A method for analyzing the road environment

Abstract

This invention relates to a method for analyzing road environments. The method includes: receiving driving trajectories regularly submitted by vehicles during a specified time period each day as corresponding first real-time trajectories; merging the first real-time trajectories with the trajectories received that day to generate the latest first daily trajectory; analyzing all first daily trajectories at the end of the specified time period each day to obtain first road records and storing them in a first road list; analyzing the road complexity of each first monitored road based on the first road list to obtain second road records and storing them in a second road list; sorting active roads by a first visual page and displaying the information of the top five roads at any time each day; and sorting complex roads by a second visual page and displaying the information of the top five roads. This invention allows for regular analysis of the road environment and provides an intuitive global road display and highlighting of key roads based on the analysis results.

Description

Technical Field

[0001] This invention relates to the field of data processing technology, and in particular to a processing method for analyzing road environment. Background Technology

[0002] With the maturity and development of autonomous driving technology, more and more new types of operating vehicles (such as autonomous / driverless taxis, unmanned delivery vehicles, etc.) are being put into operation on the road. In order to improve the traffic efficiency of such vehicles, it is necessary to regularly analyze the road environment (including the number of times the road is active, the road complexity, etc.) of the roads they travel on. Summary of the Invention

[0003] The purpose of this invention is to address the shortcomings of existing technologies by providing a method, electronic device, and computer-readable storage medium for analyzing road environments. This method collects the daily driving trajectories of all vehicles on a daily basis and analyzes the road activity frequency and road complexity of each monitored road based on these trajectories. It provides two visual pages: a first page displays the overall road activity across six time scales and identifies the top five roads; a second page displays the overall road complexity across six time scales and identifies the top five roads. This invention allows for regular analysis of the road environment (road activity frequency, road complexity) of vehicles traveling on roads and provides a clear, intuitive display of the analysis results across different time scales, along with alerts for key roads, enabling operators to monitor the conditions of critical roads promptly.

[0004] To achieve the above objectives, a first aspect of the present invention provides a method for analyzing road environments, the method comprising:

[0005] During a designated time period each day, the driving trajectories regularly uploaded by each vehicle are received as the corresponding first real-time trajectory; and the first real-time trajectory is merged with the trajectory already received that day to generate the latest first daily trajectory.

[0006] At the end of the specified time period each day, based on all the first day's trajectories, the number of road activities, total number of vehicles passing through, total mileage of vehicles passing through, total mileage of autonomous driving vehicles passing through, total driving time of vehicles passing through, total driving time of autonomous driving vehicles passing through, and total number of abnormal driving events of each first monitored road on the preset road map are analyzed to obtain the corresponding first road records, which are stored in a preset first road list; and based on the first road list, the road complexity of each first monitored road is analyzed to obtain the corresponding second road records, which are stored in a preset second road list; the preset road map includes multiple first monitored roads; the first road list includes multiple first road records; and the second road list includes multiple second road records;

[0007] At any time of day, a preset first visual page sorts active roads according to the first road list and displays the information of the top five roads; and a preset second visual page sorts complex roads according to the first and second road lists and displays the information of the top five roads.

[0008] Preferably, the first real-time trajectory includes a first vehicle identifier and multiple first trajectory points; the first trajectory point includes first trajectory point time, first trajectory point coordinates, first trajectory point driving mode, first trajectory point speed, first trajectory point acceleration, and first trajectory point hazard warning light status; the first trajectory point driving mode includes autonomous driving and manual driving; the time interval between sending two first real-time trajectories of the same vehicle is less than the trajectory duration of the first real-time trajectory;

[0009] The first daily trajectory includes a second vehicle identifier and multiple second trajectory points; the second trajectory point includes the second trajectory point time, the second trajectory point coordinates, and the second trajectory point driving mode; the second trajectory point driving mode includes autonomous driving and manual driving.

[0010] The first monitored road includes the name of the first road and the map coordinate range of the first road;

[0011] The first road record includes a first road name field, a first date field, a first number of active events field, a first total number of vehicles field, a first travel mileage field, a first autonomous driving mileage field, a first travel duration field, a first autonomous driving duration field, and a first total number of abnormal events field;

[0012] The second road record includes a second road name field, a second date field, and a first complexity field;

[0013] The first visual page includes a first set of time scale buttons, a first map area, and an active road list area. The first set of time scale buttons includes a first yesterday button, a first last week button, a first last month button, a first last quarter button, a first first half-year button, and a first custom date button. The first map area is used to load the preset road map and includes five example color blocks and corresponding five activity range description texts. The five example color blocks in the first map area include first, second, third, fourth, and fifth color blocks, and the five activity range description texts in the first map area include first, second, third, fourth, and fifth activity ranges. The first, second, third, fourth, and fifth color blocks correspond one-to-one with the first, second, third, fourth, and fifth activity ranges. The active road list area includes five display records, each of which consists of eight fields: serial number, road segment name, activity count, number of vehicles, total mileage, autonomous driving mileage, total duration, and autonomous driving duration.

[0014] The second visual page includes a second set of time scale buttons, a second map area, and a complex road list area. The second set of time scale buttons includes a second yesterday button, a second last week button, a second last month button, a second last quarter button, a second first half-year button, and a second custom date button. The second map area is used to load the preset road map and provides five example color blocks and corresponding five complexity range description texts. The five example color blocks in the second map area include the sixth, seventh, eighth, ninth, and tenth color blocks, and the five complexity range description texts in the second map area include the first, second, third, fourth, and fifth complexity ranges. The sixth, seventh, eighth, ninth, and tenth color blocks correspond one-to-one with the first, second, third, fourth, and fifth complexity ranges, respectively. The complex road list area includes five display records, each of which consists of six fields: serial number, road segment name, total mileage, autonomous driving mileage, total duration, and autonomous driving duration.

[0015] Preferably, the step of merging the first real-time trajectory with the trajectory received on the same day to generate the latest first trajectory for the current day specifically includes:

[0016] The first real-time trajectory is taken as the corresponding current real-time trajectory; and the first trajectory marker of the day whose second vehicle identifier matches the first vehicle identifier of the current real-time trajectory is taken as the corresponding current trajectory of the day.

[0017] The first and second trajectory points that have the same time as the trajectory points in the current real-time trajectory and the current day trajectory are recorded as a pair of paired trajectory points, and the first trajectory point in each pair of trajectory points is used to replace the corresponding second trajectory point;

[0018] All first trajectory points in the current real-time trajectory whose time is later than the time of the last second trajectory point in the current day's trajectory are recorded as new trajectory points; and each of the new trajectory points is added as a new second trajectory point and added to the current day's trajectory in chronological order to generate the latest first day's trajectory.

[0019] Preferably, the step of analyzing the number of road activities, total number of vehicles passing through, total mileage of vehicles passing through, total mileage of autonomous driving of vehicles passing through, total driving time of vehicles passing through, total driving time of autonomous driving of vehicles passing through, and total number of abnormal driving events of each first monitored road on the preset road map based on all the first day's trajectories to obtain the corresponding first road records and storing them in the preset first road list specifically includes:

[0020] Seven counters, initialized to 0, are assigned to each of the first monitored roads: counter 1, counter 2, counter 3, counter 4, counter 5, counter 6, and counter 7. Each of the first monitored roads is used as the corresponding current day's trajectory. The first counter is used to count the number of active events on the corresponding road. The second counter is used to count the total number of vehicle trips on the corresponding road. The third counter is used to count the total driving mileage of all vehicles passing through the corresponding road. The fourth counter is used to count the total autonomous driving mileage of all vehicles passing through the corresponding road. The fifth counter is used to count the total driving time of all vehicles passing through the corresponding road. The sixth counter is used to count the total autonomous driving time of all vehicles passing through the corresponding road. The seventh counter is used to count the total number of abnormal driving events occurring on the corresponding road.

[0021] The coordinates of all the second trajectory points of the current day's trajectory are extracted and sorted in chronological order to form a corresponding first coordinate sequence; duplicate second trajectory point coordinates in the first coordinate sequence are filtered out; multiple first sampling point coordinates are obtained by sampling at intervals of a preset first interval length starting from the first second trajectory point coordinate of the first coordinate sequence; the preset road map is queried, and the first monitored road corresponding to the first road map coordinate range that matches each of the first sampling point coordinates is taken as the corresponding first road; and the first counter of the first road is incremented by 1; wherein, the road length between two adjacent first sampling point coordinates matches the first interval length;

[0022] The system queries the preset road map and extracts the first road name of the first monitored road corresponding to the coordinate range of the first road map that matches the coordinates of the second trajectory points of each second trajectory point in the current day's trajectory. In the current day's trajectory, multiple consecutive second trajectory points with the same first trajectory point road name are extracted to form a corresponding first segment trajectory. A single second trajectory point with a different first trajectory point road name from its preceding and following adjacent second trajectory points is also extracted to form a corresponding first segment trajectory. Within each first segment trajectory, a single or multiple consecutive second trajectory points with the driving mode set to autonomous driving are extracted to form a corresponding second segment trajectory.

[0023] The road name of the first trajectory point corresponding to each of the first segment trajectories is taken as the corresponding segment trajectory road name; and the preset road map is queried, and the first monitored road corresponding to the first road name that matches each of the segment trajectory road names is taken as the corresponding second road; and the second counter of each second road is incremented by 1;

[0024] The coordinates of the first and last second trajectory points of each first segment trajectory are marked as the corresponding first segment start coordinates and first segment end coordinates; the preset road map is queried to obtain the road length from the first segment start coordinates to the first segment end coordinates as the corresponding first segment mileage length L1; and the third counter of the second road corresponding to each first segment trajectory is incremented by L1.

[0025] The coordinates of the first and last second trajectory points of each second segment trajectory are designated as the corresponding second segment start coordinates and second segment end coordinates; the preset road map is queried to obtain the road length from the second segment start coordinate to the second segment end coordinate as the corresponding second segment mileage length L2; and the fourth counter of the second road corresponding to each second segment trajectory is incremented by L2.

[0026] The times of the first and last second trajectory points of each first segment trajectory are recorded as the corresponding first segment start time and first segment end time; the first segment driving time t1 is obtained by subtracting the first segment start time from the first segment end time; and the fifth counter of the second road corresponding to each first segment trajectory is incremented by t1;

[0027] The times of the first and last second trajectory points of each second segment trajectory are recorded as the corresponding second segment start time and second segment end time; the second segment driving time t2 is obtained by subtracting the second segment start time from the second segment end time; and t2 is added to the sixth counter of the second road corresponding to each second segment trajectory.

[0028] Abnormal driving events are identified for each of the first segment trajectories, and the total number of identified abnormal events is counted to generate the corresponding total number of events n for the first segment; and the seventh counter for the second road corresponding to each of the first segment trajectories is incremented by n;

[0029] The first road name corresponding to each of the first monitored roads is used as the corresponding first road name field, the corresponding first counter is used as the corresponding first active count field, the corresponding second counter is used as the corresponding first total vehicle count field, the corresponding third counter is used as the corresponding first travel mileage field, the corresponding fourth counter is used as the corresponding first autonomous driving mileage field, the corresponding fifth counter is used as the corresponding first travel duration field, the corresponding sixth counter is used as the corresponding first autonomous driving duration field, and the corresponding seventh counter is used as the corresponding first total abnormal event field; the date information of any second trajectory point in the current day's trajectory is extracted as the corresponding first date field; and the first road name field, first date field, first active count field, first total vehicle count field, first travel mileage field, first autonomous driving mileage field, first travel duration field, first autonomous driving duration field, and first total abnormal event field are combined to form the corresponding first road record and stored in the preset first road list.

[0030] Furthermore, the step of identifying abnormal driving events in each of the first segment trajectories and generating a corresponding total number n of events for the first segment by statistically analyzing the total number of identified abnormal events specifically includes:

[0031] Based on seven preset abnormal event recognition models, the first segmented trajectory is processed to obtain seven types of recognition results; the seven abnormal event recognition models include an autonomous driving exit abnormal event recognition model, an emergency braking abnormal event recognition model, an ultra-low speed abnormal event recognition model, an overspeed abnormal event recognition model, a dangerous state abnormal event recognition model, an autonomous driving disengagement abnormal event recognition model, and a collision level event recognition model; the seven types of recognition results include the first, second, third, fourth, fifth, sixth, and seventh recognition results; the first recognition result corresponds to the autonomous driving exit abnormal event recognition model, including no abnormality and autonomous driving exit abnormality; The second identification result corresponds to the emergency braking abnormal event identification model, including no abnormality and emergency braking abnormality; the third identification result corresponds to the ultra-low speed abnormal event identification model, including no abnormality and ultra-low speed abnormality; the fourth identification result corresponds to the speeding abnormal event identification model, including no abnormality and speeding abnormality; the fifth identification result corresponds to the dangerous state abnormal event identification model, including no abnormality and dangerous state abnormality; the sixth identification result corresponds to the autonomous driving disengagement abnormal event identification model, including no abnormality and autonomous driving disengagement abnormality; the seventh identification result corresponds to the collision level event identification model, including no abnormality and abnormal collision level.

[0032] The number of non-abnormal identification results among the seven categories of identification results is counted to generate the corresponding total number of abnormal events; and the obtained total number of abnormal events is used as the corresponding total number of events n in the first segment.

[0033] Preferably, the step of analyzing the road complexity of each of the first monitored roads according to the first road list to obtain the corresponding second road record and storing it in a preset second road list specifically includes:

[0034] Extract the first date field of the latest first road record in the first road list as the corresponding first date; mark all first road records in the first road list whose first date field satisfies the first date as road records of the current day; and generate a corresponding first total M by counting the total number of road records of the current day.

[0035] The first travel mileage field, the first autonomous driving mileage field, the first travel duration field, the first autonomous driving duration field, and the first total number of abnormal events field of each of the daily road records are extracted to form a first road vector of shape 1×5; and the first road vector of the obtained first total number M is used to form a first road tensor of shape M×5; and the first road tensor is processed based on a preset road complexity prediction model to obtain a corresponding first complexity vector of shape M×1; the first complexity vector includes the first road complexity of the first total number M;

[0036] The first road name field, the first date field, and the corresponding first road complexity of each road record for that day are used as the corresponding second road name field, the second date field, and the first complexity field to form the corresponding second road record, which is then stored in a preset second road list.

[0037] Preferably, the step of sorting active roads according to the first road list and displaying the information of the top five roads by a preset first visual page specifically includes:

[0038] Load the first visual page; and use the button selected by the user in the first group of time scale buttons on the first visual page as the corresponding first button;

[0039] The first button is identified; if the first button is the first yesterday button, the date information of the current system time is extracted as the corresponding current date, and the date information of yesterday is determined according to the current date to obtain the corresponding yesterday date, and the yesterday date is used as the corresponding first time period range; if the first button is the first last week button, the date information of the current system time is extracted as the corresponding current date, and the start date and end date information of the previous week are determined according to the current date to obtain the corresponding last week date range, and the last week date range is used as the corresponding first time period range; if the first button is the first last month button, the date information of the current system time is extracted as the corresponding current date, and the start date and end date information of the previous month are determined according to the current date to obtain the corresponding last month date range, and the last month date range is used as the corresponding first time period range; if the... If the first button is the "Previous Quarter" button, the current system time date information is extracted as the corresponding current day date. Based on the current day date, the start and end dates of the previous quarter are determined to obtain the corresponding previous quarter date range, and this previous quarter date range is used as the corresponding first time period range. If the first button is the "First Half-Year" button, the current system time date information is extracted as the corresponding current day date. Based on the current day date, the start and end dates of the first half of the year are determined to obtain the corresponding first half-year date range, and this first half-year date range is used as the corresponding first time period range. If the first button is the "Custom Date" button, a calendar display pop-up is provided to the user, and the user confirms the input start and end dates on the calendar display pop-up to form the corresponding custom date range, and this custom date range is used as the corresponding first time period range.

[0040] Extract the first road records from the first road list whose first date field satisfies the first time period range to form a corresponding first record set; cluster the first road records in the first record set according to road name, and cluster the first road records with the same first road name field into a corresponding second record set; calculate the average of all first active count fields in each second record set to generate a corresponding first average active count, calculate the average of all first total vehicle count fields to generate a corresponding first average total vehicle count, calculate the average of all first travel mileage fields to generate a corresponding first average total mileage, calculate the average of all first autonomous driving mileage fields to generate a corresponding first average total autonomous driving mileage, calculate the average of all first travel time fields to generate a corresponding first average total time, and calculate the average of all first autonomous driving time fields to generate a corresponding first average total autonomous driving time; and combine the first road name field, first average active count, first average total vehicle count, first average total mileage, and first average autonomous driving time corresponding to each second record set. The total mileage of autonomous driving, the first average total time, and the first average total time of autonomous driving constitute the corresponding first road average record; and the corresponding example color block is determined as the corresponding first road color based on the correspondence between the first average number of active activities of each first road average record and the first, second, third, fourth, or fifth number range; and the road display color of the corresponding first monitored road is set on the loaded map of the first map area of ​​the first visual page based on the first road color; and all the obtained first road average records are sorted in descending order of the first average number of active activities to generate the corresponding first record sequence; and the display content of the road segment name, number of active activities, number of vehicles, total mileage, first average total mileage, first average total autonomous driving mileage, first average total time, and first average total time of autonomous driving of the first five first road average records in the first record sequence is set for the road segment name, number of active activities, number of vehicles, total mileage, autonomous driving mileage, total time, and autonomous driving time fields of the five corresponding display records in the active road list area of ​​the first visual page.

[0041] Preferably, the step of using a preset second visual page to perform complex road sorting based on the first and second road lists and displaying the information of the top five roads specifically includes:

[0042] Load the second visual page; and use the button selected by the user in the second group of time scale buttons on the second visual page as the corresponding second button;

[0043] The second button is identified; if the second button is the second yesterday button, the date information of the current system time is extracted as the corresponding current date, and the date information of yesterday is determined based on the current date to obtain the corresponding yesterday date, and the yesterday date is used as the corresponding second time period range; if the second button is the second last week button, the date information of the current system time is extracted as the corresponding current date, and the start date and end date information of the previous week are determined based on the current date to obtain the corresponding last week date range, and the last week date range is used as the corresponding second time period range; if the second button is the second last month button, the date information of the current system time is extracted as the corresponding current date, and the start date and end date information of the previous month are determined based on the current date to obtain the corresponding last month date range, and the last month date range is used as the corresponding second time period range; if the... If the second button is the second "Previous Quarter" button, the current system time date information is extracted as the corresponding current date, and the start and end dates of the previous quarter are determined based on the current date to obtain the corresponding previous quarter date range, which is then used as the corresponding second time period range. If the second button is the second "First Half of the Year" button, the current system time date information is extracted as the corresponding current date, and the start and end dates of the first half of the year are determined based on the current date to obtain the corresponding first half of the year date range, which is then used as the corresponding second time period range. If the second button is the second "Custom Date" button, a calendar display pop-up is provided to the user, and the user confirms the input start and end dates on the calendar display pop-up to form the corresponding custom date range, which is then used as the corresponding second time period range.

[0044] The first road records in the first road list whose first date field satisfies the second time period range are extracted to form a corresponding third record set; the first road records in the third record set are clustered by road name, and the first road records with the same first road name field are clustered into a corresponding fourth record set; the average of all first travel mileage fields in each of the fourth record sets is calculated to generate a corresponding second average total mileage, the average of all first autonomous driving mileage fields is calculated to generate a corresponding second average total autonomous driving mileage, the average of all first travel time fields is calculated to generate a corresponding second average total time, and the average of all first autonomous driving time fields is calculated to generate a corresponding second average total autonomous driving time; and the first road name field, the second average total mileage, the second average total autonomous driving mileage, the second average total time, and the second average total autonomous driving time corresponding to each of the fourth record sets are used to form a corresponding second road average record;

[0045] Extract the second road records from the second road list whose second date field satisfies the second time period range to form a corresponding fifth record set; cluster the second road records in the fifth record set according to road name, and group the second road records with the same second road name field into a corresponding sixth record set; calculate the mean of all the first complexity fields in each of the sixth record sets to generate a corresponding first average complexity; and form a corresponding third road average record by combining the second road name field and the first average complexity of each of the sixth record sets; the third road average record corresponds one-to-one with the second road average record.

[0046] The corresponding second and third road average records are merged to generate a corresponding fourth road average record. The fourth road average record includes a third road name, a third average total mileage, a third average total autonomous driving mileage, a third average total time, a third average total autonomous driving time, and a second average complexity. The third road name is consistent with the first road name field of the corresponding second road average record and the second road name field of the corresponding third road average record. The third average total mileage, the third average total autonomous driving mileage, the third average total time, and the third average total autonomous driving time are respectively the second average total mileage, the second average total autonomous driving mileage, the second average total time, and the second average total autonomous driving time of the corresponding second road average record. The second average complexity is the first average complexity of the corresponding third road average record.

[0047] Based on the correspondence between the second average complexity of each of the fourth road average records and the first, second, third, fourth, or fifth complexity ranges, a corresponding example color block is determined as the corresponding second road color; and on the loaded map of the second map area of ​​the second visual page, the road display color of the corresponding first monitored road is set based on the second road color; and all the obtained fourth road average records are sorted in descending order of the second average complexity to generate a corresponding second record sequence; and based on the third road name, third average total mileage, third average total autonomous driving mileage, third average total time, and third average total autonomous driving time of the top five fourth road average records in the second record sequence, the display content of the road segment name, total mileage, autonomous driving mileage, total time, and autonomous driving time fields of the five corresponding display records in the complex road list area of ​​the second visual page is set.

[0048] A second aspect of the present invention provides an electronic device, including: a memory, a processor, and a transceiver;

[0049] The processor is used to couple with the memory, read and execute instructions in the memory to implement the steps of the method described in the first aspect above;

[0050] The transceiver is coupled to the processor, and the processor controls the transceiver to send and receive messages.

[0051] A third aspect of the present invention provides a computer-readable storage medium storing computer instructions that, when executed by a computer, cause the computer to perform the instructions described in the first aspect.

[0052] This invention provides a method, electronic device, and computer-readable storage medium for analyzing road environments. It collects the daily driving trajectories of all vehicles on a daily basis and analyzes the road activity frequency and road complexity of each monitored road based on these trajectories. Two visual pages are provided: a first page displays the overall road activity at six time scales and shows the top five roads; a second page displays the overall road complexity at six time scales and shows the top five roads. This invention achieves the technical goal of periodically analyzing the road environment (road activity frequency, road complexity) and adds a technical means to intuitively display the overall road conditions and key road conditions at different time scales, helping to improve operators' attention to key roads. Attached Figure Description

[0053] Figure 1 This is a schematic diagram of a method for analyzing the road environment provided in Embodiment 1 of the present invention;

[0054] Figure 2 This is a schematic diagram of the first visual page provided in Embodiment 1 of the present invention;

[0055] Figure 3 This is a schematic diagram of the second visible page provided in Embodiment 1 of the present invention;

[0056] Figure 4 This is a schematic diagram of the structure of an electronic device provided in Embodiment 2 of the present invention. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely 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 are within the scope of protection of this invention.

[0058] Embodiment 1 of the present invention provides a processing method for analyzing the road environment, which can periodically analyze the road environment (road activity frequency, road complexity) of the road through which vehicles pass, and can intuitively display the analysis results as a whole road and highlight key roads according to different time scales; Figure 1 This is a schematic diagram of a method for analyzing the road environment provided in Embodiment 1 of the present invention, as shown below. Figure 1 As shown, this method mainly includes the following steps:

[0059] Step 1: During a designated time period each day, receive the driving trajectories regularly uploaded by each vehicle as the corresponding first real-time trajectory; and merge the first real-time trajectory with the trajectory already received that day to generate the latest first daily trajectory.

[0060] The first real-time trajectory includes a first vehicle identifier and multiple first trajectory points; each first trajectory point includes the first trajectory point time, first trajectory point coordinates, first trajectory point driving mode, first trajectory point speed, first trajectory point acceleration, and first trajectory point hazard warning light status; the first trajectory point driving mode includes autonomous driving and manual driving; the time interval between sending two consecutive first real-time trajectories of the same vehicle is less than the trajectory duration of the first real-time trajectory;

[0061] The first daily trajectory includes a second vehicle identifier and multiple second trajectory points; the second trajectory point includes the second trajectory point time, the second trajectory point coordinates, and the second trajectory point driving mode; the second trajectory point driving mode includes autonomous driving and manual driving.

[0062] Specifically, it includes: Step 11, receiving the driving trajectory regularly uploaded by each vehicle during a specified time period each day as the corresponding first real-time trajectory;

[0063] Here, the designated daily time period is a pre-set data collection period, which can default to 00:00 of the current day to 00:00 of the next day; each vehicle in this embodiment of the invention is a vehicle equipped with an on-board device that can periodically upload its driving trajectory through the on-board device, and each vehicle corresponds to a unique vehicle number, i.e., the first vehicle identifier; the first real-time trajectory is the driving trajectory of the corresponding vehicle in a recent period of time, which includes multiple trajectory points, i.e., first trajectory points, and each first trajectory point corresponds to a set of collected information, wherein: the first trajectory point time is the corresponding data collection time, the first trajectory point coordinates are the corresponding vehicle positioning coordinates, and the first trajectory point driving mode is the driving mode of the vehicle at the current trajectory point, including self-driving mode. For both autonomous and manual driving, the speed at the first trajectory point is the real-time vehicle speed at the current trajectory point, the acceleration at the first trajectory point is the real-time acceleration at the current trajectory point, and the hazard warning light status at the first trajectory point is the status of the vehicle's hazard warning lights at the current trajectory point, including whether they are on or off. It should be noted that the time interval between two adjacent first trajectory points in the first real-time trajectory is fixed and related to a preset sampling frequency. In addition, the time interval between each vehicle uploading the first real-time trajectory is also fixed and related to a preset uploading frequency. Furthermore, the trajectory duration of the first real-time trajectory uploaded by each vehicle must be greater than the uploading time interval to ensure the robustness of subsequent steps in stitching together the first day's trajectory.

[0064] Step 12: Merge the first real-time trajectory with the trajectory received that day to generate the latest first trajectory for that day;

[0065] Specifically, this includes: step 121, taking the current first real-time trajectory as the corresponding current real-time trajectory; and taking the first day trajectory marker that matches the second vehicle identifier with the first vehicle identifier of the current real-time trajectory as the corresponding current day trajectory marker;

[0066] Step 122: Record the first and second trajectory points with the same time as the current real-time trajectory and the trajectory point in the current day as a pair of paired trajectory points, and replace the corresponding second trajectory point with the first trajectory point in each pair of trajectory points;

[0067] Step 123: Record all first trajectory points in the current real-time trajectory whose time is later than the time of the last second trajectory point in the current day's trajectory as newly added trajectory points; and add each newly added trajectory point as a newly added second trajectory point to the current day's trajectory in chronological order to generate the latest first day's trajectory.

[0068] For example, if the current daily trajectory has already saved trajectory point information for 100 time points (time 1 to time 100), and the current real-time trajectory includes trajectory point information from time 95 to time 105, then step 12 will use the trajectory point information from time 95 to time 100 of the current real-time trajectory to replace the trajectory point information from time 95 to time 100 in the current daily trajectory, and will add the trajectory point information from time 101 to time 105 of the current real-time trajectory to the end of the current daily trajectory, so that the current daily trajectory stores trajectory point information for 105 time points (time 1 to time 105).

[0069] Step 2: At the end of the designated time period each day, based on all the first day's trajectories, analyze the number of road activities, total number of vehicles passing through, total mileage of vehicles passing through, total mileage of autonomous driving vehicles passing through, total driving time of vehicles passing through, total driving time of autonomous driving vehicles passing through, and total number of abnormal driving events for each first monitored road on the preset road map to obtain the corresponding first road records and store them in the preset first road list; and based on the first road list, analyze the road complexity of each first monitored road to obtain the corresponding second road records and store them in the preset second road list;

[0070] The preset road map includes multiple first-monitored roads; each first-monitored road includes its name and the coordinate range of its map.

[0071] The first road list includes multiple first road records; each first road record includes a first road name field, a first date field, a first number of active times field, a first total number of vehicles field, a first travel mileage field, a first autonomous driving mileage field, a first travel duration field, a first autonomous driving duration field, and a first total number of abnormal events field.

[0072] The second road list includes multiple second road records; each second road record includes a second road name field, a second date field, and a first complexity field.

[0073] Specifically, step 21 involves analyzing the number of active road activities, total number of passing vehicles, total mileage of passing vehicles, total mileage of autonomous driving of passing vehicles, total driving time of passing vehicles, total driving time of autonomous driving of passing vehicles, and total number of abnormal driving events of each first monitored road on the preset road map based on all first daily trajectories to obtain the corresponding first road records and storing them in the preset first road list.

[0074] Specifically, this includes: Step 211, assigning seven counters initialized to 0 to each of the first monitored roads, namely the first, second, third, fourth, fifth, sixth and seventh counters; and taking any one of the first daily trajectories as the corresponding current daily trajectory;

[0075] The system includes: a first counter to count the number of active times on the corresponding road; a second counter to count the total number of times all vehicles pass through the corresponding road; a third counter to count the total driving mileage of all vehicles passing through the corresponding road; a fourth counter to count the total autonomous driving mileage of all vehicles passing through the corresponding road; a fifth counter to count the total driving time of all vehicles passing through the corresponding road; a sixth counter to count the total autonomous driving time of all vehicles passing through the corresponding road; and a seventh counter to count the total number of abnormal driving events that occur on all vehicles passing through the corresponding road.

[0076] Step 212: Extract the coordinates of all second trajectory points of the current day's trajectory, sort them in chronological order to form a corresponding first coordinate sequence; filter out duplicate second trajectory point coordinates in the first coordinate sequence; sample multiple first sampling point coordinates starting from the first second trajectory point coordinate of the first coordinate sequence at preset first interval length; query a preset road map, and select the first monitored road corresponding to the first road map coordinate range that matches each first sampling point coordinate as the corresponding first road; and increment the first counter of the first road by 1.

[0077] Among them, the road length between two adjacent first sampling point coordinates matches the first interval length;

[0078] Here, the preset road map in this embodiment of the invention is the road map of the current monitored area; the first interval length is a preset length; in this embodiment of the invention, the first interval length is used as a reference for counting the number of road activities. If the first interval length of the most recent traveled by a vehicle is all on the same road, the activity count counter for that road, i.e., the first counter, will only be incremented by 1. If the first interval length of the most recent traveled by a vehicle crosses two or more roads, the activity count counters for the first and last roads, i.e., the first counter, will only be incremented by 1. Based on this method of counting the number of road activities in this embodiment of the invention, the longer the road and the more intersections, the higher the corresponding number of road activities.

[0079] Step 213: Query the preset road map, extract the first road name of the first monitored road corresponding to the first road map coordinate range that matches the coordinates of each second trajectory point of the current day's trajectory, and use it as the corresponding first trajectory point road name; in the current day's trajectory, extract multiple consecutive second trajectory points with the same first trajectory point road name to form a corresponding first segment trajectory, and also extract a single second trajectory point whose first trajectory point road name is different from the first trajectory points adjacent to it to form a corresponding first segment trajectory; in each first segment trajectory, extract a single or multiple consecutive second trajectory points whose driving mode is autonomous driving to form a corresponding second segment trajectory.

[0080] Here, the number of first-segment trajectories generated depends on the number of roads the vehicle passes through during the day's driving. Each first-segment trajectory is actually a single driving trajectory of the vehicle on one of the roads. Each first-segment trajectory may contain one or more second-segment trajectories. Each second-segment trajectory is actually a single driving trajectory of the vehicle when it activates autonomous driving during its driving on this monitored road.

[0081] For example, if vehicle A's travel path on a given day is from road A to road B and then back from road B to road A, then three first-segment trajectories will be generated: first-segment trajectory A1, first-segment trajectory B, and first-segment trajectory A2. Assume the time period of the trajectory point of first-segment trajectory A1 is time a1-a... 100 During the time period, and during the journey, vehicle A is at time a1-a 10 The time period adopts automatic driving, time a 11 -a 90 The time period adopts manual driving, time a 91 -a 100 If the time period switches back to autonomous driving, then two second-segment trajectories can be decomposed from the first segment trajectory A1: a1-a 10 The second segment trajectory 1 and time a of the time period 91 -a 100 The second segment trajectory of the time period 2;

[0082] Step 214: Take the road name of the first trajectory point corresponding to each first segment trajectory as the corresponding segment trajectory road name; query the preset road map, take the first monitoring road corresponding to the first road name that matches the road name of each segment trajectory as the corresponding second road; and increment the second counter of each second road by 1.

[0083] Here, in this embodiment of the invention, the statistics of passing vehicle parameters for each road are performed by the number of passing vehicles, rather than by the passing vehicles themselves;

[0084] For example, if the same vehicle passes through the same road 3 times at 3 different time periods, then 3 corresponding first segment trajectories will be generated, and the second counter for that road will be incremented by 1 3 times.

[0085] Step 215: Mark the coordinates of the first and last second trajectory points of each first segment trajectory as the corresponding first segment start coordinates and first segment end coordinates; query the preset road map to obtain the road length from the first segment start coordinates to the first segment end coordinates as the corresponding first segment mileage length L1; and increment the third counter of the second road corresponding to each first segment trajectory by L1.

[0086] Here, in the embodiments of the present invention, when calculating the total driving mileage of all vehicles passing through each road, the actual calculation is to sum the trajectory lengths (mileage lengths) of all first segment trajectories on each road;

[0087] Step 216: Mark the coordinates of the first and last second trajectory points of each second segment trajectory as the corresponding second segment start coordinates and second segment end coordinates; query the preset road map to obtain the road length from the second segment start coordinates to the second segment end coordinates as the corresponding second segment mileage length L2; and increment the fourth counter of the second road corresponding to each second segment trajectory by L2.

[0088] Here, in the embodiments of the present invention, when calculating the total autonomous driving mileage of all vehicles passing through each road, the actual calculation is to sum the trajectory lengths (mileage lengths) of all second segment trajectories on each road;

[0089] Step 217: Record the first trajectory point time of the first and last second trajectory points of each first segment trajectory as the corresponding first segment start time and first segment end time; and obtain the corresponding first segment driving time t1 by subtracting the first segment start time from the first segment end time; and increment the fifth counter of the second road corresponding to each first segment trajectory by t1;

[0090] Here, in the embodiments of the present invention, when calculating the total driving time of all vehicles passing through each road, the actual calculation is to sum the trajectory times of all first segment trajectories on each road;

[0091] Step 218: Record the time of the first trajectory point of the first and last second trajectory points of each second segment trajectory as the corresponding second segment start time and second segment end time; and obtain the corresponding second segment driving time t2 by subtracting the second segment start time from the second segment end time; and add t2 to the sixth counter of the second road corresponding to each second segment trajectory.

[0092] Here, in the embodiments of the present invention, when calculating the total autonomous driving time of all vehicles passing through each road, the actual calculation is to sum the trajectory times of all second segment trajectories on each road;

[0093] Step 219: Identify abnormal driving events for each first segment trajectory and generate the corresponding first segment event total n by counting the total number of identified abnormal events; and increment the seventh counter of the second road corresponding to each first segment trajectory by n.

[0094] Specifically, it includes: step 2191, identifying abnormal driving events for each first segment trajectory and generating the corresponding first segment event total number n by statistically analyzing the total number of identified abnormal events;

[0095] Specifically, it includes: step 21911, based on the preset seven types of abnormal event recognition models, the first segment trajectory is identified and processed to obtain seven types of recognition results;

[0096] The seven types of abnormal event recognition models include: autonomous driving exit abnormal event recognition model, emergency braking abnormal event recognition model, ultra-low speed abnormal event recognition model, speeding abnormal event recognition model, dangerous state abnormal event recognition model, autonomous driving disengagement abnormal event recognition model, and collision level event recognition model. The seven types of recognition results include the first, second, third, fourth, fifth, sixth, and seventh recognition results. The first recognition result corresponds to the autonomous driving exit abnormal event recognition model, including no abnormality and autonomous driving exit abnormality; the second recognition result corresponds to the emergency braking abnormal event recognition model, including no abnormality and emergency braking abnormality; the third recognition result corresponds to the ultra-low speed abnormal event recognition model, including no abnormality and ultra-low speed abnormality; the fourth recognition result corresponds to the speeding abnormal event recognition model, including no abnormality and speeding abnormality; the fifth recognition result corresponds to the dangerous state abnormal event recognition model, including no abnormality and dangerous state abnormality; the sixth recognition result corresponds to the autonomous driving disengagement abnormal event recognition model, including no abnormality and autonomous driving disengagement abnormality; and the seventh recognition result corresponds to the collision level event recognition model, including no abnormality and abnormal collision level.

[0097] Here, in this embodiment of the invention, seven types of abnormal event recognition models are pre-constructed according to the proposed seven types of abnormal event definition rules: autonomous driving exit abnormal event recognition model, emergency braking abnormal event recognition model, ultra-low speed abnormal event recognition model, speeding abnormal event recognition model, dangerous state abnormal event recognition model, autonomous driving disengagement abnormal event recognition model, and collision level event recognition model; and each abnormal event recognition model performs abnormal event analysis on a single driving trajectory of a vehicle on a certain road, i.e., the first segment trajectory.

[0098] The following is a brief explanation of the abnormal event definition rules for the seven types of abnormal event recognition models: 1) The autonomous driving exit abnormal event recognition model generates an autonomous driving exit abnormality whenever a state switch from autonomous driving to manual driving is detected in the trajectory during abnormal event analysis of the first segment trajectory; 2) The emergency braking abnormal event recognition model considers situations where the deceleration acceleration exceeds a specified threshold at multiple consecutive moments, with some instances of excessively large deceleration acceleration, as emergency braking abnormalities; 3) The ultra-low speed abnormal event recognition model considers situations where the vehicle speed is within a specified low-speed threshold range and lower than the average speed of surrounding vehicles at multiple consecutive moments during abnormal event analysis of the first segment trajectory as ultra-low speed abnormalities; 4) Speeding abnormal events. When analyzing abnormal events in the first segment trajectory, the identification model considers situations where the vehicle speed exceeds a specified threshold at multiple consecutive moments as speeding anomalies; 5) When analyzing abnormal events in the first segment trajectory, the dangerous state anomaly identification model considers situations where the hazard warning light is on at multiple consecutive moments as dangerous state anomalies; 6) When analyzing abnormal events in the first segment trajectory, the autonomous driving disengagement anomaly identification model considers situations where the speed remains above a specified threshold after switching from autonomous driving mode to manual driving mode as autonomous driving disengagement anomalies; 7) When analyzing abnormal events in the first segment trajectory, the collision level event identification model identifies whether a collision has occurred and confirms the corresponding collision level based on changes in deceleration and acceleration at multiple consecutive time points.

[0099] Step 21912: Count the number of identification results that are not without anomalies among the seven categories of identification results to generate the corresponding total number of abnormal events; and use the obtained total number of abnormal events as the corresponding total number of events n in the first segment.

[0100] Step 2192: Increment n on the seventh counter of the second road corresponding to each first segment trajectory;

[0101] Step 220: The first road name corresponding to each first monitored road is used as the corresponding first road name field; the first counter is used as the corresponding first active count field; the second counter is used as the corresponding first total vehicle count field; the third counter is used as the corresponding first travel mileage field; the fourth counter is used as the corresponding first autonomous driving mileage field; the fifth counter is used as the corresponding first travel duration field; the sixth counter is used as the corresponding first autonomous driving duration field; and the seventh counter is used as the corresponding first total abnormal event field. The date information of any second trajectory point in the current day's trajectory is extracted as the corresponding first date field. The first road record, composed of the obtained first road name field, first date field, first active count field, first total vehicle count field, first travel mileage field, first autonomous driving mileage field, first travel duration field, first autonomous driving duration field, and first total abnormal event field, is stored in a preset first road list.

[0102] Step 22: Analyze the road complexity of each first monitored road according to the first road list to obtain the corresponding second road record and store it in the preset second road list;

[0103] Specifically, this includes: Step 221, extracting the first date field of the latest first road record in the first road list as the corresponding first date; marking all first road records in the first road list whose first date field satisfies the first date as road records of that day; and generating a corresponding first total number M by calculating the total number of road records of that day;

[0104] Step 222: Extract the first travel mileage field, first autonomous driving mileage field, first travel duration field, first autonomous driving duration field, and first total number of abnormal events field from each day's road records to form a first road vector of shape 1×5; and form a first road tensor of shape M×5 from the first road vector of the obtained first total M; and perform road complexity processing on the first road tensor based on the preset road complexity prediction model to obtain the corresponding first complexity vector of shape M×1;

[0105] The first complexity vector includes the first road complexity of the first total number M;

[0106] Here, in this embodiment of the invention, a pre-trained and mature artificial intelligence model based on a multilayer perceptron (MLP) neural network, namely a road complexity prediction model, is used to predict road complexity. The data dimensions of the model input tensor include: total mileage, autonomous driving mileage, total duration, autonomous driving duration, and total number of abnormal events. The data dimension of the model output vector includes a complexity.

[0107] Step 223: The first road name field, the first date field, and the corresponding first road complexity of each road record for that day are used as the corresponding second road name field, second date field, and first complexity field to form the corresponding second road record and stored in the preset second road list.

[0108] Step 3: At any time of day, the preset first visual page sorts active roads according to the first road list and displays the information of the top five roads; and the preset second visual page sorts complex roads according to the first and second road lists and displays the information of the top five roads.

[0109] Specifically, this includes: Step 31, at any time of day, the preset first visual page sorts the active roads according to the first road list and displays the information of the top five roads;

[0110] Among them, such as Figure 2 As shown in the schematic diagram of the first visual page provided in Embodiment 1 of the present invention, the first visual page includes a first set of time scale buttons, a first map area, and an active road list area; the first set of time scale buttons includes a first yesterday button, a first last week button, a first last month button, a first last quarter button, a first first half-year button, and a first custom date button; the first map area is used to load a preset road map and includes five example color blocks and corresponding five active frequency range description texts; the five example color blocks in the first map area include first, second, third, fourth, and fifth color blocks, and the five active frequency range description texts in the first map area include first, second, third, fourth, and fifth frequency ranges, with the first, second, third, fourth, and fifth color blocks corresponding one-to-one with the first, second, third, fourth, and fifth frequency ranges; the active road list area includes 5 display records, each display record consisting of eight fields: serial number, road segment name, active frequency, number of vehicles, total mileage, autonomous driving mileage, total duration, and autonomous driving duration;

[0111] Specifically, this includes: step 311, loading the first visual page; and using the button selected by the user in the first group of time scale buttons on the first visual page as the corresponding first button;

[0112] Step 312: Identify the first button; if the first button is the first yesterday button, extract the date information of the current system time as the corresponding current date, and determine the date information of yesterday based on the current date to obtain the corresponding yesterday date, and use the yesterday date as the corresponding first time period range; if the first button is the first last week button, extract the date information of the current system time as the corresponding current date, and determine the start date and end date information of the previous week based on the current date to obtain the corresponding last week date range, and use the last week date range as the corresponding first time period range; if the first button is the first last month button, extract the date information of the current system time as the corresponding current date, and determine the start date and end date information of the previous month based on the current date to obtain the corresponding last month date range, and use the last month date range as the corresponding first time period range. If the first button is the "First Previous Quarter" button, the current system time date information is extracted as the corresponding current date, and the start and end dates of the previous quarter are determined based on the current date to obtain the corresponding previous quarter date range, which is then used as the corresponding first time period range. If the first button is the "First First Half of the Year" button, the current system time date information is extracted as the corresponding current date, and the start and end dates of the first half of the year are determined based on the current date to obtain the corresponding first half of the year date range, which is then used as the corresponding first time period range. If the first button is the "First Custom Date" button, a calendar display pop-up is provided to the user, and the user confirms the entered start and end dates on the calendar display pop-up to form the corresponding custom date range, which is then used as the corresponding first time period range.

[0113] Step 313: Extract the first road records in the first road list whose first date field meets the first time period range to form a corresponding first record set; cluster the first road records in the first record set according to road name, and cluster the first road records with the same first road name field into a corresponding second record set; calculate the average of all first active times fields in each second record set to generate the corresponding first average active times, calculate the average of all first total vehicle fields to generate the corresponding first average total vehicle number, calculate the average of all first travel mileage fields to generate the corresponding first average total mileage, calculate the average of all first autonomous driving mileage fields to generate the corresponding first average total autonomous driving mileage, calculate the average of all first travel time fields to generate the corresponding first average total time, and calculate the average of all first autonomous driving time fields to generate the corresponding first average total autonomous driving time; and use the first road name field, first average active times, first average total vehicle number, first average total mileage, and first time period range corresponding to each second record set to form a corresponding second record set. The first average total autonomous driving mileage, the first average total time, and the first average total autonomous driving time constitute the corresponding first road average record; and the corresponding example color block is determined as the corresponding first road color based on the correspondence between the first average number of active events of each first road average record and the range of the first, second, third, fourth, or fifth number of events; and the road display color of the corresponding first monitored road is set on the loaded map of the first map area of ​​the first visual page based on the first road color; and the first record sequence is generated by sorting all the obtained first road average records in descending order of the first average number of active events; and the display content of the road segment name, number of active events, number of vehicles, total mileage, first average total autonomous driving mileage, first average total time, and first average total autonomous driving time of the top five first road average records in the first record sequence is set for the display content of the road segment name, number of active events, number of vehicles, total mileage, autonomous driving mileage, total time, and autonomous driving time fields of the five corresponding display records in the active road list area of ​​the first visual page;

[0114] Step 32: The preset second visual page sorts the complex roads according to the first and second road lists and displays the information of the top five roads.

[0115] Among them, such as Figure 3As shown in the schematic diagram of the second visual page provided in Embodiment 1 of the present invention, the second visual page includes a second set of time scale buttons, a second map area, and a complex road list area; the second set of time scale buttons includes a second yesterday button, a second last week button, a second last month button, a second last quarter button, a second first half-year button, and a second custom date button; the second map area is used to load a preset road map and provides five example color blocks and corresponding five complexity range description texts; the five example color blocks in the second map area include the sixth, seventh, eighth, ninth, and tenth color blocks, and the five complexity range description texts in the second map area include the first, second, third, fourth, and fifth complexity ranges, with the sixth, seventh, eighth, ninth, and tenth color blocks corresponding one-to-one with the first, second, third, fourth, and fifth complexity ranges; the complex road list area includes five display records, each display record consisting of six fields: serial number, road segment name, total mileage, autonomous driving mileage, total duration, and autonomous driving duration;

[0116] Specifically, this includes: step 321, loading the second visual page; and using the button selected by the user in the second group of time scale buttons on the second visual page as the corresponding second button;

[0117] Step 322: Identify the second button; if the second button is the second yesterday button, extract the date information of the current system time as the corresponding current date, and determine the date information of yesterday based on the current date to obtain the corresponding yesterday date, and use yesterday date as the corresponding second time period range; if the second button is the second last week button, extract the date information of the current system time as the corresponding current date, and determine the start date and end date information of the previous week based on the current date to obtain the corresponding last week date range, and use last week date range as the corresponding second time period range; if the second button is the second last month button, extract the date information of the current system time as the corresponding current date, and determine the start date and end date information of the previous month based on the current date to obtain the corresponding last month date range, and use last month date range as the corresponding second time period range. If the second button is the "Second Previous Quarter" button, the current system time date information is extracted as the corresponding current date, and the start and end dates of the previous quarter are determined based on the current date to obtain the corresponding previous quarter date range, which is then used as the corresponding second time period range. If the second button is the "Second First Half of the Year" button, the current system time date information is extracted as the corresponding current date, and the start and end dates of the first half of the year are determined based on the current date to obtain the corresponding first half of the year date range, which is then used as the corresponding second time period range. If the second button is the "Second Custom Date" button, a calendar display pop-up is provided to the user, who confirms the entered start and end dates on the pop-up to form the corresponding custom date range, which is then used as the corresponding second time period range.

[0118] Step 323: Extract the first road records from the first road list whose first date field meets the second time period range to form the corresponding third record set; cluster the first road records in the third record set according to road name, and group the first road records with the same first road name field into one category to form the corresponding fourth record set; calculate the average of all first travel mileage fields in each fourth record set to generate the corresponding second average total mileage, calculate the average of all first autonomous driving mileage fields to generate the corresponding second average total autonomous driving mileage, calculate the average of all first travel duration fields to generate the corresponding second average total duration, and calculate the average of all first autonomous driving duration fields to generate the corresponding second average total autonomous driving duration; and form the corresponding second road average record by combining the first road name field, second average total mileage, second average total autonomous driving mileage, second average total duration, and second average total autonomous driving duration corresponding to each fourth record set.

[0119] Step 324: Extract the second road records from the second road list whose second date field meets the second time period range to form the corresponding fifth record set; cluster the second road records in the fifth record set according to road name, and group the second road records with the same second road name field into one category to form the corresponding sixth record set; calculate the mean of all first complexity fields in each sixth record set to generate the corresponding first average complexity; and form the corresponding third road mean record by the second road name field and the first average complexity of each sixth record set.

[0120] Among them, the average record of the third road corresponds one-to-one with the average record of the second road;

[0121] Step 325: Merge the corresponding second and third road mean records to generate the corresponding fourth road mean record;

[0122] The fourth road average record includes the third road name, third average total mileage, third average total autonomous driving mileage, third average total time, third average total autonomous driving time, and second average complexity. The third road name is consistent with the first road name field of the corresponding second road average record and the second road name field of the corresponding third road average record. The third average total mileage, third average total autonomous driving mileage, third average total time, and third average total autonomous driving time are respectively the second average total mileage, second average total autonomous driving mileage, second average total time, and second average total autonomous driving time of the corresponding second road average record. The second average complexity is the first average complexity of the corresponding third road average record.

[0123] Step 326: Determine the corresponding example color block as the corresponding second road color based on the correspondence between the second average complexity of each fourth road average record and the first, second, third, fourth, or fifth complexity range; set the road display color of the corresponding first monitored road on the loaded map in the second map area of ​​the second visual page based on the second road color; sort all the obtained fourth road average records in descending order of second average complexity to generate the corresponding second record sequence; and set the display content of the road segment name, total mileage, autonomous driving mileage, total time, and autonomous driving time fields of the 5 corresponding display records in the complex road list area of ​​the second visual page according to the third road name, third average total mileage, third average total autonomous driving mileage, third average total time, and third average total autonomous driving time of the top five fourth road average records in the second record sequence.

[0124] Figure 4This is a schematic diagram of an electronic device provided in Embodiment 2 of the present invention. This electronic device can be the aforementioned terminal device or server, or it can be a terminal device or server connected to the aforementioned terminal device or server that implements the method of the embodiments of the present invention. Figure 4 As shown, the electronic device may include: a processor 301 (e.g., CPU), a memory 302, and a transceiver 303; the transceiver 303 is coupled to the processor 301, and the processor 301 controls the transmission and reception operations of the transceiver 303. The memory 302 may store various instructions for performing various processing functions and implementing the processing steps described in the foregoing method embodiments. Preferably, the electronic device involved in the embodiments of the present invention further includes: a power supply 304, a system bus 305, and a communication port 306. The system bus 305 is used to realize communication connections between components. The communication port 306 is used for communication between the electronic device and other peripherals.

[0125] exist Figure 4 The system bus 305 mentioned can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This system bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 4 The symbol is represented by a single thick line, but this does not imply that there is only one bus or one type of bus. The communication interface is used to enable communication between the database access device and other devices (e.g., clients, read-write libraries, and read-only libraries). Memory may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk drive.

[0126] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), graphics processing units (GPUs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0127] It should be noted that the embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when run on a computer, cause the computer to perform the methods and processes provided in the above embodiments.

[0128] This invention also provides a chip for executing instructions, which is used to perform the processing steps described in the foregoing method embodiments.

[0129] This invention provides a method, electronic device, and computer-readable storage medium for analyzing road environments. It collects the daily driving trajectories of all vehicles on a daily basis and analyzes the road activity frequency and road complexity of each monitored road based on these trajectories. Two visual pages are provided: a first page displays the overall road activity at six time scales and shows the top five roads; a second page displays the overall road complexity at six time scales and shows the top five roads. This invention achieves the technical goal of periodically analyzing the road environment (road activity frequency, road complexity) and adds a technical means to intuitively display the overall road conditions and key road conditions at different time scales, helping to improve operators' attention to key roads.

[0130] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0131] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented in hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0132] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A processing method of analyzing a road environment, characterized by, The method comprises: During a specified period of each day, receiving driving trajectories periodically sent by each vehicle as corresponding first real-time trajectories; and merging the first real-time trajectories with trajectories received on the same day to generate the latest first daily trajectory; At the end of the specified period of each day, analyzing road activity times, total vehicle passes, total pass mileage, total automatic driving pass mileage, total driving time, total automatic driving time, and total number of abnormal driving events of each first monitored road on a preset road map according to all the first daily trajectories to obtain corresponding first road records and store them in a preset first road list; and analyzing road complexity of each first monitored road according to the first road list to obtain corresponding second road records and store them in a preset second road list; the preset road map comprises a plurality of first monitored roads; the first road list comprises a plurality of first road records; and the second road list comprises a plurality of second road records; At any time of each day, sorting active roads according to the first road list and displaying information of the top five roads on a preset first visual page; and sorting complex roads according to the first and second road lists and displaying information of the top five roads on a preset second visual page.

2. The processing method for analyzing road environment according to claim 1, characterized in that: The first real-time trajectory comprises a first vehicle identifier and a plurality of first trajectory points; and the first trajectory point comprises a first trajectory point time, a first trajectory point coordinate, a first trajectory point driving mode, a first trajectory point speed, a first trajectory point acceleration, and a first trajectory point hazard warning light state; The first trajectory point driving mode comprises automatic driving and manual driving; and the sending time interval of two first real-time trajectories of the same vehicle is less than the trajectory length of the first real-time trajectory; The first daily trajectory comprises a second vehicle identifier and a plurality of second trajectory points; and the second trajectory point comprises a second trajectory point time, a second trajectory point coordinate, and a second trajectory point driving mode; and the second trajectory point driving mode comprises automatic driving and manual driving; The first monitored road comprises a first road name and a first road map coordinate range; The first road record comprises a first road name field, a first date field, a first activity time field, a first total vehicle number field, a first pass mileage field, a first automatic driving mileage field, a first pass time field, a first automatic driving time field, and a first total number of abnormal events field; The second road record comprises a second road name field, a second date field, and a first complexity field. The first visual page comprises a first set of time scale buttons, a first map area and an active road list area; the first set of time scale buttons comprises a first yesterday button, a first last week button, a first last month button, a first last quarter button, a first last half year button and a first custom date button; the first map area is used to load the preset road map and comprises five example color blocks and corresponding five active frequency range description texts; the five example color blocks of the first map area comprise a first, a second, a third, a fourth and a fifth color block, and the five active frequency range description texts of the first map area comprise a first, a second, a third, a fourth and a fifth frequency range, and the first, the second, the third, the fourth and the fifth color block correspond to the first, the second, the third, the fourth and the fifth frequency range respectively; the active road list area comprises five display records, and each display record is composed of eight fields of serial number, road segment name, active frequency, vehicle number, total mileage, autonomous driving mileage, total time length and autonomous driving time length. The second visual page comprises a second set of time scale buttons, a second map area and a complex road list area; the second set of time scale buttons comprises a second yesterday button, a second last week button, a second last month button, a second last quarter button, a second last half year button and a second custom date button; the second map area is used to load the preset road map and provides five example color blocks and corresponding five complexity range description texts; the five example color blocks of the second map area comprise a sixth, a seventh, an eighth, a ninth and a tenth color block, and the five complexity range description texts of the second map area comprise a first, a second, a third, a fourth and a fifth complexity range, and the sixth, the seventh, the eighth, the ninth and the tenth color block correspond to the first, the second, the third, the fourth and the fifth complexity range respectively; the complex road list area comprises five display records, and each display record is composed of six fields of serial number, road segment name, total mileage, autonomous driving mileage, total time length and autonomous driving time length.

3. The processing method of analyzing a road environment according to claim 2, characterized by, The first real-time trajectory is combined with the received trajectory of the day to generate the latest first daily trajectory, specifically comprising: The current first real-time trajectory is taken as a corresponding current real-time trajectory; and the first daily trajectory tag matched with the first vehicle identifier of the current real-time trajectory is taken as a corresponding current daily trajectory; The first and second trajectory points with the same time in the current real-time trajectory and the current daily trajectory are recorded as a group of paired trajectory points, and the first trajectory point in each paired trajectory point is used to replace the corresponding second trajectory point; All the first trajectory points in the current real-time trajectory whose time is later than the time of the last second trajectory point in the current daily trajectory are recorded as new trajectory points; and each new trajectory point is added to the current daily trajectory as a new second trajectory point and in chronological order to generate the latest first daily trajectory.

4. The processing method of analyzing a road environment according to claim 2, characterized by, The first road record corresponding to the analysis of the road activity number, the total number of passing vehicles, the total mileage of passing vehicles, the total mileage of automatic driving of passing vehicles, the total driving time of passing vehicles, the total automatic driving time of passing vehicles and the total number of abnormal driving events of each first monitoring road on the preset road map according to all the first daily trajectories, specifically comprising: Seven counters initialized to 0 are assigned to each of the first monitoring roads, which are the first, second, third, fourth, fifth, sixth and seventh counters; and any of the first daily trajectories is taken as the corresponding current daily trajectory; the first counter is used to count the activity number of the corresponding road; the second counter is used to count the total number of passing vehicle numbers of all passing vehicles on the corresponding road; the third counter is used to count the total driving mileage of all passing vehicles on the corresponding road; the fourth counter is used to count the total automatic driving mileage of all passing vehicles on the corresponding road; the fifth counter is used to count the total driving time of all passing vehicles on the corresponding road; the sixth counter is used to count the total automatic driving time of all passing vehicles on the corresponding road; and the seventh counter is used to count the total number of abnormal driving events of all passing vehicles on the corresponding road; All the second trajectory point coordinates of the current daily trajectory are extracted, sorted in chronological order to form a corresponding first coordinate sequence; and the repeated second trajectory point coordinates in the first coordinate sequence are filtered out; and a plurality of first sampling point coordinates are obtained by interval point sampling from the first second trajectory point coordinate of the first coordinate sequence at a preset first interval length; and the first monitoring road corresponding to the first road map coordinate range matching each of the first sampling point coordinates is queried from the preset road map as the corresponding first road; and the first counter of the first road is incremented by 1; wherein the road length between two adjacent first sampling point coordinates matches the first interval length; The first road name of the first monitoring road corresponding to the first road map coordinate range matching the second trajectory point coordinate of each second trajectory point of the current daily trajectory is extracted as the corresponding first trajectory point road name by querying the preset road map; and in the current daily trajectory, the second trajectory points with the same first trajectory point road name for a plurality of consecutive second trajectory points are extracted to form a corresponding first segmented trajectory, and a single second trajectory point with the first trajectory point road name different from that of the adjacent second trajectory points is also extracted to form a corresponding first segmented trajectory; and in each of the first segmented trajectories, the second trajectory points with a single or a plurality of consecutive second trajectory points driving mode as automatic driving are extracted to form a corresponding second segmented trajectory; corresponding first segment starting coordinate and first segment ending coordinate; and querying the preset road map to obtain a road length from the first segment starting coordinate to the first segment ending coordinate as a corresponding first segment mileage length L1; and adding L1 to the third counter of the second road corresponding to each first segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second segment ending coordinate as a corresponding second segment mileage length L2; and adding L2 to the fourth counter of the second road corresponding to each second segment trajectory; corresponding second segment starting coordinate and second segment ending coordinate; and querying the preset road map to obtain a road length from the second segment starting coordinate to the second The first road name corresponding to each of the first monitored road is taken as the corresponding first road name field, the corresponding first counter is taken as the corresponding first active times field, the corresponding second counter is taken as the corresponding first vehicle total number field, the corresponding third counter is taken as the corresponding first passing mileage field, the corresponding fourth counter is taken as the corresponding first autonomous driving mileage field, the corresponding fifth counter is taken as the corresponding first passing time length field, the corresponding sixth counter is taken as the corresponding first autonomous driving time length field, and the corresponding seventh counter is taken as the corresponding first total number of abnormal events field; and the date information of any one of the second trajectory point times in the current daily trajectory is extracted as the corresponding first date field; and the first road name field, the first date field, the first active times field, the first vehicle total number field, the first passing mileage field, the first autonomous driving mileage field, the first passing time length field, the first autonomous driving time length field and the first total number of abnormal events field are taken as the corresponding first road record and stored in the first road list.

5. The processing method of analyzing a road environment according to claim 4, characterized by, The first segmented trajectory is identified for abnormal driving events, and the total number of identified abnormal events is counted to generate a corresponding first segmented event total number n, specifically including: Seven types of abnormal event identification models are used to identify and process the first segmented trajectory to obtain seven types of identification results; the seven types of abnormal event identification models include an autonomous driving exit abnormal event identification model, an emergency braking abnormal event identification model, an ultra-low speed abnormal event identification model, an overspeed abnormal event identification model, a dangerous state abnormal event identification model, an autonomous driving disengagement abnormal event identification model and a collision level event identification model; the seven types of identification results include first, second, third, fourth, fifth, sixth and seventh identification results; the first identification result corresponds to the autonomous driving exit abnormal event identification model and includes no abnormality and autonomous driving exit abnormality; the second identification result corresponds to the emergency braking abnormal event identification model and includes no abnormality and emergency braking abnormality; the third identification result corresponds to the ultra-low speed abnormal event identification model and includes no abnormality and ultra-low speed abnormality; the fourth identification result corresponds to the overspeed abnormal event identification model and includes no abnormality and overspeed abnormality; the fifth identification result corresponds to the dangerous state abnormal event identification model and includes no abnormality and dangerous state abnormality; the sixth identification result corresponds to the autonomous driving disengagement abnormal event identification model and includes no abnormality and autonomous driving disengagement abnormality; and the seventh identification result corresponds to the collision level event identification model and includes no abnormality and abnormal collision level; The number of identification results in the seven types of identification results that are not no abnormality is counted to generate a corresponding total number of abnormal events; and the obtained total number of abnormal events is taken as the corresponding first segmented event total number n.

6. The processing method of analyzing a road environment according to claim 2, characterized by, The road complexity of each first monitoring road is analyzed according to the first road list, and a corresponding second road record is stored in a preset second road list, specifically including: The first date field of the latest first road record in the first road list is extracted as a corresponding first date; all first road records in the first road list whose first date fields satisfy the first date are marked as daily road records; and the total number of the daily road records is counted to generate a corresponding first total number M; The first passing mileage field, the first autonomous driving mileage field, the first passing time field, the first autonomous driving time field and the first total number of abnormal events field of each daily road record are extracted to form a first road vector with a shape of 1×5; the first road vector of the first total number M is formed; and a road complexity prediction model is used to process the first road tensor to obtain a corresponding first complexity vector with a shape of M×1; the first complexity vector includes the first road complexity of the first total number M; The first road name field, the first date field and the corresponding first road complexity of each daily road record are used as the corresponding second road name field, the second date field and the first complexity field to form a corresponding second road record stored in the preset second road list.

7. The processing method of analyzing a road environment according to claim 2, characterized by, The first road list is sorted according to the first visual page, and the top five road information is displayed, specifically including: The first visual page is loaded; and the button selected by the user in the first group of time scale buttons of the first visual page is used as a corresponding first button. identifying the first button; if the first button is the first yesterday button, extracting the date information of the current system time as the corresponding current date, and determining the corresponding yesterday date according to the current date and the date information of yesterday, and taking the yesterday date as the corresponding first time period range; if the first button is the first last week button, extracting the date information of the current system time as the corresponding current date, and determining the corresponding last week date range according to the current date and the starting date and ending date information of the last week, and taking the last week date range as the corresponding first time period range; if the first button is the first last month button, extracting the date information of the current system time as the corresponding current date, and determining the corresponding last month date range according to the current date and the starting date and ending date information of the last month, and taking the last month date range as the corresponding first time period range; if the first button is the first last quarter button, extracting the date information of the current system time as the corresponding current date, and determining the corresponding last quarter date range according to the current date and the starting date and ending date information of the last quarter, and taking the last quarter date range as the corresponding first time period range; if the first button is the first first half year button, extracting the date information of the current system time as the corresponding current date, and determining the corresponding first half year date range according to the current date and the starting date and ending date information of the first half year, and taking the first half year date range as the corresponding first time period range; if the first button is the first custom date button, providing a calendar display pop-up window to the user through a pop-up window, and taking the input starting date and ending date on the calendar display pop-up window as the corresponding custom date range, and taking the custom date range as the corresponding first time period range. extracting the first road records in the first road list whose first date field meets the first time period range to form a corresponding first record set; clustering the first road records in the first record set by road name, grouping the first road records with the same first road name field into a corresponding second record set; performing mean value calculation on all the first active times fields of the second record sets to generate a corresponding first average active time, performing mean value calculation on all the first vehicle total fields to generate a corresponding first average vehicle total, performing mean value calculation on all the first total mileage fields to generate a corresponding first average total mileage, performing mean value calculation on all the first autonomous driving mileage fields to generate a corresponding first average autonomous driving total mileage, performing mean value calculation on all the first total time length fields to generate a corresponding first average total time length, and performing mean value calculation on all the first autonomous driving time length fields to generate a corresponding first average autonomous driving total time length; forming a corresponding first road mean value record from the first road name field, the first average active time, the first average vehicle total, the first average total mileage, the first average autonomous driving total mileage, the first average total time length, and the first average autonomous driving total time length of each second record set; determining a corresponding example color block as a corresponding first road color according to the corresponding relationship between the first average active time of each first road mean value record and the first, second, third, fourth, or fifth number range; setting the road display color of the corresponding first monitoring road based on the first road color on the loaded map of the first map area of the first visual page; sorting all the obtained first road mean value records in descending order of the first average active time to generate a corresponding first record sequence; and setting the display content of the road name, active time, vehicle number, total mileage, autonomous driving mileage, total time length, and autonomous driving time length fields of the five corresponding display records in the active road list area of the first visual page according to the first road name field, the first average active time, the first average vehicle total, the first average total mileage, the first average autonomous driving total mileage, the first average total time length, and the first average autonomous driving total time length of the top five first road mean value records in the first record sequence.

8. The processing method of analyzing a road environment according to claim 2, characterized by, The second visual page displays the top five road information according to the first and second road lists, specifically including: loading the second visual page; and selecting a corresponding second button in the second set of time scale buttons on the second visual page as the button selected by the user; identifying the second button; if the second button is the second yesterday button, extracting the date information of the current system time as the corresponding current date, determining the corresponding yesterday date according to the current date and the date information of yesterday, and taking the yesterday date as the corresponding second time period range; if the second button is the second last week button, extracting the date information of the current system time as the corresponding current date, determining the corresponding last week date range according to the current date and the starting date and ending date information of the last week, and taking the last week date range as the corresponding second time period range; if the second button is the second last month button, extracting the date information of the current system time as the corresponding current date, determining the corresponding last month date range according to the current date and the starting date and ending date information of the last month, and taking the last month date range as the corresponding second time period range; if the second button is the second last quarter button, extracting the date information of the current system time as the corresponding current date, determining the corresponding last quarter date range according to the current date and the starting date and ending date information of the last quarter, and taking the last quarter date range as the corresponding second time period range; if the second button is the second first half year button, extracting the date information of the current system time as the corresponding current date, determining the corresponding first half year date range according to the current date and the starting date and ending date information of the first half year, and taking the first half year date range as the corresponding second time period range; if the second button is the second custom date button, providing a calendar display pop-up window to the user through a pop-up window, and taking the input starting date and ending date on the calendar display pop-up window as the corresponding custom date range, and taking the custom date range as the corresponding second time period range. extracting the first road records in the first road list whose first date field meets the second time period range to form a corresponding third record set; clustering the first road records in the third record set by road name, and grouping the first road records with the same first road name field into a corresponding fourth record set; performing mean value calculation on all the first passing mile fields of each fourth record set to generate a corresponding second average total mile, performing mean value calculation on all the first autonomous driving mile fields to generate a corresponding second average autonomous driving total mile, performing mean value calculation on all the first passing time length fields to generate a corresponding second average total time length, and performing mean value calculation on all the first autonomous driving time length fields to generate a corresponding second average autonomous driving total time length; and forming a corresponding second road average record from the first road name field, the second average total mile, the second average autonomous driving total mile, the second average total time length and the second average autonomous driving total time length of each fourth record set; extracting the second road records in the second road list whose second date field meets the second time period range to form a corresponding fifth record set; clustering the second road records in the fifth record set by road name, and grouping the second road records with the same second road name field into a corresponding sixth record set; performing mean value calculation on all the first complexity fields of each sixth record set to generate a corresponding first average complexity; and forming a corresponding third road average record from the second road name field and the first average complexity of each sixth record set; the third road average record corresponds one-to-one to the second road average record; merging the corresponding second and third road average records to generate a corresponding fourth road average record; the fourth road average record includes a third road name, a third average total mile, a third average autonomous driving total mile, a third average total time length, a third average autonomous driving total time length and a second average complexity; the third road name is consistent with the first road name field of the corresponding second road average record and the second road name field of the third road average record; the third average total mile, the third average autonomous driving total mile, the third average total time length and the third average autonomous driving total time length are the second average total mile, the second average autonomous driving total mile, the second average total time length and the second average autonomous driving total mile of the corresponding second road average record respectively; and the second average complexity is the first average complexity of the corresponding third road average record; According to the second average complexity of each fourth road average record and the corresponding relationship of the first, second, third, fourth or fifth complexity range, a corresponding example color block is determined as a corresponding second road color; and the road display color of the corresponding first monitoring road is set based on the second road color on the loaded map of the second map area of the second visual page; and all the fourth road average records obtained are sorted in descending order of the second average complexity to generate a corresponding second record sequence; and the third road name, the third average total mileage, the third average automatic driving total mileage, the third average total time length and the third average automatic driving total time length of the top five fourth road average records in the second record sequence are set to the display content of the section name, total mileage, automatic driving mileage, total time length and automatic driving time length fields of the five corresponding display records in the complex road list area of the second visual page.

9. An electronic device, comprising: Comprise: a memory, a processor and a transceiver; the processor is used for coupling with the memory, reading and executing the instructions in the memory to realize the method steps of any one of claims 1-8; the transceiver is coupled with the processor, and the transceiver is controlled by the processor to perform message transmission and reception.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, when the computer instructions are executed by the computer, the computer instructions make the computer execute the instructions of the method of any one of claims 1-8.

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