Assisted driving control method, apparatus and device for passing through road under construction, and storage medium

Abstract

An assisted driving control method, apparatus and device for passing through a road under construction, and a storage medium. The assisted driving control method for passing through a road under construction comprises: acquiring cloud construction information and perceived road-condition information; on the basis of the perceived road-condition information, performing confidence determination on the cloud construction information; when a determination result indicates that the cloud construction information has high confidence, performing collision prediction on a vehicle on the basis of the perceived road-condition information and the cloud construction information; and when a collision prediction result indicates that a collision may occur, performing assisted control on the vehicle, such that the vehicle can rapidly respond to changes in the road under construction, thereby reducing accidents and improving the driving experience.

Description

Assisted driving control methods, devices, equipment, and storage media for construction roads

[0001] Related applications

[0002] This application claims priority to Chinese patent application filed on December 16, 2024, with application number 2024118511240, entitled "Assisted Driving Control Method, Apparatus, Equipment and Storage Medium for Driving on Construction Roads", the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application relates to the field of intelligent driving technology, and in particular to assisted driving control methods, devices, equipment and storage media for driving on construction roads. Background Technology

[0004] With the development of intelligent driving, intelligent driving can greatly reduce driver fatigue;

[0005] However, intelligent driving still has some limitations on construction roads. When the road is blocked by cones / water-filled barriers, the sensors are affected by weather (such as nighttime, rainy or foggy weather) and obstruction by the vehicle in front (such as when following a vehicle), which causes the merging information of the cones / water-filled barriers to be recognized too late. This results in the vehicle changing lanes or decelerating too late. Especially in high-speed scenarios, accidents involving collisions with construction areas often occur, which seriously affects the intelligent driving experience.

[0006] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0007] The main objective of this application is to provide an auxiliary driving control method, device, equipment, and storage medium for driving on construction roads, aiming to solve the technical problem of inaccurate identification by intelligent driving due to sensors.

[0008] To achieve the above objectives, this application proposes an assisted driving control method for navigating construction roads, the assisted driving control method for navigating construction roads comprising:

[0009] Obtain construction information and road condition information from the cloud;

[0010] The credibility of the cloud-based construction information is determined based on the perceived road condition information.

[0011] When the judgment result is credible, collision prediction is performed on the vehicle based on the perceived road condition information and the cloud construction information.

[0012] When the collision prediction result indicates that a collision is possible, auxiliary control is applied to the vehicle.

[0013] In one embodiment, the step of determining the credibility of the cloud-based construction information based on the perceived road condition information includes:

[0014] If the cloud-based construction information identifies traffic control facilities within a preset area ahead of the vehicle, and the perceived road condition information also identifies traffic control facilities within the preset area ahead of the vehicle, then the cloud-based construction information is deemed reliable.

[0015] In one embodiment, after determining whether traffic control facilities exist within a preset area in front of the vehicle based on the cloud-based construction information when traffic control facilities are detected, the method further includes:

[0016] If the traffic control facility does not exist within the preset area, the cloud-based construction information is determined to be unreliable, and the perceived road condition information is uploaded to update the cloud-based construction information to remove the marker for the traffic control facility.

[0017] In one embodiment, the step of predicting vehicle collisions based on the perceived road condition information and the cloud-based construction information includes:

[0018] When it is determined that there are traffic control facilities within a first preset distance in front of the vehicle based on the perceived road condition information and the cloud construction information, the vehicle-side judgment is performed on the traffic control facilities.

[0019] When the traffic control facility is in the lane, the collision prediction result is determined to be a possible collision.

[0020] In one embodiment, the step of providing auxiliary control to the vehicle when the collision prediction result indicates a possible collision includes:

[0021] When the collision prediction result indicates that a collision is possible, it is determined whether there are traffic control facilities in the adjacent lanes of the vehicle and whether there are lane-changing conditions in the adjacent lanes.

[0022] When there are no traffic control facilities in the adjacent lane and lane-changing conditions exist in the adjacent lane, the vehicle is controlled to change lanes to the adjacent lane.

[0023] In one embodiment, the method further includes:

[0024] When there are no traffic control facilities in the adjacent lane and no lane-changing conditions in the adjacent lane, determine whether the vehicle can pass in its own lane;

[0025] If so, then control the vehicle to decelerate and pass through the lane;

[0026] If not, then control the vehicle to continuously decelerate and wait for a lane change opportunity.

[0027] In one embodiment, the method further includes:

[0028] If, during the process of controlling the vehicle to continuously decelerate while waiting for a lane change opportunity, the distance between the vehicle and the merging point is detected to be less than a preset distance, the vehicle is controlled to brake.

[0029] In one embodiment, the method further includes:

[0030] When traffic control facilities exist in the adjacent lane of the vehicle, the vehicle is controlled to slow down and pass through according to the boundary of the traffic control facilities.

[0031] In one embodiment, the step of providing auxiliary control to the vehicle when the collision prediction result indicates a possible collision includes:

[0032] When the collision prediction result indicates that a collision is possible, and the adjacent lane of the vehicle is an emergency lane, the vehicle is controlled to slow down and pass according to the boundary of the traffic control facility and the road boundary on the other side.

[0033] In one embodiment, the method further includes:

[0034] When it is determined that there are traffic control facilities within a first preset distance in front of the vehicle based on the perceived road condition information and the cloud construction information, the vehicle-side judgment is performed on the traffic control facilities.

[0035] When the traffic control facility is not in the vehicle's lane, the vehicle is controlled to proceed straight through.

[0036] In one embodiment, the method further includes:

[0037] When it is determined that there are traffic control facilities within a first preset distance in front of the vehicle based on the perceived road condition information and the cloud construction information, the vehicle-side judgment is performed on the traffic control facilities.

[0038] If the traffic control facility is on the vehicle lane, and there is no traffic control facility in the adjacent lane or on the lane line of the vehicle, then the vehicle is controlled to change lanes to the adjacent lane.

[0039] If the traffic control facility is on the vehicle lane, and there is a traffic control facility in the adjacent lane or on the lane line of the vehicle, then the vehicle is controlled to proceed straight through.

[0040] In one embodiment, after the step of predicting vehicle collisions based on the perceived road condition information and the cloud-based construction information, the method further includes:

[0041] When the traffic control facility is in an adjacent lane, the collision prediction result is determined to be a possible collision;

[0042] Control the vehicle to reduce its speed to a preset range to pass safely.

[0043] In one embodiment, the method further includes:

[0044] Based on the perceived road condition information, traffic control facilities ahead of the vehicle are identified, and the vehicle's positioning information and the data of the traffic control facilities are obtained. The data includes the construction type of the traffic control facilities, the lateral and longitudinal positions of the traffic control facilities relative to the vehicle, and the lane in which the traffic control facilities are located.

[0045] The vehicle's location information and the traffic control facility's data are uploaded to the cloud to update the cloud construction information.

[0046] Furthermore, to achieve the above objectives, this application also proposes an auxiliary driving control device for driving on construction roads, the device comprising:

[0047] The information acquisition module is used to acquire construction information from the cloud and road condition information from the sensor.

[0048] A credibility assessment module is used to assess the credibility of the cloud-based construction information based on the perceived road condition information.

[0049] The prediction module is used to predict vehicle collisions based on the perceived road condition information and the cloud-based construction information when the judgment result is reliable.

[0050] The control module is used to provide auxiliary control to the vehicle when the collision prediction result indicates that a collision is possible.

[0051] In addition, to achieve the above objectives, this application also proposes an auxiliary driving control device for navigating construction roads, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the auxiliary driving control method for navigating construction roads as described above.

[0052] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the assisted driving control method for traversing construction roads as described above.

[0053] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the assisted driving control method for navigating construction roads as described above.

[0054] One or more technical solutions proposed in this application have at least the following technical effects:

[0055] It acquires cloud-based construction information and perceived road condition information; it assesses the credibility of cloud-based construction information based on perceived road condition information; when the assessment result is credible, it performs collision prediction for the vehicle based on perceived road condition information and cloud-based construction information; when the collision prediction result indicates a possible collision, it provides assisted vehicle control, enabling rapid response to changes in the construction road, thereby reducing accidents and improving the driving experience. Attached Figure Description

[0056] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0057] To more clearly illustrate the technical solutions in the embodiments of this application 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.

[0058] Figure 1 is a schematic flowchart of the assisted driving control method for construction roads provided in this application, according to Embodiment 1.

[0059] Figure 2 is a flowchart of the assisted driving decision-making process provided in Embodiment 1 of the assisted driving control method for construction roads in this application;

[0060] Figure 3 is a map update flowchart provided in Embodiment 1 of the assisted driving control method for construction roads in this application;

[0061] Figure 4 is a flowchart illustrating the second embodiment of the assisted driving control method for construction roads provided in this application.

[0062] Figure 5 is a flowchart of the map marker reliability judgment provided in Embodiment 2 of the assisted driving control method for construction roads in this application;

[0063] Figure 6 is a schematic diagram of the module structure of the auxiliary driving control device for construction roads in an embodiment of this application;

[0064] Figure 7 is a schematic diagram of the hardware operating environment of the assisted driving control method for construction roads in the embodiments of this application.

[0065] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0066] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0067] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0068] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0069] When intelligent driving vehicles pass through temporary cone / water-filled barrier construction sections, the limitations of existing sensors, such as other vehicles obstructing the view in front of the vehicle, or weather conditions like rain, fog, or nighttime, can cause the sensors to fail to detect the merging of cones / water-filled barriers in time. This can lead to vehicles failing to change lanes in time or braking too late, especially at high speeds on highways. This often results in collisions with construction areas, causing driver complaints and severely impacting the intelligent driving experience.

[0070] To address the above issues, this strategy proposes a control method for construction roads, which overcomes the limitations of intelligent driving when navigating construction roads and improves the user experience.

[0071] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device capable of performing the above functions, such as an auxiliary driving control device for navigating construction roads. The following description uses an auxiliary driving control device for navigating construction roads as an example to illustrate this embodiment and the subsequent embodiments.

[0072] Based on this, the present application provides an assisted driving control method for driving through construction roads. Referring to FIG1, FIG1 is a flowchart of the first embodiment of the assisted driving control device method for driving through construction roads of the present application.

[0073] In this embodiment, the method for using an auxiliary driving control device through a construction road includes steps S10 to S40:

[0074] Step S10: Obtain cloud-based construction information and road condition information;

[0075] It should be noted that cloud-based construction information is stored on cloud servers and includes detailed information about the construction area, such as its location, type of construction, and traffic control facilities.

[0076] Perceived road condition information refers to road condition information collected in real time by vehicle sensors, including vehicle location, location and type of surrounding objects (such as traffic control facilities).

[0077] Step S20: Determine the credibility of the cloud-based construction information based on the perceived road condition information;

[0078] It should be noted that because temporary construction and repairs are often rapid, or due to location or map errors, incorrect construction areas may be marked on the map. Therefore, it is necessary to combine sensor information to determine the reliability of map markers. If the map markers are reliable, the marker information can be used for decision-making and control; if they are unreliable, decision-making and control must rely solely on sensor information.

[0079] It should be understood that credibility assessment is to evaluate the accuracy and timeliness of cloud-based construction information in order to determine whether this information can be relied upon for subsequent operations.

[0080] Step S30: When the judgment result is credible, perform collision prediction on the vehicle based on perceived road condition information and cloud construction information.

[0081] It should be noted that collision prediction is based on factors such as the vehicle's current position, speed, and surrounding environment to predict whether the vehicle is likely to collide with traffic control facilities in the construction area.

[0082] In one feasible implementation, step S30 may include: if traffic control facilities are identified in a preset area in front of the vehicle based on cloud construction information, and traffic control facilities are also identified in a preset area in front of the vehicle based on perceived road condition information, then the cloud construction information is determined to be reliable.

[0083] In another feasible implementation, step S30 may include steps A11 to A12:

[0084] Step A11: When it is determined that there are traffic control facilities within the first preset distance in front of the vehicle based on the perceived road condition information and cloud construction information, the vehicle-side judgment is made on the traffic control facilities;

[0085] In the specific implementation, it is determined whether there is cone / water barrier information within a distance L in front of the vehicle (e.g., within 200 meters), and the vehicle-side judgment is performed.

[0086] It should be noted that the first preset distance can be set, such as 200 meters, 300 meters, etc.

[0087] Traffic control facilities, also known as cones or water-filled barriers, are used for road construction, maintenance, or other temporary traffic control to ensure the safety of the construction area and the orderly flow of traffic.

[0088] Step A12: When the traffic control facility is in the lane, determine the collision prediction result as a possible collision.

[0089] In practical implementation, if the traffic control facility is in the lane, and the collision prediction result indicates a possible collision, the following strategy is adopted:

[0090] If both the sensor and the map determine that there are no cones / water barriers in the adjacent lane and no other vehicles in the adjacent lane are obstructing the lane change, then the vehicle will change lanes to the adjacent lane in advance to pass through the construction area.

[0091] If the map and perception determine that there are no cones / water barriers in the adjacent lane, but the traffic volume in the adjacent lane is high and the vehicle cannot change lanes to the adjacent lane, then the vehicle will determine whether it can pass through its own lane based on the information of the nearest and farthest cones marked on the map. If the vehicle can pass through its own lane, it will reduce the set speed and slow down to pass through; if the vehicle cannot pass through its own lane, it will continue to slow down and wait for a chance to change lanes. If it is still unable to change lanes, when the distance to the merging point is less than the preset distance, the vehicle will brake suddenly and stop the vehicle before merging.

[0092] Furthermore, when the traffic control facility is in an adjacent lane, the collision prediction result is determined to be a possible collision;

[0093] Control the vehicle to reduce its speed to the preset range to pass safely.

[0094] In practice, if the map and perception determine that there are cones / water barriers in the adjacent lane, the vehicle speed is reduced and the vehicle is controlled according to the boundaries of the cones / water barriers identified by the perception on both sides.

[0095] Step S40: When the collision prediction result indicates that a collision may occur, assist control is applied to the vehicle.

[0096] It should be noted that auxiliary control means that the system automatically intervenes in the vehicle's operation to avoid or mitigate the consequences of a collision.

[0097] It should be noted that if there are cones / water barriers within a distance L (e.g., within 200 meters) ahead on the map, and the cones / water barriers are only in the driver's lane, if the map indicates that there are no cones / water barriers in the adjacent lane and on the lane line, and the driver senses that there are no cones / water barriers in the adjacent lane and on the lane line, then the driver will change lanes to the adjacent lane; otherwise, the driver will not change lanes and will continue straight.

[0098] As shown in Figure 2, the system first checks if the map ahead indicates construction. If the construction information on the map is reliable, the system will navigate according to the map information to prepare to pass through the construction area. If the perception system detects cones or water-filled barriers, the system will further determine whether these construction signs are in the user's lane. If the construction signs are in the user's lane, the system will check if there are construction signs in adjacent lanes and determine if there are lane-changing conditions. If there are no construction signs in adjacent lanes and lane-changing conditions exist, the system will control the vehicle to change lanes to pass through the construction area. If there are no construction signs in adjacent lanes but no lane-changing conditions exist, the system will control the vehicle to slow down and pass through. If the construction signs are not in the user's lane, the system will determine if it is permissible to proceed straight through. If so, the vehicle will proceed straight through the construction area; if not, the system will take appropriate measures, such as changing lanes or slowing down. In addition, the system will also decide whether to slow down or brake suddenly to avoid a collision based on traffic flow and vehicle speed. The entire flowchart illustrates a closed-loop decision-making system that combines map information and real-time perception data to ensure that vehicles can safely and accurately pass through construction sections. In this way, driver assistance systems can improve responsiveness to construction zones, reduce potential traffic accidents, and enhance driving safety and reliability.

[0099] In one feasible implementation, step S40 may include: when the collision prediction result indicates that a collision may occur, determining whether there are traffic control facilities in the adjacent lane of the vehicle and determining whether there are lane-changing conditions in the adjacent lane; when there are no traffic control facilities in the adjacent lane and there are lane-changing conditions in the adjacent lane, controlling the vehicle to change lanes to the adjacent lane.

[0100] In another feasible implementation, step S40 may include steps A21 to A23:

[0101] Step A21: When the collision prediction result indicates that a collision is possible, determine whether there are traffic control facilities in the adjacent lanes of the vehicle;

[0102] It should be noted that if there are cones / water barriers within a distance L (e.g., within 200 meters) ahead on the map, but no cones / water barriers are visible in the vehicle's lane, and the sensor does not detect cones / water barriers in the vehicle's lane, the vehicle should proceed straight through, and lane changes are prohibited in the construction area.

[0103] Step A22: If there are no traffic control facilities in the adjacent lane of the vehicle, determine whether there are conditions for changing lanes in the adjacent lane;

[0104] Step A23: When there is a lane-changing condition in the adjacent lane, control the vehicle to change lanes to the adjacent lane;

[0105] Step A24: When there are no lane-changing conditions in the adjacent lane, control the vehicle to brake.

[0106] It should be noted that when there are traffic cones / water-filled barriers within a distance L (e.g., within 200 meters) ahead on the map, and these cones / barriers are in the driving lane, the following strategy is adopted:

[0107] If both the sensor and the map determine that there are no cones / water barriers in the adjacent lane and no other vehicles in the adjacent lane are obstructing the lane change, then the vehicle will change lanes to the adjacent lane in advance to pass through the construction area.

[0108] If the map and perception determine that there are no cones / water barriers in the adjacent lane, but the traffic volume in the adjacent lane is high and the vehicle cannot change lanes to the adjacent lane, then the vehicle will determine whether it can pass through its own lane based on the information of the nearest and farthest cones marked on the map. If the vehicle can pass through its own lane, it will reduce the set speed and slow down to pass through; if the vehicle cannot pass through its own lane, it will continue to slow down and wait for a chance to change lanes. If it is still unable to change lanes, when the distance to the merging point is less than the preset distance, the vehicle will brake suddenly and stop the vehicle before merging.

[0109] If the map and sensors determine that there are cones / water barriers in the adjacent lane, the vehicle speed will be reduced. The vehicle will then control itself based on the boundaries of the cones / water barriers identified by the sensors on both sides.

[0110] If the map shows that the adjacent lane is an emergency lane, reduce the vehicle's set speed and control the vehicle according to the boundary of the cones / water barriers and the road boundary on the other side;

[0111] Furthermore, based on the perceived road condition information, traffic control facilities in front of the vehicle are identified, and the vehicle's positioning information and data of the traffic control facilities are obtained. The data includes the construction type of the traffic control facilities, the lateral and longitudinal positions of the traffic control facilities relative to the vehicle, and the lane in which the traffic control facilities are located.

[0112] Vehicle location information and traffic control facility data are uploaded to the cloud to update cloud construction information.

[0113] It should be noted that when the positioning and map are normal, when a vehicle with assisted driving passes through a temporary construction section with cones / water-filled barriers, regardless of whether the intelligent driving is activated, if the sensors detect multiple cones / water-filled barriers ahead, the vehicle will record the information of the cones / water-filled barriers within 20 meters, including: the vehicle's positioning information, the type of construction detected, the vehicle's lateral and longitudinal position relative to each cone / water-filled barrier, the lateral position of the center of the cone / water-filled barrier from the left lane line, whether the cone / water-filled barrier is on the lane line, and the lane in which the cone / water-filled barrier is located (if the cone / water-filled barrier is on the lane line, then it does not belong to any lane). The above information will be uploaded to the cloud for the map module.

[0114] It should be understood that traffic control facility data is key point data. To accelerate lightweight map updates, it's necessary to reduce the amount of data recorded on the map. Therefore, the cloud computing module needs to process the cones / water barriers based on perception and recognition information and the vehicle's location, marking key points. Key point data includes: the starting latitude and longitude coordinates of the cones / water barriers, the ending latitude and longitude coordinates of the cones / water barriers, whether there are cones / water barriers in each lane, the latitude and longitude of the farthest cone / water barrier from the left lane line in each lane, the latitude and longitude of the nearest cone / water barrier from the left lane line in each lane, whether the farthest and nearest cones / water barriers are on the lane lines, and the type of construction object.

[0115] When subsequent vehicles pass through this section of road and detect the cones / water barriers, the location of the cones / water barriers will be uploaded to the cloud again, and the cone / water barrier marking information will be identified before the cloud map is corrected; if the vehicles pass through this section of road and do not detect the cones / water barriers, the cone / water barrier markings for this temporary construction site will be removed from the cloud map.

[0116] Once the construction site is marked on the map, the map module needs to send the marked location to the vehicle.

[0117] As shown in Figure 3, the system first checks whether the vehicle's positioning system and map data are working properly. This is the foundation for ensuring the accuracy of subsequent operations. The system then identifies whether traffic cones / water barriers are detected at the current location. If the positioning and map are normal, the system uses the vehicle's perception system (such as cameras and radar) to identify whether there are construction signs, such as traffic cones or water barriers, within 20 meters ahead. The system then uploads the lateral and longitudinal positions of the traffic cones / water barriers within 20 meters ahead, their lane locations, and the vehicle's position to the cloud. Once a construction sign is detected, the system collects the specific location information of these signs and uploads it to the cloud. After receiving the information, the cloud calculates key points, including the latitude and longitude coordinates of the starting and ending points of the construction site, as well as the positions of the farthest and nearest traffic cones / water barriers in each lane. The system checks whether there is already a construction information marker at the current location. If there is no construction information marker, the system creates a new construction marker on the map. If there is already a construction information marker, the system modifies the existing construction sign data based on the newly uploaded information. If the vehicle passes through a construction section but does not detect traffic cones / water barriers, the system removes the construction point marker from the cloud map.

[0118] This embodiment provides an assisted driving control method for driving on construction roads, which acquires cloud-based construction information and perceived road condition information; judges the credibility of cloud-based construction information based on perceived road condition information; when the judgment result is credible, performs collision prediction on the vehicle based on perceived road condition information and cloud-based construction information; when the collision prediction result indicates that a collision may occur, performs assisted control on the vehicle, which can quickly respond to changes in construction roads, thereby reducing accidents and improving the driving experience.

[0119] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, please refer to Figure 4, step S20, including steps S201 to S203:

[0120] Step S201: Identify traffic control facilities ahead of the vehicle based on perceived road condition information;

[0121] In practice, vehicle-mounted sensors (such as cameras, radar, lidar, etc.) are used to collect road condition information ahead, and image recognition or object detection algorithms are used to identify traffic control facilities (such as cones, water-filled barriers, etc.) to ensure that the vehicle can detect traffic control facilities ahead in real time and provide a basis for subsequent decision-making.

[0122] Step S202: When traffic control facilities are detected in a preset area in front of the vehicle, determine whether traffic control facilities exist in the preset area based on cloud construction information.

[0123] In practice, the traffic control facility information perceived by the vehicle is compared with the construction information in the cloud to check whether there are any recorded traffic control facilities in the preset area; this verifies the accuracy of the construction information in the cloud and ensures that the vehicle can make the correct driving decision based on the latest construction situation.

[0124] Furthermore, if there are no traffic control facilities in the preset area, the cloud-based construction information is determined to be unreliable. At the same time, the perceived road condition information is uploaded to update the cloud-based construction information and remove the markers for traffic control facilities.

[0125] It should be noted that if the cloud-based construction information does not record the traffic control facilities perceived by the vehicle, then the cloud-based information is considered unreliable. In this case, the vehicle needs to upload the perceived road condition information to the cloud in order to update the construction information and remove incorrect traffic control facility markers.

[0126] Step S203: When traffic control facilities exist within the preset area, determine that the cloud-based construction information is reliable.

[0127] In practice, if the cloud-based construction information records traffic control facilities perceived by vehicles, then the cloud-based information is considered reliable.

[0128] It should be noted that when the system detects the presence of traffic cones / water-filled barriers in a lane, but these barriers are not marked on the map, the map construction marker information is unreliable. In this case, the system needs to make corresponding decisions and controls based on the perceived information. The same decision-making and control procedures should be followed according to the map's reliable scenario as described above.

[0129] As shown in Figure 5, the system first checks if the map ahead indicates construction. If there are no construction marks on the map, the system will further use its perception system to identify whether there are construction signs such as cones or water-filled barriers ahead. If the perception system identifies cones or water-filled barriers, the system will check if there are construction marks on the corresponding lanes on the map. If there are no corresponding construction marks on the map, the system will consider the map information unreliable and may need to update the map information or take other measures to ensure safety. If there are construction marks on the map, the system will further determine whether these marks are reliable. If the system determines that the construction information marked on the map is reliable, the vehicle will navigate according to the map information to prepare to pass through the construction area. If the vehicle has already passed the construction endpoint marked on the map, the system will confirm this and may update the vehicle's navigation status to reflect that it has passed through the construction area.

[0130] This embodiment provides an assisted driving control method for roads under construction. The method identifies traffic control facilities ahead of the vehicle based on perceived road condition information. When traffic control facilities are detected in a preset area ahead of the vehicle, the method determines whether traffic control facilities exist in the preset area based on cloud-based construction information. If traffic control facilities exist in the preset area, the method determines that the cloud-based construction information is reliable. The reliability of the cloud-based construction information is confirmed, enabling the vehicle to rely on this information for subsequent driving decisions and safe operations.

[0131] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the assisted driving control method for construction roads. Any simple modifications based on this technical concept are within the scope of protection of this application.

[0132] This application also provides an auxiliary driving control device for navigating construction roads. Referring to Figure 6, the auxiliary driving control device for navigating construction roads includes:

[0133] Information acquisition module 10 is used to acquire cloud-based construction information and road condition information.

[0134] The credibility judgment module 20 is used to judge the credibility of cloud-based construction information based on perceived road condition information.

[0135] The prediction module 30 is used to predict vehicle collisions based on perceived road condition information and cloud-based construction information when the judgment result is credible.

[0136] The control module 40 is used to provide auxiliary control of the vehicle when the collision prediction result indicates that a collision may occur.

[0137] The assisted driving control device for navigating construction roads provided in this application, employing the assisted driving control method for navigating construction roads described in the above embodiments, can solve the technical problem of inaccurate identification by intelligent driving due to sensors. Compared with the prior art, the beneficial effects of the assisted driving control device for navigating construction roads provided in this application are the same as those of the assisted driving control method for navigating construction roads provided in the above embodiments, and other technical features in the assisted driving control device for navigating construction roads are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0138] In one embodiment, the credibility judgment module 20 is further configured to identify traffic control facilities ahead of the vehicle based on perceived road condition information.

[0139] When traffic control facilities are detected in a preset area in front of the vehicle, the presence of traffic control facilities in the preset area is determined based on cloud-based construction information.

[0140] When traffic control facilities exist within the preset area, the reliability of cloud-based construction information is determined.

[0141] In one embodiment, the credibility judgment module 20 is further configured to determine that the cloud construction information is unreliable when there are no traffic control facilities in the preset area, and simultaneously upload perceived road condition information to update the cloud construction information and remove the markers of traffic control facilities.

[0142] In one embodiment, the prediction module 30 is further configured to make a vehicle-side judgment on traffic control facilities when it is determined, based on perceived road condition information and cloud construction information, that there are traffic control facilities within a first preset distance in front of the vehicle.

[0143] When the traffic control facility is in the lane, the collision prediction result is determined to be a possible collision.

[0144] In one embodiment, the control module 40 is further configured to determine whether there are traffic control facilities in the adjacent lanes of the vehicle when the collision prediction result indicates that a collision may occur;

[0145] If there are no traffic control facilities in the adjacent lanes of the vehicle, determine whether there are conditions for changing lanes in the adjacent lanes;

[0146] When there is a lane-changing opportunity in the adjacent lane, control the vehicle to change lanes to the adjacent lane;

[0147] When there are no lane-changing conditions in the adjacent lane, control the vehicle to brake.

[0148] In one embodiment, the prediction module 30 is further configured to determine that a collision prediction result is likely when the traffic control facility is in an adjacent lane;

[0149] Control the vehicle to reduce its speed to the preset range to pass safely.

[0150] In one embodiment, the control module 40 is further configured to identify traffic control facilities in front of the vehicle based on perceived road condition information, and obtain the vehicle's positioning information and data of the traffic control facilities, including the construction type of the traffic control facilities, the lateral and longitudinal positions of the traffic control facilities relative to the vehicle, and the lane in which the traffic control facilities are located.

[0151] Vehicle location information and traffic control facility data are uploaded to the cloud to update cloud construction information.

[0152] This application provides an auxiliary driving control device for driving through construction roads. The auxiliary driving control device for driving through construction roads includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the auxiliary driving control method for driving through construction roads in the first embodiment described above.

[0153] Referring to Figure 7 below, a schematic diagram of a driving assistance control device suitable for implementing embodiments of this application on a road construction site is shown. The driving assistance control device for road construction in this application embodiment may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. The driving assistance control device for road construction shown in Figure 7 is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0154] As shown in Figure 7, the auxiliary driving control device for navigating construction roads may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 1002 or a program loaded from storage device 1003 into random access memory (RAM) 1004. RAM 1004 also stores various programs and data required for the operation of the auxiliary driving control device for navigating construction roads. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via bus 1005. Input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the driver assistance control equipment on the construction road to exchange data wirelessly or via wired communication with other devices. Although the figure shows a driver assistance control equipment on a construction road with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems may be implemented alternatively.

[0155] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0156] The assisted driving control device for navigating construction roads provided in this application, employing the assisted driving control method for navigating construction roads described in the above embodiments, can solve the technical problem of inaccurate identification by intelligent driving due to sensors. Compared with the prior art, the beneficial effects of the assisted driving control device for navigating construction roads provided in this application are the same as the beneficial effects of the assisted driving control method for navigating construction roads provided in the above embodiments, and other technical features in this assisted driving control device for navigating construction roads are the same as those disclosed in the method of the previous embodiment, and will not be repeated here.

[0157] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0158] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0159] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the assisted driving control method for traversing a construction road as described in the above embodiments.

[0160] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0161] The aforementioned computer-readable storage medium may be included in the auxiliary driving control device for use on the construction road; or it may exist independently and not be installed in the auxiliary driving control device for use on the construction road.

[0162] The aforementioned computer-readable storage medium carries one or more programs that, when executed by the auxiliary driving control device on the construction road, cause the auxiliary driving control device on the construction road to: acquire cloud-based construction information and perceived road condition information; determine the credibility of the cloud-based construction information based on the perceived road condition information; when the determination result is credible, perform collision prediction for the vehicle based on the perceived road condition information and the cloud-based construction information; and perform auxiliary control for the vehicle when the collision prediction result indicates that a collision may occur.

[0163] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0164] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0165] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0166] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the aforementioned assisted driving control method for navigating construction roads. This solves the technical problem of inaccurate identification by intelligent driving systems caused by sensors. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the assisted driving control method for navigating construction roads provided in the above embodiments, and will not be repeated here.

[0167] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described assisted driving control method for navigating construction roads.

[0168] The computer program product provided in this application can solve the technical problem of inaccurate identification by intelligent driving caused by sensors. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the assisted driving control method for driving through construction roads provided in the above embodiments, and will not be repeated here.

[0169] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for assisted driving control on construction roads, characterized in that, The assisted driving control method for navigating construction roads includes: Obtain construction information and road condition information from the cloud; The credibility of the cloud-based construction information is determined based on the perceived road condition information. When the judgment result is credible, collision prediction is performed on the vehicle based on the perceived road condition information and the cloud construction information. When the collision prediction result indicates that a collision is possible, auxiliary control is applied to the vehicle.

2. The assisted driving control method for navigating construction roads as described in claim 1, characterized in that, The step of determining the credibility of the cloud-based construction information based on the perceived road condition information includes: If the cloud-based construction information identifies traffic control facilities within a preset area ahead of the vehicle, and the perceived road condition information also identifies traffic control facilities within the preset area ahead of the vehicle, then the cloud-based construction information is deemed reliable.

3. The assisted driving control method for navigating construction roads as described in claim 2, characterized in that, After determining whether traffic control facilities exist within the preset area based on the cloud-based construction information when traffic control facilities are detected in the preset area ahead of the vehicle, the method further includes: If the traffic control facility does not exist within the preset area, the cloud-based construction information is determined to be unreliable, and the perceived road condition information is uploaded to update the cloud-based construction information to remove the marker for the traffic control facility.

4. The assisted driving control method for navigating construction roads as described in claim 1, characterized in that, The step of predicting vehicle collisions based on the perceived road condition information and the cloud-based construction information includes: When it is determined that there are traffic control facilities within a first preset distance in front of the vehicle based on the perceived road condition information and the cloud construction information, the vehicle-side judgment is performed on the traffic control facilities. When the traffic control facility is in the lane, the collision prediction result is determined to be a possible collision.

5. The assisted driving control method for navigating construction roads as described in claim 1, characterized in that, The step of providing auxiliary control to the vehicle when the collision prediction result indicates a possible collision includes: When the collision prediction result indicates that a collision is possible, it is determined whether there are traffic control facilities in the adjacent lanes of the vehicle and whether there are lane-changing conditions in the adjacent lanes. When there are no traffic control facilities in the adjacent lane and lane-changing conditions exist in the adjacent lane, the vehicle is controlled to change lanes to the adjacent lane.

6. The assisted driving control method for navigating construction roads as described in claim 5, characterized in that, The method further includes: When there are no traffic control facilities in the adjacent lane and no lane-changing conditions in the adjacent lane, determine whether the vehicle can pass in its own lane; If so, then control the vehicle to decelerate and pass through the lane; If not, then control the vehicle to continuously decelerate and wait for a lane change opportunity.

7. The assisted driving control method for navigating construction roads as described in claim 6, characterized in that, The method further includes: If, during the process of controlling the vehicle to continuously decelerate while waiting for a lane change opportunity, the distance between the vehicle and the merging point is detected to be less than a preset distance, the vehicle is controlled to brake.

8. The assisted driving control method for navigating construction roads as described in claim 5, characterized in that, The method further includes: When traffic control facilities exist in the adjacent lane of the vehicle, the vehicle is controlled to slow down and pass through according to the boundary of the traffic control facilities.

9. The assisted driving control method for navigating construction roads as described in claim 1, characterized in that, The step of providing auxiliary control to the vehicle when the collision prediction result indicates a possible collision includes: When the collision prediction result indicates that a collision is possible, and the adjacent lane of the vehicle is an emergency lane, the vehicle is controlled to slow down and pass according to the boundary of the traffic control facility and the road boundary on the other side.

10. The assisted driving control method for navigating construction roads as described in claim 1, characterized in that, The method further includes: When it is determined that there are traffic control facilities within a first preset distance in front of the vehicle based on the perceived road condition information and the cloud construction information, the vehicle-side judgment is performed on the traffic control facilities. When the traffic control facility is not in the vehicle's lane, the vehicle is controlled to proceed straight through.

11. The assisted driving control method for navigating construction roads as described in claim 1, characterized in that, The method further includes: When it is determined that there are traffic control facilities within a first preset distance in front of the vehicle based on the perceived road condition information and the cloud construction information, the vehicle-side judgment is performed on the traffic control facilities. If the traffic control facility is on the vehicle lane, and there is no traffic control facility in the adjacent lane or on the lane line of the vehicle, then the vehicle is controlled to change lanes to the adjacent lane. If the traffic control facility is on the vehicle lane, and there is a traffic control facility in the adjacent lane or on the lane line of the vehicle, then the vehicle is controlled to proceed straight through.

12. The assisted driving control method for navigating construction roads as described in claim 1, characterized in that, After the step of predicting vehicle collisions based on the perceived road condition information and the cloud-based construction information, the method further includes: When traffic control facilities are in adjacent lanes, the collision prediction result is determined to be a possible collision; Control the vehicle to reduce its speed to a preset range to pass safely.

13. The assisted driving control method for navigating construction roads as described in claim 1, characterized in that, The method further includes: Based on the perceived road condition information, traffic control facilities ahead of the vehicle are identified, and the vehicle's positioning information and the data of the traffic control facilities are obtained. The data includes the construction type of the traffic control facilities, the lateral and longitudinal positions of the traffic control facilities relative to the vehicle, and the lane in which the traffic control facilities are located. The vehicle's location information and the traffic control facility's data are uploaded to the cloud to update the cloud construction information.

14. An auxiliary driving control device for navigating construction roads, characterized in that, The device includes: The information acquisition module is used to acquire construction information from the cloud and road condition information from the sensor. A credibility assessment module is used to assess the credibility of the cloud-based construction information based on the perceived road condition information. The prediction module is used to predict vehicle collisions based on the perceived road condition information and the cloud-based construction information when the judgment result is reliable. The control module is used to provide auxiliary control to the vehicle when the collision prediction result indicates that a collision may occur.

15. An auxiliary driving control device for use on construction roads, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the assisted driving control method for navigating a construction road as described in any one of claims 1 to 13.

16. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the assisted driving control method for traversing a construction road as described in any one of claims 1 to 13.

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