between the own vehicle and the target abnormal front vehicle.

[0225] Step S4045, controlling the vehicle according to the longitudinal time distance.

[0226] Specifically, the above step S3045 may include the following steps:

[0227] Step c1, comparing the longitudinal time interval with the preset alarm time interval.

[0228] Among them, the preset alarm interval is calculated based on the current vehicle speed corresponding to the vehicle, the minimum deceleration value of the vehicle for risk avoidance, the shortest time required for the continuous alarm to trigger the driver's response, and the driver's takeover reaction time threshold.

[0229] Specifically, the electronic device can calculate the preset alarm time interval according to the following formula:

[0230] Preset alarm interval = V 本车当前车速 / a 本车避险最小减速度值 +The minimum duration of continuous alarm required to trigger driver response+The driver's response time threshold for taking over.

[0231] The shortest time for a driver to react and the threshold for the driver to take over the processing reaction time can be input into the electronic device by the user according to relevant information, or sent to the electronic device by other devices, or determined according to multiple experimental data. The implementation of this application does not specifically limit the shortest time for a driver to react and the threshold for the driver to take over the processing reaction time.

[0232] Specifically, the electronic device compares the longitudinal time interval with a preset alarm time interval.

[0233] Step c2: if the longitudinal time distance is less than the preset alarm time distance, the vehicle is controlled to output the current state information and current abnormal position information of the target abnormal front vehicle, and output alarm prompt information to the driver.

[0234] Specifically, if the longitudinal time interval is less than the preset alarm time interval, the electronic device can control the vehicle to output the current state information and current abnormal position information of the target abnormal front vehicle, and output alarm prompt information to the driver.

[0235] Among them, the current state information of the target abnormal front vehicle may include information such as the current speed, current heading angle, and current posture of the target abnormal front vehicle.

[0236] Step c3, comparing the longitudinal time interval with the preset emergency avoidance time interval.

[0237] Among them, the preset emergency avoidance time interval is calculated based on the current vehicle speed corresponding to the vehicle, the minimum deceleration value of the vehicle for avoidance, and the tolerance threshold from the issuance of the driving control signal to the realization of control; the preset emergency avoidance time interval is less than the preset alarm time interval.

[0238] Exemplarily, the electronic device may calculate the preset emergency avoidance time interval according to the following formula:

[0239] Preset emergency avoidance time interval = V 本车当前车速 / a 本车避险最小减速度值 + The driving control signal is issued to the tolerance threshold to achieve control.

[0240] The tolerance threshold from when the driving control signal is sent to when the control is achieved is used to characterize the tolerance threshold from when the electronic device sends the driving control signal to when the vehicle achieves control according to the driving control signal. The tolerance threshold from when the driving control signal is sent to when the control is achieved can be input by the user into the electronic device based on relevant information, or can be sent to the electronic device by other devices, or can be determined based on multiple experimental data. The present application does not specifically limit the tolerance threshold from when the driving control signal is sent to when the control is achieved.

[0241] Specifically, after comparing the longitudinal time interval with the preset alarm time interval and outputting the alarm prompt information, the electronic device also needs to continue to compare the longitudinal time interval with the preset emergency avoidance time interval.

[0242] Step c4: If the longitudinal time distance is less than the preset emergency avoidance time distance, the vehicle is controlled to slow down and stop.

[0243] Specifically, if the longitudinal time distance is less than the preset emergency avoidance time distance, the electronic device can send an emergency avoidance deceleration and parking signal to the driving control module through the vehicle bus. After receiving the current state information and current position information of the target traffic flow abnormal flow calculated by the electronic device, the alarm module sends an auditory, visual and tactile alarm to the driver.

[0244] The driving control module, after receiving the driving control signal for emergency avoidance deceleration and stopping received by the vehicle bus, calculates the deceleration value and steering wheel steering angle value required for the vehicle to avoid danger according to the driving control strategy for intelligent driving emergency collision avoidance, and realizes the deceleration and stopping of the vehicle through the driving actuator.

[0245] For example, Figure 5 The figure shows the structure of the vehicle. The vehicle is equipped with a forward sensing laser radar, a forward sensing camera, a forward sensing millimeter wave radar, a navigation map device, and a combined positioning device consisting of GNSS+RTK+IMU+wheel speed sensor.

[0246] (1) The ECU calculation unit determines the road the vehicle is on. The ECU calculation unit determines the road section the vehicle is on based on the vehicle positioning information provided by the combined positioning module and the road section location information provided by the navigation map module.

[0247] (2) When the road section where the vehicle is located is a continuous flat section, the ECU calculation unit determines whether the traffic flow in front of the vehicle is abnormal, that is, based on at least two types of sensors, it detects whether there is abnormal traffic flow in each vehicle in front of the vehicle within a preset range.

[0248] (3) The ECU calculation unit issues an alarm message indicating that the traffic flow ahead is abnormal. The ECU calculation unit issues a driving control signal to decelerate and stop in front of the vehicle with abnormal traffic flow.

[0249] (4) If, after the ECU calculation unit issues an alarm message, the driving distance T between the vehicle and the nearest vehicle in the abnormal traffic flow ahead is less than the emergency avoidance condition threshold, where T = S the time distance between the vehicle and the vehicle with abnormal speed in the traffic flow / V the vehicle, the emergency avoidance condition threshold = V the vehicle / a the minimum deceleration value of the vehicle for risk avoidance + the tolerance threshold for the driving control signal to be sent to the driving control module to implement control, an emergency avoidance deceleration and stop signal is sent to the driving control module through the vehicle bus.

[0250] (5) After receiving the abnormal traffic flow status information ahead and the position information of the abnormal traffic flow vehicle closest to the vehicle from the ECU computing unit, the alarm module sends an auditory, visual and tactile alarm to the driver.

[0251] (6) The driving control module, after receiving the driving control signal for emergency avoidance deceleration and stopping from the vehicle bus, calculates the deceleration value and steering wheel steering angle value required for the vehicle to avoid danger according to the driving control strategy for intelligent driving emergency collision avoidance, and realizes the deceleration and stopping of the vehicle through the driving actuator.

[0252] The vehicle driving control method provided by the embodiment of the present application obtains the driving trajectory and current position information corresponding to each front vehicle detected by at least two types of sensors; predicts the future position information of each front vehicle in a future preset time period according to the driving trajectory and current position information corresponding to each front vehicle, thereby ensuring the accuracy of the predicted future position information of each front vehicle in a future preset time period. For each front vehicle, the future driving section is determined according to the future position information, thereby ensuring the accuracy of the determined future driving section. The future driving section is identified, and it is detected whether the future driving section is a continuous plane section, thereby ensuring the accuracy of the obtained detection result. If the future driving section is a continuous plane section, the road length of the future driving section is obtained. If the road length is less than or equal to the preset road length threshold, it is determined that the future driving section of each front vehicle in the future preset time period meets the preset conditions. It is ensured that the future driving section of each front vehicle in the future preset time period meets the accuracy of the preset conditions.

[0253] If the future driving section of each front vehicle in the future preset time period meets the preset conditions, the current speed of each front vehicle transmitted by at least two types of sensors is obtained, so that the current speed of each front vehicle can be obtained from multiple directions. For each front vehicle, the current speed of the front vehicle detected by each sensor is compared with the current speed of the adjacent vehicle corresponding to the front vehicle, and the speed difference between the current vehicle corresponding to each sensor and the adjacent vehicle is obtained, which ensures the accuracy of the speed difference between the current vehicle corresponding to each sensor and the adjacent vehicle. For each front vehicle, the speed difference detected by each sensor is compared with the preset speed difference; if there are at least two speed differences detected by sensors that are greater than the preset speed difference, and the speed difference is greater than the preset speed difference for a duration greater than the preset duration, the front vehicle is determined as an abnormal front vehicle; based on each abnormal front vehicle, the abnormal traffic flow is determined. The accuracy of the determined abnormal traffic flow is guaranteed. Therefore, the problem that the traditional traffic flow monitoring system often relies on a single sensor and cannot fully and accurately obtain traffic flow information, resulting in inaccurate judgment of abnormal traffic flow conditions and untimely response is solved.

[0254] Then, the current abnormal position information corresponding to each abnormal front vehicle in each abnormal traffic flow is obtained; according to each current abnormal position information, the target abnormal front vehicle closest to the vehicle is determined from each abnormal front vehicle, thereby ensuring the accuracy of the determined target abnormal front vehicle. The longitudinal distance between the target abnormal front vehicle and the vehicle is obtained; the longitudinal distance is divided by the current vehicle speed corresponding to the vehicle to obtain the longitudinal time distance of the vehicle equivalent to the target abnormal front vehicle, thereby ensuring the accuracy of the calculated longitudinal time distance. The longitudinal time distance is compared with the preset alarm time distance; if the longitudinal time distance is less than the preset alarm time distance, the vehicle is controlled to output the current state information and current abnormal position information of the target abnormal front vehicle, and the alarm prompt information is output to the driver, thereby ensuring the accuracy of the output of the current state information and current abnormal position information of the target abnormal front vehicle, and the accuracy of the output of the alarm prompt information to the driver. The longitudinal time distance is compared with the preset emergency avoidance time distance; if the longitudinal time distance is less than the preset emergency avoidance time distance, the vehicle is controlled to slow down and stop, thereby ensuring the accuracy of controlling the vehicle to slow down and stop, thereby ensuring the driving safety of the vehicle.

[0255] In this embodiment, a vehicle driving control device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0256] This embodiment provides a vehicle driving control device, such as Figure 6 As shown, including:

[0257] The acquisition module 501 is used to acquire the current road information corresponding to the current road where the vehicle is located;

[0258] The determination module 502 is used to identify the current road information and determine whether the current road is a continuous plane section; the abnormal traffic flow is composed of at least two abnormal front vehicles in abnormal state among the front vehicles;

[0259] A detection module 503 is used to detect whether there is abnormal traffic flow in each front vehicle within a preset range in front of the vehicle based on at least two types of sensors if the vehicle is on a continuous flat road section;

[0260] The control module 504 is used to control the vehicle according to the relationship between the abnormal traffic flow and the vehicle if there is abnormal traffic flow.

[0261] In some optional embodiments, the above-mentioned determination module 502 is specifically used to identify the current road information and detect whether the current road is a fork or an intersection; if the current road is not a fork and not an intersection, the road slope corresponding to the current road is obtained; if the road slope is less than a preset slope threshold, the curve radius corresponding to the current road is obtained; if the curve radius is greater than the preset curve radius, it is determined that the current road is a continuous plane section.

[0262] In some optional embodiments, the above-mentioned detection module 503 is specifically used to obtain the current position information and / or current speed information of each front vehicle detected by at least two types of sensors; track the current position information and / or current speed information of each front vehicle detected by each sensor; for each front vehicle, if there is a front vehicle whose current position information and / or current speed information detected by at least two types of sensors is continuously lost for more than a disappearance judgment time threshold, then determine that the front vehicle whose current position information and / or current speed information is continuously lost is an abnormal front vehicle; based on each abnormal front vehicle, determine abnormal traffic flow.

[0263] In some optional embodiments, the above-mentioned detection module 503 is specifically used to identify current road information and determine the current lane width; obtain the driving trajectory of each front vehicle detected by at least two types of sensors; for each front vehicle, compare the driving trajectory detected by each sensor with the corresponding lane trajectory in the target lane where the front vehicle was located a preset time ago; if there is a lateral deviation between the driving trajectory of the front vehicle detected by at least two types of sensors and the lane trajectory that is greater than the current lane width, the front vehicle is determined as an abnormal front vehicle; based on each abnormal front vehicle, determine abnormal traffic flow.

[0264] In some optional embodiments, the above-mentioned detection module 503 is specifically used to detect whether the future driving section of each front vehicle within a preset time period in the future meets the preset conditions; if the future driving section of each front vehicle within the preset time period in the future meets the preset conditions, then the current speed of each front vehicle transmitted by at least two types of sensors is obtained; for each front vehicle, the current speed of the front vehicle detected by each sensor is compared with the current speed of the adjacent vehicle corresponding to the front vehicle to obtain the speed difference between the current vehicle corresponding to each sensor and the adjacent vehicle; for each front vehicle, according to the speed difference between the front vehicle and the adjacent vehicle detected by each sensor, it is judged whether there is abnormal traffic flow in the front vehicle.

[0265] In some optional embodiments, the above-mentioned detection module 503 is specifically used to compare the speed difference detected by each sensor with the preset speed difference for each front vehicle; if there are at least two speed difference values ​​detected by sensors that are greater than the preset speed difference value, and the speed difference value is greater than the preset speed difference value for a duration greater than the preset duration, the front vehicle is determined as an abnormal front vehicle; based on each abnormal front vehicle, abnormal traffic flow is determined.

[0266] In some optional embodiments, the detection module 503 is specifically used to obtain the driving trajectory and current position information corresponding to each front vehicle detected by at least two types of sensors; predict the future position information of each front vehicle within a preset time period in the future based on the driving trajectory and current position information corresponding to each front vehicle; determine the future driving section for each front vehicle based on the future position information; identify the future driving section and detect whether the future driving section is a continuous plane section; if the future driving section is a continuous plane section, obtain the road length of the future driving section; if the road length is less than or equal to the preset road length threshold, determine that the future driving section of each front vehicle within the preset time period in the future meets the preset conditions.

[0267] In some optional embodiments, the above-mentioned control module 504 is specifically used to obtain the current abnormal position information corresponding to each abnormal front vehicle in each abnormal traffic flow; determine the target abnormal front vehicle closest to the vehicle from each abnormal front vehicle based on the current abnormal position information; obtain the longitudinal distance between the target abnormal front vehicle and the vehicle; divide the longitudinal distance by the current vehicle speed corresponding to the vehicle to obtain the longitudinal time distance between the vehicle and the target abnormal front vehicle; and control the vehicle based on the longitudinal time distance.

[0268] In some optional implementations, the control module 504 is specifically used to compare the longitudinal time interval with a preset alarm time interval; the preset alarm time interval is calculated based on the current vehicle speed corresponding to the vehicle, the minimum deceleration value of the vehicle for risk avoidance, the shortest time required for the driver to react and the driver's takeover reaction time threshold;

[0269] If the longitudinal time distance is less than the preset alarm time distance, the vehicle is controlled to output the current state information and current abnormal position information of the target abnormal front vehicle, and output alarm prompt information to the driver; the longitudinal time distance is compared with the preset emergency avoidance time distance; the preset emergency avoidance time distance is calculated based on the current vehicle speed corresponding to the vehicle, the minimum deceleration value of the vehicle for avoidance, and the tolerance threshold from the driving control signal to the control realization; the preset emergency avoidance time distance is less than the preset alarm time distance;

[0270] If the longitudinal time distance is less than the preset emergency avoidance time distance, the vehicle will be controlled to slow down and stop.

[0271] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0272] The vehicle driving control device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0273] The embodiment of the present invention also provides an electronic device having the above Figure 6 The vehicle travel control device shown.

[0274] See also Figure 7 , Figure 7 is a schematic diagram of the structure of an electronic device provided by an optional embodiment of the present invention, such as Figure 7 As shown, the electronic device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the electronic device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple electronic devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 7 A processor 10 is taken as an example.

[0275] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0276] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0277] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0278] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0279] The electronic device further comprises a communication interface 30 for the electronic device to communicate with other devices or a communication network.

[0280] The embodiment of the present application also provides a vehicle, including an electronic device, a vehicle body, and at least two types of sensors. Specifically, the vehicle may include at least two types of sensors such as a forward sensing laser radar, a forward sensing camera, a forward sensing millimeter wave radar, a navigation map device, and a combined positioning device composed of a GNSS+RTK+IMU+wheel speed sensor. The electronic device is used to execute the vehicle driving control method of any of the above embodiments.

[0281] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0282] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0283] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A vehicle driving control method, characterized in that: The method comprises: Obtain the current road information corresponding to the current road where the vehicle is located; Identifying the current road information to determine whether the current road is a continuous plane section; If the vehicle is on the continuous flat road section, detecting whether there is an abnormal traffic flow among the front vehicles within a preset range in front of the vehicle based on at least two types of sensors; the abnormal traffic flow is composed of at least two abnormal front vehicles in abnormal state among the front vehicles; If there is an abnormal traffic flow, the vehicle is controlled according to the relationship between the abnormal traffic flow and the vehicle.

2. The method according to claim 1, characterized in that The identifying the current road information and determining whether the current road is a continuous plane section includes: Identify the current road information and detect whether the current road is a fork or an intersection; If the current road is not a fork and is not an intersection, then obtaining the road slope corresponding to the current road; If the road slope is less than a preset slope threshold, obtaining a curve radius corresponding to the current road; If the curve radius is greater than the preset curve radius, the current road is determined to be the continuous plane section.

3. The method according to claim 1, characterized in that The detecting whether there is abnormal traffic flow in each vehicle ahead within a preset range ahead of the vehicle based on at least two types of sensors includes: Acquire current position information and / or current speed information of each of the front vehicles detected by at least two types of sensors; Tracking the current position information and / or the current speed information of each of the front vehicles detected by each of the sensors; For each of the front vehicles, if the current position information and / or the current speed information of the front vehicle detected by at least two types of sensors is continuously lost for a time period exceeding a disappearance judgment time threshold, the front vehicle whose current position information and / or the current speed information is continuously lost is determined to be the abnormal front vehicle; The abnormal traffic flow is determined based on each of the abnormal front vehicles.

4. The method according to claim 1, characterized in that: The detecting whether there is abnormal traffic flow in each vehicle ahead within a preset range ahead of the vehicle based on at least two types of sensors includes: Identifying the current road information and determining the current lane width; Acquire the driving track of each of the front vehicles detected by at least two types of sensors; For each of the front vehicles, comparing the driving trajectory detected by each of the sensors with a corresponding lane trajectory in the target lane where the front vehicle was located a preset time ago; If the lateral deviation between the driving trajectory of the front vehicle and the lane trajectory detected by at least two types of sensors is greater than the current lane width, the front vehicle is determined as the abnormal front vehicle; The abnormal traffic flow is determined based on each of the abnormal front vehicles.

5. The method according to claim 1, characterized in that The detecting whether there is abnormal traffic flow in each vehicle ahead within a preset range ahead of the vehicle based on at least two types of sensors includes: Detecting whether the future driving section of each of the front vehicles within a future preset time period meets the preset conditions; If the future driving section of each of the front vehicles within the future preset time period meets the preset condition, obtaining the current speed of each of the front vehicles transmitted by at least two types of sensors; For each of the front vehicles, the current speed of the front vehicle detected by each of the sensors is compared with the current speed of the adjacent vehicle corresponding to the front vehicle to obtain the speed difference between the current vehicle corresponding to each of the sensors and the adjacent vehicle; For each of the front vehicles, a speed difference between the front vehicle and the adjacent vehicle is obtained according to detection by each of the sensors, and it is determined whether there is abnormal traffic flow in the front vehicle.

6. The method according to claim 5, characterized in that For each of the front vehicles, determining whether there is an abnormal traffic flow in the front vehicle based on the speed difference between the front vehicle and the adjacent vehicle detected by each sensor, includes: For each of the front vehicles, comparing the speed difference value detected by each of the sensors with a preset speed difference value; If the speed difference detected by at least two sensors is greater than the preset speed difference, and the duration of the speed difference being greater than the preset speed difference is greater than the preset duration, the front vehicle is determined as the abnormal front vehicle; The abnormal traffic flow is determined based on each of the abnormal front vehicles.

7. The method according to claim 5, characterized in that The detecting whether the future travel section of each of the front vehicles within the future preset time period meets the preset conditions includes: Acquire the driving track and current position information corresponding to each of the front vehicles detected by at least two types of sensors; Predicting the future position information of each of the front vehicles within the future preset time period according to the driving trajectory and the current position information corresponding to each of the front vehicles; For each of the front vehicles, determining the future driving section according to the future position information; Identifying the future driving section and detecting whether the future driving section is a continuous plane section; If the future driving section is a continuous plane section, obtaining the road length of the future driving section; If the road length is less than or equal to a preset road length threshold, it is determined that the future driving section of each of the leading vehicles within the future preset time period meets the preset condition.

8. The method according to claim 1, characterized in that If there is an abnormal traffic flow, the vehicle is controlled according to the relationship between the abnormal traffic flow and the vehicle, including: Acquire current abnormal position information corresponding to each abnormal front vehicle in each abnormal traffic flow; According to each of the current abnormal position information, determining a target abnormal front vehicle closest to the host vehicle from among the abnormal front vehicles; Obtaining the longitudinal distance between the target abnormal front vehicle and the host vehicle; The longitudinal distance is divided by the current vehicle speed corresponding to the host vehicle to obtain the longitudinal time distance between the host vehicle and the target abnormal front vehicle; The host vehicle is controlled according to the longitudinal time distance.

9. The method according to claim 8, characterized in that The controlling the vehicle according to the longitudinal time distance includes: The longitudinal time interval is compared with a preset alarm time interval; the preset alarm time interval is calculated based on the current vehicle speed corresponding to the vehicle, the minimum deceleration value of the vehicle for risk avoidance, the shortest time required for the driver to react and the driver's takeover reaction time threshold; If the longitudinal time distance is less than the preset alarm time distance, the vehicle is controlled to output the current state information of the target abnormal front vehicle and the current abnormal position information, and output alarm prompt information to the driver; The longitudinal time distance is compared with a preset emergency avoidance time distance; the preset emergency avoidance time distance is calculated according to the current vehicle speed corresponding to the vehicle, the minimum deceleration value of the vehicle for avoiding danger, and the tolerance threshold from the issuance of the driving control signal to the realization of control; the preset emergency avoidance time distance is less than the preset warning time distance; If the longitudinal time distance is less than the preset emergency avoidance time distance, the vehicle is controlled to decelerate and stop.

10. A vehicle driving control device, characterized in that: The device comprises: An acquisition module is used to obtain current road information corresponding to the current road where the vehicle is located; A determination module, used to identify the current road information and determine whether the current road is a continuous plane section; a detection module, configured to detect, if the vehicle is on the continuous flat road section, whether there is an abnormal traffic flow among the front vehicles within a preset range in front of the vehicle based on at least two types of sensors; the abnormal traffic flow is composed of at least two abnormal front vehicles in abnormal state among the front vehicles; The control module is used to control the vehicle according to the relationship between the abnormal traffic flow and the vehicle if there is an abnormal traffic flow.

11. An electronic device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the vehicle driving control method according to any one of claims 1 to 9 by executing the computer instructions.

12. A vehicle, characterized in that: The vehicle comprises an electronic device, a vehicle body and at least two types of sensors, and the electronic device is used to execute the vehicle driving control method according to any one of claims 1 to 9.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the vehicle driving control method according to any one of claims 1 to 9.

14. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the vehicle driving control method according to any one of claims 1 to 9.

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