Traffic safety support system

Abstract

This traffic safety support system includes: a warning device equipped with an alarm and mounted on a light vehicle; and a traffic safety support device. The traffic safety support system is configured as follows. The traffic safety support device can access big data including traffic volume information associated with a position on a map. The warning device is capable of directly or indirectly communicating with the traffic safety support device, and issues a warning from the alarm, according to the position information of the light vehicle on which said warning device is mounted, said position information being transmitted to the traffic safety support device, and to the risk level obtained from the big data. Thus, using a warning device that can be mounted on a light vehicle such as a bicycle makes it possible not only to notify the driver of said light vehicle of the risk that an accident that may occur nearby, but also to reduce the risk of an accident involving said light vehicle.

Description

Traffic safety support system

[0001] The present invention relates to a traffic safety support system, and is particularly suitable for use in supporting the safe driving of light vehicles such as bicycles.

[0002] Various systems for supporting the safe driving of bicycles have been proposed.

[0003] In Patent Document 1, video information obtained from bicycles, automobiles, etc. around the host vehicle is aggregated on a server, and the position information of other vehicles and pedestrians is shown to the driver of the host vehicle together with map information and further warned, thereby helping to prevent collision accidents. A traffic safety support device and the like are disclosed.

[0004] Patent Document 2 discloses a bicycle travel state recording device that can appropriately warn the driver of a bicycle. It is supposed to be able to judge based on the current travel state such as inclination and acceleration / deceleration and the past travel state, and issue a warning to the driver. Also, when communicating with an external server and detecting approach to a dangerous location, a warning may be issued to the driver.

[0005] Patent Document 3 discloses a safety system for a two-wheeled vehicle that can notify the rider and surrounding vehicles of the vehicle body's wobbling by the brightness and darkness of the light emitted by the lamp. When the vehicle body's wobbling is detected by a sensor that detects the steering angle of the handlebar, warning lights are generated in the headlight and taillight to prompt attention to surrounding vehicles such as following vehicles.

[0006] International Publication WO2020 / 217316A1 Japanese Patent Application Laid-Open No. 2019-217978 Japanese Patent Application Laid-Open No. 2014-34237

[0007] According to the traffic safety support system disclosed in Patent Document 1, the cyclist can use the positional information of other vehicles and pedestrians to know in advance about approaching pedestrians and other vehicles from their blind spots and prepare for head-on encounters. However, the inventors have noticed that when the cyclist perceives danger, they do not necessarily issue a warning to those around them, such as following or riding alongside vehicles or pedestrians. Similarly, the bicycle riding state recording device disclosed in Patent Document 2 also only warns the cyclist, and does not consider the need to warn surrounding vehicles or pedestrians. On the other hand, the motorcycle safety system disclosed in Patent Document 3 warns surrounding vehicles, such as following vehicles, but because it is based on the steering angle of the handlebars, the warning is based only on the riding state of the own vehicle.

[0008] The inventors realized that, in addition to warning drivers of light vehicles such as bicycles about the risk of head-on collisions, there may be situations where, if the risk of accidents is high around the light vehicle, it is necessary to warn surrounding vehicles and pedestrians in advance.

[0009] The objective of the present invention is to reduce the risk of accidents involving light vehicles, such as bicycles, by using a warning device that can be mounted on the vehicle to warn people other than the driver of the light vehicle about the risk of accidents that may occur in the surrounding area.

[0010] The means for solving these problems are described below, but other problems and novel features will become apparent from the description and accompanying drawings in this specification.

[0011] According to one embodiment of the present invention, the following applies:

[0012] In other words, the traffic safety support system includes a warning device equipped with a warning antenna and mounted on a light vehicle, and a traffic safety support device, and is configured as follows: The traffic safety support device is capable of accessing big data including traffic volume information associated with locations on a map. The warning device is capable of communicating directly or indirectly with the traffic safety support device, and issues a warning from the warning antenna in accordance with the location information of the light vehicle on which it is mounted, which is sent to the traffic safety support device, and the degree of danger determined from the big data.

[0013] The effects obtained by the above embodiment can be briefly described below.

[0014] In other words, by using a warning device that can be mounted on a bicycle or other light vehicle to warn people other than the driver of the light vehicle about the risk of accidents that may occur in the surrounding area, the risk of accidents involving the light vehicle can be reduced.

[0015] Figure 1 is an explanatory diagram showing the basic configuration of the traffic safety support system of the present invention. Figure 2 is an explanatory diagram showing one embodiment of data control and risk level determination. Figure 3 is an explanatory diagram showing one embodiment of risk level determination that takes real-time data into account. Figure 4 is an explanatory diagram showing one embodiment of the algorithm for calculating risk level data. Figure 5 is an explanatory diagram showing another embodiment of the algorithm for calculating risk level data. Figure 6 is a block diagram showing one embodiment of the traffic safety support system of the present invention. Figure 7 is a block diagram showing another embodiment of the traffic safety support system of the present invention. Figure 8 is a block diagram showing yet another embodiment of the traffic safety support system of the present invention.

[0016] 1. Outline of Embodiments First, an outline of the representative embodiments disclosed in this application will be given. The reference numerals in parentheses in the drawings that are referenced in the outline of the representative embodiments are merely illustrative examples of components included in the concept of the components to which they are attached.

[0017] [1] Traffic safety support system that issues warnings to the surroundings based on big data (Figures 1, 2, 6-8) A typical embodiment disclosed in this application is a traffic safety support system (100) that includes a warning device (50) equipped with warning devices (52, 53) and mounted on a light vehicle (BM), and a traffic safety support device (10), and is configured as follows.

[0018] The traffic safety support device is capable of accessing big data, including traffic volume information (4) associated with locations on a map. The warning device is capable of communicating directly or indirectly with the traffic safety support device and issues a warning from the warning device in accordance with the location information of the light vehicle on which it is installed, which is sent to the traffic safety support device, and the degree of danger determined from the big data based on said location information.

[0019] Here, location information refers to information that identifies a location on Earth, such as latitude and longitude, and can be obtained, for example, by positioning using the Global Positioning System (GPS). Traffic volume information refers to the traffic volume at a certain location, area, or road, and is defined as the number of moving objects (pedestrians, light vehicles such as bicycles, and automobiles) estimated from GPS information collected from a smartphone, etc., and is specified as the number per unit time for each area or road. Traffic volume information may be organized by time of day, day of the week, and may also include additional information such as season and weather, and may be used as input data for a machine learning model.

[0020] This allows for the use of warning devices that can be mounted on light vehicles such as bicycles to warn people other than the driver of the light vehicle about the risk of accidents that may occur in the surrounding area, thereby reducing the risk of accidents involving the light vehicle.

[0021] [2] Big data + real-time data (Figure 3) In [1], the traffic safety support system further acquires real-time data representing the surroundings of the light vehicle and / or its own state, and adjusts the risk level based on the real-time data.

[0022] This allows for a more accurate assessment of the level of risk and the issuance of timely warnings. Here, real-time data refers to data representing the surrounding conditions and / or the state of the light vehicle at the time the level of risk assessment is performed (i.e., in real time).

[0023] [3] The warning device issues a warning based on the risk level determination by the traffic safety support device (Figure 6) In the traffic safety support system of [1], the warning device comprises a positioning unit (GPS unit 57), a communication interface (58), and a warning control unit (51). The position acquired by the positioning unit is transmitted as position information from the communication interface to the traffic safety support device, and the warning control unit issues a warning from the warning device according to the operating mode output by the traffic safety support device based on the risk level.

[0024] This allows for the inexpensive construction of a traffic safety support system. The traffic safety support device (10) performs the data control processing and risk assessment that determines what kind of warning the warning device (50) should issue. The warning device (50) only needs to transmit location information and issue warnings according to the instructed operating mode, so it does not require high-performance computing capabilities.

[0025] [4] Warning device determines degree of danger (Figure 7) In the traffic safety support system of [2], the warning device comprises a positioning unit (GPS unit 57), a communication interface (58), and a warning control unit (51). The position acquired by the positioning unit is transmitted as position information from the communication interface to the traffic safety support system. The warning control unit determines the degree of danger based on a portion of the big data specified by the position information from the big data received via the communication interface, and issues a warning from the warning device according to the operating mode determined based on the degree of danger.

[0026] This allows for the issuance of more accurate warnings. This is because the warning device (50) performs the risk assessment, including adjusting the risk level based on real-time data, so that changes in real-time data can be reflected in the risk assessment more quickly.

[0027] [5] The warning device determines the degree of danger based on data from a sensor attached to the light vehicle (Figure 7) In the traffic safety support system of [4], the warning device is equipped with a sensor (55). The real-time data includes sensor data acquired by the sensor, and the warning device adjusts the degree of danger based on the sensor data and issues a warning from the warning device according to an operating mode determined based on the adjusted degree of danger.

[0028] This enables the issuance of a quick and appropriate warning. The sensor (55) does not necessarily have to be built into the warning device (50), and may be a sensor attached to the light vehicle and connected by wire or wireless. Since the sensor data can be used immediately for danger level determination within the warning device (50) without transmitting it to the traffic safety support device (10), a quick and appropriate warning can be issued.

[0029] [6] Relay by a mobile information terminal such as a smartphone with GPS (Figure 8) In [1], the traffic safety support system is further configured to include a mobile information terminal (20).

[0030] The portable information terminal includes a positioning unit (GPS unit 27) capable of determining its own position, a communication unit (28) capable of communicating with the warning device, and a communication interface (21) capable of communicating with the traffic safety support device. The position determined by the positioning unit is transmitted as position information to the traffic safety support device via the communication interface, and the warning device is controlled via the communication unit to issue a warning.

[0031] This makes it possible to provide an inexpensive warning device (50). Here, the mobile information terminal (20) is, for example, a smartphone mounted in the same light vehicle or carried by the driver of that light vehicle, and by using the GPS unit (27) of the smartphone and the communication interface (21) that communicates with a mobile phone line or wireless LAN (Local Area Network), the warning device (50) can be constructed inexpensively. The warning device (50) only needs to be connected to and controlled by the mobile information terminal (smartphone) via short-range communication such as Bluetooth (see Figure 1, it receives the operating mode), and does not need to have a GPS or other positioning unit, or means to communicate directly with the traffic safety support device (10), which is usually located in the cloud.

[0032] [7] Relay using a smartphone equipped with GPS and a camera, etc. (Figure 8) In [2], the traffic safety support system further comprises a portable information terminal (20).

[0033] The aforementioned portable information terminal includes a positioning unit (GPS unit 27) for determining its own position, a communication unit (28) for communicating with the warning device, and a communication interface (21) for communicating with the traffic safety support device. The position determined by the positioning unit is transmitted as location information to the traffic safety support device via the communication interface.

[0034] The aforementioned portable information terminal further comprises at least one of a camera (26), an acceleration sensor, and a gyro sensor (sensor 25 in Figure 8), and utilizes at least one of the following as part of the real-time data: video footage of the surroundings captured by the camera, the speed of the light vehicle acquired by the acceleration sensor, and the tilt of the light vehicle acquired by the gyro sensor.

[0035] This allows for the issuance of warnings quickly and appropriately while providing the warning device (50) at a low cost. The camera (26) and sensors (55) such as acceleration sensors and gyroscopes can be those built into a smartphone or other portable information terminal (20) (they do not need to be built-in; they may be sensors attached to the light vehicle and connected by wire or wireless). Since the sensor data can be used immediately for danger level determination within the portable information terminal (20) without transmitting it to the traffic safety support device (10), quick and appropriate warnings can be issued.

[0036] [8] Risk assessment using a smartphone (Figure 8) In the traffic safety support system of [6] or [7], the mobile information terminal receives limited big data extracted from the big data, which is data surrounding the location information, determines the risk level based on the limited big data, and controls the warning issued by the warning device based on the determined risk level.

[0037] This allows the traffic safety support device (10) to handle data control, which involves extracting necessary data from big data, thereby reducing the load on the smartphone or other mobile information terminal (20).

[0038] [9] Adjustment of risk level based on lane In the traffic safety support system of [8], the portable information terminal is configured to be able to identify the lane and direction in which the light vehicle is traveling. Compared to the risk level when the identified direction is forward and the lane is a roadway, the risk level is lowered when the lane is a bicycle lane, higher when the lane is a sidewalk, and further increased when the identified direction is reverse.

[0039] This allows for a more accurate assessment of the risk of collision and enables the issuance of appropriate warnings.

[0040]

[10] Risk assessment taking into account accident history information (Figures 1-5) In the traffic safety support system of any one of items [1] to [9], the big data includes accident history information (3), and the risk is determined taking into account the accident history information.

[0041] As a result, the risk of an accident can be determined with higher accuracy, and a more appropriate warning can be issued.

[0042] 〔11〕Combination with warning to driver based on big data (PCT / JP2023 / 032287) (FIG. 8) In the traffic safety support system according to any one of 〔6〕 to 〔10〕, the portable information terminal has an information processing unit (22) and a display unit (24). The information processing unit sequentially transmits a traffic information request together with the position information to the traffic safety support device via the communication interface. In response to the traffic information request, map information around the moving body and peripheral moving body information which is the position information of other moving bodies are received via the communication interface, and the peripheral moving body information is mapped on the received map information and displayed on the display unit. The portable information terminal calculates the risk of collision from the relationship between the situation around itself in the video captured by the camera, its own position information, and the peripheral moving body information, and further maps a warning according to the risk of collision on the map information and displays it on the display unit.

[0043] As a result, it is possible to warn the driver of a light vehicle such as a bicycle of an imminent danger and a potential danger based on big data including traffic volume information using a portable information terminal that can be installed.

[0044] 2. Details of the Embodiment The embodiment will be described in further detail.

[0045] 〔Embodiment 1〕 FIG. 1 is an explanatory diagram showing the basic configuration of the traffic safety support system 100 of the present invention. The traffic safety support system 100 of the present invention includes a traffic safety support device 10 (not explicitly shown in FIG. 1) and a warning device 50 mounted on a light vehicle BM such as a bicycle, and is configured as follows. A portable information terminal 20 such as a smartphone may be mounted on the light vehicle BM.

[0046] The traffic safety support device 10 is, for example, a cloud server that can access big data including traffic volume information 4 associated with locations on a map, and stores map information 2 and the big data including traffic volume information 4 associated with the map information 2. The big data does not need to be stored on the same physical server, but only needs to be stored in an accessible state on the same cloud. Traffic volume information 4 is the traffic volume at a certain location, area, or road, and is, for example, the number of pedestrians, light vehicles such as bicycles, and vehicles such as automobiles measured or estimated from GPS information collected from a smartphone, etc. (information that identifies the location where the smartphone, etc. was located by a combination of location and date and time determined by GPS), and is defined as the number per unit time for each area or road. Traffic volume information 4 may be organized by time of day, day of the week, and may also be accompanied by additional information such as season and weather, and may be a machine learning model that has been trained using this as input data. Traffic volume information 4 may be part of big data including GPS information collected from the aforementioned smartphones, and does not necessarily need to be stored in the storage device of a single server. It may consist of various types of information distributed across the cloud and stored in a distributed manner across the storage devices of multiple servers located in the cloud.

[0047] The warning device 50 is capable of communicating directly or indirectly with the traffic safety support device 10 and includes a warning device (e.g., a light-emitting warning device 52 or an audible warning device 53). The warning device 50 may also include a warning control unit 51 and a GPS unit 57, and may transmit its own location information directly or indirectly to the traffic safety support device 10. Alternatively, without a GPS unit 57, the warning device 50 may transmit location information obtained from a GPS unit 27 (not shown in Figure 1) of a portable information terminal 20 such as a smartphone mounted on the same light vehicle BM or carried by the driver of the same light vehicle BM to the traffic safety support device 10 from that portable information terminal 20.

[0048] When the warning device 50 communicates directly with the traffic safety support device 10, for example, an LPWA (Low Power Wide Area network) can be used. When communicating indirectly, for example, it communicates with the portable information terminal 20 such as a smartphone via Bluetooth. Between the portable information terminal 20 and the traffic safety support device 10, a mobile phone line such as 5G or a wireless LAN (Local Area Network) may be used, or vehicle-to-vehicle or vehicle-to-road communication may be used. In this specification and the drawings (especially FIGS. 6 to 8), hardware for communicating with the traffic safety support device 10 that can perform relatively long-distance communication such as a mobile phone line and is implemented as a cloud server via the Internet is referred to as communication interfaces 13, 21, 31, and an interface for relatively short-distance wired or wireless communication is referred to as the communication unit 28. The communication hardware that the warning device 50 should include is referred to as the communication interface 58 when communicating directly with the traffic safety support device 10, and the hardware for communicating with the portable information terminal 20 such as a smartphone via short-distance wireless or wired communication such as Bluetooth is referred to as the communication unit 58.

[0049] The position information sent to the traffic safety support device 10 is used to obtain the degree of danger as the position information of the light vehicle BM on which this warning device 50 itself is mounted. For example, first, by the data control process Rd, traffic volume information around the position represented by the received position information is cut out from the traffic volume information 4 stored in the traffic safety support device 10. This is called region-limited big data. The "surrounding" may be a uniform area such as within a predetermined length range centered on the position represented by the position information, but may also be a route (road) within a certain range such as the road on which the light vehicle BM is traveling and the roads intersecting it. Furthermore, it is not necessary to be within a range of equal distance in either direction around the light vehicle BM, and it may be a wide range in the traveling direction of the light vehicle BM. Also, when the traffic volume information 4 is classified by information such as day of the week and time zone, it may be narrowed down according to the day of the week and time zone when the light vehicle BM is passing through.

[0050] The risk assessment process Rr is performed on traffic volume information 4 included in the area-limited big data. As described above, when the surrounding traffic volume information is extracted, if the congestion level of the road being traveled on is above a certain level, it is determined to be dangerous and an operation mode is output to issue a warning from the flashing warning device 52 or the audible warning device 53 of the warning device 50.

[0051] The data control process Rd, which extracts necessary data from big data, and the risk determination process Rd, which determines the degree of risk from the extracted data and outputs an operating mode for what kind of warning to issue to the warning device 50, may be performed by the traffic safety support device 10, by a mobile information terminal 20 such as a smartphone, or by equipping the warning device 50 with a processor or the like to give it data processing capabilities and performing the process in the warning device 50, or by distributing the processing as appropriate.

[0052] The system may be configured to sequentially acquire the position of the light vehicle BM, extract its movement over time, i.e., its direction of travel, and use this information for risk assessment. For example, the system may normally calculate the risk based only on the congestion in the direction of travel, but when approaching an intersection with another road, it may also take into account the congestion of the intersecting road. For example, if the intersecting road is congested, the risk will be calculated as high even if the light vehicle BM goes straight or turns left or right at the intersection. Furthermore, since speed can also be extracted from the movement over time, it is preferable to configure the system to adjust the risk by also taking the speed of travel into account. For example, even if the risk is high based on the direction of travel, if the speed is sufficiently reduced, a minimal warning is sufficient, and the risk can be adjusted to decrease.

[0053] This allows for the use of a warning device 50, which can be mounted on a light vehicle BM such as a bicycle, to warn those around the light vehicle BM, other than the driver, of the risk of accidents that may occur in the surrounding area, thereby reducing the risk of accidents involving the light vehicle BM. Furthermore, while most conventional technologies warn the driver, this technology can warn everyone uniformly without involving the driver, thus eliminating human-dependent variations. Moreover, the warning device 50 only needs to have a simple communication function and a simple control function that operates the warning devices (52, 53, etc.) according to the received operating mode, so it can be constructed at extremely low cost.

[0054] [Use of Real-Time Data] The traffic safety support system 100 is further preferably configured to acquire real-time data and use it for risk assessment. Real-time data refers to data representing the state of the light vehicle BM itself and / or the surrounding conditions at the time of risk assessment (i.e., in real time). Data representing the state of the light vehicle BM itself can be obtained, for example, from acceleration sensors mounted on the warning device 50 or a mobile information terminal 20 such as a smartphone, or from acceleration sensors mounted on the light vehicle BM, and tilt and wobble can be obtained from a gyro sensor. Data representing the surrounding conditions of the light vehicle BM itself includes location information of pedestrians, bicycles and other light vehicles, automobiles and other vehicles, etc., that are passing by when the risk assessment is performed, and can be obtained by the light vehicle observing its surroundings. For example, it may include congestion levels obtained from images of the surroundings taken by a camera, and data indicating the presence of following vehicles and parallel vehicles detected by distance measuring sensors such as ultrasonic or microwave sensors, Doppler sensors, etc. Alternatively, it may include information on surrounding vehicles acquired by vehicle-to-vehicle communication, etc. Real-time data may also include information such as ambient light, weather conditions, and the lane (roadway, sidewalk, or bicycle lane) in which the light vehicle is traveling.

[0055] The traffic safety support system 100 can determine the degree of danger more accurately by incorporating real-time data in addition to big data for danger assessment. This is because the danger assessment based on big data can be adjusted by real-time data. For example, even if a road, day of the week, and time of day is extremely congested according to big data, and the danger assessment based solely on big data would warrant issuing a warning, if real-time data indicates that congestion is low at that moment, the danger assessment can be lowered. Conversely, even if a road, day of the week, and time of day is extremely rarely congested according to big data, and the danger assessment based solely on big data would not warrant issuing a warning, if real-time data indicates that congestion is severe at that moment, the danger assessment can be raised.

[0056] Furthermore, it is even more preferable to configure the system so that mobile body information 1, which is recognized by other mobile bodies and mapped to the map information 2 of the traffic safety support device 10, as described in Patent Document 1, can be used as real-time data. Information on other mobile bodies located in areas that cannot be detected by the light vehicle BM itself (for example, blind spots of buildings or other vehicles) can also be included in the real-time data, enabling more accurate risk assessment.

[0057] Furthermore, the lane and direction of travel of the light vehicle BM can be determined, for example, by analyzing images taken from the vehicle itself. It may also be determined using road-to-road communication or high-precision GPS. When the lane and direction of travel of the light vehicle BM can be determined, the level of risk can be adjusted accordingly. For example, compared to the level of risk when the determined direction is forward and the lane is a roadway, the level of risk is lower when the lane is a bicycle lane, higher when the lane is a sidewalk, and even higher when the determined direction is reversed.

[0058] [Risk Assessment Considering Accident History Information] Big data may also include accident history information 3. The risk assessment process Rr can be performed taking this accident history information 3 into account. This allows for a more accurate determination of the risk of accidents and enables more appropriate warnings. Since accident history is a record of actual accidents, it indicates the possibility of some cause that triggered the accident, in addition to parameters that can be clearly understood, such as congestion levels. Therefore, if there is a large amount of accident history, the risk assessment process Rr can be adjusted to increase the risk level.

[0059] [Specific Examples of Data Control Processing Rd and Risk Determination Processing Rr] Figure 2 is an explanatory diagram showing one embodiment of data control processing Rd and risk determination processing Rr. The big data includes traffic volume information 4 and may also include accident history information 3. Traffic volume information 4 is the number of vehicles and pedestrians associated with location data and time data. In the example in Figure 2, the number of accidents is included as accident history information 3 for the same location data and time data.

[0060] The data control process Rd sends a data request to the big data side using the position data and time data of the light vehicle BM itself. The position data and time data can be obtained, for example, by a warning device 50 mounted on the light vehicle BM or by a GPS unit (57, 27) built into a portable information terminal 20, but is not limited to this, and may be obtained by any method.

[0061] The data control process Rd extracts and receives area-limited big data from the big data in response to a data request. The area-limited big data includes traffic volume information 4 within a predetermined range, derived from the location and time data that formed the basis of the data request. The data control process Rd creates judgment target data Ta, Tb, and Tc from the traffic volume information 4 included in the area-limited big data. The judgment target data may be of multiple types. For example, Ta may be only the number of vehicles, Tb may be the number of vehicles and pedestrians, and Tc may be data that includes the number of accidents in addition to the number of vehicles and pedestrians. Each of these does not need to be a single scalar value, but may be a matrix (array), vector, or tuple consisting of multiple numerical values.

[0062] In the risk assessment process Rr, based on the input assessment criteria Ca, Cb, and Cc, risk data Da, Db, and Dc are obtained from the assessment target data Ta, Tb, and Tc, respectively, and an operation mode is determined that specifies what kind of warning to issue based on the obtained risk data Da, Db, and Dc. When multiple risk data Da, Db, and Dc are input, the operation mode may simply be determined based on the highest risk data, or the operation mode may be determined by some algorithm. For example, when the risk data Da based only on the number of vehicles is the highest, an operation mode is specified in which the flashing warning device 52 is illuminated as a warning mainly for surrounding vehicles; when the risk data Db based on the number of vehicles and pedestrians is the highest, a warning sound is generated by the voice warning device 53 or a warning announcement is made as a warning mainly for surrounding pedestrians; and when the risk data Dc that also considers accident history information 3 is the highest, a warning is generated that reaches not only surrounding vehicles and pedestrians but also the driver.

[0063] Figure 3 is an explanatory diagram showing one embodiment of risk assessment that incorporates real-time data. As described above, the traffic safety support system 100 can determine the risk level more accurately and issue warnings appropriately by further acquiring real-time data representing the surroundings and / or the state of the light vehicle BM and adjusting the risk level data Da, Db, Dc based on that real-time data. In Figure 3, the process up to the creation of the judgment target data Ta, Tb, Tc is the same as in Figure 2. In the risk assessment process Rr, based on the input judgment criteria Ca, Cb, Cc, the risk level data Da, Db, Dc is obtained from the judgment target data Ta, Tb, Tc, respectively, and the operation mode that specifies what kind of warning to issue is determined based on the obtained risk level data Da, Db, Dc is also the same as in Figure 2, but the risk level data Da, Db, Dc is adjusted based on the sensor judgment data Sa, Sb, Sc created from real-time data.

[0064] Figure 4 is an explanatory diagram illustrating one embodiment of an algorithm for calculating risk data. The judgment criteria Ca, Cb, and Cc can be quantified by assigning one or more criterion values ​​to the number of vehicles, the number of pedestrians, and the number of accidents, respectively. For example, judgment criterion Ca can be configured to include only the number of vehicles in accordance with the data to be judged Ta, Cb can be configured to include criterion values ​​for the number of vehicles and pedestrians in accordance with the data to be judged Tb, and Cc can be configured to include a criterion value for the number of accidents in addition to these two, in accordance with the data to be judged Tc. The judgment criteria Cc illustrated in Figure 4 are, for example, that a risk level of 3 is assigned to 100 or more vehicles, 2 to 100 vehicles, and 1 to 10 vehicles; a risk level of 3 is assigned to 10 vehicles; a risk level of 3 is assigned to 500 or more pedestrians, 2 to 500 pedestrians, and 1 to 100 pedestrians; a risk level of 2 is assigned to 2 accidents, 1 accident is assigned to 1 accident, and 0 accidents is assigned to 0 accidents, and so on. The final risk level data Dc is obtained by adding these values ​​together after applying weights using coefficients Wv, Wp, and Wh.

[0065] In Figure 4, sensor judgment data Sc, created from real-time data, is also input. The sensor judgment data Sc includes real-time data on the number of vehicles and pedestrians, and consists of an adjustment coefficient Pv based on the real-time number of vehicles and an adjustment coefficient Pp based on the real-time number of pedestrians. The risk level is adjusted by multiplying these coefficients by the respective risk data for the number of vehicles and pedestrians before weighting is applied. For example, when the real-time number of vehicles is large, the adjustment coefficient Pv is increased to give more weight to the risk level based on the number of vehicles, and when there are no real-time vehicles, the adjustment coefficient Pv is set to 0, thereby ignoring the risk level calculated based on the number of vehicles in the big data. The same applies to the real-time number of pedestrians. Figure 4 does not include an algorithm for adjusting the risk level calculated based on accident history using real-time data, but this may be added. For example, if the accident history is concentrated at night, the weighting can be increased when the real-time data is at night, and if the accident history is concentrated during rainy weather, the weighting can be increased when the real-time data is during rainy weather.

[0066] In Figure 5, in addition to the big data traffic volume information 4, mobile object information 1, which has been aggregated into the traffic safety support device 10 using the technology disclosed in Patent Document 1, is also input. Mobile object information 1 is information that is aggregated by mapping it onto map information 2 when multiple mobile objects detect other mobile objects in their surroundings using camera images, etc., and associate it with the position information of each mobile object. It is real-time information and covers a wide area, including areas that are blind spots from the perspective of the object itself. Furthermore, it can be associated with position data and time data and can take the same data format as the big data traffic volume information 4. Therefore, as shown in Figure 5, it is input together with the judgment target data Ta, Tb, Tc, rather than the sensor judgment data Sa, Sb, Sc side created from real-time data. More specifically, for the judgment target data of vehicle count (big data) and pedestrian count (big data) on the big data side, the real-time vehicle count (real) and pedestrian count (real) included in mobile object information 1 are weighted by a predetermined coefficient and added. Other processing is the same as described above, referring to Figure 4.

[0067] The real-time number of vehicles (real) and number of pedestrians (real) included in the mobile information 1 may be multiplied by a predetermined coefficient, similar to the sensor judgment data Sa, Sb, and Sc.

[0068] [Embodiment 2] Figure 6 is a block diagram showing one embodiment of the traffic safety support system 100 of the present invention. As described above, the data control processing Rd and the risk determination processing Rr may be configured to be executed in either the traffic safety support device 10 and the warning device 50, or in a mobile information terminal 20 such as a smartphone. The traffic safety support system 100 in Figure 6 does not include a mobile information terminal 20 such as a smartphone, and consists of the traffic safety support device 10 and the warning device 50, with the traffic safety support device 10 configured to execute both the data control processing Rd and the risk determination processing Rr.

[0069] The traffic safety support device 10 is a cloud server comprising a storage unit 11, an information processing unit 12, and a communication interface 13. The storage unit 11 stores traffic volume information 4, which is big data. It may also store accident history information 3. The information processing unit 12 consists of a processor, cache memory, and main memory, and performs data processing by executing programs. The communication interface 13 is an interface that can communicate with various devices via a communication network 90. ​​The communication network 90 may be the internet or a closed network, and the physical layer can be implemented using a mobile phone line, wireless LAN (Local Area Network), LPWA, etc.

[0070] The warning device 50 comprises a light-emitting warning device 52, an audible warning device 53, a warning control unit 51, a GPS unit 57, and a communication interface 58. The light-emitting warning device 52 and the audible warning device 53 are hardware that emit warnings using light and sound, respectively, and can be used interchangeably by taking advantage of the fact that light is mainly effective for vehicles and sound is mainly effective for pedestrians. In addition, it may be configured to emit warnings using other media such as vehicle-to-vehicle communication. The warning control unit 51 has its functions implemented by firmware using, for example, a microcomputer. The communication interface 58 is hardware for communicating directly or indirectly with the traffic safety support device 10 and is implemented with software for controlling the communication protocol. The warning device 50 may also include a sensor 55.

[0071] The warning device 50 transmits position (latitude and longitude) data and time data acquired by the GPS unit 57 to the traffic safety support device 10 via the communication network 90 through the communication interface 58. The information processing unit 12 of the traffic safety support device 10 performs data control processing Rd and risk determination processing Rr, as described with reference to Figure 2. In data control processing Rd, a data request for big data is generated from the received position data and time data, and big data limited to the area around the position and the time period including that time is extracted to become area-limited big data, and this is used to create data to be judged. In risk determination processing Rr, a determination is made on this data to be judged based on predetermined judgment criteria, and the operating mode is determined from the result. The determined operating mode is transmitted to the warning device 50 via the communication interface 13. Furthermore, the system may be configured to adjust the risk level and determine the operating mode by taking accident history information 3 into consideration.

[0072] The warning device 50 receives this operating mode via the communication interface 58, and the warning control unit 51 generates or stops a warning from the light-emitting warning device 52 and the voice-emitting warning device 53 according to the received operating mode. The warnings from the light-emitting warning device 52 and the voice-emitting warning device 53 may be either a binary state of either being generated or not, or they may be configured to generate various modes depending on the level and target of the warning. For example, the warning from the light-emitting warning device 52 is the flashing of a light-emitting element, and the flashing period may be shortened as the degree of danger increases. The voice-emitting warning device 53 is an alarm sound, and the volume may be increased or the intermittent period shortened as the degree of danger increases, or it may be an announcement that specifically notifies the danger by voice.

[0073] The warning device 50 may further include a sensor 55. Real-time data acquired by the sensor 55 is transmitted to the traffic safety support device 10 via the communication network 90 from the communication interface 58. The information processing unit 12 of the traffic safety support device 10 can perform data control processing Rd and risk determination processing Rr that takes into account the real-time data as described with reference to Figure 3. It may also be configured to adjust the risk level and determine the operating mode by taking into account accident history information 3.

[0074] The sensor 55 may be, for example, an ultrasonic distance sensor, a Doppler sensor, a microwave sensor, etc., for detecting the presence or approach of surrounding vehicles or pedestrians, or a camera capable of taking pictures of the surroundings, or it may be an acceleration sensor or gyro sensor for detecting the driving state of the vehicle, or an illuminance sensor or rainfall sensor for detecting the environment.

[0075] The traffic safety support system 100 of this second embodiment may be configured such that the traffic safety support device 10 can use the moving object information 1 as part of the real-time information to adjust the degree of danger and determine the operating mode, as described in the first embodiment with reference to Figure 5.

[0076] As described above, with the traffic safety support system 100 of this second embodiment, almost all data processing can be performed by the information processing unit 12 of the traffic safety support device 10, so the warning device 50 can be constructed at a very low cost.

[0077] [Embodiment 3] Figure 7 is a block diagram showing the configuration of the traffic safety support system 100 of this embodiment 3. The hardware configuration is the same as in Figure 6, so redundant explanations will be omitted, but the danger level determination process Rr is executed not by the information processing unit 12 of the traffic safety support device 10, but by the warning control unit 51 of the warning device 50. In Figure 7, the warning control unit 51 is shown to have its functions implemented by firmware using, for example, a microcomputer, but if the data processing performance of that microcomputer is high, it can be used as is to function as the warning control unit 51 of this embodiment 3.

[0078] In order for the warning control unit 51 of the warning device 50 to execute the risk level determination process Rr, the traffic safety support device 10 transmits the data to be determined Tx, Tb, and Tc to the warning device 50 via the communication interface 13. The warning control unit 51 then executes the risk level determination process Rr, as described with reference to Figure 2, on the received data to be determined Tx, Tb, and Tc.

[0079] The warning device 50 may be configured to obtain real-time data from the sensor 55 mounted on it, and the warning control unit 51 may be configured to execute the risk level determination process Rr, as described with reference to Figure 3, on the judgment target data Tx, Tb, Tc received. Unlike Embodiment 2, there is no need to send the real-time data itself or the sensor data Sa, Sb, Sc created from it from the warning device 50 to the traffic safety support device 10, thus reducing the amount of data communication. Furthermore, since the real-time data can be used quickly by the warning control unit 51 of the warning device 50 for the risk level determination process Rr without communication delay, the real-time data can be quickly reflected in the determination of the operating mode, i.e., in the generation of a warning.

[0080] Furthermore, even when the warning control unit 51 of the warning device 50 performs a risk determination process Rr, it may be configured to adjust the risk level and determine the operating mode by taking into account the accident history information 3, as described with reference to Figure 3 in Embodiment 2. Moreover, as described with reference to Figure 5 in Embodiment 1, the warning control unit 51 of the warning device 50 may be configured to adjust the risk level and determine the operating mode by using the moving object information 1 as part of the real-time information.

[0081] As described above, the traffic safety support system 100 of this third embodiment can quickly reflect real-time data in the generation of warnings.

[0082] [Embodiment 4] Figure 8 is a block diagram showing the configuration of the traffic safety support system 100 of this embodiment 4. The traffic safety support system 100 of this embodiment 4 differs from embodiments 2 and 3 in that a portable information terminal 20, such as a smartphone, is interposed between the traffic safety support device 10 and the warning device 50. The warning device 50 does not need to communicate directly with the traffic safety support device 10, but only needs to communicate via the portable information terminal 20. Therefore, reference numeral 58 is written as "communication unit" instead of "communication interface," and is implemented using, for example, short-range wireless communication such as Bluetooth.

[0083] The mobile information terminal 20 is comprised of a communication interface 21, an information processing unit 22, a storage unit 23, a display unit 24, a sensor 25, a camera 26, a GPS unit 27, and a communication unit 28. The communication interface 21 can communicate with the traffic safety support device 10 via the communication network 90, the communication unit 28 can communicate with the warning device 50, and the information processing unit 22 works in cooperation with the information processing unit 12 of the traffic safety support device 10 to perform data control processing Rd and risk determination processing Rr. All components, including other components, can be implemented using components that are already present in a typical smartphone. Location data and time data acquired by the GPS unit 27 are used for data control processing Rd, and data acquired by the camera 26 and sensor 25 can be used as real-time data for risk determination processing Rr.

[0084] The data control process Rd may be executed in the information processing unit 12 of the traffic safety support device 10, and the risk determination process Rr may be executed in the information processing unit 22 of the portable information terminal 20. When using data acquired by the camera 26 and sensor 25 as real-time data, there is no need to transmit it through the communication network 90, so it can be quickly reflected in the determination of the operating mode. Alternatively, both the data control process Rd and the risk determination process Rr may be executed in the information processing unit 12 of the traffic safety support device 10. The portable information terminal 20 only needs to function as a relay, so computational performance is not required. Alternatively, both the data control process Rd and the risk determination process Rr may be configured to be executed in the information processing unit 22 of the portable information terminal 20. Even in this case, when using data acquired by the camera 26 and sensor 25 as real-time data, there is no need to transmit it through the communication network 90, so it can be quickly reflected in the determination of the operating mode.

[0085] The portable information terminal 20 can be mounted on a mobile device in the technology disclosed in Patent Document 1 and can also have the function of detecting surrounding mobile devices and transmitting this information to the traffic safety support device 10. In Figure 8, another portable information terminal 30 is connected to the communication network 90, and this may also be a portable information terminal 30 mounted on a mobile device in the technology disclosed in Patent Document 1 and can also have the function of detecting surrounding mobile devices and transmitting this information to the traffic safety support device 10.

[0086] In this fourth embodiment, as described with reference to Figure 3 in the second embodiment, the system may be configured to adjust the risk level and determine the operating mode by taking into account the accident history information 3. Furthermore, as described with reference to Figure 5 in the first embodiment, the warning control unit 51 of the warning device 50 may be configured to use the moving object information 1 as part of the real-time information to adjust the risk level and determine the operating mode.

[0087] As described above, with the traffic safety support system 100 of this embodiment 4, almost all data processing can be performed collaboratively by the traffic safety support device 10 and the portable information terminal 20, so the warning device 50 can be constructed at a very low cost. Furthermore, the portable information terminal 20 can be made to handle some of the other traffic safety support functions, such as the technology disclosed in Patent Document 1, and the results can be mutually utilized.

[0088] [Embodiment 5] The inventor has created an invention relating to a traffic safety support system that can use a portable information terminal that can be mounted on a bicycle to show the rider of the bicycle the risk of accidents that may occur in the surroundings, thereby enabling the avoidance of accidents involving bicycles, and has filed an international application as PCT / JP2023 / 032287. A typical embodiment disclosed in the international application is a portable information terminal 20 mounted on a mobile body (BM), comprising a communication interface 21 capable of communicating with a traffic safety support device 10, a GPS unit 27 which is a positioning unit that identifies the position of the mobile body, a camera 26 capable of photographing the area around the mobile body (BM), a display unit 24, and an information processing unit 22, and is configured as follows.

[0089] The information processing unit 22 performs the following operations.

[0090] The mobile body (BM) sequentially transmits a traffic information request to the traffic safety support device 10 via the communication interface 21, along with its own location information identified by the GPS unit 27. In response to the traffic information request, the mobile body (BM) receives map information of its surroundings and surrounding mobile body information, which is the location information of other mobile bodies, via the communication interface 21, maps the surrounding mobile body information onto the received map information, and displays it on the display unit 24.

[0091] Based on the relationship between the surrounding environment captured by the camera 26, its own position information, and the surrounding moving object information, the risk of collision is calculated, and a warning corresponding to that risk is further mapped onto the map information and displayed on the display unit 24.

[0092] This makes it possible to provide a traffic safety support system that uses a portable information terminal 20 that can be mounted on a bicycle (BM) to show the driver of the bicycle (BM) the risk of accidents that may occur in the surrounding area, thereby enabling them to avoid accidents involving bicycles. Specifically, when the moving object is a bicycle and the mounted mobile terminal is a smartphone, the smartphone's display shows other moving objects mapped on a map of the user's surroundings. The system can calculate the risk of collision between the user and other moving objects, including those identified by the user through photography, and warn the user by displaying the risk on the map if the risk of collision is high.

[0093] The "risk of collision" referred to here is different from the risk of collision in Embodiments 1 to 4. The risk of collision in Embodiments 1 to 4 is the risk of an accident occurring around the light vehicle BM itself, and the target of the warning in this case is pedestrians and vehicles in the surrounding area rather than the driver of the light vehicle BM himself. On the other hand, the "risk of collision" referred to in this embodiment assumes the risk of the light vehicle BM itself colliding with other moving objects (pedestrians, light vehicles such as bicycles, vehicles such as automobiles), and the target of the warning is the driver of the light vehicle BM himself.

[0094] As described above, the traffic safety support device 10 is, for example, a cloud server that can access big data including traffic volume information 4 associated with locations on a map, and stores map information 2 and big data including traffic volume information 4 associated with the map information 2. The location information included in the traffic information request transmitted sequentially from the portable information terminal 20 mounted on the light vehicle BM, which is a mobile body such as a bicycle, can also be used as the location information of the light vehicle BM on which the warning device 50 of Embodiments 1 and 4 is mounted, and is used to determine the risk of collision as described above and to execute a risk determination process Rr to determine whether or not to issue a warning to the surroundings from the warning device 50, in conjunction with executing a warning display to the driver of the light vehicle BM accordingly.

[0095] The traffic safety support device 10 may store accident history information 3 in addition to traffic volume information 4 as big data. Based on the accident history information 3, the risk level of collision in this embodiment 5 can be adjusted and reflected in the warning display to the driver. In addition, as explained with reference to Figure 2, the same accident history information 3 can be taken into consideration to adjust the risk level in the risk level determination process Rr and determine the operating mode.

[0096] In this embodiment 5, the surrounding mobile body information, which includes map information of the area around the mobile body (BM) and the location information of other mobile bodies, is stored as mobile body information 1 in the storage unit 11 of the traffic safety support device 10, and can be used as part of the real-time information, as described with reference to Figure 5 in Embodiment 1. This allows for the determination of the risk of collision and the display of a warning to the driver, as well as the adjustment of the risk level in the risk level determination process Rr, enabling the warning device 50 to issue an appropriate warning.

[0097] Furthermore, the lane and direction of travel of the light vehicle BM can be identified, for example, by analyzing images of the surroundings taken from the vehicle itself. It may also be identified using road-to-road communication or high-precision GPS. When the lane and direction of travel of the light vehicle BM can be identified, the risk of collision can be adjusted accordingly. Compared to the risk of collision when the identified direction is forward and the lane is a roadway, the risk of collision is lowered when the lane is a bicycle lane, higher when the lane is a sidewalk, and further increased when the identified direction is reversed. The identified lane and direction can also be used to adjust the risk in the risk assessment process Rr. For example, compared to the risk when the identified direction is forward and the lane is a roadway, the risk is lowered when the lane is a bicycle lane, higher when the lane is a sidewalk, and further increased when the identified direction is reversed. In addition to adjusting the level of danger, the system can also be used to optimize the target of warnings. For example, if sidewalks, bicycle lanes, and roadways are clearly separated, and the light vehicle BM is traveling in either the bicycle lane or the roadway, warnings to pedestrians are not very important, so the warnings to surrounding vehicles using the flashing warning device 52 are prioritized. On the other hand, if the vehicle is traveling on a sidewalk, the warnings to surrounding pedestrians using the audible warning device 53 are prioritized.

[0098] Although the present inventors have described the invention in detail based on embodiments above, it goes without saying that the present invention is not limited thereto and can be modified in various ways without departing from its essence.

[0099] The present invention relates to a traffic safety support device and a program installed on a portable information terminal capable of communicating with the traffic safety support device, and is particularly suitable for avoiding bicycle collisions.

[0100] 1 Mobile information 2 Map information 3 Accident history information 4 Traffic volume information 10 Traffic safety support device 11 Memory unit 12 Information processing unit 13 Communication interface 20, 30 Portable information terminal 21, 31 Communication interface 22, 32 Information processing unit 23, 33 Memory unit 24, 34 Display unit 25, 35 Sensor 26, 36 Camera 27, 37, 57 Positioning unit (GPS unit) 28 Communication unit 40 Mobile device 50 Warning device 51 Warning control unit 52 Light-emitting warning device 53 Voice-emitting warning device 55 Sensor 58 Communication unit / communication interface 90 Communication network 100 Traffic safety support system

Claims

1. A traffic safety support system comprising a warning device equipped with a warning antenna and mounted on a light vehicle, and a traffic safety support device, wherein the traffic safety support device is capable of accessing big data including traffic volume information associated with locations on a map, the warning device is capable of communicating directly or indirectly with the traffic safety support device, and the warning device issues a warning in accordance with the location information of the light vehicle on which it is mounted, which is sent to the traffic safety support device, and the degree of danger determined from the big data based on said location information.

2. The traffic safety support system according to claim 1, further comprising acquiring real-time data representing the surroundings and / or the state of the light vehicle, and adjusting the degree of risk based on the real-time data.

3. The traffic safety support system according to claim 1, wherein the warning device comprises a positioning unit, a communication interface, and a warning control unit, the position acquired by the positioning unit is transmitted as position information from the communication interface to the traffic safety support device, and the warning control unit issues a warning from the warning device according to the operating mode output by the traffic safety support device based on the degree of danger.

4. The traffic safety support system according to claim 2, wherein the warning device comprises a positioning unit, a communication interface, and a warning control unit, the position acquired by the positioning unit is transmitted as position information from the communication interface to the traffic safety support device, the warning control unit determines the degree of risk based on a portion of the big data specified by the position information from the big data received via the communication interface, and issues a warning from the warning device according to an operating mode determined based on the degree of risk.

5. The traffic safety support system according to claim 4, wherein the warning device comprises a sensor, the real-time data includes sensor data acquired by the sensor, and the warning device adjusts the degree of danger based on the sensor data and issues a warning from the warning device according to an operating mode determined based on the adjusted degree of danger.

6. The traffic safety support system according to claim 1, further including a portable information terminal, wherein the portable information terminal comprises a positioning unit capable of determining its own position, a communication unit capable of communicating with the warning device, and a communication interface capable of communicating with the traffic safety support device, the position determined by the positioning unit being transmitted as position information to the traffic safety support device via the communication interface, and the warning device being controlled via the communication unit to issue the warning.

7. The traffic safety support system according to claim 2, further comprising a portable information terminal, the portable information terminal comprising a positioning unit for determining its own position, a communication unit for communicating with the warning device, and a communication interface for communicating with the traffic safety support device, the position determined by the positioning unit being transmitted to the traffic safety support device as position information via the communication interface, the portable information terminal further comprising at least one of a camera, an acceleration sensor, and a gyro sensor, and utilizing at least one of the surrounding image captured by the camera, the speed of the light vehicle acquired by the acceleration sensor, and the tilt of the light vehicle acquired by the gyro sensor as part of the real-time data, the traffic safety support system.

8. The traffic safety support system according to claim 6 or claim 7, wherein the mobile information terminal receives limited big data obtained by extracting data surrounding the location information from the big data, determines the degree of risk based on the limited big data, and controls the warning issued from the warning device based on the determined degree of risk.

9. The traffic safety support system according to claim 8, wherein the portable information terminal identifies the lane and direction in which the light vehicle is traveling, and compared to the degree of danger when the identified direction is forward and the lane is a roadway, the degree of danger is reduced when the lane is a bicycle lane, increased when the lane is a sidewalk, and further increased when the identified direction is reverse.

10. A traffic safety support system according to any one of claims 1 to 9, wherein the big data includes accident history information, and the risk level is determined by taking the accident history information into consideration.

11. The traffic safety support system according to any one of claims 6 to 10, wherein the portable information terminal comprises an information processing unit and a display unit, the information processing unit sequentially transmits a traffic information request along with the location information to the traffic safety support device via the communication interface, the information processing unit receives, in response to the traffic information request, map information of the surroundings of the mobile body and surrounding mobile body information, which is the location information of other mobile bodies, via the communication interface, maps the surrounding mobile body information onto the received map information and displays it on the display unit, and the portable information terminal calculates the risk of collision from the relationship between the situation around itself in the image captured by the camera, its own location information, and the surrounding mobile body information, and further maps a warning corresponding to the risk of collision onto the map information and displays it on the display unit.

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