Detection method and related device

Abstract

The invention discloses a detection method and a related device, and relates to the field of intelligent driving, and the method comprises the steps: obtaining the current static time and the lane of a to-be-recognized obstacle vehicle, and the static movement time information of the obstacle vehicle of the adjacent lane of the to-be-recognized obstacle vehicle, generating an initial time threshold value according to the lane, and obtaining a target time threshold value based on the static moving time information and the initial time threshold value, and determining whether the obstacle vehicle to be identified is a target obstacle vehicle according to the target time threshold value and the current static time. According to the invention, the appropriate target time threshold is obtained based on the real environment where the to-be-identified obstacle vehicle is located, and the accuracy and timeliness of identifying the target obstacle vehicle are improved.

Description

Technical Field

[0001] This application relates to the field of intelligent driving technology, and in particular to a detection method and related device. Background Technology

[0002] During vehicle operation, situations that disrupt traffic are frequently encountered. For example, a disabled vehicle stopped in the road due to a malfunction can impede the movement of other vehicles, or a vehicle may stop in the road for various reasons, affecting traffic. In autonomous driving technologies, such obstructive vehicles affecting the driver's movement are called "dead cars," and the identification of "dead cars" is particularly important. When using autonomous driving functions, if a "dead car" is not identified, the vehicle may remain stationary behind it. If it is incorrectly identified as a "dead car," the vehicle may frequently change lanes or detour, resulting in a poor user experience. Therefore, how to identify "dead cars" has become an urgent problem to be solved. Summary of the Invention

[0003] In view of the above problems, this application provides a detection method and related device to achieve the purpose of timely and accurate detection of "dead vehicles" that affect the driving of the vehicle. The specific solution is as follows:

[0004] The first aspect of this application provides a detection method, comprising:

[0005] Obtain the current stationary time and lane of the vehicle to be identified, as well as the stationary movement time information of the vehicles in the adjacent lanes of the vehicle to be identified;

[0006] An initial time threshold is generated based on the lane in which the vehicle is located;

[0007] Based on the stationary movement time information and the initial time threshold, the target time threshold is obtained;

[0008] Based on the target time threshold and the current stationary time, determine whether the vehicle to be identified as the target obstacle vehicle.

[0009] Optionally, if there are multiple obstructing vehicles in adjacent lanes, a target time threshold is obtained based on the stationary movement time information and the initial time threshold, including:

[0010] The system iterates through multiple adjacent lane obstacle vehicles in sequence. For the currently traversed adjacent lane obstacle vehicle, the first intermediate time threshold is updated based on the stationary movement time information of the currently traversed adjacent lane obstacle vehicle to obtain the second intermediate time threshold. The first intermediate time threshold when traversing the first adjacent lane obstacle vehicle is the initial time threshold, the first intermediate time threshold when traversing non-first adjacent lane obstacle vehicles is the second intermediate time threshold obtained in the previous traversal, and the second intermediate time threshold obtained when traversing the last adjacent lane obstacle vehicle is the target time threshold.

[0011] Optionally, the first intermediate time threshold is updated based on the stationary movement time information of the currently traversed adjacent lane obstacle vehicles to obtain a second intermediate time threshold, including:

[0012] If the currently visited adjacent lane obstacle vehicle is stationary, then the first time threshold adjustment parameter is determined based on the current stationary time of the currently visited adjacent lane obstacle vehicle.

[0013] If the currently visited adjacent lane obstacle is not stationary, the first time threshold adjustment parameter is determined based on the last stationary time and last moving time of the currently visited adjacent lane obstacle.

[0014] The first intermediate time threshold is updated based on the first time threshold adjustment parameter to obtain the second intermediate time threshold.

[0015] Optionally, based on a target time threshold and the current stationary time, determine whether the vehicle to be identified as the target obstacle vehicle, including:

[0016] Calculate the ratio of the current standstill time to the target time threshold;

[0017] If the ratio is greater than the preset ratio threshold, the vehicle to be identified as the target obstacle vehicle is determined.

[0018] If the ratio is less than or equal to the preset ratio threshold, then the vehicle to be identified as the obstacle is determined not to be the target obstacle vehicle.

[0019] Optionally, before determining whether the vehicle to be identified as an obstacle is the target obstacle vehicle based on the target time threshold and the current stationary time, the method further includes:

[0020] If the lane where the obstacle to be identified is located is the rightmost lane in a multi-lane road or a single lane, the second time threshold adjustment parameter is determined based on the relative position of the obstacle to be identified to the center line of the lane where the obstacle to be identified is located and whether the obstacle to be identified has illuminated at least one of the following:

[0021] The target time threshold is updated based on the second time threshold adjustment parameter, and the updated time threshold is used as the target time threshold.

[0022] Optionally, before determining whether the vehicle to be identified as an obstacle is the target obstacle vehicle based on the target time threshold and the current stationary time, the method further includes:

[0023] Obtain the first orientation angle of the obstacle vehicle to be identified and the second orientation angle of the lane in which the obstacle vehicle is located;

[0024] Calculate the difference in orientation angle between the first orientation angle and the second orientation angle;

[0025] Determine the third time threshold adjustment parameter corresponding to the orientation angle difference;

[0026] The target time threshold is updated based on the third time threshold adjustment parameter, and the updated time threshold is used as the target time threshold.

[0027] Optionally, before determining whether the vehicle to be identified as an obstacle is the target obstacle vehicle based on the target time threshold and the current stationary time, the method further includes:

[0028] If the headlights of the vehicle to be identified are already on, the fourth time threshold adjustment parameter is determined based on whether the on lights are brake lights or hazard lights.

[0029] The target time threshold is updated based on the fourth time threshold adjustment parameter, and the updated time threshold is used as the target time threshold.

[0030] Optionally, before determining whether the vehicle to be identified as an obstacle is the target obstacle vehicle based on the target time threshold and the current stationary time, the method further includes:

[0031] Determine whether the first condition is met. The first condition is that there is an intersection within the first distance threshold range in front of the lane where the obstacle vehicle to be identified is located, and there is a traffic light signal at the intersection.

[0032] If so, then determine whether the traffic light signal is red;

[0033] If so, then determine the fifth time threshold adjustment parameter;

[0034] The target time threshold is updated based on the fifth time threshold adjustment parameter, and the updated time threshold is used as the target time threshold.

[0035] Optionally, before determining whether the vehicle to be identified as an obstacle is the target obstacle vehicle based on the target time threshold and the current stationary time, the method further includes:

[0036] Determine whether there is a first vehicle. The first vehicle refers to a vehicle located in the lane where the obstacle to be identified is located and whose distance from the obstacle to be identified is less than a preset second distance threshold.

[0037] If there is only a first vehicle behind the vehicle to be identified as an obstacle, then it is determined whether the first condition is met. The first condition is that the following distance of the first vehicle is less than the preset third distance threshold.

[0038] If there is no first vehicle or the first condition is met, then under the condition that the lane where the obstacle vehicle to be identified is located is a single lane, it is determined whether the second condition is met. The second condition is that the distance between the obstacle vehicle to be identified and the nearest stop line in front is greater than a preset fourth distance threshold.

[0039] If the second condition is met, the sixth time threshold adjustment parameter is determined based on at least one of the following: whether the obstacle vehicle to be identified is a preset large vehicle, whether the distance between the obstacle vehicle to be identified and the vehicle itself is less than a preset fifth distance threshold, and whether other vehicles between the obstacle vehicle to be identified and the vehicle itself are braking.

[0040] The target time threshold is updated based on the sixth time threshold adjustment parameter, and the updated time threshold is used as the target time threshold.

[0041] A second aspect of this application provides a detection device, comprising:

[0042] The basic information acquisition unit is used to acquire the current stationary time and lane of the obstacle vehicle to be identified, as well as the stationary movement time information of the obstacle vehicles in the adjacent lanes of the obstacle vehicle to be identified.

[0043] The initial time threshold generation unit is used to generate an initial time threshold based on the lane in which the vehicle is located.

[0044] The target time threshold determination unit is used to obtain the target time threshold based on stationary movement time information and the initial time threshold;

[0045] The target obstacle vehicle determination unit is used to determine whether the obstacle vehicle to be identified is the target obstacle vehicle based on the target time threshold and the current stationary time.

[0046] A third aspect of this application provides a computer program product including computer-readable instructions that, when executed on an electronic device, cause the electronic device to perform the detection method as described above.

[0047] A fourth aspect of this application provides an electronic device including at least one processor and a memory connected to the processor, wherein:

[0048] Memory is used to store computer programs;

[0049] The processor is used to execute computer programs to enable electronic devices to perform detection methods as described above.

[0050] The fifth aspect of this application provides a computer storage medium carrying one or more computer programs, which, when executed by an electronic device, enable the electronic device to perform the detection method as described above.

[0051] As can be seen from the above technical solutions, the detection method provided in this application takes into account that the stationary time of a vehicle during normal parking is often related to its lane. For example, in most scenarios, the waiting time in the right-turn lane (such as the time spent waiting for traffic lights or waiting for vehicles ahead) is shorter than the waiting time in the straight lane. Therefore, this application obtains the current stationary time and lane of the obstacle vehicle to be identified and generates an initial time threshold based on the lane. Furthermore, considering that the stationary time of obstacles in adjacent lanes of the obstacle vehicle to be identified may affect the stationary time of the obstacle vehicle to be identified, for example, if there is a disabled vehicle that has been stationary for a long time in the adjacent lane, the presence of the disabled vehicle may cause the waiting time of the obstacle vehicle to be identified to increase. Therefore, the initial time threshold is adjusted based on the stationary and movement time information of obstacles in adjacent lanes of the obstacle vehicle to be identified, which can improve the accuracy of the target time threshold and thus improve the accuracy of identifying the target obstacle vehicle.

[0052] Meanwhile, the target time threshold is a dynamically adjustable time threshold based on the lane where the obstacle vehicle to be identified is located, the current stationary time, and the stationary movement time of the obstacle vehicle in the adjacent lane. Therefore, the target time threshold is more in line with the current environment of the obstacle vehicle to be identified, and there will be no problem of the target time threshold being set too high or too low. The appropriate target time threshold also improves the timeliness of the determination of the target obstacle vehicle. Attached Figure Description

[0053] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0054] Figure 1 A schematic diagram of a system architecture is provided for this application;

[0055] Figure 2 A schematic diagram of an optional hardware structure for a terminal 100 provided in this application;

[0056] Figure 3 This application provides a schematic diagram of the structure of a server 200;

[0057] Figure 4 A schematic flowchart of a detection method provided in an embodiment of this application;

[0058] Figure 5 This is a schematic diagram of the structure of a detection device provided in an embodiment of this application;

[0059] Figure 6This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0060] The embodiments of this application are described below with reference to the accompanying drawings. The terminology used in the implementation section of this application is for explaining specific embodiments only and is not intended to limit the scope of this application.

[0061] The embodiments of this application will now be described with reference to the accompanying drawings. Those skilled in the art will recognize that, with technological advancements and the emergence of new scenarios, the technical solutions provided in the embodiments of this application are equally applicable to similar technical problems.

[0062] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms are interchangeable where appropriate; this is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of elements is not necessarily limited to those elements, but may include other elements not explicitly listed or inherent to those processes, methods, products, or apparatuses.

[0063] This application can be applied to the field of intelligent driving technology. The following is an explanation using a specific application scenario.

[0064] During the operation of an autonomous vehicle, it may encounter an obstacle vehicle (referred to as a "dead vehicle" in this application) that affects its driving due to prolonged stationary status and the possibility of remaining stationary for a period of time. Continuously stopping and waiting for a dead vehicle will affect the traffic efficiency of the autonomous vehicle. Therefore, it is necessary to detect dead vehicles in front of the autonomous vehicle in a timely manner and detour around them during the operation.

[0065] Currently, the above application scenario is merely an example of this application and is not intended to limit the application scenario of this application.

[0066] After carefully studying relevant application scenarios, the inventors of this case conceived in the initial stage of the idea that a fixed time threshold could be set, and the stationary time of a disabled vehicle in front of the vehicle could be detected in real time. If the detected stationary time exceeded the fixed time threshold, the disabled vehicle in front of the vehicle would be judged as a "dead vehicle." This initial solution could identify dead vehicles to a certain extent and improve the traffic efficiency of the vehicle to some extent. However, the following problems still exist: First, it is prone to misidentification. For example, vehicles queuing at the stop line at an intersection may be misjudged as dead vehicles, vehicles temporarily parked may be misjudged as dead vehicles, and disabled vehicles may not be judged as dead vehicles. This reduces both traffic efficiency and the safety of the vehicle. Second, if the fixed time threshold is too large, there will be a problem of untimely determination of dead vehicles. That is, due to an inappropriate fixed time threshold setting, it may take a long time to determine whether a vehicle in front of the vehicle is a dead vehicle, which greatly reduces traffic efficiency.

[0067] To address the aforementioned issues, the inventors conducted further in-depth research and ultimately proposed a detection method and related apparatus, which will be described in detail below.

[0068] See Figure 1 , Figure 1 A schematic diagram of a system architecture is shown. The system may include a terminal 100 and a server 200. The server 200 may include one or more servers (…). Figure 1 (The example includes a server), and the server 200 can provide the detection method provided in the embodiments of this application to one or more terminals.

[0069] The terminal 100 may have a third-party system application installed on it. The application and webpage can provide an interface. The terminal 100 can receive relevant parameters input by the user on the interface and send the parameters to the server 200. The server 200 can obtain the processing result based on the received parameters and return the processing result to the terminal 100.

[0070] It should be understood that in some optional implementations, the terminal 100 can also complete the action of obtaining the processing result based on the received parameters on its own, without the need for the server to cooperate. This application embodiment is not limited to this.

[0071] The following description Figure 1 The product form of the mid-terminal 100;

[0072] The terminal 100 in this application embodiment can be a mobile phone, tablet computer, wearable device, vehicle device, augmented reality (AR) / virtual reality (VR) device, laptop computer, ultra-mobile personal computer (UMPC), netbook, personal digital assistant (PDA), electronic control unit (ECU), microcontroller unit (MCU), etc., and this application embodiment does not impose any restrictions on it.

[0073] Figure 2 A schematic diagram of an optional hardware structure for terminal 100 is shown.

[0074] refer to Figure 2 As shown, the terminal 100 may include a radio frequency unit 110, a memory 120, an input unit 130, a display unit 140, a camera 150 (optional), an audio circuit 160 (optional), a speaker 161 (optional), a microphone 162 (optional), a headphone jack 163 (optional), a processor 170, an external interface 180, a power supply 190, and other components. Those skilled in the art will understand that... Figure 2 These are merely examples of terminals or multi-functional devices and do not constitute a limitation on terminals or multi-functional devices. They may include more or fewer components than shown in the illustration, or combine certain components, or use different components.

[0075] The input unit 130 can be used to receive input numerical or character information, and to generate key signal inputs related to user settings and function control of the portable multi-functional device. Specifically, the input unit 130 may include a touchscreen 131 (optional) and / or other input devices 132. The touchscreen 131 can collect touch operations performed by the user on or near it (such as operations performed by the user using fingers, knuckles, styluses, or any suitable object on or near the touchscreen), and drive the corresponding connection devices according to a pre-set program. The touchscreen can detect the user's touch actions, convert the touch actions into touch signals and send them to the processor 170, and can receive and execute commands sent by the processor 170; the touch signal includes at least touch point coordinate information. The touchscreen 131 can provide an input interface and an output interface between the terminal 100 and the user. In addition, various types of touchscreens, such as resistive, capacitive, infrared, and surface acoustic wave, can be used to implement the touchscreen. Besides the touchscreen 131, the input unit 130 may also include other input devices. Specifically, other input devices 132 may include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, joystick, etc.

[0076] Among them, the input device 132 can receive input data, etc.

[0077] The display unit 140 can be used to display information input by the user or information provided to the user, various menus of the terminal 100, interactive interfaces, file display, and / or playback of any multimedia file.

[0078] The memory 120 can be used to store instructions and data. The memory 120 may primarily include an instruction storage area and a data storage area. The data storage area can store various types of data, such as multimedia files and text. The instruction storage area can store software units such as operating systems, applications, and instructions required for at least one function, or subsets or extended sets thereof. It may also include non-volatile random access memory. It provides the processor 170 with hardware, software, and data resources for managing the computing device, supporting control software and applications. It is also used for storing multimedia files, as well as storing running programs and applications.

[0079] The processor 170 is the control center of the terminal 100. It connects various parts of the terminal 100 via various interfaces and lines. By running or executing instructions stored in the memory 120 and calling data stored in the memory 120, it performs various functions and processes data of the terminal 100, thereby controlling the terminal device as a whole. Optionally, the processor 170 may include one or more processing units; preferably, the processor 170 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 170. In some embodiments, the processor and memory can be implemented on a single chip; in some embodiments, they can also be implemented separately on independent chips. The processor 170 can also be used to generate corresponding operation control signals, send them to the corresponding components of the computing processing device, read and process data in the software, especially read and process data and programs in the memory 120, so that the various functional modules therein perform corresponding functions, thereby controlling the corresponding components to act according to the instructions.

[0080] The memory 120 can be used to store software code related to the detection method, and the processor 170 can execute the steps of the detection method and can also schedule other units (such as the input unit 130 and the display unit 140 mentioned above) to achieve the corresponding functions.

[0081] The radio frequency unit 110 (optional) can be used for receiving and transmitting signals during information transmission or calls. For example, it can receive downlink information from the base station and process it for the processor 170; additionally, it can transmit uplink data to the base station. Typically, the RF circuit includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low-noise amplifier (LNA), a duplexer, etc. Furthermore, the radio frequency unit 110 can also communicate wirelessly with network devices and other devices. This wireless communication can use any communication standard or protocol, including but not limited to Global System for Mobile Communication (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), email, Short Messaging Service (SMS), etc.

[0082] In this embodiment of the application, the radio frequency unit 110 can send data to the server 200 and receive the processing results sent by the server 200.

[0083] It should be understood that the radio frequency unit 110 is optional and can be replaced with other communication interfaces, such as a network port.

[0084] The terminal 100 also includes a power supply 190 (such as a battery) that supplies power to various components. Preferably, the power supply can be logically connected to the processor 170 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system.

[0085] Terminal 100 also includes an external interface 180, which can be a standard Micro USB interface or a multi-pin connector, which can be used to connect terminal 100 to other devices for communication or to connect a charger to charge terminal 100.

[0086] Although not shown, terminal 100 may also include a flash, a Wireless Fidelity (WiFi) module, a Bluetooth module, sensors with various functions, etc., which will not be described in detail here. Some or all of the methods described below can be applied to, for example... Figure 2 In the terminal 100 shown.

[0087] The following description Figure 1 The product form of the mid-range server 200;

[0088] Figure 3 A structural diagram of a server 200 is provided, as follows: Figure 3 As shown, server 200 includes bus 201, processor 202, communication interface 203, and memory 204. Processor 202, memory 204, and communication interface 203 communicate with each other via bus 201.

[0089] Bus 201 can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0090] The processor 202 can be any one or more of the following processors: a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor (MP), or a digital signal processor (DSP).

[0091] Memory 204 may include volatile memory, such as random access memory (RAM). Memory 204 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0092] The memory 204 can be used to store software code related to the detection method, and the processor 202 can execute the steps of the chip's detection method, and can also schedule other units to achieve corresponding functions.

[0093] It should be understood that the aforementioned terminal 100 and server 200 can be centralized or distributed devices. The processors (e.g., processor 170 and processor 202) in the aforementioned terminal 100 and server 200 can be hardware circuits (such as application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), general-purpose processors, DSPs, microprocessors, or microcontrollers, etc.) or combinations of these hardware circuits. For example, the processor can be a hardware system with instruction execution capabilities, such as a CPU or DSP, or a hardware system without instruction execution capabilities, such as an ASIC or FPGA, or a combination of the aforementioned hardware systems without instruction execution capabilities and hardware systems with instruction execution capabilities.

[0094] This application provides a detection method, which is applied to... Figure 1 Taking the computer device in the figure above as an example, the computer device can specifically be the terminal 100 in the figure above, or a system composed of terminal 100 and server 200. The detection method of the embodiment of this application will be described in detail below with reference to the accompanying drawings.

[0095] Reference Figure 4 , Figure 4 This is a flowchart illustrating a detection method provided in an embodiment of this application. The method includes:

[0096] Step S401: Obtain the current stationary time and lane of the obstacle vehicle to be identified, as well as the stationary movement time information of the obstacle vehicles in the adjacent lanes of the obstacle vehicle to be identified.

[0097] Here, the obstacle to be identified can be a vehicle-type obstacle relative to the vehicle itself; that is, for the vehicle itself, the obstacle to be identified can be an obstacle that affects the vehicle's passage. In this embodiment of the application, the obstacle to be identified is in a stationary state, and the detection method provided in this application can be used to determine whether the obstacle to be identified is a dead vehicle (i.e., a vehicle that cannot move for a period of time in the future).

[0098] This application embodiment can detect stationary obstacle vehicles around the vehicle in real time. Optionally, the obstacle vehicles to be identified include stationary obstacle vehicles detected at the current moment, as well as stationary obstacle vehicles detected at historical moments before the current moment, but do not include obstacle vehicles that have been identified as dead vehicles or moving obstacle vehicles.

[0099] Under normal circumstances, only vehicles in front of the vehicle will affect its passage. Therefore, the vehicle to be identified can be any vehicle within a preset range in front of the vehicle.

[0100] It is worth noting that the vehicle to be identified as an obstacle and the vehicle itself are not necessarily in the same lane.

[0101] The current stationary time of the obstacle vehicle to be identified refers to the time elapsed from the moment the obstacle vehicle stopped most recently until the current moment.

[0102] The aforementioned adjacent lane obstacle vehicle refers to an obstacle located in the adjacent lane (i.e., the side lane, more specifically, the left and right lanes adjacent to the lane where the obstacle vehicle is located) of the obstacle vehicle to be identified. In other words, for the obstacle vehicle to be identified, the adjacent lane obstacle vehicle is an obstacle vehicle that affects the passage of the obstacle vehicle to be identified.

[0103] Step S402: Generate an initial time threshold based on the lane in which the lane is located.

[0104] Considering that the stationary time of a vehicle when it is normally parked is often related to its lane, for example, in most scenarios, the waiting time in the right-turn lane (such as the time spent waiting for traffic lights or waiting for the vehicle in front to move) is shorter than the waiting time in the straight lane, it is necessary to generate an initial time threshold that matches the lane where the obstacle to be identified is located, based on the lane where the obstacle to be identified is located.

[0105] The vehicle to be identified as an obstacle can travel on a single-lane road or a multi-lane road, meaning the road where the vehicle is located includes at least one lane. In this embodiment, if the road where the vehicle is located includes multiple lanes, then at least some of the lanes have different initial time thresholds for matching.

[0106] For example, if the lane where the obstacle vehicle to be identified is located is a single lane, the initial time threshold is 30 seconds; if the lane where the obstacle vehicle to be identified is located is the leftmost lane in a multi-lane road, the initial time threshold is 70 seconds; if the lane where the obstacle vehicle to be identified is located is the rightmost lane in a multi-lane road, the initial time threshold is 6 seconds; and if the lane where the obstacle vehicle to be identified is located is the middle lane in a multi-lane road, the initial time threshold is 30 seconds.

[0107] Step S403: Based on the stationary movement time information and the initial time threshold, obtain the target time threshold.

[0108] Considering that the stationary time of vehicles in adjacent lanes of the vehicle to be identified may affect the stationary time of the vehicle to be identified, for example, if there is a disabled vehicle (or obstacle) that cannot move for a long time in the adjacent lane of the vehicle to be identified, the presence of the disabled vehicle may cause the waiting time of the vehicle to be identified to be longer. Therefore, the initial time threshold is adjusted according to the stationary movement time information of the vehicles in adjacent lanes of the vehicle to be identified, and the adjusted target time threshold is obtained.

[0109] It should be noted that there may be no obstacle vehicle in the adjacent lane of the lane where the obstacle vehicle to be identified is located, that is, there is no obstacle vehicle in the adjacent lane of the obstacle vehicle to be identified. In this case, the stationary movement time information of the obstacle vehicle in the adjacent lane of the obstacle vehicle to be identified obtained in step S401 is empty. At this time, the initial time threshold can be directly determined as the target time threshold.

[0110] It should also be noted that for each obstacle vehicle to be identified, there may be multiple obstacle vehicles in adjacent lanes. Therefore, the process of "obtaining the target time threshold based on the stationary movement time information and the initial time threshold" may include: sequentially traversing multiple obstacle vehicles in adjacent lanes; for the obstacle vehicle currently traversed during the traversal, updating the first intermediate time threshold based on the stationary movement time information of the currently traversed obstacle vehicle to obtain the second intermediate time threshold; wherein, if it is the first obstacle vehicle in the adjacent lane during the traversal, the first intermediate time threshold is equal to the initial time threshold; if it is not the first obstacle vehicle in the adjacent lane during the traversal, the first intermediate time threshold is equal to the second intermediate time threshold obtained in the previous traversal (that is, assigning the second intermediate time threshold obtained in the previous traversal to the first intermediate time threshold in the current traversal); if it is the last obstacle vehicle in the adjacent lane during the traversal, the second intermediate time threshold is the target time threshold.

[0111] For example, for a vehicle to be identified as an obstacle, there are three adjacent lane obstacles: vehicle 1, vehicle 2, and vehicle 3. The initial time threshold can be updated based on the stationary movement time information of vehicle 1 to obtain intermediate time threshold 1. The intermediate time threshold 1 can be updated based on the stationary movement time information of vehicle 2 to obtain intermediate time threshold 2. The intermediate time threshold 2 can be updated based on the stationary movement time information of vehicle 3 to obtain the target time threshold.

[0112] Optionally, the process of "updating the first intermediate time threshold based on the stationary movement time information of the currently traversed adjacent lane obstacle vehicle to obtain the second intermediate time threshold" may include: if the currently traversed adjacent lane obstacle vehicle is stationary, then determine the first time threshold adjustment parameter based on the current stationary time of the currently traversed adjacent lane obstacle vehicle; if the currently traversed adjacent lane obstacle vehicle is not stationary, then determine the first time threshold adjustment parameter based on the previous stationary time and previous movement time of the currently traversed adjacent lane obstacle vehicle; and update the first intermediate time threshold based on the first time threshold adjustment parameter to obtain the second intermediate time threshold.

[0113] Here, the current stationary time of the adjacent lane obstacle vehicle refers to the time elapsed from the moment the adjacent lane obstacle vehicle stopped (i.e., the current stationary time) until the current moment; the previous stationary time of the adjacent lane obstacle vehicle refers to the stationary time of the adjacent lane obstacle vehicle during the previous stationary time before the current stationary time; and the previous movement time of the adjacent lane obstacle vehicle refers to the stationary time of the adjacent lane obstacle vehicle during the previous movement time before the current stationary time. For example, as time progresses, there are times t0, t1, t2, t3, and t4, where t4 is the current time, t3 is the closest time to t4 before t4, t2 is the closest time to t3 before t3, t1 is the closest time to t2 before t2, and t0 is the closest time to t1 before t1. The obstacle vehicle in the adjacent lane is in a moving state from time t0 to t1, in a stationary state from time t1 to t2, in a moving state from time t2 to t3, and in a stationary state from time t3 to t4. Then, the current stationary time refers to the total duration from t3 to t4, the previous stationary time refers to the total duration from t1 to t2, and the previous moving time refers to the total duration from t2 to t3.

[0114] That is, if the currently visited adjacent lane obstacle vehicle is currently stationary, then the stationary movement time information of the currently visited adjacent lane obstacle vehicle includes the current stationary time. A first time threshold adjustment parameter can be obtained based on this current stationary time, and the first intermediate time threshold can be updated according to the first time threshold adjustment parameter to obtain a second intermediate time threshold. Here, the current stationary time refers to the duration for which the currently visited adjacent lane obstacle vehicle is currently stationary.

[0115] Optionally, the process of "obtaining the first time threshold adjustment parameter based on the current stop time" can be implemented by the following formula: factor1 = stop_time / C, where factor1 represents the first time threshold adjustment parameter, stop_time represents the current stop time of the obstacle vehicle in the adjacent lane that is currently being traversed, and C is a constant whose specific value can be determined according to the actual application scenario; in one possible implementation, C = 10.0.

[0116] If the currently visited adjacent lane obstacle vehicle is currently in a non-stationary state (i.e., moving), then the stationary-movement time information of the currently visited adjacent lane obstacle vehicle includes the last stationary time and the last moving time. A first time threshold adjustment parameter can be obtained based on the last stationary time and the last moving time. Then, the first intermediate time threshold is updated according to the first time threshold adjustment parameter to obtain a second intermediate time threshold. Optionally, a time range can be set so that both the last stationary time and the last moving time are within the time range.

[0117] Optionally, the process of “obtaining the first time threshold adjustment parameter based on the last stationary time and the last moving time” includes: if the last stationary time > the last moving time, then factor1 = (last stationary time - last moving time) / last moving time; if the last stationary time ≤ the last moving time, then factor1 = 0.

[0118] Optionally, in both of the above scenarios, the process of "updating the first intermediate time threshold according to the first time threshold adjustment parameter to obtain the second intermediate time threshold" can be implemented by the following formula: middle_time_threshold=[1.0+min(1.0,factor1)]×base_time_threshold, where base_time_threshold represents the first intermediate time threshold and middle_time_threshold represents the second intermediate time threshold.

[0119] The formula “middle_time_threshold=[1.0+min(1.0,factor1)]×base_time_threshold” is explained as follows: First, find the minimum value between 1.0 and factor1. Then, add the minimum value to 1.0. Finally, multiply the sum by base_time_threshold. The product is equal to middle_time_threshold.

[0120] Step S404: Determine whether the obstacle vehicle to be identified is the target obstacle vehicle based on the target time threshold and the current stationary time.

[0121] If a vehicle has been stationary since it stopped at some point before the current time, and may remain stationary for some time to come, it may affect the vehicle's movement. Therefore, it is defined as a target obstacle vehicle, i.e., a dead vehicle.

[0122] In this embodiment, it can be determined whether the obstacle vehicle to be identified is a dead vehicle based on the target time threshold and the current stationary time.

[0123] Optionally, the process of "determining whether the vehicle to be identified as an obstacle is a target obstacle based on a target time threshold and the current stationary time" may include: calculating the ratio of the current stationary time to a target time threshold; if the ratio is greater than a preset ratio threshold, the vehicle to be identified is determined to be a target obstacle; if the ratio is less than or equal to the preset ratio threshold, the vehicle to be identified is determined not to be a target obstacle. Optionally, the preset ratio threshold may be 0.6.

[0124] To enable those skilled in the art to better understand the embodiments of this application, the overall implementation process will be described in detail below through a specific example.

[0125] This embodiment of the application continuously detects stationary obstacle vehicles at various angles in front of the vehicle during its operation. Detected obstacle vehicles are marked as obstacle vehicles to be identified. These obstacle vehicles are continuously tracked during the subsequent operation of the vehicle until they are determined to be target obstacle vehicles (i.e., the vehicle stops moving), or until movement of the obstacle vehicle is detected. Since the stationary obstacle vehicles at various angles in front of the vehicle may differ at different times, this embodiment of the application can detect and mark obstacle vehicles to be identified in real time or periodically (e.g., every 0.5 seconds).

[0126] For each obstacle vehicle marked in the above process, it can be determined whether each obstacle vehicle is a target obstacle vehicle according to the above steps S401 to S404. If the obstacle vehicle is not determined to be a target obstacle vehicle at the current time, the obstacle vehicle will continue to be detected at the next time. If the obstacle vehicle moves at the next time, the tracking ends. If the obstacle vehicle does not move at the next time, the current stationary time and stationary-movement time information in step S401 are updated, and then it is determined whether the obstacle vehicle is a target obstacle vehicle at the next time according to steps S402 to S404, and so on.

[0127] Once a vehicle is identified as a target obstacle, the vehicle can take various measures, such as detouring, to improve traffic efficiency.

[0128] The detection method provided in this application takes into account that the stationary time of a vehicle during normal parking is often related to its lane. For example, in most scenarios, the waiting time in the right-turn lane (such as the time spent waiting for traffic lights or waiting for vehicles ahead) is shorter than the waiting time in the straight lane. Therefore, this application obtains the stationary time and lane of the obstacle vehicle to be identified around the vehicle and generates an initial time threshold based on the lane. Furthermore, considering that the stationary time of obstacles in adjacent lanes of the obstacle vehicle to be identified may affect the stationary time of the obstacle vehicle to be identified, for example, if there is a disabled vehicle that has been stationary for a long time in the adjacent lane, the presence of the disabled vehicle may increase the waiting time of the obstacle vehicle to be identified. Therefore, the initial time threshold is adjusted based on the stationary and movement time information of obstacles in adjacent lanes of the obstacle vehicle to be identified, which can improve the accuracy of the target time threshold, thereby improving the accuracy of identifying the target obstacle vehicle and reducing the problem of misidentifying the target obstacle vehicle.

[0129] Meanwhile, the target time threshold is a dynamically adjustable time threshold based on the lane where the vehicle to be identified is located, the current stationary time, and the stationary movement time of the vehicle in the adjacent lane. Therefore, the target time threshold is more in line with the current environment of the vehicle to be identified, and there will be no problem of the target time threshold being set too high or too low. The appropriate target time threshold also improves the timeliness of the identification of the target vehicle, so that the vehicle can take more timely countermeasures and improve traffic efficiency.

[0130] Based on the above embodiments, the inventors of this case have conducted further research and discovered that, in addition to the influence of the lane where the obstacle vehicle to be identified is located and the obstacle vehicles in adjacent lanes, the target time threshold is also related to the following factors: the relative position information of the obstacle vehicle to be identified and its lane, the relative orientation information of the obstacle vehicle to be identified and its lane, the information of the lights that the obstacle vehicle to be identified has turned on, the traffic light information in front of the obstacle vehicle to be identified, the type of obstacle vehicle to be identified, and the distance between the obstacle vehicle and the vehicle itself. These factors will be introduced one by one below.

[0131] In the first embodiment, the relative position information of the obstacle vehicle to be identified and its lane is provided.

[0132] It should be understood that vehicles typically travel in the middle of their lane or even slightly to the left when driving on the road. If a vehicle is in the rightmost lane and parked slightly to the right of the lane's center line, it is likely that the vehicle needs to be parked for an extended period of time for some reason, such as a vehicle malfunction, waiting for someone, etc. In this case, the probability of the vehicle being considered "dead" is higher. Therefore, the target time threshold can be further adjusted and updated based on the relative position information of the vehicle to be identified and its lane.

[0133] Based on this, in one possible implementation, this embodiment may further include the following steps: if the lane where the obstacle vehicle to be identified is located is the rightmost lane in a multi-lane road or a single lane, then a second time threshold adjustment parameter is determined based on at least one of the relative position of the obstacle vehicle to be identified and the center line of the lane where the obstacle vehicle to be identified is located, and whether the obstacle vehicle to be identified has its brake lights on; the target time threshold is updated according to the second time threshold adjustment parameter, and the updated time threshold is used as the target time threshold.

[0134] Optionally, the process of "determining the second time threshold adjustment parameter based on at least one of the relative positions of the obstacle vehicle to be identified and the center line of the lane where the obstacle vehicle is located, and whether the obstacle vehicle is braking" may include: if the entire body of the obstacle vehicle to be identified is to the right of the center line of the lane where the obstacle vehicle is located, then the second time threshold adjustment parameter factor2 = 0.3; if the leftmost side of the obstacle vehicle to be identified is to the left of the lane center line and the distance from the lane center line is less than a preset value, and the obstacle vehicle to be identified has not illuminated its brake lights, then the second time threshold adjustment parameter factor2 = 0.3; for other scenarios besides the above two cases, The second time threshold adjustment parameter factor2 = 1.4 × min(0.5, a), where a = fabs(left_l) / [fabs(left_l) + fabs(right_l)], fabs represents taking the absolute value, left_l and right_l are both values ​​obtained based on the Frenet coordinate system, left_l refers to the minimum value of each leftmost point of the obstacle vehicle to be identified on the abscissa l of the Frenet coordinate system, and right_l refers to the maximum value of each rightmost point of the obstacle vehicle to be identified on the abscissa l of the Frenet coordinate system.

[0135] The explanation of the formula "factor2=1.4×min(0.5,a)" is as follows: First, find the minimum value between 0.5 and a, then multiply the minimum value by 1.4, and the product value is equal to factor2.

[0136] Optionally, the process of "adjusting the parameters according to the second time threshold to update the target time threshold, and using the updated time threshold as the target time threshold" can be implemented by the following formula: stop_time_threshold = factor2 × stop_time_threshold, where stop_time_threshold represents the target time threshold.

[0137] The formula "stop_time_threshold = factor2 × stop_time_threshold" is explained as follows: Multiplying factor2 by stop_time_threshold results in a product equal to stop_time_threshold. Here, stop_time_threshold multiplied by factor2 represents the target time threshold before the update process of "adjusting the target time threshold according to the second time threshold parameter," which is the value calculated in the previous step. Stop_time_threshold equal to the product represents the updated target time threshold after the update process of "adjusting the target time threshold according to the second time threshold parameter."

[0138] In this embodiment, in addition to considering the relative position information of the obstacle vehicle to be identified and its lane, the factor of whether the obstacle vehicle's brake lights are illuminated is also taken into account. This is because: if the obstacle vehicle brakes and stops in the rightmost lane, the obstacle vehicle itself may not be malfunctioning, and the need to stop is due to some reason attributable to the driver. In this case, the obstacle vehicle may move at any time, and the probability of it stopping for a long time is relatively low. However, if the obstacle vehicle stops in the rightmost lane with its vehicle slightly to the right and its brake lights not illuminated, there is a high probability that the obstacle vehicle has stalled and stopped, and in this case, the probability of the obstacle vehicle stopping for a long time is relatively high. Therefore, an appropriate second time threshold adjustment parameter can be set based on the above probabilities to make the updated target time threshold more accurate.

[0139] In the second embodiment, the relative orientation information of the obstacle vehicle to be identified and its lane is provided.

[0140] Generally, when a vehicle is traveling normally in its lane, the direction in which the vehicle is facing should be the same as or have a very small difference in relative orientation angle with the direction of its lane. If, when the vehicle is stationary, there is a significant difference in orientation angle between the vehicle and its lane, it indicates that the vehicle may have an abnormality requiring a prolonged stop, such as a car accident causing the vehicle's orientation to be inconsistent with its lane. In this case, the probability of the vehicle being stopped is high. Based on this, the target time threshold can be updated based on the relative orientation information of the obstacle vehicle to be identified and its lane.

[0141] In one possible implementation, this embodiment may include the following steps: obtaining a first orientation angle of the obstacle vehicle to be identified and a second orientation angle of the lane where the obstacle vehicle is located; calculating the orientation angle difference between the first and second orientation angles; determining a third time threshold adjustment parameter corresponding to the orientation angle difference; updating a target time threshold according to the third time threshold adjustment parameter, and using the updated time threshold as the target time threshold. Here, the first orientation angle refers to the orientation angle of the front of the obstacle vehicle to be identified. For example, if the obstacle vehicle to be identified is located at 30 degrees north of east, then the first orientation angle is 30 degrees.

[0142] It should be noted that the vehicle to be identified may cross lanes and stop. In this case, the lane where the vehicle to be identified is located can be the lane closest to the center of the vehicle to be identified, or the lane that has the largest area to accommodate the vehicle to be identified.

[0143] Optionally, the second orientation angle of the lane where the obstacle vehicle to be identified is located can be calculated by the curvature of each point on the center line of the lane where the obstacle vehicle to be identified is located.

[0144] Optionally, the process of "determining the third time threshold adjustment parameter corresponding to the orientation angle difference" can be as follows: determine the third time threshold adjustment parameter corresponding to the orientation angle difference from the pre-set mapping relationship between the angle difference and the time threshold adjustment parameter. That is, in this embodiment, a mapping relationship can be generated in advance, and the calculated time threshold adjustment parameter corresponding to the orientation angle difference can be obtained by querying the mapping relationship, which is then used as the third time threshold adjustment parameter.

[0145] Optionally, the process of "updating the target time threshold according to the third time threshold adjustment parameter" mentioned above may include: stop_time_threshold = stop_time_threshold × factor3, where factor3 represents the third time threshold adjustment parameter.

[0146] The formula "stop_time_threshold = stop_time_threshold × factor3" means that multiplying stop_time_threshold by factor3 results in a product equal to stop_time_threshold. Here, the stop_time_threshold multiplied by factor3 represents the target time threshold before the update process of "adjusting the parameter according to the third time threshold to update the target time threshold," while the stop_time_threshold equal to the product represents the target time threshold after the update process of "adjusting the parameter according to the third time threshold to update the target time threshold."

[0147] The third embodiment is to identify the vehicle lights of the obstacle vehicle that have been turned on.

[0148] Consider an application scenario: If the vehicle to be identified as an obstacle illuminates its brake lights while parked, it's likely due to an anomaly ahead requiring it to stop and wait. Once the anomaly is resolved, the vehicle will move again. In this scenario, the probability of the vehicle being stuck is low. However, if the vehicle to be identified as an obstacle illuminates its hazard lights while parked, it may be due to some reason requiring it to remain parked for an extended period. In this scenario, the probability of the vehicle being stuck is higher. Based on this, the target time threshold can be adjusted and updated based on the illuminated lights of the vehicle to be identified.

[0149] Specifically, if the headlights of the vehicle to be identified as an obstacle are already on, the fourth time threshold adjustment parameter is determined based on whether the on-lights are brake lights or hazard lights; the target time threshold is updated based on the fourth time threshold adjustment parameter, and the updated time threshold is used as the target time threshold.

[0150] Optionally, the process of "determining the fourth time threshold adjustment parameter based on whether the illuminated vehicle light is a brake light or a hazard light" may include: if the illuminated vehicle light is a brake light, then the fourth time threshold adjustment parameter factor4 = 5.0; if the illuminated vehicle light is a hazard light, then the fourth time threshold adjustment parameter factor4 = 0.2; if the illuminated vehicle light is neither a brake light nor a hazard light, then the fourth time threshold adjustment parameter factor4 = 1.

[0151] Furthermore, the process of "updating the target time threshold by adjusting the parameters according to the fourth time threshold" includes: stop_time_threshold = stop_time_threshold × factor4.

[0152] The formula "stop_time_threshold = stop_time_threshold × factor4" is explained as follows: Multiplying stop_time_threshold by factor4 results in a product equal to stop_time_threshold. Here, the stop_time_threshold multiplied by factor4 represents the target time threshold before the update process of "adjusting the parameters according to the fourth time threshold to update the target time threshold," while the stop_time_threshold equal to the product represents the target time threshold after the update process of "adjusting the parameters according to the fourth time threshold to update the target time threshold."

[0153] It should be noted that the above-mentioned fourth time threshold adjustment parameter factor4 of 5.0 or 0.2 is only an example and is not intended to limit this application. However, it is necessary to make the fourth time threshold adjustment parameter factor4 greater than 1 when the brake lights are on and less than 1 when the hazard lights are on. In this way, when the brake lights are on, the target time threshold stop_time_threshold can be increased by the fourth time threshold adjustment parameter factor4, thereby reducing the ratio in step S404 and avoiding the situation where the vehicle to be identified is mistakenly identified as a stopped vehicle due to a long braking time. Conversely, when the hazard lights are on, the target time threshold stop_time_threshold can be decreased by the fourth time threshold adjustment parameter factor4, thereby increasing the ratio in step S404, so as to increase the probability of the vehicle to be identified as a stopped vehicle when the hazard lights are on.

[0154] Fourth embodiment: Traffic light information in front of the obstacle vehicle to be identified.

[0155] It is understandable that red light waiting times may vary on different roads, resulting in differences in the stationary time of the obstacle vehicle to be identified when waiting at red lights. Therefore, it is necessary to set appropriate time threshold adjustment parameters based on the red light waiting time to obtain a more accurate target time threshold.

[0156] Specifically, this embodiment may include: determining whether a first condition is met, wherein the first condition is that there is an intersection within a first distance threshold range in front of the lane where the obstacle vehicle to be identified is located and there is a traffic light signal at the intersection; if so, determining whether the traffic light signal is a red light signal; if so, determining a fifth time threshold adjustment parameter; updating the target time threshold according to the fifth time threshold adjustment parameter, and using the updated time threshold as the target time threshold.

[0157] Considering that when the vehicle is too far from the intersection (e.g., greater than a preset distance), it is difficult for the vehicle to detect whether there is a traffic light signal, let alone whether it is a red light signal. This makes it impossible to determine whether the first condition is met or whether the traffic light signal is red. In this case, in order to make a better judgment, the beyond-line-of-sight information provided by the map can be used to view the traffic light signal at the intersection from the road provided by the map and determine whether the traffic light signal is red.

[0158] Optionally, the process of "determining the fifth time threshold adjustment parameter" can set the fifth time threshold adjustment parameter kDefaultRedTrafficLightMultiplier based on the time when the red light signal is on, i.e. the red light waiting time. Then, the process of "updating the target time threshold based on the fifth time threshold adjustment parameter" can include: stop_time_threshold = stop_time_threshold × kDefaultRedTrafficLightMultiplier.

[0159] To better understand the above formula, the formula "stop_time_threshold = stop_time_threshold × kDefaultRedTrafficLightMultiplier" is explained as follows: Multiplying stop_time_threshold by kDefaultRedTrafficLightMultiplier results in a product equal to stop_time_threshold. Here, the stop_time_threshold multiplied by kDefaultRedTrafficLightMultiplier represents the target time threshold before the update process of "adjusting the target time threshold according to the fifth time threshold parameter," while the stop_time_threshold equal to the product represents the target time threshold after the update process of "adjusting the target time threshold according to the fifth time threshold parameter."

[0160] In this embodiment, when the light is red, the fifth time threshold adjustment parameter kDefaultRedTrafficLightMultiplier can be set to 1. This increases the target time threshold stop_time_threshold, thereby reducing the ratio in step S404 and preventing the vehicle to be identified from being mistakenly identified as a stopped vehicle due to a long red light duration.

[0161] The fifth embodiment identifies the type of obstacle vehicle to be identified and its distance from the vehicle.

[0162] To ensure safety, large vehicles (trucks, vans, etc.) should be avoided from being identified as stopped vehicles as much as possible. Similarly, smaller vehicles (cars, motorcycles, etc.) should not be identified as stopped vehicles when they are close to the vehicle. Based on this principle, this embodiment can update the target time threshold based on the type of obstacle vehicle to be identified and its distance from the vehicle.

[0163] Optionally, this embodiment determines whether a first vehicle exists. The first vehicle refers to a vehicle located in the lane where the obstacle to be identified is located and whose distance from the obstacle to be identified is less than a preset second distance threshold. If the first vehicle exists only behind the obstacle to be identified, it is determined whether a first condition is met. The first condition is that the following distance of the first vehicle is less than a preset third distance threshold. If there is no first vehicle or the first condition is met, it is determined whether a second condition is met if the lane where the obstacle to be identified is located is a single lane. The second condition is that the distance between the obstacle to be identified and the nearest stop line is greater than a preset fourth distance threshold. If the second condition is met, a sixth time threshold adjustment parameter is determined based on at least one of the following: whether the obstacle to be identified is a preset large vehicle, whether the distance between the obstacle to be identified and the vehicle is less than a preset fifth distance threshold, and whether other vehicles between the obstacle to be identified and the vehicle are braking. The target time threshold is updated according to the sixth time threshold adjustment parameter, and the updated time threshold is used as the target time threshold.

[0164] In the above process, by judging the first vehicle and the first condition, the positional relationship between the vehicle to be identified and other vehicles in its lane can be obtained. If there is no first vehicle, it means that there are no vehicles within the second distance threshold in front of and behind the obstacle vehicle in its lane. At this time, the obstacle vehicle to be identified is considered to be a single vehicle with no other vehicles in front or behind. If there is only a first vehicle behind the obstacle vehicle to be identified (i.e., there are no vehicles in front of the obstacle vehicle within the second distance threshold), and the following distance of the first vehicle (i.e., the distance to the nearest vehicle in front) is less than the third distance threshold, then the first vehicle and the obstacle vehicle to be identified form a queue structure, and the obstacle vehicle to be identified is the vehicle at the head of the queue.

[0165] When the obstacle to be identified is a single vehicle or the vehicle at the head of the queue, there is a possibility of detouring around the obstacle. However, if the lane where the obstacle is located is a single lane, whether the detouring condition is met needs to be further judged according to the second condition, that is, it is necessary to judge whether the distance between the obstacle and the nearest stop line is greater than the preset fourth distance threshold. Only when it is greater than the preset fourth distance threshold is there a possibility of detouring.

[0166] It should be understood that it is only meaningful to identify the target obstacle vehicle if there is a possibility of detouring around the obstacle vehicle on the road. Therefore, under the condition of satisfying the second condition, this embodiment can determine the sixth time threshold adjustment parameter based on at least one of the following: whether the obstacle vehicle to be identified is a preset large vehicle, whether the distance between the obstacle vehicle to be identified and the vehicle is less than a preset fifth distance threshold, and whether other vehicles between the obstacle vehicle to be identified and the vehicle are braking. Then, the target time threshold is updated according to the sixth time threshold adjustment parameter.

[0167] The aforementioned large vehicles can be custom-defined, meaning that the type of vehicle that can be classified as a large vehicle can be defined by the vehicle itself. For example, the vehicle can be classified as a large vehicle based on experience, its starting acceleration, its overtaking speed, and other information such as the vehicle's length and width.

[0168] Optionally, the process of "updating the target time threshold according to the sixth time threshold adjustment parameter" includes: stop_time_threshold = stop_time_threshold × isolated_w, where isolated_w represents the sixth time threshold adjustment parameter.

[0169] The formula "stop_time_threshold = stop_time_threshold × isolated_w" is explained as follows: Multiplying stop_time_threshold by isolated_w results in a product equal to stop_time_threshold. Here, the stop_time_threshold multiplied by isolated_w represents the target time threshold before the update process of "adjusting the target time threshold according to the sixth time threshold parameter," while the stop_time_threshold equal to the product represents the target time threshold after the update process of "adjusting the target time threshold according to the sixth time threshold parameter."

[0170] Optionally, the process of "determining a sixth time threshold adjustment parameter based on at least one of the following: whether the obstacle vehicle to be identified is a preset large vehicle, whether the distance between the obstacle vehicle to be identified and the vehicle is less than a preset fifth distance threshold, and whether other vehicles between the obstacle vehicle to be identified and the vehicle are braking" may include: the first process and the second process described below.

[0171] First process: If the obstacle vehicle to be identified is a large vehicle, then the sixth time threshold adjustment parameter isolated_w = 0.5; if the obstacle vehicle to be identified is not a large vehicle, and the distance between the obstacle vehicle to be identified and the vehicle itself is less than 50.0 meters, then the sixth time threshold adjustment parameter isolated_w = 0.5; if the obstacle vehicle to be identified is not a large vehicle, and the distance between the obstacle vehicle to be identified and the vehicle itself is greater than or equal to 50.0 meters, then the sixth time threshold adjustment parameter isolated_w = 0.3.

[0172] Specifically, for situations where the distance between a large vehicle or an obstacle to be identified and the vehicle itself is less than 50.0 meters, since bypassing the obstacle to be identified can easily lead to accidents, for safety reasons, the sixth time threshold adjustment parameter isolated_w is set to a larger value. This can increase the target time threshold stop_time_threshold, thereby reducing the ratio in step S404, which reduces the probability that a large vehicle or a small vehicle less than 50.0 meters away from the vehicle will be judged as a dead vehicle, thus improving safety.

[0173] The second process involves updating the sixth time threshold adjustment parameter based on whether other vehicles between the vehicle to be identified and the vehicle itself are braking, resulting in the updated sixth time threshold adjustment parameter. Specifically, if other vehicles between the vehicle to be identified and the vehicle itself have illuminated their brake lights, then isolated_w = isolated_w × 2.0.

[0174] The formula "isolated_w = isolated_w × 2.0" is explained as follows: Multiplying isolated_w by 2.0 yields the product value of isolated_w. Here, isolated_w multiplied by 2.0 refers to the original sixth time threshold adjustment parameter before the update process, which involves updating the sixth time threshold adjustment parameter to obtain the updated sixth time threshold adjustment parameter. The isolated_w equal to the product value refers to the updated sixth time threshold adjustment parameter after the update process, which involves updating the sixth time threshold adjustment parameter to obtain the updated sixth time threshold adjustment parameter.

[0175] When there is an intermediate vehicle between the vehicle to be identified and the vehicle itself, and the intermediate vehicle is braking, the risk of the vehicle going around the vehicle to be identified is high. In this case, the sixth time threshold adjustment parameter isolated_w is increased to reduce the target time threshold, thereby reducing the ratio in step S404. This can reduce the probability that large vehicles or small vehicles less than 50.0 meters away from the vehicle are judged as dead vehicles, thus improving safety.

[0176] It should be noted that some parameters in the above embodiments, such as 50.0 meters, 0.5, and 0.3, are optimal parameter values ​​provided by the inventors after studying actual application scenarios. However, the actual vehicle environment may be complex and variable. Therefore, in practical applications, the parameter values ​​can be adaptively adjusted according to the specific environment of the vehicle, and no limitation is made here.

[0177] The above description provides five factors related to the target time threshold: the relative position of the obstacle vehicle to be identified to its lane, the relative orientation of the obstacle vehicle to be identified to its lane, the illuminated headlights of the obstacle vehicle to be identified, the traffic light information in front of the obstacle vehicle to be identified, the type of the obstacle vehicle to be identified, and the distance to the vehicle. In this embodiment, these five factors can be combined with the initial time threshold or the target time threshold in steps S401 to S404, or at least two, three, four, or all of the five factors can be combined first, and then combined with the initial time threshold or the target time threshold in steps S401 to S404 to form more schemes for identifying the target obstacle vehicle. Specifically, these schemes include the following:

[0178] First, after obtaining the initial time threshold through step S402, the initial time threshold is used as the target time threshold, and the target time threshold is updated using any one of the first, second, third, fourth, and fifth embodiments.

[0179] Second, after obtaining the initial time threshold through step S402, the initial time threshold is used as the target time threshold. The target time threshold is first updated using any one of the first, second, third, fourth, and fifth embodiments, and then the target time threshold is updated a second time using any one of the remaining four unused embodiments.

[0180] Third, after obtaining the initial time threshold through step S402, the initial time threshold is used as the target time threshold. First, the target time threshold is updated for the first time using any one of the first, second, third, fourth, and fifth embodiments. Then, the target time threshold is updated for the second time using any one of the remaining four unused embodiments. Finally, the target time threshold is updated for the third time using any one of the remaining three unused embodiments.

[0181] Fourth, after obtaining the initial time threshold through step S402, the initial time threshold is used as the target time threshold. First, the target time threshold is updated for the first time using any one of the first, second, third, fourth, and fifth embodiments. Then, the target time threshold is updated for the second time using any one of the remaining four unused embodiments. Next, the target time threshold is updated for the third time using any one of the remaining three unused embodiments. Finally, the target time threshold is updated for the fourth time using any one of the remaining two unused embodiments.

[0182] Fifth, after obtaining the initial time threshold through step S402, the initial time threshold is used as the target time threshold. First, the target time threshold is updated for the first time using any one of the first, second, third, fourth, and fifth embodiments. Then, the target time threshold is updated for the second time using any one of the remaining four unused embodiments. Next, the target time threshold is updated for the third time using any one of the remaining three unused embodiments. Then, the target time threshold is updated for the fourth time using any one of the remaining two unused embodiments. Finally, the target time threshold is updated for the fifth time using one of the remaining unused embodiments.

[0183] Sixth, after obtaining the target time threshold through step S404, the target time threshold is updated using any one of the first, second, third, fourth, and fifth embodiments.

[0184] Seventh, after obtaining the target time threshold through step S404, the target time threshold is first updated using any one of the first, second, third, fourth, and fifth embodiments, and then the target time threshold is updated a second time using any one of the remaining four unused embodiments.

[0185] Eighth, after obtaining the target time threshold through step S404, the target time threshold is first updated using any one of the first, second, third, fourth and fifth embodiments, then the target time threshold is updated a second time using any one of the remaining four unused embodiments, and then the target time threshold is updated a third time using any one of the remaining three unused embodiments.

[0186] Ninth, after obtaining the target time threshold through step S404, the target time threshold is first updated using any one of the first, second, third, fourth, and fifth embodiments. Then, the target time threshold is updated a second time using any one of the remaining four unused embodiments. Next, the target time threshold is updated a third time using any one of the remaining three unused embodiments. Finally, the target time threshold is updated a fourth time using any one of the remaining two unused embodiments.

[0187] Tenth, after obtaining the target time threshold through step S404, the target time threshold is first updated using any one of the first, second, third, fourth, and fifth embodiments. Then, the target time threshold is updated a second time using any one of the remaining four unused embodiments. Next, the target time threshold is updated a third time using any one of the remaining three unused embodiments. After that, the target time threshold is updated a fourth time using any one of the remaining two unused embodiments. Finally, the target time threshold is updated a fifth time using one of the remaining unused embodiments.

[0188] In summary, this application can freely combine the factors provided above to obtain a variety of methods for identifying target obstacle vehicles. Each method is based on a more reasonable target time threshold obtained from the real environment of the obstacle vehicle to be identified. Finally, the target obstacle vehicle is judged based on the target time threshold, which improves the timeliness and accuracy of the target obstacle vehicle judgment.

[0189] The above describes a detection method provided by an embodiment of this application. The following describes the apparatus for performing the above detection method.

[0190] Please see Figure 5 , Figure 5 This is a schematic diagram of a detection device provided in an embodiment of this application. Figure 5 As shown, the device includes:

[0191] The basic information acquisition unit 501 is used to acquire the current stationary time and lane of the obstacle vehicle to be identified, as well as the stationary movement time information of the obstacle vehicles in the adjacent lanes of the obstacle vehicle to be identified.

[0192] The initial time threshold generation unit 502 is used to generate an initial time threshold based on the lane in which it is located.

[0193] The target time threshold determination unit 503 is used to obtain the target time threshold based on the stationary movement time information and the initial time threshold;

[0194] The target obstacle vehicle judgment unit 504 is used to determine whether the obstacle vehicle to be identified is a target obstacle vehicle based on the target time threshold and the current stationary time.

[0195] In one possible implementation, when there are multiple adjacent lane obstacle vehicles, the target time threshold determination unit can be specifically used to: sequentially traverse multiple adjacent lane obstacle vehicles; for the currently traversed adjacent lane obstacle vehicle, update the first intermediate time threshold according to the stationary movement time information of the currently traversed adjacent lane obstacle vehicle to obtain a second intermediate time threshold, wherein the first intermediate time threshold when traversing the first adjacent lane obstacle vehicle is the initial time threshold, the first intermediate time threshold when traversing non-first adjacent lane obstacle vehicles is the second intermediate time threshold obtained in the previous traversal, and the second intermediate time threshold obtained when traversing the last adjacent lane obstacle vehicle is the target time threshold.

[0196] In one possible implementation, when there are multiple obstructing vehicles in adjacent lanes, the process of the target time threshold determination unit updating the first intermediate time threshold based on the stationary-movement time information of the currently traversed obstructing vehicles in adjacent lanes to obtain the second intermediate time threshold may include: if the currently traversed obstructing vehicle in adjacent lanes is stationary, then determining the first time threshold adjustment parameter based on the current stationary time of the currently traversed obstructing vehicle in adjacent lanes; if the currently traversed obstructing vehicle in adjacent lanes is not stationary, then determining the first time threshold adjustment parameter based on the previous stationary time and previous movement time of the currently traversed obstructing vehicle in adjacent lanes; updating the first intermediate time threshold based on the first time threshold adjustment parameter to obtain the second intermediate time threshold.

[0197] In one possible implementation, the target obstacle vehicle determination unit can be used to: calculate the ratio of the current stationary time to a target time threshold; if the ratio is greater than a preset ratio threshold, then determine that the obstacle vehicle to be identified is the target obstacle vehicle; if the ratio is less than or equal to the preset ratio threshold, then determine that the obstacle vehicle to be identified is not the target obstacle vehicle.

[0198] In one possible implementation, the detection provided in this application embodiment may further include: a first target time threshold adjustment unit.

[0199] The first target time threshold adjustment unit is used to determine the second time threshold adjustment parameter before the target obstacle vehicle judgment unit determines whether the obstacle vehicle to be identified is the target obstacle vehicle. If the lane where the obstacle vehicle to be identified is located is the rightmost lane in a multi-lane road or a single lane, the second time threshold adjustment parameter is determined based on at least one of the relative position of the obstacle vehicle to be identified and the center line of the lane where the obstacle vehicle to be identified is located and whether the obstacle vehicle to be identified has its brake lights illuminated. The target time threshold is updated based on the second time threshold adjustment parameter, and the updated time threshold is used as the target time threshold.

[0200] In one possible implementation, the detection provided in this application embodiment may further include: a second target time threshold adjustment unit.

[0201] The second target time threshold adjustment unit is used to obtain the first orientation angle of the obstacle to be identified and the second orientation angle of the lane where the obstacle to be identified is located before the target obstacle vehicle judgment unit determines whether the obstacle to be identified is the target obstacle vehicle; calculate the orientation angle difference between the first orientation angle and the second orientation angle; determine the third time threshold adjustment parameter corresponding to the orientation angle difference; update the target time threshold according to the third time threshold adjustment parameter, and use the updated time threshold as the target time threshold.

[0202] In one possible implementation, the detection provided in this application embodiment may further include: a third target time threshold adjustment unit.

[0203] The third target time threshold adjustment unit is used to determine the fourth time threshold adjustment parameter based on whether the headlights of the obstacle to be identified are brake lights or hazard lights before the target obstacle vehicle judgment unit determines whether the obstacle to be identified is the target obstacle vehicle; the target time threshold is updated based on the fourth time threshold adjustment parameter, and the updated time threshold is used as the target time threshold.

[0204] In one possible implementation, the detection provided in this application embodiment may further include: a fourth target time threshold adjustment unit.

[0205] The fourth target time threshold adjustment unit is used to determine whether the first condition is met before the target obstacle vehicle judgment unit determines whether the obstacle vehicle to be identified is the target obstacle vehicle. The first condition is that there is an intersection within a first distance threshold range in front of the lane where the obstacle vehicle to be identified is located and there is a traffic light signal at the intersection. If so, it is determined whether the traffic light signal is a red light signal. If so, the fifth time threshold adjustment parameter is determined. The target time threshold is updated according to the fifth time threshold adjustment parameter, and the updated time threshold is used as the target time threshold.

[0206] In one possible implementation, the detection provided in this application embodiment may further include: a fifth target time threshold adjustment unit.

[0207] The fifth target time threshold adjustment unit is used to determine whether a first vehicle exists before the target obstacle vehicle judgment unit determines whether the obstacle to be identified is a target obstacle vehicle. The first vehicle refers to a vehicle located in the lane where the obstacle to be identified is located and whose distance from the obstacle to be identified is less than a preset second distance threshold. If there is only a first vehicle behind the obstacle to be identified, it is determined whether a first condition is met. The first condition is that the following distance of the first vehicle is less than a preset third distance threshold. If there is no first vehicle or the first condition is met, it is determined whether a second condition is met under the condition that the lane where the obstacle to be identified is located is a single lane. The second condition is that the distance between the obstacle to be identified and the nearest stop line is greater than a preset fourth distance threshold. If the second condition is met, a sixth time threshold adjustment parameter is determined based on at least one of the following: whether the obstacle to be identified is a preset large vehicle, whether the distance between the obstacle to be identified and the vehicle is less than a preset fifth distance threshold, and whether other vehicles between the obstacle to be identified and the vehicle are braking. The target time threshold is updated according to the sixth time threshold adjustment parameter, and the updated time threshold is used as the target time threshold.

[0208] This application also provides an electronic device in its embodiments. (See reference...) Figure 6 The diagram illustrates a structural schematic suitable for implementing the electronic device in the embodiments of this application. The electronic device in the embodiments of this application may include, but is not limited to, fixed terminals such as mobile phones, laptops, PDAs (Personal Digital Assistants), PADs (Portable Application Devices), desktop computers, etc. Figure 6 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0209] like Figure 6 As shown, the electronic device may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory ROM 602 or a program loaded from a storage device 608 into a random access memory RAM 603. When the electronic device is powered on, the RAM 603 also stores various programs and data required for the operation of the electronic device. The processing unit 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0210] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 608 including, for example, memory cards, hard drives, etc.; and communication devices 609. Communication device 609 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have alternatively.

[0211] This application also provides a computer program product including computer-readable instructions, which, when executed on an electronic device, cause the electronic device to implement any of the detection methods provided in this application.

[0212] This application also provides a computer-readable storage medium that carries one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any of the detection methods provided in this application.

[0213] It should also be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the device embodiment drawings provided in this application, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines.

[0214] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, training equipment, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0215] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0216] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, training device, or data center to another website, computer, training device, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line, DSL) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs (Digital Versatile Discs)), or semiconductor media (e.g., solid-state drives (SSDs)).

Claims

1. A method of detection, characterized in that, The method comprises the following steps: acquiring a current static time and a lane where a to-be-identified obstacle vehicle is located, and static moving time information of a neighboring lane obstacle vehicle of the to-be-identified obstacle vehicle; generating an initial time threshold according to the lane where the to-be-identified obstacle vehicle is located; obtaining a target time threshold based on the static moving time information and the initial time threshold; determining whether the to-be-identified obstacle vehicle is a target obstacle vehicle according to the target time threshold and the current static time.

2. The detection method according to claim 1, characterized in that, If there are multiple neighboring lane obstacle vehicles, the obtaining of the target time threshold based on the static moving time information and the initial time threshold comprises: sequentially traversing the multiple neighboring lane obstacle vehicles, and for a currently traversed neighboring lane obstacle vehicle, updating a first intermediate time threshold according to static moving time information of the currently traversed neighboring lane obstacle vehicle to obtain a second intermediate time threshold, wherein the first intermediate time threshold when traversing a first neighboring lane obstacle vehicle is the initial time threshold, the first intermediate time threshold when traversing a neighboring lane obstacle vehicle other than the first neighboring lane obstacle vehicle is a second intermediate time threshold obtained in a previous traversal, and the second intermediate time threshold obtained when traversing a last neighboring lane obstacle vehicle is the target time threshold.

3. The detection method according to claim 2, characterized in that, The updating of the first intermediate time threshold according to the static moving time information of the currently traversed neighboring lane obstacle vehicle to obtain the second intermediate time threshold comprises: if the currently traversed neighboring lane obstacle vehicle is in a static state, determining a first time threshold adjustment parameter according to a current static time of the currently traversed neighboring lane obstacle vehicle; if the currently traversed neighboring lane obstacle vehicle is in a non-static state, determining the first time threshold adjustment parameter according to a last static time and a last moving time of the currently traversed neighboring lane obstacle vehicle; updating the first intermediate time threshold according to the first time threshold adjustment parameter to obtain the second intermediate time threshold.

4. The method of claim 1, wherein The determining of whether the to-be-identified obstacle vehicle is the target obstacle vehicle according to the target time threshold and the current static time comprises: calculating a ratio of the current static time to the target time threshold; if the ratio is greater than a preset ratio threshold, determining that the to-be-identified obstacle vehicle is the target obstacle vehicle; if the ratio is less than or equal to the preset ratio threshold, determining that the to-be-identified obstacle vehicle is not the target obstacle vehicle.

5. The detection method according to claim 1, before the determining of whether the to-be-identified obstacle vehicle is the target obstacle vehicle according to the target time threshold and the current static time, further comprising: if a lane where the to-be-identified obstacle vehicle is located is a rightmost lane in a multi-lane or a single lane, determining a second time threshold adjustment parameter according to at least one of a relative position of the to-be-identified obstacle vehicle to a center line of the lane where the to-be-identified obstacle vehicle is located and whether the to-be-identified obstacle vehicle is lighting a brake light; updating the target time threshold according to the second time threshold adjustment parameter, and the updated time threshold is taken as the target time threshold.

6. The detection method according to claim 5, characterized in that, Before the determining whether the to-be-identified obstacle vehicle is the target obstacle vehicle according to the target time threshold and the current static time, the method further comprises: acquiring a first orientation angle of the to-be-identified obstacle vehicle and a second orientation angle of a lane where the to-be-identified obstacle vehicle is located; calculating an orientation angle difference between the first orientation angle and the second orientation angle; determining a third time threshold adjustment parameter corresponding to the orientation angle difference; updating the target time threshold according to the third time threshold adjustment parameter, and taking the updated time threshold as the target time threshold.

7. The detection method according to claim 6, characterized in that, Before the determining whether the to-be-identified obstacle vehicle is the target obstacle vehicle according to the target time threshold and the current static time, the method further comprises: if the vehicle light of the to-be-identified obstacle vehicle is on, determining a fourth time threshold adjustment parameter according to whether the on vehicle light is a brake light or a double flash light; updating the target time threshold according to the fourth time threshold adjustment parameter, and taking the updated time threshold as the target time threshold.

8. The detection method according to claim 7, characterized in that, Before the determining whether the to-be-identified obstacle vehicle is the target obstacle vehicle according to the target time threshold and the current static time, the method further comprises: determining whether a first condition is met, the first condition being that there is an intersection within a first distance threshold range in front of the lane where the to-be-identified obstacle vehicle is located and there is a traffic light signal at the intersection; if yes, determining whether the traffic light signal is a red light signal; if yes, determining a fifth time threshold adjustment parameter; updating the target time threshold according to the fifth time threshold adjustment parameter, and taking the updated time threshold as the target time threshold.

9. The assay of any one of claims 1 to 8, wherein, Before the determining whether the to-be-identified obstacle vehicle is the target obstacle vehicle according to the target time threshold and the current static time, the method further comprises: determining whether there is a first vehicle, the first vehicle being a vehicle located in the lane where the to-be-identified obstacle vehicle is located and having a distance less than a preset second distance threshold from the to-be-identified obstacle vehicle; if there is only the first vehicle behind the to-be-identified obstacle vehicle, determining whether a first condition is met, the first condition being that a following distance of the first vehicle is less than a preset third distance threshold; if there is no first vehicle or the first condition is met, under the condition that the lane where the to-be-identified obstacle vehicle is located is a single lane, determining whether a second condition is met, the second condition being that a distance between the to-be-identified obstacle vehicle and a nearest stop line in front is greater than a preset fourth distance threshold; if the second condition is met, determining a sixth time threshold adjustment parameter according to at least one of whether the to-be-identified obstacle vehicle is a preset large vehicle, whether a distance between the to-be-identified obstacle vehicle and the ego vehicle is less than a preset fifth distance threshold, and whether other vehicles between the to-be-identified obstacle vehicle and the ego vehicle are braking; updating the target time threshold according to the sixth time threshold adjustment parameter, and taking the updated time threshold as the target time threshold.

10. A detection device, characterized in that The method comprises: an basic information acquisition unit, configured to acquire a current static time and a lane where a to-be-identified obstacle vehicle is located, and static movement time information of a neighboring lane obstacle vehicle of the to-be-identified obstacle vehicle; An initial time threshold generating unit is configured to generate an initial time threshold according to the current lane; A target time threshold determining unit is configured to obtain a target time threshold based on the static moving time information and the initial time threshold; A target obstacle vehicle judging unit is configured to determine whether the to-be-identified obstacle vehicle is a target obstacle vehicle according to the target time threshold and the current static time.

11. A computer program product, characterised in that, The computer readable instructions, when executed on an electronic device, cause the electronic device to implement the detection method according to any one of claims 1 to 9.

12. An electronic device, comprising: The electronic device comprises at least one processor and a memory connected to the processor, wherein: The memory is configured to store computer programs; The processor is configured to execute the computer programs, so that the electronic device can implement the detection method according to any one of claims 1 to 9.

13. A computer storage medium, characterized in that The storage medium carries one or more computer programs, and when the one or more computer programs are executed by an electronic device, the electronic device can implement the detection method according to any one of claims 1 to 9.

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