Snow removal determination support system, program, and road management method

Abstract

To provide a safe and secure road traffic environment to a road user by determining the optimum snow removal work period on a snowy road surface so as to prevent a delay of the snow removal work and deterioration of a road traffic function.SOLUTION: A snow removal determination support system comprises: an information acquisition section for acquiring information related to a vehicle travel state including a bus delay time due to snow and information related to a road surface state including presence / absence of road width reduction due to piled snow; an analysis section for analyzing the vehicle travel state and the road surface state obtained from the information acquired by the information acquisition section; and a determination section for determining necessity of snow removal based on a result analyzed by the analysis section.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to optimizing snow removal decisions on snow-covered road surfaces. [Background technology]

[0002] In cold, snowy regions, in order to maintain urban functions and ensure smooth road traffic during the winter, it is necessary to remove snow from roads when snow accumulates, and visual patrols are conducted to determine when snow removal work should be carried out. [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] Takikawa City Civil Engineering Division, "Please cooperate with snow removal and disposal," Snowplow deployment times, [online], December 17, 2015, Takikawa City, [Searched September 19, 2023], Internet<URL:https: / / www.city.takikawa.hokkaido.jp / 240kensetsu / 01doboku / 07zyosetu / > [Non-Patent Document 2] Hiroo Town Construction and Waterworks Division, "About snow removal on town roads", Snowplow deployment standards, [online], Date of publication unknown, Hiroo Town, [Searched on September 19, 2023], Internet<URL:https: / / www.town.hiroo.lg.jp / kurashi / seikatsu / josetsu / choudounojosetsu / > Summary of the Invention [Problem to be solved by the invention]

[0004] Visual patrols are used to determine when snow removal work should be performed, but there is variation in the judgment of the timing of snow removal work depending on the experience of the patrol members, etc. This causes delays in snow removal work and reduces road traffic functions during the winter. [Means for solving the problem]

[0005] The above problems can be solved by the invention having the following configuration. [1] A snow removal and disposal decision-making support system comprising an information acquisition unit that acquires information regarding vehicle driving conditions, including bus delays due to snow, an analysis unit that analyzes the vehicle driving conditions obtained from the information acquired by the information acquisition unit, and a decision unit that determines the need for snow removal and disposal based on the results of the analysis by the analysis unit, wherein the decision unit determines the need for snow removal and disposal. [2] A snow removal decision-making support system comprising an information acquisition unit that acquires information on vehicle driving conditions, including bus delays due to snow, and information on road surface conditions, including whether or not road width has been reduced due to snow accumulation; an analysis unit that analyzes the vehicle driving conditions and road surface conditions obtained from the information acquired by the information acquisition unit; and a decision unit that determines the need for snow removal based on the results of the analysis by the analysis unit, wherein the decision unit determines the need for snow removal. [3] A program for causing a computer to function as the snow removal decision support system described in [1] or [2]. [4] A road management method using a computer, characterized in that the computer acquires information regarding vehicle driving conditions, including bus delays due to snow, via a network, analyzes the vehicle driving conditions obtained from the acquired information, and determines the need for snow removal and disposal from the results of the analysis. [5] A road management method using a computer, characterized in that the computer acquires, via a network, information on vehicle driving conditions, including bus delays due to snow, and information on road surface conditions, including whether or not road width has been reduced due to snow accumulation, analyzes the vehicle driving conditions and road surface conditions obtained from the acquired information, and determines the need for snow removal and disposal from the results of the analysis. Effect of the Invention

[0006] By determining the optimal timing for snow removal work on snow-covered roads, the present invention can prevent delays in snow removal work and a decline in road traffic functions, thereby providing road users with a safe and secure road traffic environment. [Brief description of the drawings]

[0007] [Figure 1] 1 is a system configuration diagram of a snow removal decision support system according to the present invention. [Diagram 2] FIG. 11 is a flow chart illustrating an example of a flow of a patrol. [Diagram 3] FIG. 11 is a flow chart illustrating an example of a flow of a fixed camera. [Figure 4] FIG. 2 is a diagram showing an example of a road surface condition. [Diagram 5] FIG. 2 is a cross-sectional view showing an example of road surface conditions (unevenness of a snow-covered road surface). [Figure 6] FIG. 2 is a cross-sectional view showing an example of road surface conditions (thickness of packed snow on the road surface). [Figure 7] FIG. 1 is a diagram illustrating an example of a traffic situation. [Figure 8] FIG. 1 is a diagram showing an example of a road space situation. [Figure 9] FIG. 1 is a diagram illustrating an example of weather conditions. [Figure 10] FIG. 2 is a diagram illustrating an example of a vehicle driving situation. [Figure 11] 1 is a flow chart showing a flow of an example of a snow removal decision support system of the present invention. [Figure 12] FIG. 13 is a diagram showing an example of a determination criterion in a decision unit of the present invention. [Figure 13] 1 is a diagram illustrating an example of a hardware configuration of a snow removal decision support system according to the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] Hereinafter, an embodiment of the snow removal decision support system of the present invention will be described with reference to the drawings. Note that the present embodiment described below does not unduly limit the contents of the present disclosure described in the claims. In addition, not all of the configurations described in the present embodiment are essential components of the present disclosure. In addition, each of the configurations constituting the feature group can also be an invention.

[0009] 1 is a system configuration diagram of a snow removal decision support system 600 of the present invention. Snow removal decision support system 600 includes an information acquisition unit 610 that acquires information on road surface conditions, traffic conditions, road space conditions, weather conditions, and vehicle driving conditions, an analysis unit 620 that analyzes the road surface conditions, traffic conditions, road space conditions, weather conditions, and vehicle driving conditions obtained from the information acquired by the information acquisition unit 610, and a decision unit 630 that decides the need for snow removal from the results of the analysis by the analysis unit 620. The snow removal decision support system 600 of the embodiment is communicatively connected to a road surface condition providing server 100, a traffic condition providing server 200, a road space condition providing server 300, a weather condition providing server 400, and a vehicle driving condition providing server 500 via a network NW. Although FIG. 1 shows only one vehicle Vh and one terminal device TM for grasping road surface conditions, a plurality of vehicles Vh and terminal devices TM may be connected to a network NW. Although FIG. 1 shows only one fixed camera CAM for grasping the road space situation, multiple fixed cameras CAM may be connected to the network NW.

[0010] The terminal device TM, the fixed camera CAM, the road surface condition providing server 100, the traffic condition providing server 200, the road space condition providing server 300, the weather condition providing server 400, the vehicle travel condition providing server 500, and the snow removal decision support system 600 communicate via a network NW. The network NW includes, for example, some or all of a WAN (Wide Area Network), a LAN (Local Area Network), the Internet, a provider device, a wireless base station, a dedicated line, and the like. The communication method is not limited to the network NW, but data can also be sent and received via a memory card. Data can also be downloaded and uploaded via the network NW.

[0011] The terminal device TM is used by a user who gets into the vehicle Vh. The terminal device TM is a mobile phone such as a smartphone, a tablet terminal, or the like. The terminal device TM may be a communication type drive recorder mounted on the vehicle Vh or a stationary in-vehicle device, and may be equipped with an image recognition function using AI (artificial intelligence). The terminal device TM has a road patrol application installed therein, which cooperates with the road surface condition providing server 100 . The terminal device TM includes a positioning device such as a GPS (Global Positioning System) receiver, a communication device for connecting to the network NW, input / output devices such as a G sensor (acceleration sensor), a camera, and a touch panel, and a processor such as a CPU (Central Processing Unit).

[0012] 2 is a flow chart showing an example of the flow of a patrol. When the terminal device TM presses a patrol start button of a road patrol application (S1), the terminal device TM starts collecting position information, acceleration information, images, etc. (S2). After the patrol is completed, the user presses a patrol end button in the road patrol application (S3) to transmit the position information, acceleration information, video, etc. of the terminal device TM to the road surface condition providing server 100 (S4). The road surface condition providing server 100 determines the presence or absence of unevenness on the road surface based on the measurement information transmitted from the terminal device TM, and identifies the location of the road surface determined to be uneven. The position information, acceleration information, video, and the like transmitted to the road surface condition providing server 100 may be measurement information from a private car, a taxi, a truck, and the like.

[0013] Fixed-point cameras CAM are installed on roads (main arterial roads, roads with heavy traffic, major bus routes, roads important for transporting and clearing snow to snow dumps, roads connecting to schools, public facilities, and emergency hospitals, etc.), buildings around intersections, and roadside posts and poles. Fixed-point cameras CAM are live cameras, web cameras, network cameras, etc. that are capable of communication. The fixed camera CAM may be a communication-type drive recorder or a small unmanned aerial vehicle such as a drone, and may be equipped with an image recognition function using AI (artificial intelligence). The fixed camera CAM has a built-in camera application that communicates with the road space situation providing server 300 . The fixed camera CAM includes a lens, an image sensor, a positioning device such as a GPS (Global Positioning System) receiver, a communication device for connecting to the network NW, and a processor such as a CPU (Central Processing Unit).

[0014] 3 is a flow chart showing an example of the flow of the fixed camera CAM. The fixed camera CAM periodically or intermittently collects road space conditions (S5), and automatically transmits images, position information, date and time information, etc. to the road space conditions providing server 300 periodically or intermittently (S6). The road space situation providing server 300 judges the height of snow banks (snow mountains on the roadside, omitted below) based on the images transmitted from the fixed camera CAM, and identifies the positions of the road spaces judged to be dangerous spots.

[0015] The road surface condition providing server 100 provides road surface conditions via the network NW to the snow removal decision support system 600. The road surface conditions provided are information for each road, and include some or all of the following: freezing of the road surface, snow accumulation and snow quality on the road surface, unevenness of the snow-covered road surface, ruts and mortars on the snow-covered road surface, thickness of packed snow on the road surface, and whether or not the road width has been reduced due to snow accumulation. FIG. 4 is a diagram showing an example of road surface conditions, where a portion 110 of the snow-covered road surface with severe bumps is displayed in black on the map.

[0016] FIG. 5 is a cross-sectional view showing an example of road surface conditions (unevenness of a snow-covered road surface), where unevenness 120 of the road surface caused by snow is indicated by wavy lines.

[0017] On snowy roads, snow melts easily near manholes, resulting in a step between the road surface and the packed snow surface. Figure 6 is a cross-sectional view showing an example of road surface conditions (thickness of packed snow on the road surface), and the height of the step near the manhole can be calculated from acceleration information from the terminal device TM, etc., to determine the packed snow thickness 130.

[0018] The traffic condition providing server 200 provides traffic conditions via the network NW to the snow removal decision support system 600. The traffic conditions provided are information for each road, and include some or all of the following: traffic volume, passing speed, average speed, and the presence or absence of congestion or congestion. FIG. 7 is a diagram showing an example of traffic conditions, with locations 210 of heavy traffic congestion being displayed in black on the map.

[0019] The road space condition providing server 300 provides the road space condition via the network NW to the snow removal decision support system 600. The road space condition provided is information for each road, and includes some or all of the following: avalanches, snowdrifts, height of snow banks caused by accumulated snow, poor visibility at intersections caused by snow banks, narrowing of road width caused by accumulated snow, whether large vehicles are stuck, whether vehicles have been involved in accidents, etc. FIG. 8 is a diagram showing an example of a road space situation, where dangerous points 310 with high snow banks are displayed in black on the map.

[0020] The weather condition providing server 400 provides weather conditions via the network NW to the snow removal decision support system 600. The weather conditions provided are information for each region, and include some or all of the following: time, weather (sunny, rainy, snowy, etc.), temperature, amount of snowfall, snow depth, wind speed, and the presence or absence of warnings (blizzard, heavy snow, etc.) and advisories (heavy snow, snowstorm, avalanche, etc.). FIG. 9 shows an example of weather conditions, in which snowfall amount 410 and warning 420 are displayed in numbers and letters.

[0021] The vehicle travel status providing server 500 provides vehicle travel status to the snow removal decision support system 600 via the network NW. The provided vehicle travel status is information for each road and route obtained from vehicles such as route buses and circular buses, and includes some or all of the following: bus delay time against the winter schedule (a timetable that takes into account winter traffic conditions), the bus travel position (which lane out of three lanes in each direction the bus is traveling in, etc.), the number of vehicles ahead of the bus, the number of vehicles lined up next to each other, whether or not the road width has been reduced due to snow accumulation, skidding points, tire spinning points, tire lock points, sudden braking points, etc. If there is no winter schedule, the bus delay time against the normal schedule may be used. Vehicle driving status can be in the form of the latest route information (vehicle ID, route name, delays, predicted departure and arrival times, passing, etc.) based on the open data dynamic bus information format (GTFS real-time), vehicle position information (vehicle latitude and longitude, approach information, congestion level, etc.), and operation information (service suspension, detours, accidents, stuck buses, traffic obstructions, images before and after the bus, etc.). FIG. 10 is a diagram showing an example of a vehicle driving situation, where a location 510 where the tires are spinning is displayed in black on the map.

[0022] As a method for grasping the narrowing of road width due to snow accumulation, in addition to judging the snow accumulation situation using the camera function and image recognition function of the smartphone, communication type drive recorder, fixed point camera, etc. installed in the vehicle, it is acceptable to use the same function to judge the narrowing of road width from the number of lanes and the number of vehicles lined up side by side. Also, it is acceptable to determine the lane driving position (which lane out of three lanes on one side the vehicle is driving in, which lane out of two lanes on one side the vehicle is driving in, etc.) from the latitude and longitude of the route bus or the like that is traveling, and to judge the narrowing of road width due to snow accumulation.

[0023] The information acquisition unit 610 operating in the snow removal decision support system 600 acquires the road surface conditions from the road surface condition providing server 100, the traffic conditions from the traffic condition providing server 200, the road space conditions from the road space condition providing server 300, the weather conditions from the weather condition providing server 400, and the vehicle driving conditions from the vehicle driving condition providing server 500 via the network NW. The road surface conditions provided by the road surface condition providing server 100 are stored as road surface information 640. The traffic conditions provided by the traffic condition providing server 200 are stored as traffic information 650. The road space conditions provided by the road space condition providing server 300 are stored as road space information 660. The weather conditions provided by the weather condition providing server 400 are stored as weather information 670. The vehicle driving conditions provided by the vehicle driving condition providing server 500 are stored as vehicle driving information 680. The information acquired by the information acquisition unit 610 may be only a part of the road surface conditions, traffic conditions, road space conditions, weather conditions, and vehicle driving conditions.

[0024] An analysis unit 620 operating in the snow removal decision support system 600 analyzes each piece of information obtained from the information acquired by the information acquisition unit 610, including road surface information 640, traffic information 650, road space information 660, weather information 670, and vehicle driving information 680, and stores the analysis results as 690. The information analyzed by the analysis unit 620 may be only a part of the road surface information 640, the traffic information 650, the road space information 660, the weather information 670, and the vehicle travel information 680.

[0025] A decision unit 630 operating in the snow removal decision support system 600 comprehensively decides the need for snow removal based on some or all of the analysis results 690 for each piece of information analyzed by the analysis unit 620, and stores the result as a decision result 695.

[0026] FIG. 11 is a flow chart showing an example of the flow of the snow removal decision support system 600. The information acquisition unit 610 periodically acquires (e.g., every few minutes) road surface condition information from the road surface condition providing server 100 (S10). The information acquisition unit 610 periodically acquires (e.g., every few minutes) traffic condition information from the traffic condition providing server 200 (S11). The information acquisition unit 610 periodically acquires (e.g., every few minutes) road space condition information from the road space condition providing server 300 (S12). The information acquisition unit 610 periodically acquires (e.g., every few minutes) weather condition information from the weather condition providing server 400 (S13). The information acquisition unit 610 periodically acquires (e.g., every few minutes) vehicle driving condition information from the vehicle driving condition providing server 500 (S14). Then, the analysis unit 620 extracts locations where the road width is severe from the road surface information 640 (S15). The analysis unit 620 extracts locations where traffic congestion is severe from the traffic information 650 (S16). The analysis unit 620 extracts dangerous locations where snow banks are high (snow banks of about 1m or more) from the road space information 660 (S17). The analysis unit 620 extracts locations where the amount of snowfall is 10cm or more from the start of snowfall from the weather information 670 (S18). The analysis unit 620 extracts locations where buses are delayed by 30 minutes or more from the vehicle travel information 680 (S19). Next, based on the results of the above analysis, the decision unit 630 comprehensively decides whether snow removal is necessary (S20). Furthermore, information from road users utilizing SNS (Social Networking Services) such as X (formerly Twitter) may be included.

[0027] 12 is a diagram showing an example of the judgment criteria in the decision unit 630. The decision unit 630 decides that snow removal is necessary in the following cases: heavy snowfall of 10 cm / h or more (element 1) 631, road width reduction due to snow accumulation causing bus delays of 30 minutes or more (element 2) 632, snow melting due to fine weather causing the unevenness of the snow-covered road surface to worsen and causing heavy traffic congestion (element 3) 633, heavy snow warnings are issued causing cars to slip and skid, cars to get stuck in snow, and congestion (element 4) 634, brakes do not work on frozen roads at -10°C (frequent tire locks) causing accidents resulting in self-inflicted damage, and congestion (element 5) 635, etc. Furthermore, the judgment result 695 determined by the decision unit 630 may include functions such as email notification to snow removal companies, providing data to a GIS (Geographic Information System) for road managers, and disclosing information to road users (such as a website or smartphone app).

[0028] The snow removal decision support system 600 can be effective in one or more of the following conditions: road surface condition, traffic condition, road space condition, weather condition, and vehicle driving condition. Furthermore, by using two or more elements, a synergistic effect can be obtained.

[0029] <Hardware configuration> FIG. 13 is a diagram showing an example of the hardware configuration of the terminal device TM, the fixed camera CAM, the road surface condition providing server 100, the traffic condition providing server 200, the road space condition providing server 300, the weather condition providing server 400, the vehicle driving condition providing server 500, and the snow removal judgment support system 600. This diagram shows an example in which the terminal device TM is a mobile phone such as a smartphone. The terminal device TM is configured such that, for example, a CPU 701, a RAM 702, a ROM 703, a secondary storage device 704 such as a flash memory, a touch panel 705, and a wireless communication module 706 are interconnected by an internal bus or a dedicated communication line. An application program such as a road patrol application is downloaded via a network NW and stored in the secondary storage device 704. The fixed camera CAM is configured such that, for example, a CPU 901, a RAM 902, a ROM 903, a secondary storage device 904 such as a flash memory, a lens / image sensor 905, and a communication device 906 are interconnected by an internal bus or a dedicated communication line. An application program such as a camera application is downloaded via the network NW and stored in the secondary storage device 904 . Each server is configured such that, for example, a NIC 801, a CPU 802, a RAM 803, a ROM 804, a secondary storage device 805 such as a flash memory or a HDD, and a drive device 806 are interconnected by an internal bus or a dedicated communication line. A portable storage medium such as an optical disk is mounted in the drive device 806. A program stored in the secondary storage device 805 or the portable storage medium mounted in the drive device 806 is expanded in the RAM 803 by a DMA controller (not shown) or the like, and executed by the CPU 802, thereby realizing the functional units of each server. The road surface information 640, the traffic information 650, the road space information 660, the weather information 670, the vehicle driving information 680, the analysis result 690, and the judgment result 695 are stored in the secondary storage device 805. Note that each server may be cloud computing.

[0030] The above describes the form for carrying out the present invention using an embodiment, but the present invention is not limited to such an embodiment, and various modifications and substitutions can be made within the scope that does not deviate from the gist of the present invention. [Explanation of symbols]

[0031] 100: Road condition server 200: Traffic information server 300: Road space situation providing server 400: Weather information server 500: Vehicle driving status server 600: Snow removal decision support system 610: Information acquisition department 620: Analysis Department 630: Decision-making department 640: Road surface information 650: Traffic information 660: Road spatial information 670: Weather Information 680: Vehicle driving information 690:Analysis results 695: Judgment result

Claims

1. an information acquisition unit that acquires information regarding vehicle driving conditions including bus delay times due to snow; an analysis unit that analyzes a vehicle driving situation obtained from the information acquired by the information acquisition unit; A decision unit that decides the necessity of snow removal based on the results of the analysis by the analysis unit; wherein the decision unit decides whether or not snow removal is necessary.

2. an information acquisition unit that acquires information regarding vehicle driving conditions, including bus delay times due to snow, and information regarding road surface conditions, including whether or not road width has been reduced due to snow accumulation; an analysis unit that analyzes a vehicle travel condition and a road surface condition obtained from the information acquired by the information acquisition unit; A decision unit that decides the necessity of snow removal based on the results of the analysis by the analysis unit; wherein the decision unit decides whether or not snow removal is necessary.

3. A program for causing a computer to function as the snow removal decision support system according to claim 1 or 2.

4. A road management method using a computer, comprising: The computer acquires information regarding vehicle driving conditions, including bus delay times due to snow, via a network; Analyzing the vehicle driving status obtained from the acquired information, A road management method characterized in that the need for snow removal is determined based on the results of the analysis.

5. A road management method using a computer, comprising: The computer acquires, via a network, information on vehicle driving conditions, including bus delay times due to snow, and information on road surface conditions, including whether or not road widths have been narrowed due to snow accumulation, Analyzing the vehicle driving conditions and road surface conditions obtained from the acquired information, A road management method characterized in that the need for snow removal is determined based on the results of the analysis.

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