Pedestrian road planning method and device, electronic equipment and storage medium

Abstract

Embodiments of the present application disclose a pedestrian road planning method and device, electronic equipment and a storage medium. The pedestrian road planning method comprises: acquiring road information of a region to be planned and position information of a pedestrian; matching the position information with the road information to obtain illegal position information of the pedestrian; and planning a pedestrian road in the region to be planned according to the illegal position information. Embodiments of the present application adjust and plan the pedestrian road in the region to be planned based on the illegal position information, automatically confirm a region with a safety hazard and a planning region to be corrected in the region to be planned, thereby improving the rationality and efficiency of urban road planning and reducing the frequency of illegal behavior of the pedestrian.

Description

Technical Field

[0001] The present invention relates to the field of urban planning technology, and in particular to a pedestrian road planning method, apparatus, electronic device and storage medium. Background Technology

[0002] Due to technological limitations, municipal departments have made unreasonable plans for pedestrian walkways. At the same time, the varying levels of public awareness have led some citizens to walk on lawns without sidewalks, causing many adverse effects on lawn management, or to cross motor vehicle lanes without designated pedestrian crossings, which has an adverse effect on the normal travel of motor vehicles and seriously endangers the safety of citizens crossing the lanes.

[0003] Currently, municipal departments typically adjust and plan pedestrian walkways in cities based on reports from road monitoring, traffic police, or nearby residents. For example, if a pedestrian walkway has already been created by foot traffic on a lawn, a paving stone can be laid to form a proper pedestrian walkway; or pedestrian crossings can be added to lanes where vehicles frequently cross the road. However, this method of road adjustment and planning requires a significant manpower investment for monitoring, feedback, and reporting, making it inefficient. Furthermore, without timely feedback or monitoring, it can easily lead to unnecessary traffic congestion or accidents. Summary of the Invention

[0004] This invention provides a pedestrian road planning method, apparatus, electronic device, and storage medium to improve the accuracy and efficiency of pedestrian road planning and reduce the waste of human resources.

[0005] In a first aspect, embodiments of the present invention provide a pedestrian path planning method, comprising:

[0006] Obtain road information and pedestrian location information for the area to be planned;

[0007] The location information is matched with the road information to obtain the pedestrian's violation location information;

[0008] Based on the location information of the violation, pedestrian walkways within the area to be planned are planned.

[0009] Secondly, embodiments of the present invention also provide a pedestrian path planning device, comprising:

[0010] The information acquisition module is used to acquire road information and pedestrian location information of the area to be planned.

[0011] The violation determination module is used to match the location information with the road information to obtain the pedestrian's violation location information;

[0012] The road planning module is used to plan pedestrian roads within the area to be planned based on the violation location information.

[0013] Thirdly, embodiments of the present invention also provide an electronic device, comprising:

[0014] One or more processors;

[0015] Storage device for storing one or more programs.

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the pedestrian road planning method as described in any embodiment of the present invention.

[0017] Fourthly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the pedestrian road planning method as described in any embodiment of the present invention.

[0018] This invention, based on road information of the area to be planned, obtains the walking location information of pedestrians within that area. Based on the matching results of the location information and road information, it determines the pedestrian's violation location information. Since the violation location information can identify the area where pedestrians violate regulations, the pedestrian road planning within the area to be planned is adjusted based on this information. This achieves automatic identification of areas with safety hazards and areas requiring correction within the planning area, thereby improving the rationality and efficiency of urban road planning, reducing the frequency of pedestrian violations, and consequently lowering the probability of traffic congestion or accidents. Attached Figure Description

[0019] Figure 1 This is a flowchart of the pedestrian road planning method in Embodiment 1 of the present invention;

[0020] Figure 2 This is a schematic diagram illustrating the determination of the lateral distance of a pedestrian's location information in a road according to Embodiment 1 of the present invention;

[0021] Figure 3 This is a flowchart of the pedestrian road planning method in Embodiment 2 of the present invention;

[0022] Figure 4 This is a schematic diagram of the pedestrian road planning device in Embodiment 3 of the present invention;

[0023] Figure 5 This is a schematic diagram of the electronic device in Embodiment 4 of the present invention. Detailed Implementation

[0024] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0025] Example 1

[0026] Figure 1 This is a flowchart of the pedestrian road planning method in Embodiment 1 of the present invention. This embodiment is applicable to situations where adjustments are made to the planning of sidewalks or crosswalks in urban areas and parks. The method can be executed by a pedestrian road planning device, which can be implemented in software and / or hardware and can be configured in an electronic device, such as a backend server or other device with communication and computing capabilities. Figure 1 As shown, the method specifically includes:

[0027] Step 101: Obtain road information and pedestrian location information for the area to be planned.

[0028] The "area to be planned" refers to areas requiring pedestrian walkway adjustments, such as park areas where pedestrians indiscriminately trample on lawns, urban areas where pedestrians cross roads without crosswalks, or road areas encompassing both parks and urban areas. Road information refers to planned information on various motor vehicle roads, pedestrian walkways, and park planning within the area to be planned. Pedestrian location information refers to location information uploaded by pedestrians during their activities, such as location data uploaded periodically by pedestrians using location devices on their mobile devices.

[0029] Specifically, when it is necessary to adjust the planning of pedestrian walkways in a certain area, the area is designated as the area to be planned, and information on various planned roads within that area, as well as specific area planning information, is obtained. Pedestrian location information uploaded over a period of time is also acquired. By combining this location information with the road information of the area to be planned, pedestrian violation records are identified, and road planning adjustments are made within the area to be planned based on these records. This ensures that road planning is based on the actual location information of pedestrians, making the planned roads meet the actual needs of pedestrians.

[0030] For example, when the area to be planned is a park, since there are no motor vehicle lanes within the park, the corresponding road information includes the pedestrian walkways already set up within the park. Furthermore, plazas are typically set up within the park for people to move around freely, and the road information includes the boundary information of these plaza areas. When the area to be planned is an urban area, the road information includes motor vehicle lane information, pedestrian walkway information, and the boundary information of pedestrian crossings set up on the motor vehicle lanes. Because the actual width of the road varies at different intersections, the area of ​​the pedestrian crossings also varies; therefore, it is necessary to obtain the boundary information of the pedestrian crossings to ensure the accuracy of determining pedestrian walking regulations. Similarly, when the area to be planned is an urban area, including both park areas and urban areas, the road information includes motor vehicle lane information, pedestrian walkway information, plaza boundary information, and pedestrian crossing boundary information. Therefore, the specific scope of the area to be planned is not limited; the road information is adjusted accordingly based on the actual road and activity area layout within the area to be regulated.

[0031] In one feasible embodiment, the road information includes the boundary information of the area to be planned, road network information, pedestrian crossing area information, and pedestrian activity area information; wherein, the road network information includes motor vehicle lane information and sidewalk information.

[0032] The planning area boundary information refers to the latitude and longitude coordinates of the entire planned area. For example, if the planned area is a park, the planning area boundary information refers to the latitude and longitude coordinates of the entire park boundary. Road network information refers to the information of various roads within the planned area, including motor vehicle lanes and pedestrian walkways. For example, road network information includes the road code, road name, starting and ending center positions, road width, and road length for each road. Pedestrian crossing area information refers to the boundary information of zebra crossings set on motor vehicle lanes; that is, the pedestrian crossing area information covers the entire zebra crossing area, not just its approximate latitude and longitude coordinates. For example, the pedestrian crossing area information includes the latitude and longitude coordinates of the outermost edge of the zebra crossing. Pedestrian activity area information refers to the boundary information of areas where vehicle access can be restricted, allowing pedestrians to move freely, such as the latitude and longitude coordinates of the boundary of a plaza within a park.

[0033] By utilizing various information from the road data, we can determine the existing areas in the planned area that are open to pedestrians, and determine whether there are any instances of pedestrians walking illegally based on their actual location information, as well as the specific locations of areas where illegal walking occurs.

[0034] Step 102: Match the location information with the road information to obtain the pedestrian's violation location information.

[0035] Since the road information contains the location information of the planned areas that people can walk normally in the area to be planned, by matching the actual walking location information of pedestrians with the road information, the location information of pedestrians in abnormal walking areas can be obtained, which is the illegal location information.

[0036] In one feasible embodiment, the location information includes at least latitude and longitude information and current speed;

[0037] Accordingly, step 102 includes:

[0038] Filter out position information where the current speed is greater than the speed threshold;

[0039] Based on the boundary information and latitude and longitude information of the area to be planned, filter out location information that is not within the area to be planned;

[0040] Based on the pedestrian crossing area information, the pedestrian activity area information, and the latitude and longitude information, the location information located in the pedestrian crossing area and the pedestrian activity area is filtered to obtain the filtered location information;

[0041] The location information of pedestrian violations is determined based on the matching results of the filtered location information and road network information.

[0042] The location information uploaded by pedestrians includes real-time latitude and longitude coordinates, as well as their current speed at that latitude and longitude. A speed threshold represents the maximum speed a pedestrian can normally walk at. When a pedestrian's current speed exceeds the speed threshold, it can be considered that the pedestrian is not walking autonomously and may be using other means of transportation, such as bicycles or mobility scooters. For example, the speed threshold can be set to 15 km / h.

[0043] By comparing the current speed in the location information uploaded by pedestrians with a speed threshold, location information with a current speed greater than the speed threshold is filtered out. The filtered information can be considered as non-pedestrian location information. For example, when a pedestrian positioning device reports its location information, the current speed of the positioning device is first determined. If the current speed is greater than 15 km / h, the location information obtained by that positioning device (i.e., non-pedestrian data) is filtered out.

[0044] To improve the efficiency of matching pedestrian location information, it is necessary to first filter out location information that is not within the area to be planned. Specifically, since the location information uploaded by pedestrians may include locations outside the area to be planned, the latitude and longitude coordinates in the pedestrian's uploaded location information are determined based on the boundary information of the area to be planned. If not, the location is filtered. For example, when a pedestrian reports location information through a positioning device, the latitude and longitude coordinates in the pedestrian's location information are matched against the area to be planned to determine whether the location is within the polygonal area of ​​the area to be planned (e.g., whether it is in a park or urban area). If not, the location is filtered.

[0045] Because there are areas within the planned area where pedestrians can walk normally, such as crosswalks and pedestrian activity areas, the location information uploaded by pedestrians may contain legitimate walking locations. Therefore, this portion of location information needs to be filtered. Specifically, based on the matching results between the filtered location information and the location information within the crosswalk and pedestrian activity areas, pedestrian location information located within these areas is filtered. For example, the filtered location information is matched with normal walking areas (such as zebra crossings and park / plaza areas). If the latitude and longitude coordinates in the location information collected by the positioning device are within this normal walking area, then it is filtered.

[0046] The above filtering operations have filtered the location information of pedestrians who are not walking autonomously, pedestrians who are not in the planning area, and pedestrians who can walk normally in the planning area. The filtered location information is then matched with the pedestrian walkway information and motor vehicle lane information in the road network information to determine the illegal location information of those who are not walking on the pedestrian walkway.

[0047] Since the pedestrian and vehicle lane information in the road network data only includes information such as the center position of the road's starting and ending points, road width, and road length, it is necessary to accurately determine whether pedestrians are walking in the vehicle lane (e.g., crossing the road) or not walking on the sidewalk (e.g., walking on the grass next to the sidewalk). By matching the filtered location information with the vehicle lane and pedestrian information in the road network data, we can obtain location information indicating pedestrians not walking on the sidewalk or walking in the vehicle lane, thus identifying these as violations.

[0048] The location information is matched with the information of motor vehicle lanes. If the latitude and longitude data in the location information matches the road network data of the motor vehicle lanes, it is considered an illegal location information. It is also matched with the information of pedestrian walkways. If the latitude and longitude data in the location information does not match the road network data of the pedestrian walkways, it is considered an illegal location information.

[0049] In one feasible embodiment, the road network information includes the starting and ending points of the motor vehicle lanes and sidewalks, as well as the road width;

[0050] Accordingly, the pedestrian's violation location information is determined based on the matching results of the filtered location information and road network information, including:

[0051] Determine the lateral distance of the filtered location information within the target vehicle lane and the lateral distance within the target sidewalk; the lateral distance is determined using the following formula:

[0052]

[0053] h is the lateral distance; a is the distance between the filtered location information and the starting point of the target motor vehicle lane, or the distance between the filtered location information and the starting point of the target sidewalk; b is the distance between the filtered location information and the ending point of the target motor vehicle lane, or the distance between the filtered location information and the ending point of the target sidewalk.

[0054] If the lateral distance of the filtered location information in the target motor vehicle lane is less than the lateral threshold, then the filtered location information is determined to be illegal location information.

[0055] If the lateral distance of the filtered location information in the target sidewalk is greater than the lateral threshold, then the filtered location information is determined to be illegal location information;

[0056] The lateral threshold is determined based on the road width of the target motor vehicle lane or the target sidewalk.

[0057] The starting point of the motor vehicle lane and the sidewalk refers to the center latitude and longitude coordinates of the starting point of the road, and the ending point refers to the center latitude and longitude coordinates of the ending point of the road.

[0058] like Figure 2 The diagram illustrates the determination of a pedestrian's lateral distance within a road, where the road includes both motor vehicle lanes and sidewalks. Lateral distance represents the pedestrian's position on that road. Based on the location data, the latitude and longitude information of the pedestrian's location can be obtained, such as lng and lat representing the pedestrian's latitude and longitude coordinates, road_start_site representing the road's starting point, road_end_site representing the road's ending point, road_length representing the road's length, and road_width representing the road's width. Using the distance calculation formula between coordinate points, the distance 'a' between the filtered location and the starting point of the target motor vehicle lane or sidewalk, and the distance 'b' between the filtered location and the ending point of the target motor vehicle lane or sidewalk, can be obtained. Furthermore, based on the triangle's shape characteristics, the height 'h' of the triangle can be obtained, which is the lateral distance.

[0059] The pedestrian's location information is matched sequentially with each road in the road network. If it is matched with a motor vehicle lane in the road network, and the lateral distance is less than the lateral threshold, it means that the pedestrian is walking on a motor vehicle, and the location information is determined to be illegal location information. If it is matched with a sidewalk in the road network, and the calculated lateral distance is greater than the lateral threshold, it means that the pedestrian is not walking on the sidewalk, and the location information is determined to be illegal location information.

[0060] Optionally, before sequentially matching the pedestrian's location information with each road in the road network, coarse localization can be performed based on the pedestrian's location information and the information on motor vehicle lanes and sidewalks in the road network. This determines the motor vehicle lanes and sidewalks near the pedestrian's location and the lateral distance to these roads, thereby improving the efficiency of identifying violation locations. The lateral threshold, which represents the coverage area of ​​the road, can be set to half the width of the target motor vehicle lane or the target sidewalk.

[0061] Based on the above information on the location of violations determined by lateral distance, we can obtain information on the location of people walking on the motor vehicle lane and those not walking on the sidewalk.

[0062] Step 103: Based on the information on the location of the violation, plan the pedestrian walkways within the planned area.

[0063] After obtaining information on pedestrian violations within the planned area, pedestrian walkways within that area are planned based on this information. For example, the concentration of violations can be used to identify areas requiring correction. This could involve re-laying new pedestrian crossings on motor vehicle lanes where pedestrians frequently cross the road, or creating new sidewalks in high-traffic areas of parks. This improves the rationality of urban and park road planning, aligns with normal pedestrian walking habits, and reduces pedestrian violations.

[0064] This invention, based on road information of the area to be planned, obtains the walking location information of pedestrians within that area. Based on the matching results of the location information and road information, it determines the pedestrian's violation location information. Since the violation location information can identify the area where the pedestrian violated regulations, the pedestrian road planning within the area to be planned is adjusted based on this information. This achieves automatic identification of areas with safety hazards and areas requiring correction within the planning area, thereby improving the rationality and efficiency of urban road planning and reducing the frequency of pedestrian violations.

[0065] Example 2

[0066] Figure 3 This is a flowchart of the pedestrian path planning method in Embodiment 2 of the present invention. Embodiment 2 is a further optimization based on Embodiment 1. Figure 3 As shown, the method includes:

[0067] Step 201: Obtain road information and pedestrian location information for the area to be planned.

[0068] Step 202: Match the location information with the road information to obtain the pedestrian's violation location information.

[0069] Optionally, in the previous embodiment, a speed threshold was used to filter the location information of pedestrians who were not walking autonomously. However, due to road congestion, the speed of motor vehicles may also drop below the speed threshold. Therefore, the collected location information may include pedestrians located in congested vehicles. To further determine that the illegal location information consists entirely of autonomously walking pedestrian data, the pedestrian movement trajectory is plotted based on the positioning data in the location information. If the movement trajectory of the target pedestrian is determined to be parallel to the motor vehicle lanes in the road network based on the target pedestrian's location information, then the target pedestrian's location information is determined to be non-autonomous pedestrian data, and a filtering operation is performed.

[0070] Step 203: Sort the violation location information according to the latitude and longitude information in the violation location information.

[0071] The filtered location information containing violations is sorted according to latitude and longitude. Specifically, the violation location information is sorted in ascending or descending order based on its latitude and longitude coordinates to confirm the approximate location of the violation.

[0072] Step 204: Group the violation location information according to the distance between adjacent violation location information in the sorting results.

[0073] Since the sorting results only provide a general confirmation of the location information for each violation, further regional division is needed to obtain the distribution area information of each violation location. Specifically, the violation locations are grouped based on the distance between adjacent locations. If the distance is less than a distance threshold, it indicates that adjacent violation locations are in the same area and are grouped into the same group. After grouping, each group constitutes a violation area. For example, there may be areas with concentrated violation locations on a motor vehicle lane; or areas with concentrated violation locations on a lawn.

[0074] Specifically, after sorting the collected location information by latitude and longitude coordinates in ascending or descending order, the distance between the second point and the first point is calculated. If the distance is less than a distance threshold, they belong to the same group. This process is repeated for the next point. The distance between each point below the sorted position and each point above it is calculated. If the distance to each point is greater than the distance threshold, it indicates that the point is far from the area of ​​the previous group, and a new group is added starting from that point as a new violation area. For example, the distance threshold can be set according to the actual situation, such as 20 meters. The distance between every two points in the sorted results is calculated iteratively. Points with a distance less than 20 meters are grouped together. Each iteration compares the distance with all previous locations until the distance calculation for all locations is completed. For example, when looping to the 7th location, the distance is calculated with the previous 6 points. If the distance to any point in a group is less than 20 meters, the loop is terminated, and the 7th location is classified into that group. If the distance between the 7th location and all 6 previous locations is greater than 20 meters, the 7th location is determined to be a new group.

[0075] The violation location information is grouped according to the distance between adjacent violation location information in the sorting results to achieve regional division, dividing the violation location information into multiple groups, with each group corresponding to a violation area.

[0076] Step 205: Determine the violation weight of each group based on the device information to which the violation location information belongs.

[0077] In addition to latitude and longitude coordinates and current speed, the location information uploaded by pedestrians also includes the device information. This device information is a unique identifier, such as the mobile phone identification code used to upload the data. Optionally, the device information can be associated with the user's identity information and contact details.

[0078] Specifically, after grouping, the number of different devices associated with the violation location information within each group is determined, i.e., the number of violators in each violation area is determined, and the violation weight is determined based on the number of violators. The more violators in a group, the higher the violation weight; for example, the number of violators can be directly determined as the violation weight. The violation weight of each group indicates the pedestrian violation density within that group's area.

[0079] Step 206: Plan pedestrian walkways within the planning area according to the violation weight.

[0080] The problem of pedestrian violations stems from either inadequate pedestrian walkway planning by municipal authorities or varying levels of public awareness and responsibility. Based on these two factors, if the issue is due to varying levels of public awareness, only a small percentage of people will violate the rules; however, if the problem lies with inadequate pedestrian walkway planning, the majority will violate the rules. Therefore, the violation weight can determine the cause of pedestrian violations in each group of areas. A high violation weight indicates that the problem in that area is due to inadequate pedestrian walkway planning, requiring redesign of the pedestrian walkways, such as adding crosswalks or sidewalks. A low violation weight indicates that only a small percentage of people violate the rules in that area, indicating that the problem is not due to varying levels of public awareness and responsibility, and therefore, warning signs can be installed in that area.

[0081] In one feasible embodiment, step 206 includes:

[0082] Groups with violation weights greater than the weight threshold are identified as dense violation groups, while groups with violation weights less than the weight threshold are identified as non-dense violation groups.

[0083] The dense violation areas are identified based on the location information of violations in the dense violation groups, so that pedestrian walkways can be planned according to the dense violation areas;

[0084] Based on the location information of violations in the non-dense violation group, identify the densely violating devices and send violation reminder information to them.

[0085] The weight threshold can be set according to the actual situation and is not restricted here.

[0086] For example, the groups are sorted in descending order according to their violation weights. The top three groups by violation weight, as well as the groups with more than 100 devices included, are identified as intensive violation groups, and the remaining groups are non-intensive violation groups.

[0087] By traversing the location information of violations in each dense violation group, the scope of the covered area is determined. For example, a quadrilateral area can be used to cover the violation location information, and the latitude and longitude information of the four corners of the quadrilateral can be determined so that the quadrilateral can completely cover the violation location information in the dense violation group. Pedestrian roads are then adjusted and planned based on the location information of the quadrilateral. For example, the violation location information is displayed to the planning department in the form of a regional heat map, and the three areas with the most violations and areas with more than 100 violations are regarded as dense violation areas, and relevant departments are alerted to these areas, indicating that they need to be focused on and replanned.

[0088] Pedestrian violations in areas with low-density violation groups are considered reasonable in terms of road planning, and pedestrians should not be violating regulations. Therefore, it is necessary to send reminder messages to the high-density violation devices in each low-density violation group to remind the device operators to pay attention, and report to the management department for education after repeated violations.

[0089] In one feasible embodiment, determining densely populated violation devices based on violation location information in a non-dense violation group includes:

[0090] The violation location information is classified according to the device information in the violation location information of the non-dense violation group to obtain the violation location information of each device;

[0091] The violation location information of each device is sorted according to the latitude and longitude information or time information in the violation location information of each device;

[0092] The number of violations for each device is determined based on the distance or time difference between adjacent violation locations in the sorting results.

[0093] The number of violations determines the number of equipment involved in the violations.

[0094] The violation location information is categorized based on the device information associated with each violation location within the non-dense violation group, thus identifying the violation location information for each device within the same non-dense violation group. This allows us to determine the number of violations committed by that device in each group, i.e., the number of complete violations. For example, when a pedestrian crosses the road once, multiple violation location reports may be generated; similarly, when a pedestrian walks outside the crosswalk, multiple violation location reports may also be generated. Therefore, it is necessary to determine the number of violations committed by the pedestrian in each non-dense violation group.

[0095] Specifically, the location can be determined based on latitude and longitude information or time information in the violation location information. For example, when determining based on latitude and longitude information, the location is sorted in ascending or descending order according to the latitude and longitude coordinates. The distance between the second point and the first point is calculated. If the distance is less than a distance threshold, it belongs to the same group. The process continues, calculating the distance between each point below the sorted position and each point above it. If the distance to each point is greater than the distance threshold, it indicates that the point is far from the area of ​​the previous group, and a new group is added starting from that point as a new violation. For example, the distance threshold can be set according to actual conditions, such as 20 meters. The distance between every two points in the sorted results is calculated iteratively. Points with a distance less than 20 meters are grouped together. Each loop compares the distance with all previous locations until the distance calculation for all locations is completed. For example, when looping to the 7th location, the distance is calculated with the previous 6 points. If the distance to a point in a group is less than 20 meters, the loop ends, and this point is classified into that group; otherwise, a new group is added. The final grouping result represents the number of violations for that device. Each group corresponds to one violation by the device.

[0096] For example, when determining based on time, the time information represents the reporting time of the violation location information. The violation location information from the device is sorted in ascending or descending order according to the time information. The time difference between adjacent points is calculated sequentially. If the time difference is less than a time threshold, the two points are determined to belong to the same violation. If the time difference between the target location point and an adjacent point is greater than the time threshold, that point is considered a new violation. The time threshold can be determined based on the pedestrian's walking speed and the area coverage of non-dense violation groups; for example, it can be set to 1 minute.

[0097] Based on the number of violations by each device in each non-intensive violation group, intensive violation devices are identified, and violation alerts are sent to these devices. For example, if the number of violations by a target device in any non-intensive violation group exceeds a threshold, that device is identified as an intensive violation device, and the time and location of its violation record are sent to the device to alert its owner. If the total number of violations by a target device across all non-intensive violation groups exceeds a total threshold, that device is identified as a key intensive violation device, and its associated information is sent to the relevant management department for supervision and education. For instance, based on the total number of violations by each device across all non-intensive violation groups, the associated information of the top three devices with the highest total number of violations is fed back to the relevant management department.

[0098] This invention, based on road information of a planned area, obtains pedestrian location information within that area. By matching the location information with road information, it determines the pedestrian's violation location information and identifies dense and non-dense violation areas. Different planning adjustments are then made for different types of violation areas. This accurately identifies areas with safety hazards and areas requiring correction within the planned area, thereby improving the rationality and efficiency of urban road planning and reducing the frequency of pedestrian violations. Since the areas for pedestrian road adjustment planning are determined based on actual pedestrian violation data, the accuracy of the adjustment planning is guaranteed.

[0099] Example 3

[0100] Figure 4 This is a schematic diagram of the pedestrian road planning device in Embodiment 3 of the present invention. This embodiment is applicable to the adjustment and planning of sidewalks or crosswalks in urban areas and parks. Figure 4 As shown, the device includes:

[0101] Information acquisition module 310 is used to acquire road information and pedestrian location information of the area to be planned;

[0102] The violation determination module 320 is used to match the location information with the road information to obtain the pedestrian's violation location information;

[0103] The road planning module 330 is used to plan pedestrian roads within the area to be planned based on the violation location information.

[0104] This invention, based on road information of the area to be planned, obtains the walking location information of pedestrians within that area. Based on the matching results of the location information and road information, it determines the pedestrian's violation location information. Since the violation location information can identify the area where the pedestrian violated regulations, the pedestrian road planning within the area to be planned is adjusted based on this information. This achieves automatic identification of areas with safety hazards and areas requiring correction within the planning area, thereby improving the rationality and efficiency of urban road planning and reducing the frequency of pedestrian violations.

[0105] Optionally, the road information includes boundary information of the area to be planned, road network information, pedestrian crossing area information, and pedestrian activity area information; wherein, the road network information includes motor vehicle lane information and sidewalk information.

[0106] Optionally, the location information includes at least latitude and longitude information and current speed;

[0107] Correspondingly, the violation identification module includes:

[0108] A speed filtering unit is used to filter position information where the current speed is greater than a speed threshold.

[0109] A region filtering unit is used to filter out location information that is not within the region to be planned based on the boundary information of the region to be planned and the latitude and longitude information.

[0110] The filtering information determination unit is used to filter the location information located in the pedestrian crossing area and the pedestrian activity area based on the pedestrian crossing area information, the pedestrian activity area information and the latitude and longitude information, so as to obtain the filtered location information.

[0111] The violation information determination unit is used to determine the violation location information of pedestrians based on the matching result of the filtered location information and the road network information.

[0112] Optionally, the road network information includes the starting and ending points of the motor vehicle lanes and sidewalks, as well as the road width;

[0113] Correspondingly, the violation information determination unit is specifically used for:

[0114] The lateral distances of the filtered location information within the target vehicle lane and within the target sidewalk are determined; wherein the lateral distances are determined using the following formula:

[0115]

[0116] h is the lateral distance; a is the distance between the filtered location information and the starting point of the target motor vehicle lane, or the distance between the filtered location information and the starting point of the target sidewalk; b is the distance between the filtered location information and the ending point of the target motor vehicle lane, or the distance between the filtered location information and the ending point of the target sidewalk.

[0117] If the lateral distance of the filtered location information in the target vehicle lane is less than the lateral threshold, then the filtered location information is determined to be illegal location information.

[0118] If the lateral distance of the filtered location information in the target sidewalk is greater than the lateral threshold, then the filtered location information is determined to be illegal location information;

[0119] The lateral threshold is determined based on the road width of the target motor vehicle lane or the target sidewalk.

[0120] Optional, road planning module, including:

[0121] An information sorting unit is used to sort the violation location information according to the latitude and longitude information in the violation location information;

[0122] An information grouping unit is used to group the violation location information according to the distance between adjacent violation location information in the sorting result;

[0123] The violation weight determination unit is used to determine the violation weight of each group based on the device information to which the violation location information belongs within each group.

[0124] A road planning unit is used to plan pedestrian roads within the area to be planned based on the violation weight.

[0125] Optional, road planning units include:

[0126] Grouping and determining sub-units are used to determine that groups with violation weights greater than a weight threshold are dense violation groups, and groups with violation weights less than a weight threshold are non-dense violation groups;

[0127] The dense violation group planning subunit is used to determine the dense violation area based on the violation location information in the dense violation group, so as to plan the pedestrian road according to the dense violation area;

[0128] The non-dense violation group planning subunit is used to determine the densely violating devices based on the violation location information in the non-dense violation group, so as to send violation reminder information to the densely violating devices.

[0129] Optional, non-dense violation group planning sub-units, specifically used for:

[0130] The violation location information is classified according to the device information in the violation location information of the non-dense violation group to obtain the violation location information of each device;

[0131] The violation location information of each device is sorted according to the latitude and longitude information or time information in the violation location information of each device;

[0132] The number of violations for each device is determined based on the distance or time difference between adjacent violation locations in the sorting results.

[0133] The number of violations is used to identify equipment with frequent violations.

[0134] The pedestrian road planning device provided in the embodiments of the present invention can execute the pedestrian road planning method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the pedestrian road planning method.

[0135] Example 4

[0136] Figure 5 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Figure 5 A block diagram is shown of an exemplary electronic device 12 suitable for implementing embodiments of the present invention. Figure 5 The electronic device 12 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0137] like Figure 5 As shown, the electronic device 12 is represented in the form of a general-purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, system storage device 28, and bus 18 connecting different system components (including system storage device 28 and processing unit 16).

[0138] Bus 18 represents one or more of several bus architectures, including a memory device bus or memory device controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. For example, these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0139] Electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0140] System storage device 28 may include computer system readable media in the form of volatile storage devices, such as random access memory (RAM) 30 and / or cache storage device 32. Electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write non-removable, non-volatile magnetic media (… Figure 5 Not shown; usually referred to as a "hard drive"). Although Figure 5 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 via one or more data media interfaces. Storage device 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0141] A program / utility 40 having a set (at least one) of program modules 42 may be stored in, for example, storage device 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 42 typically perform the functions and / or methods described in the embodiments of the present invention.

[0142] Electronic device 12 can also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), and with one or more devices that enable a user to interact with device 12, and / or with any device that enables device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed via input / output (I / O) interface 22. Furthermore, electronic device 12 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 20. Figure 5 As shown, network adapter 20 communicates with other modules of electronic device 12 via bus 18. It should be understood that, although... Figure 5 As not shown, other hardware and / or software modules may be used in conjunction with electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0143] Processing unit 16 executes various functional applications and data processing by running programs stored in system storage device 28, such as implementing the pedestrian road planning method provided in the embodiments of the present invention, including:

[0144] Obtain road information and pedestrian location information for the area to be planned;

[0145] The location information is matched with the road information to obtain the pedestrian's violation location information;

[0146] Based on the location information of the violation, pedestrian walkways within the area to be planned are planned.

[0147] Example 5

[0148] Embodiment 5 of the present invention also provides a computer-readable storage medium having a computer program stored thereon. When executed by a processor, the program implements the pedestrian path planning method provided in the embodiments of the present invention, including:

[0149] Obtain road information and pedestrian location information for the area to be planned;

[0150] The location information is matched with the road information to obtain the pedestrian's violation location information;

[0151] Based on the location information of the violation, pedestrian walkways within the area to be planned are planned.

[0152] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0153] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0154] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0155] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0156] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method of pedestrian road planning, characterized by, The method comprises the following steps: acquiring road information and position information of pedestrians in a region to be planned; the road information comprises boundary information of the region to be planned, road network information, pedestrian crossing region information, and pedestrian activity field region information; the road network information comprises motor vehicle lane information and sidewalk information; matching the position information with the road information to obtain illegal position information of the pedestrians; the illegal position information is position information of the pedestrians in an abnormal walking region; planning pedestrian roads in the region to be planned according to the illegal position information; the position information at least comprises longitude and latitude information and current speed; the matching of the position information with the road information to obtain the illegal position information of the pedestrians comprises the following steps: filtering position information with a current speed greater than a speed threshold; filtering position information not in the region to be planned according to the boundary information of the region to be planned and the longitude and latitude information; filtering position information in a pedestrian crossing region and a pedestrian activity field region according to the pedestrian crossing region information, the pedestrian activity field region information, and the longitude and latitude information to obtain filtered position information; determining illegal position information of the pedestrians according to a matching result of the filtered position information and the road network information; the planning of pedestrian roads in the region to be planned according to the illegal position information comprises the following steps: sorting the illegal position information according to longitude and latitude information in the illegal position information; grouping the illegal position information according to distances between adjacent illegal position information in a sorting result; determining illegal weight of each group according to device information of the illegal position information in each group; planning pedestrian roads in the region to be planned according to the illegal weight; the grouping of the illegal position information according to distances between adjacent illegal position information in the sorting result comprises: if the distance between adjacent illegal position information in the sorting result is less than a distance threshold, the adjacent illegal position information is in a same region and is divided into a same group.

2. The method of claim 1, wherein, the road network information comprises start point positions, end point positions, and road widths of motor vehicle lanes and sidewalks; correspondingly, the determination of illegal position information of the pedestrians according to a matching result of the filtered position information and the road network information comprises the following steps: determining a lateral distance of the filtered position information in a target motor vehicle lane and a lateral distance of the filtered position information in a target sidewalk; the lateral distance is determined by the following formula: ； is a lateral distance; is a distance between the filtered position information and a start position of the target motor lane, or a distance between the filtered position information and a start position of the target sidewalk; is a distance between the filtered position information and an end position of the target motor lane, or a distance between the filtered position information and an end position of the target sidewalk; if the lateral distance of the filtered position information in the target motor vehicle lane is less than a lateral threshold, the filtered position information is determined as illegal position information; if the lateral distance of the filtered position information in the target sidewalk is greater than the lateral threshold, the filtered position information is determined as illegal position information; the lateral threshold is determined according to the road width of the target motor vehicle lane or the target sidewalk.

3. The method of claim 1, wherein, the planning of pedestrian roads in the region to be planned according to the illegal weight comprises the following steps: determining groups with an illegal weight greater than a weight threshold as dense illegal groups, and groups with an illegal weight less than the weight threshold as non-dense illegal groups; determine a dense violation area according to the violation position information in the dense violation group, to plan a pedestrian road according to the dense violation area; determine a dense violation device according to the violation position information in the non-dense violation group, and send a violation reminding information to the dense violation device.

4. The method of claim 3, wherein, determine a dense violation device according to the violation position information in the non-dense violation group, and send a violation reminding information to the dense violation device. classify the violation position information according to the device information in the violation position information in the non-dense violation group, to obtain the violation position information of each device; sort the violation position information of each device according to the longitude and latitude information or the time information in the violation position information of each device; determine the number of violations of each device according to the distance or the time difference between the adjacent violation position information in the sorting result; determine the dense violation device according to the number of violations.

5. A pedestrian road planning device characterized by comprising: comprise: an information acquisition module, configured to acquire road information and position information of a pedestrian in a region to be planned; the road information comprises boundary information of the region to be planned, road network information, pedestrian crossing area information and pedestrian activity field area information; wherein the road network information comprises motor lane information and sidewalk information; a violation determination module, configured to match the position information with the road information, to obtain violation position information of the pedestrian; wherein the violation position information is position information of the pedestrian in an abnormal walking area; a road planning module, configured to plan a pedestrian road in the region to be planned according to the violation position information; the position information at least comprises longitude and latitude information and current speed; the violation determination module comprises: a speed filtering unit, configured to filter position information with current speed greater than a speed threshold value; a region filtering unit, configured to filter position information not in the region to be planned according to the boundary information of the region to be planned and the longitude and latitude information; a filtered information determination unit, configured to filter position information in a pedestrian crossing area and a pedestrian activity field area according to the pedestrian crossing area information, the pedestrian activity field area information and the longitude and latitude information, to obtain filtered position information; a violation information determination unit, configured to determine violation position information of the pedestrian according to a matching result of the filtered position information and the road network information; the road planning module comprises: an information sorting unit, configured to sort the violation position information according to the longitude and latitude information in the violation position information; an information grouping unit, configured to group the violation position information according to the distance between adjacent violation position information in the sorting result; a violation weight determination unit, configured to determine a violation weight of each group according to the device information of the violation position information in each group; a road planning unit, configured to plan a pedestrian road in the region to be planned according to the violation weight; the information sorting unit is specifically configured to, if the distance between adjacent violation position information in the sorting result is less than a distance threshold value, the adjacent violation position information is in a same area and is divided into a same group.

6. An electronic device, comprising: comprise: one or more processors; a storage device, configured to store one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement a pedestrian road planning method as claimed in any one of claims 1-4.

7. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program, when executed by a processor, implements a pedestrian road planning method as claimed in any one of claims 1-4.

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