A city bus global intelligent scanning system based on vehicle-cloud cooperation technology

Abstract

The application relates to the technical field of intelligent traffic and Internet of Vehicles communication, in particular to a city bus global intelligent scanning system based on vehicle-cloud cooperative technology. The system comprises a cloud server, a vehicle terminal, a vehicle positioning terminal, a vehicle camera device and a vehicle wireless communication device. The cloud server divides road scanning units, determines candidate scanning units according to vehicle positions, driving directions and imaging directions, and determines to-be-scanned units by judging previous effective collection time of the candidate scanning units, forms scanning task fragments and sends the scanning task fragments to the vehicle terminal. The vehicle terminal controls collection and uploads image records according to starting boundaries, ending boundaries and allowed collection directions, and the cloud server updates previous effective collection time according to the image records. The application corresponds the scanning task to the actual collection range of the vehicle, reduces repeated collection within the preset scanning effective time limit, and enables road scanning units that do not meet the collection direction and imaging direction conditions to continue to be reserved in the subsequent scanning range.

Description

Technical Field

[0001] This invention relates to the fields of intelligent transportation and vehicle-to-everything (V2X) communication technology, and in particular to an intelligent scanning system for urban public transportation based on vehicle-cloud collaboration technology. Background Technology

[0002] The field of intelligent transportation and vehicle-to-everything (V2X) communication technology mainly involves the collection, transmission, storage, and collaborative processing of information between vehicles, road environments, wireless networks, and cloud platforms. Typically, vehicle positioning terminals, cameras, and vehicle status sensors acquire vehicle location, speed, operating status, and road images, which are then transmitted to a server via cellular mobile communication links. The server associates, stores, and retrieves data based on time, location, vehicle identification, and task records, and sends data requests or control commands to the vehicle terminals. Urban public transport full-area intelligent scanning based on vehicle-cloud collaborative technology refers to using public transport vehicles as mobile information collection carriers. During vehicle operation, it collects location information, road images, vehicle operating status, and records of the surrounding environment, which are then uploaded to a cloud server via a wireless communication network. The server organizes, matches, and stores the data based on vehicle location, collection time, task area, and data status, and sends scanning tasks, data requests, or execution commands to the corresponding public transport vehicle terminals. The vehicle terminals then invoke the appropriate collection equipment according to the received commands and transmit the collection results back.

[0003] Current urban public transport road information collection mainly relies on vehicle-mounted positioning terminals and camera devices to collect vehicle locations and road images according to predetermined routes. The collected data is uploaded to the server via wireless communication links and then organized and stored according to time and location. Scanning tasks are mostly based on preset areas or fixed road sections. There is a lack of segment-by-segment correspondence between the vehicle's driving direction, the camera's imaging direction, and the road collection range. The status updates of completed road sections and road sections to be collected rely on task records, which can easily lead to duplicate collection of the same road section and situations where the collection records of some road sections do not meet the directional conditions. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent urban public transport scanning system based on vehicle-cloud collaborative technology. This system uses road scanning units corresponding to bus routes as the basis for organizing scanning tasks. It establishes a correspondence between vehicle location, driving direction, imaging direction, and the previous valid acquisition time with the road scanning units. Based on the acquisition status of the road scanning units, scanning task segments are formed. The onboard terminal controls the onboard camera device to perform acquisition according to these scanning task segments. This allows the cloud server to update the previous valid acquisition time of the road scanning units based on the actual image records acquired by the vehicle, thus forming a closed-loop processing relationship between road scanning task generation, vehicle acquisition execution, and road scanning status updates.

[0005] To achieve the above objectives, the present invention provides an intelligent scanning system for urban public transport based on vehicle-cloud collaborative technology. The system includes: a cloud server, an in-vehicle terminal, an in-vehicle positioning terminal, an in-vehicle camera device, and an in-vehicle wireless communication device. The cloud server divides the bus route into road scanning units, records the unit boundary, allowed acquisition direction, allowed imaging direction and previous valid acquisition time of each road scanning unit, and determines candidate scanning units based on the vehicle position and driving direction collected by the vehicle positioning terminal and the imaging direction of the vehicle camera device. When the candidate scanning unit does not record the previous valid acquisition time, and when the candidate scanning unit records the previous valid acquisition time and the time interval between the current time and the previous valid acquisition time reaches the preset valid scanning time limit, the candidate scanning unit is determined as the unit to be scanned. The adjacent units to be scanned are grouped into a scanning task segment according to the unit boundary. The start boundary and the end boundary are determined by the unit boundaries at both ends of the scanning task segment, and the segment is sent to the vehicle terminal through a wireless communication link. The vehicle-mounted terminal activates the vehicle-mounted camera when the vehicle position reaches the starting boundary and the driving direction is within the preset allowable acquisition direction deviation range, and stops acquisition when the vehicle position reaches the ending boundary, forming an image record containing the recorded image, acquisition time, vehicle position, driving direction and imaging direction, and uploads it through the vehicle-mounted wireless communication device; The cloud server determines the road scanning unit based on the vehicle position in the image record. When the driving direction is within the allowable acquisition direction deviation range of the corresponding road scanning unit and the imaging direction is within the allowable imaging direction deviation range, the previous valid acquisition time of the corresponding road scanning unit is updated with the acquisition time.

[0006] Furthermore, the process of determining the candidate scanning unit includes: The cloud server determines the road scanning unit corresponding to the vehicle position based on the unit boundary, and selects adjacent road scanning units along the driving direction starting from the road scanning unit. The driving direction is compared with the allowed acquisition direction of each road scanning unit, and the imaging direction is compared with the allowed imaging direction of each road scanning unit. When the driving direction is within a preset allowable acquisition direction deviation range and the imaging direction is within a preset allowable imaging direction deviation range, the corresponding road scanning unit is determined as the candidate scanning unit.

[0007] Furthermore, the cloud server determines each road scanning unit according to the arrangement relationship of the unit boundaries in the driving direction, and forms a candidate scanning unit sequence for road scanning units whose driving direction is within the allowable acquisition direction deviation range and whose imaging direction is within the allowable imaging direction deviation range, according to the arrangement relationship of the unit boundaries. The candidate scanning unit sequence is used to determine the unit to be scanned.

[0008] Furthermore, the cloud server determines the previous valid acquisition time for each candidate scanning unit in the candidate scanning unit sequence, and identifies the candidate scanning unit that has not recorded the previous valid acquisition time as the unit to be scanned. For candidate scanning units that have a recorded previous valid acquisition time, the time interval between the current time and the previous valid acquisition time is calculated. If the time interval reaches the preset valid scanning time limit, the unit is determined as a unit to be scanned. If the time interval does not reach the preset valid scanning time limit, the valid acquisition state of the corresponding road scanning unit is maintained.

[0009] Furthermore, the cloud server combines consecutive adjacent units to be scanned into a scanning task segment according to the arrangement relationship of the unit boundaries in the driving direction. The unit boundary corresponding to the unit to be scanned at the beginning position of the scanning task segment is determined as the starting boundary, and the unit boundary corresponding to the unit to be scanned at the end position of the scanning task segment is determined as the ending boundary. The starting boundary and the ending boundary are written into the scanning task segment.

[0010] Furthermore, the process of sending the scanning task segment includes: The cloud server writes the starting boundary, the ending boundary, and the allowed acquisition direction into the scanning task segment, and sends it to the vehicle terminal through a wireless communication link. The vehicle-mounted terminal receives the scanning task segment, determines the correspondence between the vehicle and the starting boundary and the ending boundary based on the vehicle position collected by the vehicle-mounted positioning terminal, starts the vehicle-mounted camera device when the vehicle position reaches the starting boundary and the driving direction is within the preset allowable acquisition direction deviation range, and stops acquisition when the vehicle position reaches the ending boundary.

[0011] Furthermore, the vehicle-mounted camera generates images during the acquisition process, and the vehicle-mounted terminal associates the images with the vehicle position, driving direction, imaging direction, and acquisition time at the corresponding acquisition time to form an image record; The vehicle-mounted terminal sends the image recording to the cloud server via the vehicle-mounted wireless communication device. The cloud server determines the corresponding road scanning unit based on the vehicle position in the image recording and uses the driving direction and imaging direction in the image recording as the effective acquisition criteria for the corresponding road scanning unit.

[0012] Furthermore, the cloud server sets allowed acquisition directions and allowed imaging directions for the road scanning unit, compares the driving direction in the image record with the allowed acquisition direction, and compares the imaging direction in the image record with the allowed imaging direction. If the driving direction is within the preset allowed acquisition direction deviation range and the imaging direction is within the preset allowed imaging direction deviation range, the corresponding image record is determined as a valid acquisition record.

[0013] Furthermore, the cloud server reads the collection time corresponding to the valid collection record and writes the collection time into the previous valid collection time of the corresponding road scanning unit; Road scanning units that have not generated a valid acquisition record retain their previous valid acquisition time and continue to be used as the criteria for determining the previous valid acquisition time of subsequent candidate scanning units.

[0014] Furthermore, the cloud server uses the acquisition time written to the corresponding road scanning unit as the updated previous valid acquisition time, and determines the previous valid acquisition time for subsequent candidate scanning units. If the time interval between the current time and the updated previous valid collection time reaches the preset valid scanning time limit, the corresponding road scanning unit is determined as the unit to be scanned; Road scanning units that have not generated a valid acquisition record retain their previous valid acquisition time and participate in the determination of subsequent candidate scanning units according to their previous valid acquisition time.

[0015] The working principle and advantages of this invention are as follows: In this invention, a cloud server uses road scanning units as the basis for the task, and uses vehicle position, driving direction, and imaging direction to determine candidate scanning units. The scanning units to be scanned are identified with a preset effective scanning time limit, so that the scanning task segments correspond to the collectable road segments. The vehicle terminal controls the start and stop of the vehicle camera device according to the start boundary, end boundary, and allowed acquisition direction, forming an image record with acquisition time, vehicle position, driving direction, and imaging direction. The cloud server verifies the acquisition direction and imaging direction of the road scanning unit based on the image record and updates the previous effective acquisition time, so that subsequent scanning tasks are generated according to the actual acquisition status of the road scanning unit, reducing repeated acquisition within the effective time limit, and retaining road scanning units that do not meet the acquisition conditions. Attached Figure Description

[0016] Figure 1 This is a flowchart of the urban public transport full-area scanning processing of the present invention; Figure 2 This is a schematic diagram illustrating the collaborative relationship between vehicle-cloud devices in this invention; Figure 3 This is a schematic diagram of the road scanning unit and the formation of scanning task segments according to the present invention; Figure 4 This is a flowchart of the vehicle-mounted data acquisition and image recording and transmission process of the present invention; Figure 5 This is a schematic diagram illustrating the status update of the road scanning unit of the present invention. Detailed Implementation

[0017] The following detailed explanation illustrates the specific implementation methods: This embodiment provides an intelligent scanning system for urban public transport based on vehicle-cloud collaborative technology. The system includes a cloud server, an on-board terminal, an on-board positioning terminal, an on-board camera device, and an on-board wireless communication device.

[0018] The cloud server is used to establish road scanning units, determine candidate scanning units and units to be scanned, generate scanning task segments, and determine the validity of uploaded image records. The vehicle-mounted positioning terminal is used to collect vehicle position and direction of travel. The vehicle-mounted camera device is used to collect road images. The vehicle-mounted terminal receives scanning task segments and controls the vehicle-mounted camera device to perform acquisition based on these segments. The vehicle-mounted wireless communication device is used for data transmission between the vehicle-mounted terminal and the cloud server.

[0019] In this embodiment, the road scanning unit is a road space unit formed according to the bus route; the unit boundary is used to determine the road range corresponding to the road scanning unit; the allowed acquisition direction is used to indicate the allowed driving direction when the bus passes through the road scanning unit; the allowed imaging direction is used to indicate the allowed imaging direction when the vehicle-mounted camera collects data from the road scanning unit; the previous valid acquisition time is used to record the acquisition time when the corresponding road scanning unit last formed a valid acquisition record.

[0020] This embodiment uses a 18.4km long bus route as an example. The bus route is divided into 40m road scanning units, forming a total of 460 road scanning units. The vehicle-mounted positioning terminal uses a GNSS satellite navigation positioning receiver, with a positioning update frequency set to 10Hz; the resolution of the images acquired by the vehicle-mounted camera is set to 1920×1080, and the image acquisition frequency is set to 10fps. The preset effective scanning time limit is set to 30min, the allowable acquisition direction deviation range is set to ±12°, and the allowable imaging direction deviation range is set to ±18°.

[0021] The positioning record output by the vehicle-mounted positioning terminal includes UTC time, positioning status, longitude, latitude, and ground heading angle. The vehicle-mounted terminal reads RMC messages in NMEA-0183 format. When the positioning status is valid and the longitude, latitude, and ground heading angle fields are complete, the longitude and latitude are used as the vehicle position, and the ground heading angle is used as the driving direction. If the positioning status is invalid, or if any of the above fields are missing, the corresponding positioning record will not participate in road scanning unit determination, candidate scanning unit determination, or unit boundary determination.

[0022] The vehicle-mounted camera device is fixedly installed on the bus. After installation, the azimuth angle of the optical axis of the vehicle-mounted camera device relative to the longitudinal direction of travel of the vehicle is calibrated. In this embodiment, the azimuth angle is set to 20°. The vehicle-mounted terminal adds the travel direction to the azimuth angle and normalizes the resulting angle to 0° to 360° to obtain the imaging direction. For example, when the travel direction is 96°, the imaging direction is 116°.

[0023] The vehicle-mounted wireless communication equipment uses cellular mobile communication devices. After acquiring the vehicle's location, driving direction, and imaging direction, the vehicle terminal uploads these information, along with the corresponding UTC time, to the cloud server via the vehicle-mounted wireless communication equipment. The cloud server then generates a scanning task segment and sends it to the vehicle terminal via the wireless communication link. Finally, the vehicle terminal records the image and uploads it to the cloud server via the vehicle-mounted wireless communication equipment.

[0024] The vehicle-mounted terminal calibrates its local clock, used for recording image acquisition time, based on the UTC time output by the vehicle positioning terminal. The cloud server's system clock uses the same UTC time base. The current time, acquisition time, and previous valid acquisition time are stored according to date and time. When times such as 08:47:00 and 08:48:14.800 are mentioned below, they all represent the corresponding times within the same operating day.

[0025] Please see Figures 1 to 5 This implementation method is carried out according to the following steps.

[0026] Establish road scanning units and corresponding scanning judgment data.

[0027] The cloud server reads the centerline data of the bus route. The centerline of the bus route consists of geographic coordinate points arranged according to the direction of bus travel. The cloud server calculates the road length between adjacent geographic coordinate points according to their arrangement and accumulates the road length along the centerline of the bus route.

[0028] When the cumulative road length reaches 40m, a unit boundary is set at the corresponding location. The centerline portion of the bus route between two adjacent unit boundaries forms a road scanning unit. When a certain broken line segment changes the cumulative road length from less than 40m to more than 40m, the location of the unit boundary is determined within that broken line segment based on the remaining road length required to reach 40m, and the road length of the next road scanning unit continues to be accumulated from that unit boundary.

[0029] 18.4km equals 18400m, and 18400m divided by 40m equals 460, thus forming 460 road scanning units.

[0030] The surface distance between adjacent geographic coordinate points is determined using the Haversine great circle distance formula: ; in, The surface distance between two geographical locations, in meters (m). The average radius of the Earth is taken as 6,371,000 m in this implementation method; and These are the latitudes of two different geographical locations; and These are the longitudes of two geographical locations. Longitude and latitude are converted from ° to rad before being substituted into the formula. The trigonometric functions in the formula are dimensionless quantities, and the central angle is... Multiplying them together gives the surface distance, expressed in meters.

[0031] The cloud server records the route mileage for each unit boundary based on the cumulative road length of the bus route centerline. When the vehicle is running, the vehicle position collected by the onboard positioning terminal is projected onto the bus route centerline to obtain the route mileage corresponding to the vehicle position.

[0032] The vehicle's location is matched with the centerline of the bus route using a map matching method. The cloud server determines the route segment corresponding to the vehicle's location based on the projected distance from the vehicle's location to each candidate line segment of the bus route centerline, combined with the bus route's direction of travel, the current direction of travel, and the route mileage corresponding to the previous valid vehicle location.

[0033] When a valid vehicle location is obtained for the first time and there is no previous valid route mileage, the route segment in which the vehicle is located is determined based on the projected distance from the vehicle location to the candidate line segment and the correspondence between the current driving direction and the direction of the candidate line segment. If there are two or more candidate line segments that cannot be uniquely determined, the current vehicle location is not included in the road scanning unit determination, and map matching continues after subsequent valid vehicle locations are obtained.

[0034] For loop sections or adjacent parallel sections in a bus route, the continuous movement relationship of the vehicle on the bus route is determined based on the route mileage corresponding to the previous valid vehicle position, the arrangement direction of the bus route, and the current driving direction.

[0035] When the route mileage corresponding to the vehicle's location falls between the route mileages of two adjacent unit boundaries, the vehicle's location is assigned to the corresponding road scanning unit. When the vehicle's location is exactly at the common unit boundary of two road scanning units, the vehicle's location is assigned to the road scanning unit on the entering side according to the current travel direction.

[0036] When a vehicle approaches the start or end boundary of a scanning task segment, the mileage corresponding to the vehicle's position is compared with the mileage corresponding to the boundary of the corresponding cell. In this implementation, 6m is set as the cell boundary determination distance. When the absolute distance difference between the two does not exceed 6m, it is determined that the vehicle's position has entered the determination range of the corresponding cell boundary.

[0037] Within the same scan task segment, the arrival status of the start boundary and the end boundary is recorded respectively, and the start boundary or end boundary that has been triggered is not triggered again in the same scan task segment.

[0038] The permissible acquisition direction for each road scanning unit is determined based on the starting and ending boundaries of the corresponding road scanning unit. The azimuth angle from the starting boundary to the ending boundary is determined using the following formula: ; in, The azimuth angle from the starting boundary to the ending boundary, in degrees; The difference between the longitude of the terminating boundary and the longitude of the starting boundary; The initial boundary latitude; To determine the terminating boundary latitude, the longitude difference and latitude are converted to rad before being substituted into trigonometric functions. The output is rad, multiplied by Convert to °, mod means modulo operation, [·] mod 360 means taking the angle value in the brackets as modulo 360°, so that the obtained azimuth angle is normalized to the range of 0°≤β<360°, and the normalized azimuth angle is used as the allowed acquisition direction.

[0039] When the installation azimuth angle of the vehicle-mounted camera device is 20°, the permissible imaging direction of the road scanning unit is obtained by adding 20° to the permissible acquisition direction and normalizing it to 0°–360°. For example, when the permissible acquisition direction of the road scanning unit is 90°, the permissible imaging direction is 110°. When the permissible acquisition direction deviation range is ±12°, the corresponding permissible acquisition direction range is 78°–102°; when the permissible imaging direction deviation range is ±18°, the corresponding permissible imaging direction range is 92°–128°.

[0040] After a road scanning unit is established, the cloud server records the unit boundary, allowed acquisition direction, allowed imaging direction, and previous valid acquisition time for each road scanning unit. For road scanning units that have not yet formed a valid acquisition record, the previous valid acquisition time is empty; for road scanning units that have formed a valid acquisition record, the previous valid acquisition time is the acquisition time from the corresponding valid acquisition record.

[0041] For example, the 101st road scanning unit corresponds to a route mileage of 4.000km to 4.040km, the 102nd road scanning unit corresponds to 4.040km to 4.080km, the 103rd road scanning unit corresponds to 4.080km to 4.120km, the 104th road scanning unit corresponds to 4.120km to 4.160km, the 105th road scanning unit corresponds to 4.160km to 4.200km, the 106th road scanning unit corresponds to 4.200km to 4.240km, the 107th road scanning unit corresponds to 4.240km to 4.280km, and the 108th road scanning unit corresponds to 4.280km to 4.320km.

[0042] Among them, the previous valid acquisition time of the 101st road scanning unit was not recorded; the previous valid acquisition time of the 102nd road scanning unit was 08:10:00; the previous valid acquisition time of the 103rd road scanning unit was 08:05:00; the previous valid acquisition time of the 105th road scanning unit was not recorded; the previous valid acquisition time of the 106th road scanning unit was 08:12:00; and the previous valid acquisition time of the 107th road scanning unit was 08:41:00.

[0043] Obtain vehicle operating conditions and determine candidate scanning units.

[0044] The vehicle-mounted positioning terminal collects the vehicle's location and direction of travel during bus operation. The terminal determines the imaging direction based on the direction of travel and the installation orientation of the onboard camera, and then uploads the vehicle location, direction of travel, imaging direction, and corresponding UTC time to a cloud server via onboard wireless communication equipment.

[0045] The vehicle-mounted positioning terminal outputs positioning records at a frequency of 10Hz, meaning a set of positioning data is generated every 0.1 seconds. When a bus travels at 30 km / h, its speed is 8.333 m / s, and the road displacement corresponding to each 0.1 second is approximately 0.833 m. The time it takes for the vehicle to pass through a 40m road scanning unit is approximately 4.800 seconds, corresponding to approximately 48 0.1-second positioning sampling intervals. The actual number of positioning records varies depending on the sampling time when the vehicle enters the road scanning unit and is not fixed at 48.

[0046] The cloud server determines the road scanning unit corresponding to the vehicle's location based on the map matching method used when establishing the road scanning unit. Using this road scanning unit as the current starting point, it sequentially reads adjacent road scanning units according to the current direction of the bus route. The reading order of the road scanning units follows the original arrangement order in the bus route and can continue until the terminus of the bus route corresponding to the current direction of travel.

[0047] For each road scanning unit that is read, the driving direction is compared with the allowed acquisition direction of the corresponding road scanning unit, and the imaging direction is compared with the allowed imaging direction of the corresponding road scanning unit.

[0048] Directional deviation is determined by the following formula: ; in, This represents the minimum directional difference between two directions, expressed in degrees (°). This refers to the current driving direction or current imaging direction, in degrees. This refers to the allowed acquisition direction or allowed imaging direction for the corresponding road scanning unit, in degrees. This is pi. The direction difference is converted from ° to rad before entering the cosine function, and the inverse cosine result is then converted back to °. The value range is 0° to 180°.

[0049] Between the driving direction and the permitted data collection direction The angle should not exceed 12°, and the distance between the imaging direction and the permissible imaging direction should be... When the angle is no more than 18°, the corresponding road scanning unit is identified as a candidate scanning unit.

[0050] If the deviation in driving direction exceeds 12°, or the deviation in imaging direction exceeds 18°, the corresponding road scanning unit is not considered a candidate scanning unit. This road scanning unit will not be considered for its previous valid acquisition time under the current vehicle operating data. After acquiring new vehicle operating data, the determination will be made again according to the new driving direction and imaging direction.

[0051] For example, the vehicle's current travel direction is 96°, and the imaging direction is 116°. The allowed acquisition direction of the 101st road scanning unit is 90°, and the allowed imaging direction is 110°. The deviation of both directions is 6°, so it is determined as a candidate scanning unit.

[0052] The allowed acquisition direction of the 102nd road scanning unit is 92°, and the allowed imaging direction is 112°. The deviation of both directions is 4°, so it is determined to be a candidate scanning unit.

[0053] The 103rd road scanning unit has an allowable acquisition direction of 95° and an allowable imaging direction of 115°, with a deviation of 1° in both directions, and is therefore identified as a candidate scanning unit.

[0054] The allowed acquisition direction of the 104th road scanning unit is 71°, and the allowed imaging direction is 91°. The deviation of both directions is 25°, so it is uncertain whether it is a candidate scanning unit.

[0055] The allowed acquisition directions for road scanning units 105, 106, and 107 are 94°, 95°, and 96°, respectively, and the allowed imaging directions are 114°, 115°, and 116°, respectively, all of which meet the corresponding directional deviation conditions.

[0056] The allowed acquisition direction of the 108th road scanning unit is 120°, and the allowed imaging direction is 140°. The deviation of both directions is 24°, so it is uncertain whether it is a candidate scanning unit.

[0057] Based on the above determination, road scanning units 101, 102, 103, 105, 106, and 107 were identified as candidate scanning units.

[0058] The candidate scan units retain their original road scan unit numbers and unit boundary relationships within the bus route. Although road scan units 103 and 105 appear consecutively in the candidate scan results, road scan unit 104 still exists between them. Therefore, road scan units 103 and 105 are not adjacent road scan units.

[0059] After receiving new valid vehicle location, driving direction, and imaging direction, the cloud server re-executes candidate scan unit determination for subsequent scan tasks that have not yet been formed and sent. The start and end boundaries of scan task segments that have already been formed and sent to the vehicle terminal remain unchanged during the execution of the current scan task segment.

[0060] The cell to be scanned is determined based on the previous valid acquisition time.

[0061] The cloud server reads the previous valid acquisition time corresponding to each candidate scanning unit and determines the previous valid acquisition time for each candidate scanning unit.

[0062] Candidate scan units for which the previous valid acquisition time has not been recorded are identified as units to be scanned.

[0063] For candidate scanning units with a recorded previous valid acquisition time, the cloud server determines the time interval based on the current time and the previous valid acquisition time, and compares this time interval with the preset valid scanning time limit of 30 minutes. If the time interval reaches 30 minutes, the corresponding candidate scanning unit is determined as the unit to be scanned. If the time interval does not reach 30 minutes, the valid acquisition status of the corresponding road scanning unit is maintained.

[0064] Both the current time and the last valid acquisition time use UTC time base and are stored in their complete date and time. When running across dates, the time interval between the two is determined based on the complete timestamp.

[0065] For example, the current time is 08:47:00.

[0066] The 101st road scanning unit did not record the previous valid acquisition time and was therefore identified as a unit to be scanned.

[0067] The previous valid acquisition time for the 102nd road scanning unit was 08:10:00, with a time interval of 37 minutes. After 30 minutes, it was identified as a unit to be scanned.

[0068] The previous valid acquisition time of the 103rd road scanning unit was 08:05:00, with a time interval of 42 minutes. After 30 minutes, it was identified as a unit to be scanned.

[0069] The 105th road scanning unit did not record the previous valid acquisition time and was identified as a unit to be scanned.

[0070] The previous valid acquisition time for the 106th road scanning unit was 08:12:00, with a time interval of 35 minutes. After 30 minutes, it was identified as a unit to be scanned.

[0071] The previous valid acquisition time for the 107th road scanning unit was 08:41:00, with a time interval of 6 minutes. Since the time interval has not reached 30 minutes, the 107th road scanning unit remains in a valid acquisition state and it is uncertain whether it is a unit to be scanned.

[0072] Therefore, the 101st, 102nd, 103rd, 105th and 106th road scanning units are the units to be scanned.

[0073] Road scanning units 101, 102, and 103 are consecutively adjacent on the bus route, forming a continuous road area to be scanned with a length of 120m. Road scanning unit 104 is not a candidate scanning unit; therefore, road scanning units 103 and 105 cannot form a continuous road area to be scanned. Road scanning units 105 and 106 are consecutively adjacent, forming a continuous road area to be scanned with a length of 80m. Road scanning unit 107 remains in active acquisition mode and does not enter its corresponding road area to be scanned.

[0074] Form scan task segments and determine start and end boundaries.

[0075] The cloud server groups adjacent units to be scanned into scanning task segments according to the arrangement of road scanning units in the bus route.

[0076] Road scanning units 101, 102, and 103 constitute the first scanning task segment. The first scanning task segment corresponds to a route mileage of 4.000km to 4.120km and has a length of 120m. The boundary of the entry-side unit of road scanning unit 101 is determined as the starting boundary of the first scanning task segment, and the boundary of the exit-side unit of road scanning unit 103 is determined as the ending boundary of the first scanning task segment.

[0077] The 105th and 106th road scanning units constitute the second scanning task segment. The second scanning task segment corresponds to a route mileage of 4.160km to 4.240km and has a length of 80m.

[0078] When a scan task segment contains multiple road scan units, the cloud server retains the allowed acquisition direction corresponding to each road scan unit, and does not replace the allowed acquisition direction of all road scan units in the scan task segment with a single allowed acquisition direction.

[0079] For example, road scanning units 101, 102, and 103 in the first scanning task segment correspond to allowable acquisition directions of 90°, 92°, and 95°, respectively. When the vehicle reaches the starting boundary of the first scanning task segment, the acquisition start determination is performed using the 90° allowable acquisition direction corresponding to road scanning unit 101 at the starting position.

[0080] The cloud server transmits the scan task segment to the vehicle terminal via a wireless communication link. After receiving the complete start boundary, end boundary, road scanning unit arrangement, and corresponding permitted acquisition direction, the vehicle terminal saves the scan task segment.

[0081] If the start boundary, end boundary, or allowed acquisition direction data is missing in a scanning task segment, the vehicle terminal will not activate the vehicle camera device according to that scanning task segment.

[0082] The vehicle-mounted camera is controlled to perform data acquisition based on the scan task segments.

[0083] The vehicle-mounted terminal continuously reads the valid vehicle position and driving direction output by the vehicle positioning terminal, and determines the positional relationship between the vehicle and the start and end boundaries of the scanning task segment based on the map matching results.

[0084] The starting boundary of the first scan task segment corresponds to a route mileage of 4.000km. When the absolute distance difference between the vehicle's current route mileage and 4.000km is 4.6m, the vehicle's position enters the 6m starting boundary determination range.

[0085] At this time, the vehicle's driving direction is 96°, the allowed acquisition direction of the 101st road scanning unit is 90°, the directional deviation is 6°, which does not exceed 12°, and the vehicle terminal controls the vehicle camera device to start acquisition.

[0086] When the absolute distance difference between the vehicle's current route mileage and the starting boundary is 4.1m, but the vehicle's driving direction is 108°, the directional deviation between the driving direction and the 90° allowable acquisition direction is 18°. If it exceeds 12°, the vehicle-mounted camera will remain in non-acquisition state.

[0087] While the vehicle remains within a 6m radius of the initial boundary, the onboard terminal continues to determine the vehicle's position and direction of travel for each new valid positioning record obtained. When both the vehicle's position and direction of travel meet the requirements, the onboard camera is activated.

[0088] If a vehicle has exceeded the starting boundary by 6m along its current direction of travel, and fails to simultaneously meet both the vehicle position and direction of travel conditions while passing through the starting boundary determination range, the scanning task segment is recorded as not executed. The on-board camera will not initiate data acquisition for this scanning task segment, and the corresponding road scanning unit will not update the previous valid acquisition time due to this scanning task segment.

[0089] While the vehicle is running along the bus route, the on-board positioning terminal continuously outputs the vehicle's position and direction of travel at 10Hz, and the on-board camera captures images at 10fps.

[0090] When a bus travels at 30 km / h, its speed is 8.333 m / s. The road displacement within 0.1 s is approximately 0.833 m. The time required for the vehicle to pass through a 40 m road scanning unit is approximately 4.800 s, corresponding to approximately 48 0.1 s sampling intervals; the time required for the vehicle to pass through the 120 m first scanning segment is approximately 14.400 s, corresponding to approximately 144 0.1 s sampling intervals; and the time required for the vehicle to pass through the 80 m second scanning segment is approximately 9.600 s, corresponding to approximately 96 0.1 s sampling intervals.

[0091] The actual number of image frames generated is related to the start-up time, stop time, and sampling clock phase of the vehicle-mounted camera device. Therefore, the above number is used to represent the sampling density under the corresponding road length and is not used as a condition for determining the effective state of the road scanning unit.

[0092] The horizontal field of view of the vehicle-mounted camera is represented using the pinhole imaging relationship: ; in, A reference target plane perpendicular to the optical axis of the vehicle-mounted camera is at a distance The corresponding horizontal visible width, in meters; The distance from the optical center of the vehicle-mounted camera to the reference target plane is expressed in meters (m). The horizontal field of view of the vehicle-mounted camera device is expressed in degrees (°). Let be the rad value corresponding to the half-horizontal field of view. The result of the tangent function is a dimensionless quantity, therefore... and All units are in m.

[0093] In this embodiment, the horizontal field of view of the vehicle-mounted camera is 78°. hour, Approximately 19.435m; when hour, It is approximately 16.196m.

[0094] The theoretical lateral visible width on the reference target plane perpendicular to the optical axis of the vehicle-mounted camera is not directly used as the coverage width of the actual road surface, nor is it included in the determination of candidate scanning units and valid acquisition records. The imaging conditions of the road scanning unit are determined based on the directional deviation between the imaging direction and the permissible imaging direction.

[0095] When the vehicle approaches the termination boundary of the first scanning task segment at 4.120km, and the absolute distance difference between the vehicle's current route mileage and the termination boundary is 7.5m, image acquisition continues; when the absolute distance difference corresponding to the subsequent effective positioning record is 3.8m, it is determined that the vehicle's position has entered the termination boundary determination range, and the vehicle terminal controls the vehicle camera device to stop the acquisition of the current scanning task segment.

[0096] When invalid positioning records occur continuously during the vehicle's passage through the termination boundary, and map matching results after the recovery of valid positioning indicate that the vehicle has already exceeded the termination boundary along the direction of travel, the on-board terminal determines that the vehicle has reached the termination boundary and stops image acquisition for the current scanning task segment.

[0097] The image is recorded and uploaded to the vehicle cloud.

[0098] When the vehicle-mounted camera generates an image, the vehicle terminal records the acquisition time of the corresponding image and establishes a correlation between the image and the vehicle's position, driving direction, and imaging direction at the corresponding acquisition time.

[0099] The vehicle-mounted camera captures images at 10fps, and the vehicle-mounted positioning terminal outputs positioning records at 10Hz. The vehicle-mounted terminal matches the images based on the absolute time difference between the image acquisition time and the positioning record UTC time.

[0100] For a given image frame, the location record with the smallest absolute time difference from the image acquisition time is selected from the location records that are valid in location status and have complete fields. In this implementation, the maximum allowable time difference is set to 0.05s.

[0101] When the minimum absolute time difference does not exceed 0.05s, the vehicle position and driving direction in the positioning record are associated with the image, and the imaging direction is determined according to the driving direction and the 20° installation azimuth angle to form an image record.

[0102] If the minimum absolute time difference exceeds 0.05s, the image will not be used to create an image record for road scanning status updates and will not be included in the subsequent valid acquisition determination.

[0103] For example, if an image frame is acquired at 08:48:12.300, and there is a valid location record with an acquisition time of 08:48:12.300, the vehicle's driving direction is 95°, and the vehicle's position, after map matching, is located in the 101st road scanning unit with an imaging direction of 115°, then an image record is formed that includes the image, the acquisition time of 08:48:12.300, the vehicle's position, the 95° driving direction, and the 115° imaging direction.

[0104] The next frame of the image was acquired at 08:48:12.400, corresponding to the next valid positioning record. At a speed of 30 km / h, the vehicle-road displacement between the two acquisitions was approximately 0.833 m.

[0105] After a complete image record is generated, the vehicle terminal uploads the image record to the cloud server via the vehicle wireless communication device.

[0106] After receiving the image record, the cloud server determines the route mileage on the center line of the corresponding bus route based on the map matching method used when establishing the road scanning unit, according to the vehicle position in the image record, and determines the road scanning unit corresponding to the image record based on the route mileage and the unit boundary.

[0107] Data lacking any of the following: image, acquisition time, vehicle location, driving direction, or imaging direction, will not be included in the valid acquisition record determination, nor will it be used to update the previous valid acquisition time.

[0108] When the vehicle passes through the first 120m scan segment at a speed of 30km / h, the passage time is approximately 14.400s. A set of acquired data forms 144 complete image records, with 47 image records corresponding to the 101st road scan unit, 49 image records corresponding to the 102nd road scan unit, and 48 image records corresponding to the 103rd road scan unit, for a total of 144 frames.

[0109] The road scanning unit corresponding to each image record is determined based on the vehicle position in the image record, and the road scanning unit is not divided according to a fixed number of frames.

[0110] Determine if the data collection record is valid.

[0111] After the cloud server determines the road scanning unit corresponding to the image record, it reads the allowed acquisition direction and allowed imaging direction of that road scanning unit.

[0112] The cloud server uses the minimum included angle calculation method of the circle used when determining candidate scanning units to determine the directional deviation between the driving direction and the allowed acquisition direction in the image record, and to determine the directional deviation between the imaging direction and the allowed imaging direction.

[0113] When the deviation in driving direction does not exceed 12° and the deviation in imaging direction does not exceed 18°, the corresponding image record is determined as a valid acquisition record.

[0114] When the deviation in driving direction exceeds 12°, the corresponding image record is uncertain as a valid acquisition record; when the deviation in imaging direction exceeds 18°, the corresponding image record is uncertain as a valid acquisition record.

[0115] For example, the allowed acquisition direction of the 101st road scanning unit is 90°, and the allowed imaging direction is 110°. In a certain image record, the driving direction is 97° and the imaging direction is 117°, with a deviation of 7° between the two directions. The corresponding image record is determined to be a valid acquisition record.

[0116] In another image recording, the driving direction is 94° and the imaging direction is 114°, with a deviation of 4° between the two directions. The corresponding image recording is determined to be a valid acquisition record.

[0117] The permitted acquisition direction of the 103rd road scanning unit is 95°, and the permitted imaging direction is 115°. After a vehicle enters the 103rd road scanning unit, when the driving direction in the image recording is between 108° and 112°, the corresponding driving direction deviation is between 13° and 17°, which exceeds 12°.

[0118] Because the installation angle of the vehicle-mounted camera is 20°, the corresponding imaging direction is 128° to 132°, which deviates from the allowable imaging direction of 115° by 13° to 17°. Although the imaging direction deviation does not exceed 18°, the driving direction deviation exceeds 12°. Therefore, the corresponding image recording is uncertain as a valid acquisition record.

[0119] Once the scanning task segment has been initiated, if the image records corresponding to some road scanning units do not meet the directional conditions, the vehicle-mounted terminal will not change the already determined start and end boundaries. After the corresponding image records are uploaded, the cloud server will perform effective acquisition and judgment according to the actual corresponding road scanning units.

[0120] Of the 144 frames of image records mentioned above, the 101st road scanning unit corresponds to 47 frames. Among them, 42 frames simultaneously meet the allowable acquisition direction deviation range and the allowable imaging direction deviation range, and are determined to be valid acquisition records. The remaining 5 frames are not determined to be valid acquisition records.

[0121] The 102nd road scanning unit corresponds to 49 frames. All 49 frames meet the two directional conditions and are therefore determined to be valid acquisition records.

[0122] The 103rd road scanning unit corresponds to 48 frames. The deviation of the driving direction in each image record exceeds 12°. Therefore, the 103rd road scanning unit did not form an effective acquisition record.

[0123] When a scanning task segment has been executed and an image record has been formed, the determination of whether the corresponding road scanning unit has formed a valid acquisition record is still based on the actual judgment result of the image record corresponding to each road scanning unit.

[0124] Update the previous valid acquisition time and establish the subsequent scan status.

[0125] After the road scanning unit generates a valid data collection record, the cloud server reads the collection time of the corresponding valid data collection record.

[0126] When there are multiple valid acquisition records for the same road scanning unit, the valid acquisition records are arranged according to the acquisition time, and the acquisition time corresponding to the valid acquisition record with the largest acquisition time value is used to update the previous valid acquisition time of the road scanning unit.

[0127] For example, if the previous valid acquisition time of the 101st road scanning unit was empty, and the acquisition time of the 42 valid acquisition records in this round is distributed between 08:48:10.600 and 08:48:14.800, then 08:48:14.800 will be recorded as the new previous valid acquisition time of the 101st road scanning unit.

[0128] The previous valid acquisition time for the 102nd road scanning unit was 08:10:00. The longest acquisition time in the 49 valid acquisition records of this round is 08:48:19.600. Therefore, the previous valid acquisition time of the 102nd road scanning unit will be updated to 08:48:19.600.

[0129] When the system re-evaluates the 101st road scanning unit at 09:05:00, the time interval between 09:05:00 and 08:48:14.800 is 16min45.2s, which is less than 30min, so the 101st road scanning unit remains in valid acquisition status.

[0130] When the system re-evaluates the 101st road scanning unit at 09:20:00, the time interval between 09:20:00 and 08:48:14.800 is 31 min 45.2 s, reaching 30 min. If the 101st road scanning unit simultaneously meets the candidate scanning unit conditions, the 101st road scanning unit is re-determined as the unit to be scanned.

[0131] The 103rd road scanning unit did not generate a valid data collection record in this round, therefore the previous valid data collection time of 08:05:00 will be retained.

[0132] At the current time of 08:50:00, the time interval between 08:50:00 and 08:05:00 is 45 minutes, reaching 30 minutes. If the 103rd road scanning unit subsequently meets the candidate scanning unit conditions again, it will still be identified as a unit to be scanned.

[0133] If a road scanning unit did not record its previous valid acquisition time and has not yet generated a valid acquisition record in the current round, it will continue to maintain the state where the previous valid acquisition time was not recorded. When this road scanning unit meets the conditions for a candidate scanning unit in the next round, it will be determined as a unit to be scanned based on the condition that the previous valid acquisition time was not recorded.

[0134] A vehicle-cloud collaborative scanning and processing process is formed.

[0135] The vehicle-mounted positioning terminal collects the vehicle's location and driving direction. The vehicle-mounted terminal determines the imaging direction based on the driving direction and the installation orientation of the vehicle-mounted camera device, and uploads the vehicle location, driving direction, imaging direction, and UTC time to the cloud server through the vehicle-mounted wireless communication device.

[0136] The cloud server determines the road scanning unit corresponding to the vehicle based on the vehicle's location, determines candidate scanning units based on the driving direction and imaging direction, determines the unit to be scanned based on the previous valid acquisition time corresponding to the candidate scanning unit, and forms a scanning task segment based on consecutive adjacent units to be scanned.

[0137] After the scanned task segment is sent to the vehicle terminal, the vehicle terminal controls the vehicle camera to start and stop the acquisition based on the vehicle position, the starting boundary, the ending boundary, and the allowed acquisition direction corresponding to the road scanning unit at the starting position.

[0138] After the vehicle-mounted camera generates an image, the vehicle-mounted terminal matches the image with the valid location record based on the UTC time, and associates the image, acquisition time, vehicle position, driving direction, and imaging direction to form an image record.

[0139] After the image records are uploaded to the cloud server, the cloud server determines the corresponding road scanning unit based on the vehicle position in the image records, and determines the valid acquisition records based on the directional deviation between the driving direction and the allowed acquisition direction and the directional deviation between the imaging direction and the allowed imaging direction.

[0140] When multiple valid acquisition records exist for the same road scanning unit, the previous valid acquisition time of the corresponding road scanning unit is updated using the valid acquisition record with the largest acquisition time value. Road scanning units that have not formed a valid acquisition record retain their original previous valid acquisition time.

[0141] Taking the aforementioned road scanning units 101 to 108 as an example, when the vehicle's current driving direction is 96° and the imaging direction is 116°, road scanning units 101, 102, 103, 105, 106 and 107 are determined as candidate scanning units.

[0142] At the current time of 08:47:00, road scanning units 101, 102, 103, 105 and 106 are identified as units to be scanned, while road scanning unit 107 remains in active acquisition mode.

[0143] The 101st to 103rd road scanning units form the first scanning task segment of 120m, and the 105th and 106th road scanning units form the second scanning task segment of 80m.

[0144] When the bus passes through the first scan segment at 30 km / h, the passage time is approximately 14.400 s. During this acquisition process, 144 complete image records were generated, with 47 frames corresponding to the 101st road scan unit, 49 frames to the 102nd road scan unit, and 48 frames to the 103rd road scan unit.

[0145] Based on the directional conditions, the 101st road scanning unit generated 42 valid acquisition records, the 102nd road scanning unit generated 49 valid acquisition records, and the 103rd road scanning unit did not generate any valid acquisition records.

[0146] The previous valid acquisition time for the 101st road scanning unit was updated to 08:48:14.800, the previous valid acquisition time for the 102nd road scanning unit was updated to 08:48:19.600, and the 103rd road scanning unit remained at 08:05:00.

[0147] When the vehicle passes through the second scanning task segment, the 80m road area corresponds to a passage time of approximately 9.600s and approximately 96 0.1s image sampling intervals at a speed of 30km / h. When the image records corresponding to the 105th and 106th road scanning units meet their respective allowable acquisition direction deviation ranges and allowable imaging direction deviation ranges, the previous valid acquisition time is updated using the valid acquisition record with the largest acquisition time value in the corresponding road scanning unit.

[0148] In this embodiment, the vehicle position is obtained by the GNSS satellite navigation positioning receiver in the vehicle-mounted positioning terminal; the driving direction is the effective ground heading angle output by the GNSS satellite navigation positioning receiver; the imaging direction is determined according to the driving direction and the installation azimuth angle of the vehicle-mounted camera device; the image is acquired by the image sensor of the vehicle-mounted camera device; the acquisition time is the vehicle-mounted terminal time calibrated with GNSSSUTC time; the current time is the UTC time of the cloud server; the unit boundary is determined according to the cumulative road length of the bus route centerline; the allowed acquisition direction is determined according to the route direction of the corresponding road scanning unit; the allowed imaging direction is determined according to the allowed acquisition direction and the installation azimuth angle of the vehicle-mounted camera device; the previous effective acquisition time is updated according to the effective acquisition records already formed by the corresponding road scanning unit.

[0149] A 40m road scanning unit at a vehicle speed of 30km / h corresponds to a transit time of approximately 4.800s and approximately 48 0.1s sampling intervals; a 120m scanning task segment corresponds to a transit time of approximately 14.400s and approximately 144 0.1s sampling intervals; an 80m scanning task segment corresponds to a transit time of approximately 9.600s and approximately 96 0.1s sampling intervals. The 10Hz positioning data from the vehicle-mounted positioning terminal and the 10fps image data from the vehicle-mounted camera device are matched using UTC time.

[0150] Each road scanning unit in the bus route stores its unit boundary, allowed acquisition direction, allowed imaging direction, and previous valid acquisition time. The current vehicle identifies candidate scanning units for road scanning units corresponding to its vehicle position, driving direction, and imaging direction, and forms scanning task segments for the units to be scanned that meet the previous valid acquisition time condition.

[0151] For road scanning units that have already had valid data collection records from the previous bus, subsequent buses will still determine their status based on the current time and the updated previous valid data collection time. If the time interval is less than 30 minutes, the corresponding road scanning unit will remain in valid data collection status; if the time interval reaches 30 minutes and the corresponding road scanning unit meets the candidate scanning unit conditions again, the corresponding road scanning unit will be re-identified as a unit to be scanned.

[0152] Using the above processing method, the previous valid acquisition time of the road scanning unit is updated based on valid acquisition records that meet the conditions of vehicle position, driving direction, and imaging direction. Road scanning units that have not formed valid acquisition records retain their original previous valid acquisition time and participate in the determination of subsequent candidate scanning units according to their original previous valid acquisition time.

[0153] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A city bus full-area intelligent scanning system based on vehicle-cloud collaborative technology, characterized in that, The system includes: a cloud server, a vehicle terminal, a vehicle positioning terminal, a vehicle camera device, and a vehicle wireless communication device; The cloud server divides the bus route into road scanning units, records the unit boundary, allowed acquisition direction, allowed imaging direction and previous valid acquisition time of each road scanning unit, and determines candidate scanning units based on the vehicle position and driving direction collected by the vehicle positioning terminal and the imaging direction of the vehicle camera device. When the candidate scanning unit does not record the previous valid acquisition time, and when the candidate scanning unit records the previous valid acquisition time and the time interval between the current time and the previous valid acquisition time reaches the preset valid scanning time limit, the candidate scanning unit is determined as the unit to be scanned. The adjacent units to be scanned are grouped into a scanning task segment according to the unit boundary. The start boundary and the end boundary are determined by the unit boundaries at both ends of the scanning task segment, and the segment is sent to the vehicle terminal through a wireless communication link. The vehicle-mounted terminal activates the vehicle-mounted camera when the vehicle position reaches the starting boundary and the driving direction is within the preset allowable acquisition direction deviation range, and stops acquisition when the vehicle position reaches the ending boundary, forming an image record containing the recorded image, acquisition time, vehicle position, driving direction and imaging direction, and uploads it through the vehicle-mounted wireless communication device; The cloud server determines the road scanning unit based on the vehicle position in the image record. When the driving direction is within the allowable acquisition direction deviation range of the corresponding road scanning unit and the imaging direction is within the allowable imaging direction deviation range, the previous valid acquisition time of the corresponding road scanning unit is updated with the acquisition time.

2. The urban public transport full-area intelligent scanning system based on vehicle-cloud collaborative technology according to claim 1, characterized in that, The process of determining the candidate scanning unit includes: The cloud server determines the road scanning unit corresponding to the vehicle position based on the unit boundary, and selects adjacent road scanning units along the driving direction starting from the road scanning unit. The driving direction is compared with the allowed acquisition direction of each road scanning unit, and the imaging direction is compared with the allowed imaging direction of each road scanning unit. When the driving direction is within a preset allowable acquisition direction deviation range and the imaging direction is within a preset allowable imaging direction deviation range, the corresponding road scanning unit is determined as the candidate scanning unit.

3. The urban public transport full-area intelligent scanning system based on vehicle-cloud collaborative technology according to claim 2, characterized in that, The cloud server determines each road scanning unit according to the arrangement of the unit boundaries in the driving direction, and forms a candidate scanning unit sequence for road scanning units whose driving direction is within the allowable acquisition direction deviation range and whose imaging direction is within the allowable imaging direction deviation range, according to the arrangement of the unit boundaries. The candidate scanning unit sequence is used to determine the unit to be scanned.

4. The urban public transport full-area intelligent scanning system based on vehicle-cloud collaborative technology according to claim 3, characterized in that, The cloud server determines the previous valid acquisition time for each candidate scanning unit in the candidate scanning unit sequence, and identifies candidate scanning units that have not recorded the previous valid acquisition time as units to be scanned. For candidate scanning units that have a recorded previous valid acquisition time, the time interval between the current time and the previous valid acquisition time is calculated. If the time interval reaches the preset valid scanning time limit, the unit is determined as a unit to be scanned. If the time interval does not reach the preset valid scanning time limit, the valid acquisition state of the corresponding road scanning unit is maintained.

5. The urban public transport full-area intelligent scanning system based on vehicle-cloud collaborative technology according to claim 4, characterized in that, The cloud server combines consecutive adjacent units to be scanned into a scanning task segment according to the arrangement of the unit boundaries in the driving direction. The unit boundary corresponding to the unit to be scanned at the beginning position of the scanning task segment is determined as the starting boundary, and the unit boundary corresponding to the unit to be scanned at the end position of the scanning task segment is determined as the ending boundary. The starting boundary and the ending boundary are written into the scanning task segment.

6. The urban public transport full-area intelligent scanning system based on vehicle-cloud collaborative technology according to claim 5, characterized in that, The process of sending the scanning task segment includes: The cloud server writes the starting boundary, the ending boundary, and the allowed acquisition direction into the scanning task segment, and sends it to the vehicle terminal through a wireless communication link. The vehicle-mounted terminal receives the scanning task segment, determines the correspondence between the vehicle and the starting boundary and the ending boundary based on the vehicle position collected by the vehicle-mounted positioning terminal, starts the vehicle-mounted camera device when the vehicle position reaches the starting boundary and the driving direction is within the preset allowable acquisition direction deviation range, and stops acquisition when the vehicle position reaches the ending boundary.

7. The urban public transport full-area intelligent scanning system based on vehicle-cloud collaborative technology according to claim 6, characterized in that, The vehicle-mounted camera generates images during the acquisition process, and the vehicle-mounted terminal associates the images with the vehicle's position, driving direction, imaging direction, and acquisition time at the corresponding acquisition time to form an image record. The vehicle-mounted terminal sends the image recording to the cloud server via the vehicle-mounted wireless communication device. The cloud server determines the corresponding road scanning unit based on the vehicle position in the image recording and uses the driving direction and imaging direction in the image recording as the effective acquisition criteria for the corresponding road scanning unit.

8. The urban public transport full-area intelligent scanning system based on vehicle-cloud collaborative technology according to claim 7, characterized in that, The cloud server sets allowed acquisition directions and allowed imaging directions for the road scanning unit, compares the driving direction in the image record with the allowed acquisition direction, and compares the imaging direction in the image record with the allowed imaging direction. If the driving direction is within the preset allowed acquisition direction deviation range and the imaging direction is within the preset allowed imaging direction deviation range, the corresponding image record is determined as a valid acquisition record.

9. The urban public transport full-area intelligent scanning system based on vehicle-cloud collaborative technology according to claim 8, characterized in that, The cloud server reads the collection time corresponding to the valid collection record and writes the collection time into the previous valid collection time of the corresponding road scanning unit. Road scanning units that have not generated a valid acquisition record retain their previous valid acquisition time and continue to be used as the criteria for determining the previous valid acquisition time of subsequent candidate scanning units.

10. The urban public transport full-area intelligent scanning system based on vehicle-cloud collaborative technology according to claim 9, characterized in that, The cloud server uses the acquisition time written to the corresponding road scanning unit as the updated previous valid acquisition time, and determines the previous valid acquisition time for subsequent candidate scanning units. If the time interval between the current time and the updated previous valid collection time reaches the preset valid scanning time limit, the corresponding road scanning unit is determined as the unit to be scanned; Road scanning units that have not generated a valid acquisition record retain their previous valid acquisition time and participate in the determination of subsequent candidate scanning units according to their previous valid acquisition time.

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