An intelligent auxiliary driving control method and device for automatically identifying traffic signal lights

Abstract

This invention discloses an intelligent assisted driving control method and device for automatically recognizing traffic lights, belonging to the field of intelligent assisted driving technology. The method comprises the following steps: acquiring the distance between the current vehicle and the intersection ahead from a road traffic information database and a vehicle-mounted camera; when the distance is less than a set distance threshold, retrieving traffic light and lane information from the road traffic information database and real-time traffic light and lane information from the vehicle-mounted camera; generating first and second signals based on successful acquisition, and converting the two signals into voice and data information respectively; selecting between driver decision-making and human-machine co-driving decision-making based on whether the vehicle is in an emergency state; in non-emergency states and with the second signal, driver decision-making is selected, while in emergency states and with the first signal, human-machine co-driving decision-making is selected. This invention provides the possibility for red-green color blind driving by combining voice recognition with assisted driving control and driver decision-making.

Description

Technical Field

[0001] This invention belongs to the field of intelligent assisted driving technology, specifically relating to an intelligent assisted driving control method and device for automatically recognizing traffic lights. Background Technology

[0002] As a primary means of transportation, automobiles provide significant convenience for daily life. Current regulations for driver's license application and use impose restrictions on applicants' physical conditions, specifically limiting their color vision to red-green color blindness. However, with the development of automated driving assistance technology, if the potential for traffic accidents caused by red-green color blindness can be eliminated, red-green color blind individuals may be able to enjoy the convenience of automobiles in the future. With improved relevant laws, the employment options for red-green color blind individuals could be narrowed, making driving a trend for them, and automobiles would become a key area for barrier-free infrastructure development.

[0003] Currently, the production and sale of vehicles specifically designed for red-green colorblind drivers have not yet been realized. Most existing devices designed to assist red-green colorblind individuals are inconvenient to carry and use. While related patents disclose solutions for assisting red-green colorblind drivers in recognizing traffic lights by converting the red and green lights into colors easily recognizable by them and displaying them on a screen, drivers' eyes are off the road when viewing the screen, posing a safety hazard.

[0004] This is a shortcoming of the existing technology. Therefore, it is very necessary to provide an intelligent assisted driving control method and device for automatically recognizing traffic lights in view of the above-mentioned defects in the existing technology. Summary of the Invention

[0005] To address the shortcomings of existing technologies in helping red-green colorblind individuals broaden their job options and enable them to drive, it is necessary to develop assisted autonomous driving technology. While related patents can convert traffic lights into colors that red-green colorblind individuals can recognize, they rely on a display screen, which poses a safety hazard as it causes the driver's gaze to leave the road. This invention provides an intelligent assisted driving control method and device that automatically recognizes traffic lights to solve the aforementioned technical problems.

[0006] In a first aspect, the present invention provides an intelligent assisted driving control method for automatically recognizing traffic lights, comprising the following steps:

[0007] S1. Obtain the distance between the current vehicle and the intersection ahead from the road traffic information database, and obtain the distance between the current vehicle and the intersection ahead from the vehicle-mounted camera;

[0008] S2. When the distance between the current vehicle and the intersection ahead is less than a set distance threshold in any of the above items, retrieve traffic light information and lane information from the road traffic information database, and collect real-time traffic light information and lane information through the vehicle camera, and generate the first signal and the second signal based on whether the real-time traffic light information and lane information collection is successful.

[0009] S3. Convert the first and second signals into voice information and data information;

[0010] S4. Identify the vehicle's emergency status and select between driver decision and human-machine co-driving decision based on whether the vehicle is in an emergency. In non-emergency situations and with the second signal, driver decision is selected, while in emergency situations and with the first signal, human-machine co-driving decision is selected.

[0011] Furthermore, the specific steps of step S1 are as follows:

[0012] S11. Obtain road traffic information database through the network and high-precision maps, and identify lane information, traffic signal information, and the first distance between the vehicle and the intersection ahead from the road traffic information database;

[0013] S12. Obtain the second distance between the current vehicle and the intersection ahead using radar and cameras, which are on-board equipment.

[0014] Furthermore, the specific steps of step S2 are as follows:

[0015] S21. Determine whether the smaller of the first distance and the second distance is less than or equal to a set distance threshold;

[0016] If so, proceed to step S22;

[0017] If not, return to step S11;

[0018] S22. Initiate vehicle surroundings information collection;

[0019] S23. Use a camera, which is an in-vehicle device, to retrieve the acceptance information of circular traffic lights, the color information of arrow lights, and the directional information of traffic lights from the road traffic information database.

[0020] S24. Use a camera, which is an in-vehicle device, to retrieve images of road traffic information database containing information on road markings, including the direction of road markings and the waiting area, and identify lane information;

[0021] S25. Retrieve images of traffic light information and road marking information from the road traffic information database;

[0022] S26. Compare whether the information retrieved from the traffic information database is the same as the information collected by the camera;

[0023] If they are the same, proceed to step S27;

[0024] If they are different, proceed to step S28;

[0025] S27. Identify vehicle perimeter information, record traffic light information and ground marking information as the first signal, and proceed to step S3;

[0026] S28. If the camera's field of view is determined to be abnormal, record the traffic light information and ground marking information as the second signal, and proceed to step S3. Abnormal camera field of view includes camera malfunction caused by extreme weather or large vehicles blocking the camera's field of view. Surrounding vehicle information includes vehicles in front of the car, parallel vehicles, pedestrians at the intersection, and vehicles at the intersection.

[0027] Furthermore, the specific steps of step S3 are as follows:

[0028] S31. Perform image conversion and information processing on the first signal to obtain first voice information and first data information, and proceed to step S41;

[0029] S32. Perform image conversion on the second signal to obtain the second speech information, and proceed to step S42;

[0030] The specific steps of step S4 are as follows:

[0031] S41. Identify whether the vehicle is currently in an emergency state based on vehicle perimeter information;

[0032] If not, proceed to step S42;

[0033] If so, proceed to step S43;

[0034] S42. Proceed to Level 1 Driver Decision Processing, then proceed to step S44;

[0035] S43. Initiate assisted driving control and secondary driver decision processing, and enter human-machine co-driving decision processing;

[0036] S44. Input the decision information into the vehicle driving end motor controller to determine the vehicle driving status.

[0037] Furthermore, the specific steps of step S41 are as follows:

[0038] S411. Determine whether parallel vehicles forcibly merge into the lane, pedestrians or vehicles run red lights, vehicles in front brake suddenly, or the remaining time of traffic lights is less than or equal to the set time threshold.

[0039] If none of them appear, proceed to step S412;

[0040] If at least one of these conditions is met, proceed to step S413;

[0041] S412. If the vehicle is determined to be in a non-Level 1 emergency state, proceed to step S42;

[0042] S413. The vehicle is determined to be in a Level 1 emergency state. Proceed to step S43.

[0043] Furthermore, the specific steps of step S42 are as follows:

[0044] S421. Input the first voice information or the second voice information to the driver;

[0045] S422. Receive the driver's decision input and generate the first decision information;

[0046] S423. Use the first decision information as the final decision information and proceed to step S44.

[0047] Furthermore, the specific steps of step S43 are as follows:

[0048] S431. While inputting the first voice information or the second voice information to the driver, input it to the driver assistance control module;

[0049] S432. Receive the driver's decision input by the driver, generate second decision information, and use the second decision information as a third signal;

[0050] S433. Obtain the output of the driver assistance control module as the fourth signal;

[0051] S434. Compare whether the third signal and the fourth signal are consistent;

[0052] If they match, proceed to step S435;

[0053] If there is a discrepancy, proceed to step S436;

[0054] S435. Use the second decision information as the final decision information and proceed to step S44;

[0055] S436. The driver assistance control module determines whether the current driver's reaction time is less than a set time threshold;

[0056] If so, proceed to step S438;

[0057] If not, proceed to step S437;

[0058] S437. The vehicle is determined to be in a non-Level 2 emergency state. Proceed to step S42.

[0059] S438. The vehicle is determined to be in a Level 2 emergency state. The driver assistance control module is activated to obtain third-party decision information.

[0060] S439. Use the third decision information as the final decision information and proceed to step S44.

[0061] Furthermore, in step S436, the driver assistance control module determines the current driver's reaction time based on the vehicle's current speed and the distance to the location of the emergency ahead.

[0062] If the current driver's reaction time is greater than or equal to the set threshold, it is considered a reactionable event.

[0063] The current driver's reaction time is less than the set threshold, which is considered an unreactable event.

[0064] In a second aspect, the present invention provides an intelligent assisted driving control system for automatically recognizing traffic lights, comprising:

[0065] The path recognition module is used to obtain the distance between the current vehicle and the intersection ahead from the road traffic information database, and the distance between the current vehicle and the intersection ahead from the vehicle-mounted camera.

[0066] The information collection module is used to retrieve traffic light information and lane information from the road traffic information database when the distance between the current vehicle and the intersection ahead is less than a set distance threshold, and to collect real-time traffic light information and lane information through the vehicle-mounted camera, and to generate the first signal and the second signal based on whether the real-time traffic light information and lane information collection is successful.

[0067] The information conversion module is used to convert the first signal and the second signal into voice information and data information;

[0068] The decision planning module is used to identify vehicle emergency states and select between driver decision and human-machine co-driving decision based on whether the vehicle is in an emergency state. In non-emergency states and under the second signal, driver decision is selected, while in emergency states and under the first signal, human-machine co-driving decision is selected.

[0069] Furthermore, the path recognition module includes:

[0070] The first path recognition unit is used to obtain road traffic information database through the network and high-precision map, and to identify lane information, traffic signal information and the first distance between the vehicle and the intersection ahead from the road traffic information database.

[0071] The second path recognition unit is used to obtain the second distance between the current vehicle and the intersection ahead by using radar and camera, which are vehicle-mounted devices.

[0072] The information collection module includes:

[0073] The information collection and judgment unit is used to determine whether the smaller of the first distance and the second distance is less than or equal to a set distance threshold.

[0074] The vehicle surrounding information collection activation unit is used to activate vehicle surrounding information collection when the smaller of the first distance and the second distance is less than or equal to a set distance threshold.

[0075] The traffic signal light information acquisition unit is used to retrieve, using a camera as an on-board device, the acceptance information of circular traffic signals, the color information of arrow lights, and the directional information from the road traffic information database.

[0076] The ground marking line information acquisition unit is used to retrieve images of marking line direction information and waiting area information from the road traffic information database using a camera that is an on-board device, and to identify lane information.

[0077] The road traffic information database retrieval unit is used to retrieve images of traffic light information and ground marking information from the road traffic information database.

[0078] The information comparison unit is used to compare whether the information retrieved from the traffic information database is the same as the information collected by the camera.

[0079] The first signal recording unit is used to identify vehicle perimeter information and record traffic light information and ground marking line information as the first signal when the information retrieved from the traffic information database is the same as the information collected by the camera.

[0080] The second signal recording unit is used to determine that the camera's field of view is abnormal when the information retrieved from the traffic information database is different from the information collected by the camera. It records the traffic light information and the ground indicator line information as the second signal.

[0081] The information conversion module includes:

[0082] The first information conversion unit is used to perform image conversion and information processing on the first signal to obtain first voice information and first data information;

[0083] The second information conversion unit is used to convert the second signal into image information to obtain the second speech information;

[0084] The decision-making and planning module includes:

[0085] An emergency state determination unit is used to identify whether the vehicle is currently in an emergency state based on vehicle perimeter information.

[0086] The driver's first decision unit is used to activate the assisted driving control and secondary driver decision processing when the current state of the vehicle is an emergency, and to enter the human-machine co-driving decision processing;

[0087] The human-machine co-driving unit is used to initiate Level 1 driver decision-making when the vehicle's current state is not an emergency.

[0088] The decision output unit is used to input decision information into the vehicle driving end motor controller to determine the vehicle driving status.

[0089] Furthermore, the emergency state determination unit includes:

[0090] The emergency condition judgment subunit is used to determine whether parallel vehicles forcibly merge into the lane, pedestrians or vehicles run red lights, vehicles in front brake suddenly, or the remaining time of traffic lights is less than or equal to a set time threshold.

[0091] The non-Level 1 emergency state determination subunit is used to determine that the vehicle is currently in a non-Level 1 emergency state when none of the conditions are met.

[0092] The Level 1 Emergency Status Determination Subunit is used to determine that the vehicle is currently in a Level 1 emergency status when at least one of the conditions is met.

[0093] Furthermore, the driver's primary decision-making unit includes:

[0094] The first driver decision input subunit is used to input the first voice information or the second voice information to the driver in a non-Level 1 emergency or non-Level 2 emergency situation.

[0095] The first decision information generation subunit receives the driver's decision input by the driver and generates the first decision information;

[0096] The first unit for generating final decision information is used to use the first decision information as the final decision information.

[0097] Furthermore, the human-machine co-driving unit includes:

[0098] The first input subunit of the driver assistance control module is used to input first or second voice information to the driver and input it to the driver assistance control module at the same time during a first-level emergency.

[0099] The second driver decision input subunit is used to receive the driver's decision input by the driver, generate the second decision information, and use the second decision information as the third signal;

[0100] The assisted driving control module output acquisition subunit is used to acquire the output of the assisted driving control module as a fourth signal;

[0101] The signal comparison subunit is used to compare whether the third signal and the fourth signal are consistent.

[0102] The second generation subunit for final decision information is used to take the second decision information as the final decision information when the third signal and the fourth signal are consistent.

[0103] The reaction time judgment subunit is used to determine whether the current driver's reaction time is less than a set time threshold when the third signal and the fourth signal are inconsistent.

[0104] The non-Level 2 emergency state determination subunit is used to determine that the vehicle is currently in a non-Level 2 emergency state if the current driver's reaction time is greater than or equal to a set time threshold.

[0105] The Level 2 Emergency State Determination Subunit is used to determine that the vehicle is currently in a Level 2 emergency state when the current driver's reaction time is less than a set time threshold, and then executes the assisted driving control module to obtain third decision information.

[0106] The third generation subunit for final decision information is used to use the third decision information as the final decision information.

[0107] The beneficial effects of this invention are as follows:

[0108] The intelligent assisted driving control method and device for automatically recognizing traffic lights provided by this invention collects environmental information through feedforward control and improves the decision-making and planning control accuracy of the entire system through information transformation, thereby comprehensively improving the decision-making effect. The parameters obtained through real-time information collection and transformation reduce the impact of changes in the driving environment and vehicle condition on the feedforward control's decision-making regarding whether to proceed, and reduce the impact of vehicle feedforward control deviations on the decision-making and planning effect. By combining voice recognition with assisted driving control and driver decision-making, the invention addresses the problem of travel inconvenience for red-green colorblind individuals, making it possible for them to drive and ensuring safe and efficient driving for them, thus providing greater convenience to their lives.

[0109] Furthermore, the design principle of this invention is reliable, the structure is simple, and it has a very wide range of application prospects.

[0110] Therefore, it is evident that the present invention has outstanding substantive features and significant progress compared with the prior art, and the beneficial effects of its implementation are also obvious. Attached Figure Description

[0111] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0112] Figure 1 This is a flowchart illustrating an embodiment of the intelligent assisted driving control method for automatically recognizing traffic lights according to the present invention.

[0113] Figure 2This is a flowchart illustrating another embodiment of the intelligent assisted driving control method for automatically recognizing traffic lights according to the present invention.

[0114] Figure 3 This is a flowchart illustrating the driving decision-making and planning process of the present invention.

[0115] Figure 4 This is a schematic diagram of the intelligent assisted driving control device for automatically recognizing traffic lights according to the present invention. Detailed Implementation

[0116] To enable those skilled in the art to better understand the technical solutions of this invention, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this invention.

[0117] Example 1:

[0118] like Figure 1 As shown, the present invention provides an intelligent assisted driving control method for automatically recognizing traffic lights, comprising the following steps:

[0119] S1. Obtain the distance between the current vehicle and the intersection ahead from the road traffic information database, and obtain the distance between the current vehicle and the intersection ahead from the vehicle-mounted camera;

[0120] S2. When the distance between the current vehicle and the intersection ahead is less than a set distance threshold in any of the above items, retrieve traffic light information and lane information from the road traffic information database, and collect real-time traffic light information and lane information through the vehicle camera, and generate the first signal and the second signal based on whether the real-time traffic light information and lane information collection is successful.

[0121] S3. Convert the first and second signals into voice information and data information;

[0122] S4. Identify the vehicle's emergency status and select between driver decision and human-machine co-driving decision based on whether the vehicle is in an emergency. In non-emergency situations and with the second signal, driver decision is selected, while in emergency situations and with the first signal, human-machine co-driving decision is selected.

[0123] Example 2:

[0124] like Figure 2 As shown, the present invention provides an intelligent assisted driving control method for automatically recognizing traffic lights, comprising the following steps:

[0125] S1. Obtain the distance between the current vehicle and the intersection ahead from the road traffic information database, and obtain the distance between the current vehicle and the intersection ahead from the vehicle-mounted camera; the specific steps of step S1 are as follows:

[0126] S11. Obtain road traffic information database through the network and high-precision maps, and identify lane information, traffic signal information, and the first distance between the vehicle and the intersection ahead from the road traffic information database;

[0127] S12. Obtain the second distance between the current vehicle and the intersection ahead using radar and cameras, which are on-board equipment;

[0128] S2. When the distance between the current vehicle and the intersection ahead is less than a set distance threshold in any of the above-mentioned items, retrieve traffic light information and lane information from the road traffic information database, and collect real-time traffic light information and lane information through the vehicle-mounted camera, and generate the first signal and the second signal based on whether the real-time traffic light information and lane information collection was successful; the specific steps of step S2 are as follows:

[0129] S21. Determine whether the smaller of the first distance and the second distance is less than or equal to a set distance threshold; for example, the distance threshold can be set to 150 meters.

[0130] If so, proceed to step S22;

[0131] If not, return to step S11;

[0132] S22. Initiate vehicle surroundings information collection;

[0133] S23. Use a camera, which is an in-vehicle device, to retrieve the acceptance information of circular traffic lights, the color information of arrow lights, and the directional information of traffic lights from the road traffic information database.

[0134] S24. Use a camera, which is an in-vehicle device, to retrieve images of road traffic information database containing information on road markings, including the direction of road markings and the waiting area, and identify lane information;

[0135] S25. Retrieve images of traffic light information and road marking information from the road traffic information database;

[0136] S26. Compare whether the information retrieved from the traffic information database is the same as the information collected by the camera;

[0137] If they are the same, proceed to step S27;

[0138] If they are different, proceed to step S28;

[0139] S27. Identify vehicle perimeter information, record traffic light information and ground marking information as the first signal, and proceed to step S3;

[0140] S28. If the camera's field of view is determined to be abnormal, record the traffic light information and ground marking information as the second signal, and proceed to step S3;

[0141] Abnormal camera field of view includes camera malfunctions caused by extreme weather or large vehicles blocking the camera's field of view.

[0142] Vehicle perimeter information includes vehicles ahead of the car, vehicles driving alongside it, pedestrians at the intersection, and vehicles at the intersection.

[0143] S3. Convert the first and second signals into voice information and data information; the specific steps of step S3 are as follows:

[0144] S31. Perform image conversion and information processing on the first signal to obtain first voice information and first data information, and proceed to step S41;

[0145] S32. Perform image conversion on the second signal to obtain the second speech information, and proceed to step S42;

[0146] S4. Identify the vehicle's emergency status and select between driver decision-making and human-machine co-driving decision-making based on whether the vehicle is in an emergency. In non-emergency situations and with the second signal, driver decision-making is selected; in emergency situations and with the first signal, human-machine co-driving decision-making is selected. The specific steps of step S4 are as follows:

[0147] S41. Identify whether the vehicle is currently in an emergency state based on vehicle perimeter information;

[0148] If not, proceed to step S42;

[0149] If so, proceed to step S43;

[0150] like Figure 3 As shown, the specific steps of step S41 are as follows:

[0151] S411. Determine whether parallel vehicles forcibly merge into lanes, pedestrians or vehicles run red lights, vehicles ahead brake suddenly, or the remaining time of traffic lights is less than or equal to a set time threshold; for example, the set time threshold is 3 seconds.

[0152] If none of them appear, proceed to step S412;

[0153] If at least one of these conditions is met, proceed to step S413;

[0154] S412. If the vehicle is determined to be in a non-Level 1 emergency state, proceed to step S42;

[0155] S413. The vehicle is determined to be in a Level 1 emergency state. Proceed to step S43.

[0156] S42. Proceed to Level 1 Driver Decision Processing, then proceed to step S44; (e.g.) Figure 3 As shown, the specific steps of step S42 are as follows:

[0157] S421. Input the first voice information or the second voice information to the driver;

[0158] S422. Receive the driver's decision input and generate the first decision information;

[0159] S423. Use the first decision information as the final decision information and proceed to step S44;

[0160] The system provides traffic condition prompts to the driver via voice, assisting the driver in making independent decisions based on actual driving conditions.

[0161] S43. Initiate assisted driving control and secondary driver decision processing, entering human-machine co-driving decision processing; provide voice and data information to the driver decision and assisted driving control modules for joint decision-making, such as... Figure 3 As shown, the specific steps of step S43 are as follows:

[0162] S431. While inputting the first voice information or the second voice information to the driver, input it to the driver assistance control module;

[0163] S432. Receive the driver's decision input by the driver, generate second decision information, and use the second decision information as a third signal;

[0164] S433. Obtain the output of the driver assistance control module as the fourth signal;

[0165] S434. Compare whether the third signal and the fourth signal are consistent;

[0166] If they match, proceed to step S435;

[0167] If there is a discrepancy, proceed to step S436;

[0168] S435. Use the second decision information as the final decision information and proceed to step S44;

[0169] S436. The driver assistance control module determines whether the current driver's reaction time is less than a set time threshold; for example, the set time threshold can be 3 seconds.

[0170] If so, proceed to step S438;

[0171] If not, proceed to step S437;

[0172] S437. The vehicle is determined to be in a non-Level 2 emergency state. Proceed to step S42.

[0173] S438. The vehicle is determined to be in a Level 2 emergency state. The driver assistance control module is activated to obtain third-party decision information.

[0174] S439. Use the third decision information as the final decision information and proceed to step S44;

[0175] S44. Input the decision information into the vehicle driving end motor controller to determine the vehicle driving status;

[0176] It should be noted that in step S436, the driver assistance control module determines the current driver's reaction time based on the vehicle's current speed and the distance to the location of the emergency ahead.

[0177] If the current driver's reaction time is greater than or equal to the set threshold, it is considered a reactionable event.

[0178] The current driver's reaction time is less than the set threshold, which is considered an unreactable event.

[0179] Example 3:

[0180] like Figure 4 As shown, the present invention provides an intelligent assisted driving control system for automatically recognizing traffic lights, comprising:

[0181] The path recognition module is used to obtain the distance between the current vehicle and the intersection ahead from the road traffic information database, and the distance between the current vehicle and the intersection ahead from the vehicle-mounted camera; the path recognition module includes:

[0182] The first path recognition unit is used to obtain road traffic information database through the network and high-precision map, and to identify lane information, traffic signal information and the first distance between the vehicle and the intersection ahead from the road traffic information database.

[0183] The second path recognition unit is used to obtain the second distance between the current vehicle and the intersection ahead by using radar and camera, which are vehicle-mounted devices.

[0184] The information collection module is used to retrieve traffic light and lane information from the road traffic information database and to collect real-time traffic light and lane information via an onboard camera when the distance between the current vehicle and the intersection ahead is less than a set distance threshold. It then generates a first signal and a second signal based on whether the real-time traffic light and lane information collection was successful. The information collection module includes:

[0185] The information collection and judgment unit is used to determine whether the smaller of the first distance and the second distance is less than or equal to a set distance threshold.

[0186] The vehicle surrounding information collection activation unit is used to activate vehicle surrounding information collection when the smaller of the first distance and the second distance is less than or equal to a set distance threshold.

[0187] The traffic signal light information acquisition unit is used to retrieve, using a camera as an on-board device, the acceptance information of circular traffic signals, the color information of arrow lights, and the directional information from the road traffic information database.

[0188] The ground marking line information acquisition unit is used to retrieve images of marking line direction information and waiting area information from the road traffic information database using a camera that is an on-board device, and to identify lane information.

[0189] The road traffic information database retrieval unit is used to retrieve images of traffic light information and ground marking information from the road traffic information database.

[0190] The information comparison unit is used to compare whether the information retrieved from the traffic information database is the same as the information collected by the camera.

[0191] The first signal recording unit is used to identify vehicle perimeter information and record traffic light information and ground marking line information as the first signal when the information retrieved from the traffic information database is the same as the information collected by the camera.

[0192] The second signal recording unit is used to determine that the camera's field of view is abnormal when the information retrieved from the traffic information database is different from the information collected by the camera. It records the traffic light information and the ground indicator line information as the second signal.

[0193] The information conversion module is used to convert the first signal and the second signal into voice information and data information; the information conversion module includes:

[0194] The first information conversion unit is used to perform image conversion and information processing on the first signal to obtain first voice information and first data information;

[0195] The second information conversion unit is used to convert the second signal into image information to obtain the second speech information;

[0196] The decision-making and planning module is used to identify vehicle emergency situations and select between driver decision-making and human-machine co-driving decision-making based on whether the vehicle is in an emergency. In non-emergency situations and under a second signal, driver decision-making is selected, while in emergency situations and under a first signal, human-machine co-driving decision-making is selected. The decision-making and planning module includes:

[0197] An emergency state determination unit is used to identify whether the vehicle is currently in an emergency state based on vehicle perimeter information; the emergency state determination unit includes:

[0198] The emergency condition judgment subunit is used to determine whether parallel vehicles forcibly merge into the lane, pedestrians or vehicles run red lights, vehicles in front brake suddenly, or the remaining time of traffic lights is less than or equal to a set time threshold.

[0199] The non-Level 1 emergency state determination subunit is used to determine that the vehicle is currently in a non-Level 1 emergency state when none of the conditions are met.

[0200] The Level 1 Emergency State Determination Subunit is used to determine that the vehicle is currently in a Level 1 emergency state when at least one of the conditions is met.

[0201] The driver's primary decision-making unit is used to activate driver assistance control and secondary driver decision processing when the vehicle's current state is an emergency, thus entering human-machine co-driving decision processing; the driver's primary decision-making unit includes:

[0202] The first driver decision input subunit is used to input the first voice information or the second voice information to the driver in a non-Level 1 emergency or non-Level 2 emergency situation.

[0203] The first decision information generation subunit receives the driver's decision input by the driver and generates the first decision information;

[0204] The first final decision information generation unit is used to use the first decision information as the final decision information.

[0205] The human-machine co-driving unit is used to initiate Level 1 driver decision-making when the vehicle's current state is non-emergency; the human-machine co-driving unit includes:

[0206] The first input subunit of the driver assistance control module is used to input first or second voice information to the driver and input it to the driver assistance control module at the same time during a first-level emergency.

[0207] The second driver decision input subunit is used to receive the driver's decision input by the driver, generate the second decision information, and use the second decision information as the third signal;

[0208] The assisted driving control module output acquisition subunit is used to acquire the output of the assisted driving control module as a fourth signal;

[0209] The signal comparison subunit is used to compare whether the third signal and the fourth signal are consistent.

[0210] The second generation subunit for final decision information is used to take the second decision information as the final decision information when the third signal and the fourth signal are consistent.

[0211] The reaction time judgment subunit is used to determine whether the current driver's reaction time is less than a set time threshold when the third signal and the fourth signal are inconsistent.

[0212] The non-Level 2 emergency state determination subunit is used to determine that the vehicle is currently in a non-Level 2 emergency state if the current driver's reaction time is greater than or equal to a set time threshold.

[0213] The Level 2 Emergency State Determination Subunit is used to determine that the vehicle is currently in a Level 2 emergency state when the current driver's reaction time is less than a set time threshold, and then executes the assisted driving control module to obtain third decision information.

[0214] The third generation subunit for final decision information is used to use the third decision information as the final decision information.

[0215] The decision output unit is used to input decision information into the vehicle driving end motor controller to determine the vehicle driving status.

[0216] It should be noted that the various modules and units of this invention communicate with each other via a CAN bus.

[0217] Although the present invention has been described in detail with reference to the accompanying drawings and preferred embodiments, the invention is not limited thereto. Various equivalent modifications or substitutions can be made to the embodiments of the invention by those skilled in the art without departing from the spirit and essence of the invention, and such modifications or substitutions should all be within the scope of the invention. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the invention should also be covered within the protection scope of the invention. Therefore, the protection scope of the invention should be determined by the scope of the claims.

Claims

1. A method for intelligent assisted driving control that automatically recognizes traffic lights, characterized in that, Includes the following steps: S1. Obtain the distance between the current vehicle and the intersection ahead from the road traffic information database, and obtain the distance between the current vehicle and the intersection ahead from the vehicle-mounted camera; S2. When the distance between the current vehicle and the intersection ahead is less than a set distance threshold in any of the above items, retrieve traffic light information and lane information from the road traffic information database, and collect real-time traffic light information and lane information through the vehicle camera. Compare whether the traffic light information and lane information retrieved from the road traffic information database are the same as the real-time traffic light information and lane information collected by the vehicle camera. If they are the same, generate the first signal; if they are different, generate the second signal. S3. Convert the first and second signals into voice information and data information; S4. Identify the vehicle's emergency status and select between driver decision and human-machine co-driving decision based on whether the vehicle is in an emergency. In non-emergency situations and with the second signal, driver decision is selected, while in emergency situations and with the first signal, human-machine co-driving decision is selected.

2. The intelligent assisted driving control method for automatically recognizing traffic lights as described in claim 1, characterized in that, The specific steps of step S1 are as follows: S11. Obtain road traffic information database through the network and high-precision maps, and identify lane information, traffic signal information, and the first distance between the vehicle and the intersection ahead from the road traffic information database; S12. Obtain the second distance between the current vehicle and the intersection ahead using radar and onboard camera, which are onboard equipment.

3. The intelligent assisted driving control method for automatically recognizing traffic lights as described in claim 2, characterized in that, The specific steps of step S2 are as follows: S21. Determine whether the smaller of the first distance and the second distance is less than or equal to a set distance threshold; If so, proceed to step S22; If not, return to step S11; S22. Initiate vehicle surroundings information collection; S23. Use the vehicle-mounted camera, which is a vehicle-mounted device, to retrieve the acceptance information of circular traffic lights, the color information of arrow lights, and the directional information of traffic lights from the road traffic information database. S24. Use the vehicle-mounted camera, which is an in-vehicle device, to retrieve images of the direction information of the road marking lines and the waiting area information from the road traffic information database, and identify lane information; S25. Retrieve images of traffic light information and road marking information from the road traffic information database; S26. Compare whether the information retrieved from the road traffic information database is the same as the information collected by the vehicle camera; If they are the same, proceed to step S27; If they are different, proceed to step S28; S27. Identify vehicle perimeter information, record traffic light information and ground marking information as the first signal, and proceed to step S3; S28. If the vehicle camera's field of view is determined to be abnormal, record the traffic light information and ground indicator line information as the second signal, and proceed to step S3.

4. The intelligent assisted driving control method for automatically recognizing traffic lights as described in claim 3, characterized in that, The specific steps of step S3 are as follows: S31. Perform image conversion and information processing on the first signal to obtain first voice information and first data information, and proceed to step S41; S32. Perform image conversion on the second signal to obtain the second speech information, and proceed to step S42; The specific steps of step S4 are as follows: S41. Identify whether the vehicle is currently in an emergency state based on vehicle perimeter information; If not, proceed to step S42; If so, proceed to step S43; S42. Proceed to Level 1 Driver Decision Processing, then proceed to step S44; S43. Initiate assisted driving control and secondary driver decision processing, and enter human-machine co-driving decision processing; S44. Input the decision information into the vehicle driving end motor controller to determine the vehicle driving status.

5. The intelligent assisted driving control method for automatically recognizing traffic lights as described in claim 4, characterized in that, The specific steps of step S41 are as follows: S411. Determine whether parallel vehicles forcibly merge into the lane, pedestrians or vehicles run red lights, vehicles in front brake suddenly, or the remaining time of traffic lights is less than or equal to the set time threshold. If none of them appear, proceed to step S412; If at least one of these conditions is met, proceed to step S413; S412. If the vehicle is determined to be in a non-Level 1 emergency state, proceed to step S42; S413. The vehicle is determined to be in a Level 1 emergency state. Proceed to step S43.

6. The intelligent assisted driving control method for automatically recognizing traffic lights as described in claim 4, characterized in that, The specific steps of step S42 are as follows: S421. Input the first voice information or the second voice information to the driver; S422. Receive the driver's decision input and generate the first decision information; S423. Use the first decision information as the final decision information and proceed to step S44.

7. The intelligent assisted driving control method for automatically recognizing traffic lights as described in claim 6, characterized in that, The specific steps of step S43 are as follows: S431. While inputting the first voice information or the second voice information to the driver, input it to the driver assistance control module; S432. Receive the driver's decision input by the driver, generate second decision information, and use the second decision information as a third signal; S433. Obtain the output of the driver assistance control module as the fourth signal; S434. Compare whether the third signal and the fourth signal are consistent; If they match, proceed to step S435; If there is a discrepancy, proceed to step S436; S435. Use the second decision information as the final decision information and proceed to step S44; S436. The driver assistance control module determines whether the current driver's reaction time is less than a set time threshold; If so, proceed to step S438; If not, proceed to step S437; S437. The vehicle is determined to be in a non-Level 2 emergency state. Proceed to step S42. S438. The vehicle is determined to be in a Level 2 emergency state. The driver assistance control module is activated to obtain third-party decision information. S439. Use the third decision information as the final decision information and proceed to step S44.

8. The intelligent assisted driving control method for automatically recognizing traffic lights as described in claim 7, characterized in that, In step S436, the driver assistance control module determines the current driver's reaction time based on the vehicle's current speed and the distance to the location of the emergency ahead; If the current driver's reaction time is greater than or equal to the set threshold, it is considered a reactionable event. The current driver's reaction time is less than the set threshold, which is considered an unreactable event.

9. An intelligent assisted driving control system for automatically recognizing traffic lights, characterized in that, include: The path recognition module is used to obtain the distance between the current vehicle and the intersection ahead from the road traffic information database, and the distance between the current vehicle and the intersection ahead from the vehicle-mounted camera. The information collection module is used to retrieve traffic light information and lane information from the road traffic information database and collect real-time traffic light information and lane information through the vehicle-mounted camera when the distance between the current vehicle and the intersection ahead is less than a set distance threshold. The module compares the traffic light information and lane information retrieved from the road traffic information database with the real-time traffic light information and lane information collected by the vehicle-mounted camera. If they are the same, a first signal is generated; if they are different, a second signal is generated. The information conversion module is used to convert the first signal and the second signal into voice information and data information; The decision planning module is used to identify vehicle emergency states and select between driver decision and human-machine co-driving decision based on whether the vehicle is in an emergency state. In non-emergency states and under the second signal, driver decision is selected, while in emergency states and under the first signal, human-machine co-driving decision is selected.

10. The intelligent assisted driving control system for automatically recognizing traffic lights as described in claim 9, characterized in that, The path recognition module includes: The first path recognition unit is used to obtain road traffic information database through the network and high-precision map, and to identify lane information, traffic signal information and the first distance between the vehicle and the intersection ahead from the road traffic information database. The second path recognition unit is used to obtain the second distance between the current vehicle and the intersection ahead by using radar and vehicle-mounted camera, which are vehicle-mounted devices. The information collection module includes: The information collection and judgment unit is used to determine whether the smaller of the first distance and the second distance is less than or equal to a set distance threshold. The vehicle surrounding information collection activation unit is used to activate vehicle surrounding information collection when the smaller of the first distance and the second distance is less than or equal to a set distance threshold. The traffic signal light information collection unit is used to retrieve the acceptance information of circular traffic signals, the color information of arrow lights, and the directional information of traffic signals from the road traffic information database using the vehicle-mounted camera, which is a vehicle-mounted device. The ground marking line information acquisition unit is used to retrieve images of marking line direction information and waiting area information from the road traffic information database using an on-board camera, which is a vehicle-mounted device, and to identify lane information. The road traffic information database retrieval unit is used to retrieve images of traffic light information and ground marking information from the road traffic information database. The information comparison unit is used to compare whether the information retrieved from the road traffic information database is the same as the information collected by the vehicle camera. The first signal recording unit is used to identify vehicle perimeter information and record traffic light information and ground indicator line information as the first signal when the information retrieved from the traffic information database is the same as the information collected by the vehicle camera. The second signal recording unit is used to determine that the field of view of the vehicle camera is abnormal when the information retrieved from the traffic information database is different from the information collected by the vehicle camera. The unit records the traffic light information and the ground indicator line information as the second signal. The information conversion module includes: The first information conversion unit is used to perform image conversion and information processing on the first signal to obtain first voice information and first data information; The second information conversion unit is used to convert the second signal into image information to obtain the second speech information; The decision-making and planning module includes: An emergency state determination unit is used to identify whether the vehicle is currently in an emergency state based on vehicle perimeter information. The driver's first decision unit is used to activate the assisted driving control and secondary driver decision processing when the current state of the vehicle is an emergency, and to enter the human-machine co-driving decision processing; The human-machine co-driving unit is used to initiate Level 1 driver decision-making when the vehicle's current state is not an emergency. The decision output unit is used to input decision information into the vehicle driving end motor controller to determine the vehicle driving status.

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