Title of the Invention: A non-transitory computer-readable medium containing a traffic monitoring device, a traffic monitoring system, a traffic monitoring method and a program. Technical field [0001] 　The present invention relates to a non-transitory computer-readable medium in which a traffic monitoring device, a traffic monitoring system, a traffic monitoring method and a program are stored. Background technology [0002] 　In emerging countries, etc., rapid population concentration is occurring in urban areas along with economic development. On the other hand, the development of transportation infrastructure such as roads, railroads, and buses has not progressed, and traffic congestion is becoming more serious due to the rapid increase in traffic volume. In order to deal with such situations, the traffic control device installed at the traffic control center manages the actual traffic conditions on the road network, controls the signal lights installed at intersections, and controls traffic congestion and traffic to drivers. There is a technology to implement traffic measures such as notification of traffic conditions. [0003] 　In connection with such a technique, Patent Document 1 discloses an imaging system provided at an intersection. The imaging system according to the patent document includes a panoramic imaging unit, a tracking target specifying unit, a plurality of specific target imaging units, and an audio information output unit. The omnidirectional imaging unit images a plurality of objects moving in and around the intersection. The tracking target specifying unit identifies the tracking target from the imaged data of the panoramic imaging unit based on predetermined conditions. The plurality of specific target image pickup units have an image pickup element having a higher image resolution than the image pickup element of the overall view imaging unit, and take an image while tracking the tracking target. The audio information output unit outputs audio information having directivity for the tracking target. [0004] 　Further, Patent Document 2 discloses a traffic control device. The traffic control device according to Patent Document 2 stores the temporal transition of the traffic condition in the target road network in the traffic condition storage unit. The traffic control device according to Patent Document 2 estimates a point where a chronic traffic problem such as a traffic jam occurs from the temporal transition of this traffic condition, and measures for solving the traffic problem at this point. Generate a plan. Then, after executing this countermeasure plan, the validity of the countermeasure plan is verified using the actual traffic conditions, and it is used as know-how when generating the subsequent countermeasure plans. [0005] 　Further, Patent Document 3 discloses a traffic system for estimating a traffic route in which a traffic jam is occurring. The traffic system according to Patent Document 3 includes traffic network data that describes the connection relationship between traffic routes. Identify another traffic route connected to the traffic route determined to be congested based on the traffic network data, determine whether or not there is congestion on that traffic route, and list the congestion along with the connection relationship. Record in. Prior art literature Patent documents [0006] Patent Document 1: Japanese Patent Application Laid-Open No. 2011-0439343 Patent Document 2: Japanese Patent Application Laid-Open No. 2005-267269 Patent Document 3: Japanese Patent Application Laid-Open No. 2015-028675 Outline of the invention Problems to be solved by the invention [0007] 　In order to deal with the problem of traffic congestion, it is necessary to identify the cause of the congestion. Here, roads often have multiple lanes. In some lanes, there is congestion, but in another lane, there is no congestion. Therefore, in order to more reliably identify the cause of congestion, it is necessary to consider the congestion in each of the plurality of lanes. On the other hand, the technique according to the above patent document does not consider the congestion of each of the plurality of lanes. Therefore, the technique according to the above patent document may not be able to reliably identify the cause of the congestion. [0008] 　The purpose of the present disclosure is to solve such a problem, and to provide a traffic monitoring device, a traffic monitoring system, a traffic monitoring method and a program capable of more reliably determining the cause of traffic congestion. To do. Means to solve problems [0009] 　The traffic monitoring device according to the present disclosure includes a vehicle information acquisition means for acquiring vehicle information regarding the traveling state of a vehicle traveling on a road, and an object other than the traveling vehicle existing in the vicinity of the traveling vehicle. An additional information acquisition means for acquiring additional information about the vehicle, a congestion determination means for determining whether or not a traffic jam has occurred in each of a plurality of lanes of the road based on the vehicle information, and a traffic jam have occurred. It has a cause determining means for determining the cause of the traffic jam by using at least the additional information for the lane determined to be. [0010] 　Further, the traffic monitoring system according to the present disclosure includes at least one detection device for detecting the state of the road and a traffic monitoring device for monitoring the traffic on the road, and the traffic monitoring device receives from the detection device. A vehicle information acquisition means for acquiring vehicle information regarding a traveling state of a vehicle traveling on a road by using the detected detection result, and a vehicle traveling by using the detection result received from the detection device. An additional information acquisition means for acquiring additional information about an object other than a moving vehicle existing in the vicinity, and whether or not traffic congestion has occurred in each of a plurality of lanes of the road based on the vehicle information. It has a traffic jam determining means for determining, and a cause determining means for determining the cause of the traffic congestion by using at least the additional information for the lane determined to have a traffic jam. [0011] 　In addition, the traffic monitoring method according to the present disclosure acquires vehicle information regarding the traveling state of a vehicle traveling on a road, and additional information regarding an object other than the traveling vehicle existing in the vicinity of the traveling vehicle. Is acquired, and based on the vehicle information, it is determined whether or not there is a traffic jam in each of the plurality of lanes of the road, and at least the additional information is obtained for the lane that is determined to have a traffic jam. To determine the cause of congestion. [0012] In addition, the program according to the present disclosure includes a step of acquiring vehicle information regarding the traveling state of a vehicle traveling on a road, and additional information regarding an object other than the traveling vehicle existing in the vicinity of the traveling vehicle. With respect to the step of acquiring the above, the step of determining whether or not there is congestion in each of the plurality of lanes of the road based on the vehicle information, and the step of determining whether or not the lane is congested. At least using the additional information, let the computer perform the step of determining the cause of the traffic jam. Effect of the invention [0013] 　According to the present disclosure, it is possible to provide a traffic monitoring device, a traffic monitoring system, a traffic monitoring method and a program capable of more reliably determining the cause of traffic congestion. A brief description of the drawing [0014] [Fig. 1] Fig. 1 is a diagram showing an outline of a traffic monitoring system according to an embodiment of the present disclosure. FIG. 2 is a diagram showing a traffic monitoring system according to the first embodiment. FIG. 3 is a diagram illustrating a plurality of intersections in which the detection device according to the first embodiment is installed. FIG. 4 is a diagram illustrating an intersection in which the detection device according to the first embodiment is installed. FIG. 5 is a diagram showing a configuration of a traffic monitoring device according to the first embodiment. FIG. 6 is a flowchart showing a traffic monitoring method executed by the traffic monitoring device according to the first embodiment. FIG. 7 is a diagram illustrating a traffic jam determination method performed by the traffic jam determination unit according to the first embodiment. FIG. 8 is a diagram illustrating a cause determination method performed by the cause determination unit according to the first embodiment. FIG. 9 is a diagram for explaining a cause determination method according to the first embodiment. [Fig. 10] Fig. 10 is a diagram illustrating an example of the relationship between a traffic obstacle and a cause of congestion. [Fig. 11] Fig. 11 is a diagram illustrating an example of the relationship between a traffic obstacle and a cause of congestion. [Fig. 12] Fig. 12 is a diagram illustrating an example of the relationship between a traffic obstacle and a cause of congestion. [Fig. 13] Fig. 13 is a diagram illustrating an example of the relationship between a traffic obstacle and a cause of congestion. [Fig. 14] Fig. 14 is a diagram illustrating an example of the relationship between a traffic obstacle and a cause of congestion. [Fig. 15] Fig. 15 is a diagram illustrating an example of the relationship between a traffic obstacle and a cause of congestion. [Fig. 16] Fig. 16 is a diagram illustrating an example of the relationship between a traffic obstacle and a cause of congestion. FIG. 17 is a diagram illustrating countermeasure information according to the first embodiment. Mode for carrying out the invention [0015] (Outline of Embodiments Related to the 　present Disclosure ) Prior to the explanation of the embodiments of the present disclosure, the outline of the embodiments according to the present disclosure will be described. FIG. 1 is a diagram showing an outline of the traffic monitoring system 1 according to the embodiment of the present disclosure. The traffic monitoring system 1 includes a traffic monitoring device 10 and at least one detection device 20. The detection device 20 and the traffic monitoring device 10 are communicably connected via a wired or wireless network. [0016] 　The detection device 20 is, for example, a camera or a sensor. The detection device 20 detects the state of the road and transmits data indicating the detection result to the traffic monitoring device 10. In particular, the detection device 20 detects the state near the intersection and transmits data indicating the detection result to the traffic monitoring device 10. When the detection device 20 is a camera, the detection device 20 transmits an image (image data) of the surroundings of the intersection to the traffic monitoring device 10. In the following, the term "image" may also mean "image data indicating an image" as a processing target in information processing. Further, the image may be a still image or a moving image. [0017] 　The traffic monitoring device 10 monitors the traffic on the road whose state is detected by the detection device 20. In particular, the traffic monitoring device 10 monitors the traffic at at least one intersection where the detection device 20 is installed. The traffic monitoring device 10 includes a vehicle information acquisition unit 11 (vehicle information acquisition means), an additional information acquisition unit 12 (additional information acquisition means), a traffic jam determination unit 13 (traffic jam determination means), and a cause determination unit 14 (cause determination). Means) and. The vehicle information acquisition unit 11 acquires vehicle information regarding the traveling state of the vehicle traveling on the road from the data received from the detection device 20. In particular, the vehicle information acquisition unit 11 acquires vehicle information regarding the traveling state of a vehicle existing near the intersection from the data received from the detection device 20. The additional information acquisition unit 12 acquires additional information regarding an object other than the traveling vehicle that exists in the vicinity of the traveling vehicle. In particular, the additional information acquisition unit 12 acquires additional information regarding an object other than the traveling vehicle that exists near the intersection. The traffic jam determination unit 13 determines whether or not traffic jam has occurred in each of the plurality of lanes of the road based on the vehicle information. In particular, the congestion determination unit 13 determines whether or not congestion has occurred in each of the plurality of lanes of the road intersecting the intersection based on the vehicle information. The cause determination unit 14 determines the cause of the congestion in the lane determined to be congested, at least based on additional information. [0018] 　As described above, the traffic monitoring device 10 according to the present disclosure determines whether or not there is congestion in each of the plurality of lanes of the road, and causes the congestion in the lane determined to be congested. To judge. Therefore, the traffic monitoring system 1 according to the present disclosure can more reliably determine the cause of the traffic jam. Therefore, it is possible to more appropriately consider countermeasures against traffic congestion. Even if the traffic monitoring system 1 is used, it is possible to more reliably determine the cause of the traffic jam. Further, the cause of the traffic congestion can be determined more reliably by using the traffic monitoring method executed by the traffic monitoring device 10 and the program for executing the traffic monitoring method. [0019] (Embodiment 1) 　Hereinafter, embodiments will be described with reference to the drawings. In order to clarify the explanation, the following description and drawings have been omitted or simplified as appropriate. Further, in each drawing, the same elements are designated by the same reference numerals, and duplicate explanations are omitted as necessary. [0020] 　FIG. 2 is a diagram showing a traffic monitoring system 1 according to the first embodiment. The traffic monitoring system 1 is composed of a plurality of detection devices 20 and a traffic monitoring device 100. The traffic monitoring device 100 corresponds to the traffic monitoring device 10 shown in FIG. The plurality of detection devices 20 and the traffic monitoring device 100 are communicably connected to each other via a wired or wireless network 2. The detection device 20 may be installed near the intersection. [0021] 　As described above, the detection device 20 is, for example, a camera or a sensor. In the following description, the case where the detection device 20 is a camera (surveillance camera) is shown. The detection device 20 transmits an image (intersection image) obtained by photographing the state near the intersection to the traffic monitoring device 100. The detection device 20 includes an image pickup device 22, an image processing device 24, and a communication device 26. The image pickup device 22 is, for example, a camera body. The image pickup apparatus 22 may be a fixed camera, a PTZ (Pan / Tilt / Zoom) camera, or both of them. The image pickup apparatus 22 photographs the vicinity of the installed intersection. [0022] 　The image processing device 24 performs necessary image processing on the intersection image captured by the image pickup device 22. The communication device 26 may include a router or the like. The communication device 26 transmits the intersection image processed by the image processing device 24 to the traffic monitoring device 100 via the network 2. At this time, the communication device 26 associates the identification information of the intersection where the detection device 20 or the detection device 20 is installed with the intersection image, and transmits the information to the traffic monitoring device 100. Thereby, the traffic monitoring device 100 can determine which intersection the received intersection image is related to. [0023] 　The traffic monitoring device 100 monitors the traffic at a plurality of intersections in which the detection device 20 is installed. The traffic monitoring device 100 is installed in a traffic control center or the like and is used by an operator who monitors traffic. The traffic monitoring device 100 determines the cause of the traffic jam using the image data (intersection image) transmitted from each detection device 20, and presents a countermeasure method against the traffic jam. [0024] 　FIG. 3 is a diagram illustrating a plurality of intersections in which the detection device 20 according to the first embodiment is installed. As illustrated in FIG. 3, in the road network 4, a plurality of roads 30 intersect at a plurality of intersections 40. That is, a plurality of roads 30 intersect to form an intersection 40. A detection device 20 is installed near each intersection 40. The traffic monitoring device 100 monitors traffic at each of the plurality of intersections 40 by using the intersection image and the identification information associated with the intersection image. [0025] 　FIG. 4 is a diagram illustrating an intersection 40 in which the detection device 20 according to the first embodiment is installed. FIG. 4 shows an intersection 40 which is a crossroad (four-forked road), but the intersection 40 is not limited to the crossroad. The intersection 40 may be a three-way intersection, another intersection such as a five-way intersection, or a rotary intersection. The detection device 20 may photograph the range (range A) indicated by the broken line circle A. [0026] 　The road 30 has a plurality of lanes 32. FIG. 4 shows an example in which a road 30 having two lanes 32 (that is, four round-trip lanes) intersects at an intersection 40 on one side of the center line 30c of the road 30. However, the number of lanes 32 included in one road 30 may be any number of 2 or more. Further, in the present embodiment, an example of right-hand traffic in which the vehicle travels on the right side is shown, but left-hand traffic may be used. Here, in FIG. 4, the right side of the intersection 40 is east, the left side is west, the upper part is north, and the lower part is south. That is, one intersection 40 has lanes 32 in which the vehicle travels in eight directions. The detection device 20 constantly photographs lanes 32 in eight directions near the intersection 40. Then, the traffic monitoring device 100 constantly monitors the lanes 32 in eight directions in the vicinity of the intersection 40 for each intersection 40. [0027] 　In addition, the lane 32 in which the vehicle heads west from the intersection 40 is defined as lanes # 1-1 and # 1-2. Here, the lane 32 far from the central line 30c is referred to as lane # 1-1, and the lane 32 close to the central line 30c is referred to as lane # 1-2. Lanes 32 from the west toward the intersection 40 are defined as lanes # 2-1 and # 2-2. Here, the lane 32 far from the central line 30c is referred to as lane # 2-1 and the lane 32 close to the central line 30c is referred to as lane # 2-2. Lanes 32 in which the vehicle heads south from the intersection 40 are defined as lanes # 3-1 and # 3-2. Here, the lane 32 far from the central line 30c is referred to as lane # 3-1 and the lane 32 close to the central line 30c is referred to as lane # 3-2. Lanes 32 from the south toward the intersection 40 are defined as lanes # 4-1 and # 4-2. Here, the lane 32 far from the central line 30c is referred to as lane # 4-1 and the lane 32 close to the central line 30c is referred to as lane # 4-2. [0028] 　The lane 32 in which the vehicle heads east from the intersection 40 is defined as lanes # 5-1 and # 5-2. Here, the lane 32 far from the central line 30c is referred to as lane # 5-1, and the lane 32 close to the central line 30c is referred to as lane # 5-2. Lanes 32 from the east toward the intersection 40 are defined as lanes # 6-1 and # 6-2. Here, the lane 32 far from the central line 30c is referred to as lane # 6-1 and the lane 32 close to the central line 30c is referred to as lane # 6-2. Lanes 32 in which the vehicle heads north from the intersection 40 are defined as lanes # 7-1 and # 7-2. Here, the lane 32 far from the central line 30c is referred to as lane # 7-1, and the lane 32 close to the central line 30c is referred to as lane # 7-2. Lanes 32 from the north toward the intersection 40 are defined as lanes # 8-1 and # 8-2. Here, the lane 32 far from the central line 30c is referred to as lane # 8-1, and the lane 32 close to the central line 30c is referred to as lane # 8-2. In this way, a total of 16 lanes 32 intersect at the intersection 40. [0029] 　FIG. 5 is a diagram showing the configuration of the traffic monitoring device 100 according to the first embodiment. The traffic monitoring device 100 has a control unit 102, a storage unit 104, a communication unit 106, and an interface unit 108 (IF; Interface) as a main hardware configuration. The control unit 102, the storage unit 104, the communication unit 106, and the interface unit 108 are connected to each other via a data bus or the like. [0030] 　The control unit 102 is, for example, a processor such as a CPU (Central Processing Unit). The control unit 102 has a function as an arithmetic unit that performs control processing, arithmetic processing, and the like. The storage unit 104 is a storage device such as a memory or a hard disk. The storage unit 104 is, for example, a ROM (Read Only Memory) or a RAM (Random Access Memory). The storage unit 104 has a function for storing a control program, an arithmetic program, and the like executed by the control unit 102. In addition, the storage unit 104 has a function for temporarily storing processed data and the like. The storage unit 104 may include a database. [0031] 　The communication unit 106 performs processing necessary for communicating with the detection device 20 (and other devices) via the network 2. The communication unit 106 may include a communication port, a router, a firewall, and the like. The interface unit 108 (IF; Interface) is, for example, a user interface (UI). The interface unit 108 has an input device such as a keyboard, a touch panel or a mouse, and an output device such as a display or a speaker. The interface unit 108 accepts a data input operation by the user (operator) and outputs information to the user. The interface unit 108 may display an image (intersection image) received from the detection device 20, a map showing a location where traffic congestion has occurred, a cause of traffic congestion, a countermeasure method thereof, and the like. [0032] 　Further, the traffic monitoring device 100 includes a vehicle information acquisition unit 112, an additional information acquisition unit 114, a traffic jam determination unit 116, a cause determination unit 120, a cause information storage unit 122, a countermeasure presentation unit 130, and a countermeasure information storage unit 132 (hereinafter,). , "Each component"). The vehicle information acquisition unit 112, the additional information acquisition unit 114, the traffic jam determination unit 116, and the cause determination unit 120 function as vehicle information acquisition means, additional information acquisition means, congestion determination means, and cause determination means, respectively. Further, the cause information storage unit 122, the countermeasure presentation unit 130, and the countermeasure information storage unit 132 function as a cause information storage means, a countermeasure presentation means, and a countermeasure information storage means, respectively. [0033] 　Each component can be realized by executing a program under the control of the control unit 102, for example. More specifically, each component can be realized by the control unit 102 executing the program stored in the storage unit 104. Further, each component may be realized by recording a necessary program on an arbitrary non-volatile recording medium and installing the necessary program as needed. Further, each component is not limited to being realized by software by a program, and may be realized by any combination of hardware, firmware, and software. Further, each component may be realized by using a user-programmable integrated circuit such as an FPGA (field-programmable gate array) or a microcomputer. In this case, this integrated circuit may be used to realize a program composed of each of the above components. The above is the same in other embodiments described later. The specific functions of each component will be described later. [0034] 　The vehicle information acquisition unit 112 corresponds to the vehicle information acquisition unit 11 shown in FIG. The vehicle information acquisition unit 112 acquires vehicle information regarding the running state of a vehicle existing in the vicinity of the intersection 40 from the image data received from the detection device 20 by image recognition or the like. At this time, the vehicle information acquisition unit 112 acquires vehicle information for each of the plurality of lanes 32 that intersect the intersection 40. Here, the "vehicle information" is information used for determining whether or not a traffic jam has occurred in the vicinity of the intersection 40. For example, the vehicle information includes the traffic volume, the average traveling speed of the vehicle, the average waiting time of the vehicle within a predetermined range of the intersection 40 (range A in FIG. 4), and the like. Here, the vehicle information can indicate the ability (intersection ability) such as how many vehicles 50 the intersection 40 can pass through. [0035] 　The additional information acquisition unit 114 corresponds to the additional information acquisition unit 12 shown in FIG. The additional information acquisition unit 114 acquires additional information regarding an object other than the traveling vehicle that exists in the vicinity of the intersection 40. Here, the "objects other than the traveling vehicle" are, for example, pedestrians and light vehicles (bicycles, etc.) at the intersection 40, closed vehicles blocking the intersection 40, and parking parked near the intersection 40. Includes vehicles, accident vehicles that are stopped due to troubles (traffic accidents, breakdowns, etc.) near the intersection 40, and falling objects. Further, the "object other than the traveling vehicle" includes a traffic light installed at the intersection 40. The additional information is information other than vehicle information and is used to determine the cause of traffic congestion. [0036] 　The traffic jam determination unit 116 corresponds to the traffic jam determination unit 13 shown in FIG. The traffic jam determination unit 116 uses vehicle information to determine whether or not traffic jam has occurred in each of the plurality of lanes 32 of the road 30 intersecting the intersection 40. Here, the place where the traffic jam occurs is referred to as the place where the traffic jam occurs. [0037] 　The cause determination unit 120 corresponds to the cause determination unit 14 shown in FIG. The cause determination unit 120 determines the cause of the congestion (the cause of the congestion) with respect to the lane 32 determined to have the congestion, using at least additional information. The cause information storage unit 122 stores congestion cause information, which is a database showing candidates that cause congestion. Here, in the traffic jam cause information, the traffic obstacle indicated by the additional information and the like and the traffic jam cause are associated with each other. [0038] 　Here, the cause determination unit 120 may determine whether or not the location where the congestion occurs is the location where the congestion is induced, and determine the cause of the congestion for the location where the congestion is induced. Here, the "traffic jam induction place" means a place where a traffic jam occurs due to some cause occurring at this place. In other words, the cause of the traffic jam occurring at the place where the traffic jam occurred but not at the place where the traffic jam was induced is that the traffic jam spread due to the traffic jam occurring at another place (the place where the traffic jam was induced). In this way, by determining the cause of the congestion at the congestion-inducing location and taking measures for the congestion-inducing location, there is a possibility that the congestion will be resolved at other congestion-inducing locations as well. Therefore, in the first embodiment, it is possible to efficiently eliminate the traffic jam. [0039] 　Further, the countermeasure information storage unit 132 stores the countermeasure information. In the countermeasure information, the cause of traffic congestion and the countermeasure method are associated with each other. Specific examples of countermeasure information will be described later. The countermeasure presentation unit 130 presents a countermeasure method for the cause of traffic congestion by using the countermeasure information. For example, the countermeasure presentation unit 130 displays the countermeasure method on the interface unit 108. In this way, by presenting the countermeasure method for traffic congestion to the user (operator) by the countermeasure presentation unit 130, it is possible to easily take countermeasures without depending on the know-how of the operator. [0040] 　FIG. 6 is a flowchart showing a traffic monitoring method executed by the traffic monitoring device 100 according to the first embodiment. First, the traffic monitoring device 100 acquires an intersection image from each of the plurality of detection devices 20 (step S102). Specifically, the communication unit 106 of the traffic monitoring device 100 receives the intersection image from each detection device 20. As a result, the vehicle information acquisition unit 112 acquires the intersection image transmitted from each detection device 20. [0041] 　Next, the vehicle information acquisition unit 112 calculates vehicle information about the intersection corresponding to the intersection image by using the intersection image and the identification information associated with the intersection image (step S104). As described above, the vehicle information is, for example, the average traveling speed v1 of the vehicle, the average waiting time Tw of the vehicle, and the traffic volume Vt. Specifically, the vehicle information acquisition unit 112 performs image recognition on the intersection image to identify each vehicle traveling in a plurality of lanes 32 connected to the intersection 40. Then, the vehicle information acquisition unit 112 calculates the traveling speed and the waiting time for each vehicle. The traveling speed is the speed at which a vehicle passes through a certain point in the lane 32 (for example, near the boundary point between the lane 32 and the intersection 40). The waiting time is the staying time of a certain vehicle in each lane 32 within a predetermined range of the intersection 40 (range A in FIG. 4). [0042] 　The vehicle information acquisition unit 112 calculates the traveling speed for each vehicle that has passed within a predetermined time (for example, 15 minutes) for each lane 32, and calculates the average traveling speed v1 by averaging them. Similarly, the vehicle information acquisition unit 112 calculates the waiting time for each vehicle that has passed within a predetermined time (for example, 15 minutes) for each lane 32, and calculates the average waiting time Tw by averaging them. Further, the vehicle information acquisition unit 112 calculates the number N of vehicles that have passed a certain point (for example, near the boundary point between the lane 32 and the intersection 40) per unit time (for example, 15 minutes) for each lane 32. Then, the traffic volume Vt is calculated. In this way, when the vehicle information acquisition unit 112 performs image recognition on the intersection image and acquires the vehicle information, it is possible to automatically determine the traffic congestion. [0043] 　Next, the additional information acquisition unit 114 acquires additional information using the intersection image and the identification information associated with the intersection image (step S106). Specifically, the additional information acquisition unit 114 recognizes images of pedestrians, light vehicles, and the like included in the intersection image by image processing, and extracts these images. In addition, the additional information acquisition unit 114 recognizes images of closed vehicles, parked vehicles, accident vehicles, falling objects, etc. included in the intersection image by image processing, and extracts these images. In addition, the additional information acquisition unit 114 receives information on the lighting interval from the traffic light installed at the intersection 40. In this way, the vehicle information acquisition unit 112 can automatically determine the cause of the traffic jam by analyzing the image of the intersection image or by receiving the information regarding the lighting interval from the traffic light. [0044] 　Next, the traffic jam determination unit 116 determines whether or not there is a traffic jam for each lane 32 of each intersection 40 (step S110). Specifically, the traffic jam determination unit 116 determines whether or not a traffic jam has occurred for each lane 32 of each intersection 40 by the method illustrated in FIG. 7. The method for determining traffic congestion is not limited to the example shown in FIG. [0045] 　FIG. 7 is a diagram illustrating a traffic jam determination method performed by the traffic jam determination unit 116 according to the first embodiment. The traffic jam determination unit 116 performs the traffic jam determination method illustrated in FIG. 7 for each of the plurality of intersections 40 by using the identification information added to the intersection image. First, the traffic jam determination unit 116 selects the lane 32 (for example, lane # 1-1) to be determined (step S112). After that, processing is performed on the selected lane 32 for S114 to S130. [0046] 　The traffic jam determination unit 116 determines whether or not the average traveling speed v1 is below a predetermined threshold value Thv (step S114). For example, Thv = 20 km / h. When it is determined that the average traveling speed v1 is lower than the threshold value Thv (YES in S114), the congestion determination unit 116 adds the congestion degree Dj (step S116). The added value can be appropriately set depending on how much the average traveling speed v1 is emphasized when determining the traffic congestion. [0047] 　Here, the degree of congestion Dj is a parameter indicating the degree of congestion. The heavier the traffic, the greater the traffic Dj. The initial value of the congestion degree Dj is set to 0. The threshold value Thv is not limited to one, and may be plural. In this case, the congestion degree Dj can also be added step by step. For example, it is assumed that Thv1 = 20 km / h, Thv2 = 10 km / h, and Thv3 = 5 km / h. In this case, the congestion degree Dj may be added by "1" when 10 ≦ v1 <20. Further, when 5 ≦ v1 <10, the congestion degree Dj may be added by “2”. Further, when v1 <5, the congestion degree Dj may be added by "3". [0048] 　Next, the congestion determination unit 116 determines whether or not the average waiting time Tw exceeds a predetermined threshold value Tht (step S118). For example, Tht = 240 seconds. When it is determined that the average waiting time Tw exceeds the threshold value Tht (YES in S118), the congestion determination unit 116 adds the congestion degree Dj (step S120). The added value can be appropriately set depending on how much the average waiting time Tw is emphasized when determining the traffic congestion. [0049] 　The threshold value Tht is not limited to one, and may be plural. In this case, the congestion degree Dj can also be added step by step. For example, it is assumed that Tht1 = 240 seconds, Tht2 = 360 seconds, and Tht3 = 480 seconds. In this case, the congestion degree Dj may be added by "1" when 240