Driving assistance devices

Abstract

To accurately estimate a vehicle position and a vehicle speed even on condition that a driving assistance apparatus using the vehicle position and the vehicle speed, which are grasped by a GPS receiving function of a portable terminal, cannot receive radio waves from a GPS satellite.SOLUTION: A driving assistance apparatus for performing driving assistance on the basis of a vehicle position and a vehicle speed of a vehicle traveling on a track comprises a sound collection part that collects sounds on the inside and outside of the vehicle. The driving assistance apparatus estimates the vehicle position and the vehicle speed on the basis of the order of the appearance of a plurality of feature sounds included in data on the vehicle sounds collected by the sound collection part.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a driving assistance device, and is suitable for track transportation systems such as railways. [Background technology]

[0002] The running speed pattern between stations (hereinafter referred to as "running pattern") varies depending on the driver, even when trains run between stations at similar times, and as a result, the amount of power consumed when running between stations also varies. By reducing the variation in running patterns and standardizing them to energy-efficient running patterns, it is possible to make railway operations more energy-efficient.

[0003] To reduce the variation in driving patterns, driver training based on reviewing driving patterns after operation and driving operation support during operation are effective. The former, driver training, is a system in which driving patterns during operation are stored in a device, and the driver reviews the visualized results of the driving patterns along with power consumption and other factors during their free time, which helps improve their own driving operation. The latter, driving operation support, includes devices that give advice on driving operation content and devices that take over driving operation itself, such as automatic driving. Hereinafter, these devices that contribute to reducing the variation in driving patterns will be referred to as driving support devices.

[0004] To realize these driving assistance devices, vehicle position and vehicle speed are required as inputs. One method for obtaining highly accurate vehicle position and vehicle speed is to obtain them from a vehicle information device that manages this information. However, this method requires modification of the vehicle information device, which makes its introduction difficult. In addition, there is a problem that it cannot be applied to vehicles that do not have a vehicle information device installed.

[0005] One method for realizing the above-described driving assistance device without connecting to a vehicle information device is to bring a mobile terminal equipped with a GPS receiving function into the vehicle, calculate the vehicle position from the latitude and longitude information acquired by the GPS receiving function, and calculate the vehicle speed from the difference in vehicle position. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Application Laid-Open No. 2013-7723 Summary of the Invention [Problem to be solved by the invention]

[0007] In conditions where radio waves from GPS satellites cannot be received due to obstructions, such as inside tunnels or around covered stations, the vehicle position cannot be determined, which limits the opportunities for utilizing driving assistance devices.In response to this, Patent Document 1 discloses a method for estimating vehicle speed by integrating acceleration using the function of an acceleration sensor provided in a mobile terminal when radio waves from GPS satellites cannot be received due to obstructions, and estimating vehicle position by integrating the vehicle speed.

[0008] However, the method based on the acceleration sensor has a problem that the estimation accuracy of the vehicle position and vehicle speed deteriorates if the orientation and angle of the mobile device are not constant. The mobile device carried on the vehicle may also be used to check route information and operation information. In such cases, the mobile device may be operated by the crew while the vehicle is in operation, so there is no guarantee that the orientation and angle of the mobile device will be constant.

[0009] Therefore, the present invention aims to provide a driving assistance technology that can ensure ample opportunities for use by using a driving assistance device that uses the vehicle position and vehicle speed obtained by the GPS receiving function of a mobile terminal to accurately estimate the vehicle position and vehicle speed in conditions where radio waves from GPS satellites cannot be received. [Means for solving the problem]

[0010] In order to solve the above-mentioned problems, one representative driving assistance device of the present invention is a driving assistance device that provides driving assistance based on the vehicle position and vehicle speed of a vehicle traveling on a track, and has a sound collection unit that collects sounds inside and outside the vehicle, including at least sounds generated by equipment mounted on the vehicle, as vehicle sound data, The sound collection unit is provided in the leading car of the vehicle, The vehicle position and the vehicle speed are estimated based on the order of appearance of a plurality of characteristic sounds included in the vehicle sound data collected by the sound collection unit. The plurality of characteristic sounds are at least two of the following sounds: the sliding sound between the wheels and brake shoes when the vehicle's air brakes are in use; the operating sound of the vehicle's master controller handle; the warning sound for passengers when the vehicle's doors are opened or closed; the door operation sound when the vehicle's doors are opened or closed; the departure melody sound in the premises of the station where the vehicle is stopping; the sound that notifies the passengers that the vehicle's doors are closed; and the sound of compressed air being discharged when the vehicle's air brakes are released. It is characterized by the following. [Effects of the Invention]

[0011] According to the present invention, it is possible to utilize a driving assistance device that uses the GPS function of a mobile terminal even on routes and between stations where there are sections where GPS signals cannot be received. Problems, configurations, and effects other than those described above will become apparent from the following description of the preferred embodiments. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a diagram illustrating a functional configuration of a driving assistance device according to a first embodiment of the present invention and an overview of each function. [Figure 2] FIG. 10 is a diagram illustrating an example of a flowchart of a process executed by a position / speed correction information generating unit. [Figure 3] FIG. 10 is a diagram showing an example of a characteristic sound expression template. [Figure 4] FIG. 10 is a diagram showing an example of a characteristic sound expression template. [Figure 5] FIG. 10 is a diagram illustrating an example of a characteristic sound history table. [Figure 6] FIG. 10 is a diagram illustrating an example of a characteristic sound history table. [Figure 7] FIG. 10 is a diagram illustrating an example of a characteristic sound history table. [Figure 8] FIG. 10 is a diagram illustrating an example of a flowchart of a process executed by a driving assistance content generation unit. [Figure 9] 10 is a schematic diagram showing an example of driving pattern data generated by the driving assistance content generation unit in the form of a speed graph between stations. FIG. [Figure 10]FIG. 4 is a diagram showing an example of driving pattern data in the form of a table. [Figure 11] FIG. 10 is a diagram illustrating an example of visualization of driving assistance content. [Figure 12] FIG. 10 is a diagram illustrating a functional configuration of a driving assistance device according to a second embodiment of the present invention and an overview of each function. DETAILED DESCRIPTION OF THE INVENTION

[0013] Hereinafter, with reference to the drawings, Examples 1 and 2 will be described as modes for carrying out the present invention. Note that the present invention is not limited to these Examples. In addition, in the description of the drawings, the same parts are denoted by the same reference numerals.

[0014] Examples 1 and 2 show examples of a driving assistance device that encourages train crew members to reflect on their driving operations by visualizing the running pattern between stations based on the vehicle position and speed estimated using GPS in railway vehicles.

[0015] In the first and second embodiments, it is assumed that a GPS function is implemented in a mobile terminal as a driving assistance device and the mobile terminal is installed in a driver's cab. However, the present invention is not limited to this assumption, and it is of course also possible to adopt a mode in which a device with a GPS function is installed in a vehicle.

[0016] In addition, in sections where GPS reception is poor, the driving assistance device estimates information about the vehicle position and vehicle speed based on sound data inside and outside the vehicle collected by a sound collection unit provided in the driving assistance device.

[0017] This makes it possible to supplement information about vehicle position and speed in sections where GPS cannot estimate vehicle position and speed during the process of visualizing driving patterns. This makes it possible to utilize driving assistance devices even in sections with poor GPS reception, leading to improved energy efficiency. [Example]

[0018] FIG. 1 is a diagram showing a functional configuration of a driving assistance device according to a first embodiment of the present invention and an overview of each function. The driving assistance device is composed of a GPS receiving unit 101, an on-track position estimation unit 102, a vehicle speed estimation unit 103, an operation unit 104, a route information management unit 105, a position and speed correction information generation unit 106, a sound collection unit 107, a characteristic sound detection unit 108, a driving assistance content generation unit 109, and a driving assistance content transmission unit 110.

[0019] The GPS receiving unit 101 generates latitude and longitude 151 at a predetermined time period based on the received GPS signal and transmits it to the on-orbit position estimating unit 102. Here, it is desirable to set the time period in consideration of the purpose of the driving assistance device, which is to enable the driver to review his driving operation by visualizing the driving pattern.

[0020] In other words, if the time period is too short, the visualized driving pattern may contain vibration components that do not exist in the actual vehicle speed due to the influence of positional variations caused by the accuracy limits of GPS.On the other hand, if the time period is too long, the reproducibility of vehicle speed changes will be poor, making it difficult for drivers to review their driving operations by visualizing the driving pattern.

[0021] Furthermore, the GPS receiving unit 101 generates a reception status 154 based on the state of the received GPS signal and transmits it to the position and speed correction information generating unit 106 and the driving assistance content generating unit 109. As an example of processing the reception status 154 generated by the GPS receiving unit 101, if it is considered that the vehicle position detection accuracy will decrease depending on the number of GPS satellites that have been acquired and the positional relationships between the GPS satellites, the reception status 154 is set to a value of "deteriorated" (meaning a poor reception state), and otherwise the reception status 154 is set to a value of "good" (meaning a good reception state).

[0022] The on-track position estimation unit 102 estimates an on-track position 152 by calculation based on the latitude and longitude 151 received from the GPS receiving unit 101 and the track shape 155 received from the track information management unit 105, and transmits the estimated on-track position 152 to the vehicle speed estimation unit 103, the track information management unit 105, and the driving assistance content generation unit 109. Here, the track shape 155 is a representation of the shape of the track on which the vehicle is traveling as point sequence data, and each point in the point sequence is associated with a value representing latitude, longitude, and an absolute position along the track. A typical example of a value representing an absolute position along the track is kilometers (hereinafter, this parameter will be referred to as "kilometers").

[0023] For example, in a car navigation system for an automobile, a technology is generally implemented that maps the position of the automobile, which is a moving body, along a predetermined route based on the latitude and longitude of the moving body acquired by GPS. On the other hand, the on-track position estimation unit 102 also compares the data of the track shape 155 with the latitude and longitude 151 to estimate the on-track position 152 corresponding to the latitude and longitude 151, so this technology of the car navigation system can be applied.

[0024] The vehicle speed estimation unit 103 calculates and estimates an estimated speed 153 based on the on-track position 152 received from the on-track position estimation unit 102, and transmits the estimated speed 153 to the driving assistance content generation unit 109. For example, the estimated speed 153 can be calculated by dividing the difference between the on-track positions 152 of adjacent periods by the time for one period.

[0025] The operation unit 104 accepts inputs made by the crew and transmits route information 156 to the route information management unit 105. For example, a specific hardware example of the operation unit 104 is a touch panel of a mobile terminal that implements the driving assistance device. Here, the contents of the route information 156 include, for example, the current station, the destination station, the train type, and the train number.

[0026] The track information management unit 105 receives track information 156 from the operation unit 104 and on-track position 152 from the on-track position estimation unit 102, and transmits track geometry 155 to the on-track position estimation unit 102 and running distance between stations 157 to the position / speed correction information generation unit 106. As described above, the track geometry 155 is a point sequence data representation of the shape of the track on which the vehicle is running. The track information management unit 105 also prepares a database of track geometry data for routes to which the driving assistance device may be applied.

[0027] Furthermore, in order to improve the efficiency of the search process for the on-track position 152 in the on-track position estimation unit 102, the route information management unit 105 transmits the track shape 155 to the on-track position estimation unit 102, limited to data on a section where the vehicle is likely to travel based on the route information 156.

[0028] On the other hand, the running distance 157 is the distance between stations where the vehicle is thought to be currently running, and is information determined based on the train number included in the received route information 156, the timetable information previously stored in the route information management unit 105, the current time, and the received on-track position 152. The reason why the received on-track position 152 is included as a determining factor for the running distance 157 is to prepare for the case where a delay occurs and an appropriate running distance 157 cannot be extracted by comparing the timetable information with the current time.

[0029] The position and speed correction information generation unit 106 receives reception status 154 from the GPS receiving unit 101, running station interval 157 from the route information management unit 105, and characteristic sound detection result 160 from the characteristic sound detection unit 108, and generates position and speed correction information 158 and transmits it to the driving assistance content generation unit 109. Here, the position and speed correction information 158 is data that is a set of four types of information: time, vehicle position, vehicle speed, and positive and negative acceleration. Details of the processing by the position and speed correction information generation unit 106 will be described later.

[0030] The sound collection unit 107 is equipped with a microphone for collecting ambient sounds both inside and outside the vehicle, and constantly collects sound while transmitting the collected sound results as vehicle sound data 159 to the characteristic sound detection unit 108. The sound collection unit 107 is assumed to be installed inside the vehicle, but if it is necessary to collect characteristic sounds (plurality of characteristic sounds shown in the characteristic sound occurrence templates of Figures 3 and 4) described below, it is preferable to install it inside a vehicle with a driver's cab (for example, the lead car).

[0031] The characteristic sound detection unit 108 searches for the presence of a specific type of characteristic sound in the vehicle sound data 159 received from the sound collection unit 107, and when a specific type of characteristic sound is detected, it transmits the type of the detected characteristic sound and the time of detection as a characteristic sound detection result 160 to the position and speed correction information generation unit 106. Examples of characteristic sounds will be described later in the detailed processing of the position and speed correction information generation unit 106.

[0032] A specific example of processing by the characteristic sound detection unit 108 will be described. The characteristic sound detection unit 108 compares the vehicle sound data 159 from the past few seconds with template data of a plurality of characteristic sounds prepared in advance at a predetermined calculation cycle. If it is determined that any of the prepared characteristic sounds is included in the vehicle sound data 159 from the past few seconds, the type of characteristic sound detected and the time of detection are stored in the characteristic sound detection result 160. Examples of characteristic sound detection methods include a method of determining the similarity of frequency spectra obtained by frequency analysis, and a method using image matching (pattern matching) of frequency spectra and image matching (pattern matching) of spectrograms.

[0033] The driving assistance content generation unit 109 receives the on-track position 152, the estimated speed 153, the reception state 154, and the position / speed correction information 158 as input, generates driving assistance content 161, and transmits it to the driving assistance content transmission unit 110. Here, the driving assistance content 161 includes at least data on the running pattern of the vehicle equipped with the driving assistance device. The running pattern data is time-series data on the vehicle position and the vehicle speed, and is information on a unit of train operation, such as for each station-to-station run or each route.

[0034] It is desirable that the driving assistance content 161 includes, in addition to the driving pattern data, time-series data of power consumption estimated from the driving pattern data. This allows the user of the driving assistance device to check the relationship between the driving pattern between stations and the resulting power consumption. Furthermore, for comparison, driving pattern data and power consumption data for an ideal driving style from the viewpoint of energy conservation are prepared in advance, and included in the driving assistance content 161, so that the user of the driving assistance device can check the difference between the ideal driving style and the current driving style together with the difference in power consumption. The details of the processing by the driving assistance content generation unit 109 will be described later.

[0035] The driving assistance content transmission unit 110 visualizes and outputs data of the driving assistance content 161 to the user of the driving assistance device. FIG. 11 is a diagram showing an example of visualization of the driving assistance content 161. An example of visualization is a graph with the vehicle position on the horizontal axis and the vehicle speed on the vertical axis (the graph shown in the upper part of FIG. 11). If the driving assistance content 161 includes driving pattern data for comparison, the driving pattern data can be displayed superimposed to facilitate comparison.

[0036] Furthermore, if the driving assistance content 161 also includes data on power consumption, the relationship between the driving pattern and power consumption can be easily understood by also visualizing a graph with the vehicle position on the horizontal axis and the power consumption on the vertical axis (the graph shown at the bottom of Fig. 11). Furthermore, by listing the power consumption between stations and the driving time in a table or the like (the table shown at the bottom of Fig. 11), the overall evaluation results for the entire route between stations can be understood.

[0037] Next, an example of processing by the position / speed correction information generating unit 106 will be described with reference to FIG. 2 is a diagram showing an example of a flowchart of the processing executed by the position and speed correction information generating unit 106. Each processing is executed by the position and speed correction information generating unit 106, and therefore, the description of the main body will be omitted below.

[0038] In STEP 201, the content of the characteristic sound detection result 160 is checked to see if a new characteristic sound has been detected by the characteristic sound detection unit 108. If the characteristic sound detection result 160 is new (yes), the process proceeds to STEP 202; if not (no), the process proceeds to STEP 203.

[0039] In STEP 202, the new characteristic sound detection result 160 confirmed in STEP 201 is registered in a characteristic sound history table. The characteristic sound history table is a table that manages the detected characteristic sound type together with the detection time. Figures 5, 6, and 7 show examples of the characteristic sound history table.

[0040] In STEP 203, the contents of the reception status 154 are checked, and if it is in the "deteriorating" state (yes), the process proceeds to STEP 204, otherwise (no), the process exits this processing flow and ends.

[0041] In STEP 204, a characteristic sound expression template corresponding to the running station interval 157 is read from the internal memory. The characteristic sound expression template is fixed data that defines the types and order of characteristic sounds to be detected at a specific position and speed within a section where it is known in advance that the reception condition 154 will be "deteriorating." Figures 3 and 4 are diagrams showing examples of characteristic sound expression templates.

[0042] The characteristic sound expression template shown in Figure 3 is an example that corresponds to the timing when the train stops at a station, that is, when the speed changes from positive to zero at the target stopping position of the station. The contents are explained below in chronological order (written in order to match Figure 3).

[0043] <Step 1> When a vehicle stops at a station, the air brakes operate just before the vehicle stops, generating a sliding noise between the brake pads and wheels (air brake sliding noise shown in Figure 3).

[0044] <Step 2> When the driver confirms that the vehicle has stopped, he moves the master controller handle position significantly to near the maximum normal brake, which generates a sound associated with operating the master controller handle (master controller handle braking operation sound, as shown in Figure 3).

[0045] <Step 3> After confirming safety on the platform, the crew operates the switch to open the doors. At that time, a warning sound is first sounded to notify passengers that the doors will be opening (door opening warning sound shown in Figure 3).

[0046] <Step 4> Next, an operating sound is generated when the door leaf operates and opens completely (door opening sound shown in Figure 3).

[0047] The characteristic sound expression template shown in Fig. 4 is an example that corresponds to the timing when the train departs from Station A, that is, when the speed changes from zero to positive at the target stopping position of Station A. The contents are explained below in chronological order (written in order to match Fig. 4).

[0048] <Step 1> When a train departs from a station, a departure melody is played to inform station passengers on the platform of the departure (departure melody (Station A) shown in Figure 4).

[0049] <Step 2> After the train crew and station staff have confirmed the safety of the platform, the train crew operates the switch to close the doors. At that time, a warning sound is first sounded to notify passengers that the doors are closing (door closing warning sound shown in Figure 4).

[0050] <Step 3> Next, an operating sound is generated when the door leaf operates and closes completely (door closing sound shown in Figure 4).

[0051] <Step 4> If a conductor is on board, a buzzer will sound in the driver's cab to inform the driver that the conductor has confirmed that the doors are closed (door closed confirmation buzzer sound shown in Figure 4).

[0052] <Step 5> The driver moves the master controller handle position from near the maximum normal brake position to the powering side, generating a sound associated with the master controller handle operation (master controller handle powering operation sound shown in Figure 4).

[0053] <Step 6> Immediately after operating the master controller handle, the air brake is released, causing the sound of air escaping from the brake cylinder (compressed air exhaust sound, as shown in Figure 4).

[0054] The characteristic sound expression templates shown in Figures 3 and 4 are prepared for each station, and in STEP 204, the characteristic sound expression template corresponding to the running distance 157 is read from the internal memory. The reason why the characteristic sound expression templates are prepared separately for each station is that, for example, the departure melody included in the departure template shown in Figure 4 may differ depending on the station, and therefore the characteristic sound may differ.

[0055] In STEP 205, it is confirmed whether or not two or more characteristic sounds among the characteristic sounds present in the characteristic sound expression template loaded in STEP 204 exist in the characteristic sound history table in a predetermined order since the time when the reception status 154 was most recently switched to "worsened." Here, the "predetermined order" means that the order is in the normal order defined in the characteristic sound expression template. Furthermore, if multiple characteristic sound expression templates have been loaded, processing is performed for each of the characteristic sound templates.

[0056] In the following (1) to (6), an example of the processing in STEP 205 and the output of the determination result in the next STEP 206 will be explained using the characteristic sound expression templates in FIGS. 3 and 4 and the characteristic sound history tables in FIGS. 5, 6 and 7.

[0057] (1) Processing example based on the characteristic sound expression template of Fig. 3 and the characteristic sound history table of Fig. 5 The four types of characteristic sounds present in the characteristic sound expression template in Figure 3 are air brake sliding sound, master controller handle braking operation sound, door opening warning sound, and door opening operation sound. A search is made to see if each of these characteristic sounds exists in the characteristic sound history table in Figure 5, and if it does, the time listed in the characteristic sound history table in Figure 5 is checked.

[0058] In the example of the characteristic sound history table in Figure 5, the following characteristic sounds can be confirmed. Air brake sliding noise: Detected at 15:15:00 Master controller handle braking operation sound: 15:15:02 detected Door opening warning sound: 15:15:03 detection Door opening sound: 15:15:06 detection

[0059] If the characteristic sounds are arranged in the order of their detection time, they will be: air brake sliding sound → master controller handle braking operation sound → door opening warning sound → door opening sound. If we check the sequence information of the characteristic sound expression template in Figure 3, we can see that they are arranged in the correct order, as it is "1" → "2" → "3" → "4".

[0060] As a result, four characteristic sounds whose order matches that of the characteristic sound occurrence template in Figure 3 have been found in the characteristic sound history table in Figure 5, so the result of the determination in STEP 206 is yes. That is, in the example of (1), it has been detected that the phenomenon "a train stops at a station" defined as the characteristic sound occurrence template in Figure 3 occurred in the time range from 15:15:00 to 15:15:06.

[0061] Here, for a normal train that stops at a station, the time from the air brake sliding sound to the door opening sound is about 10 seconds. Therefore, if the time interval between characteristic sounds is longer than this, the accuracy of the judgment can be improved by adding a process that excludes characteristic sounds that are far apart in time from the judgment.

[0062] (2) Processing example based on the characteristic sound expression template of Fig. 4 and the characteristic sound history table of Fig. 5 In the characteristic sound history table of Figure 5, six characteristic sounds (departure melody (Station A) → door closing warning sound → door closing operation sound → door closing confirmation buzzer sound → master controller handle power operation sound → compressed air discharge sound) are found whose order matches that of the characteristic sound expression template of Figure 4, so the judgment result of STEP 206 is yes. In other words, in the example of (2), it was possible to detect that the phenomenon of "a train departing from the station", which is defined as the characteristic sound expression template in Figure 4, occurred in the time range from 15:15:40 to 15:16:01.

[0063] (3) Processing example based on the characteristic sound expression template of Fig. 3 and the characteristic sound history table of Fig. 6 In the characteristic sound history table of Fig. 6, the air brake sliding sound is not found among the characteristic sounds described in the characteristic sound expression template of Fig. 3. However, the other three types of characteristic sounds (master control handle braking operation sound → door opening warning sound → door opening operation sound) are found in the order defined in the characteristic sound expression template of Fig. 3, so the determination result in STEP 206 is yes.

[0064] (4) Processing example based on the characteristic sound expression template of Fig. 4 and the characteristic sound history table of Fig. 6 None of the characteristic sounds listed in the characteristic sound expression template of Fig. 4 is found in the characteristic sound history table of Fig. 6. In this case, the determination result of STEP 206 is no.

[0065] (5) Processing example based on the characteristic sound expression template of Fig. 3 and the characteristic sound history table of Fig. 7 In the characteristic sound history table of Fig. 7, the master control handle braking operation sound is found among the characteristic sounds listed in the characteristic sound expression template of Fig. 3, but no other characteristic sounds are found. Therefore, the determination result in STEP 206 is no.

[0066] (6) Processing example based on the characteristic sound expression template of Fig. 4 and the characteristic sound history table of Fig. 7 In the characteristic sound history table of Fig. 7, the departure melody (Station A) → door closing warning sound is found in the order defined in the characteristic sound expression template of Fig. 4. In this case, two characteristic sounds whose order matches that of the characteristic sound expression template of Fig. 4 are found in the characteristic sound history table of Fig. 7, so the determination result in STEP 206 is yes.

[0067] It is also possible that two or more characteristic sounds whose order matches that of the characteristic sound occurrence template are found in the characteristic sound history table, and at the same time, characteristic sounds whose order does not match are also found in the same characteristic sound history table. In such a case, for example, a method can be considered in which characteristic sounds with a high "certainty of characteristic sound detection" are used preferentially in the judgment. Regarding the "certainty of characteristic sound detection," a method can be considered in which the characteristic sound detection unit 108 adds the degree of matching at the time of characteristic sound detection to the characteristic sound detection result 160 as information and uses this information in the position / speed correction information generation unit 106.

[0068] Furthermore, even if two or more characteristic sounds whose order matches that of the characteristic sound occurrence template are found in the characteristic sound history table, if the "certainty of characteristic sound detection" is lower than a predetermined threshold, it is possible to change the process to a "no" determination result in STEP 206. This makes it possible to eliminate cases where the movement of one's own vehicle is mistakenly recognized due to picking up the sound of another vehicle.

[0069] In STEP 206, if the determination result is yes, the process proceeds to STEP 207, and if the determination result is no, the process exits this processing flow and ends.

[0070] In STEP 207, position and speed correction information 158 is generated and sent to driving support content generation unit 109. Position and speed correction information 158 is data that is a set of four types of information: time, vehicle position, vehicle speed, and positive or negative acceleration.

[0071] For example, if the determination result in STEP 206 is yes for the characteristic sound occurrence template of FIG. 3 and the characteristic sound history table of FIG. 5 corresponding to station A, the data constituting the position and speed correction information 158 will be as follows: ·Time: 15:15:02 Vehicle position: The distance in kilometers corresponding to the target stop position at Station A Vehicle speed: zero Acceleration: Negative (because the velocity changes from positive to zero)

[0072] Here, the timing of the master controller handle braking operation sound is stored as the stopping time, but if the master controller handle braking operation sound is not detected, it is also possible to store a time estimated from the timing of other detected characteristic sounds. For example, since it is generally 2 to 3 seconds between the master controller handle braking operation sound and the door opening warning sound, if the master controller handle braking operation sound is not detected but the door opening warning sound is, the time 2 to 3 seconds before the detection of the door opening warning sound can be used.

[0073] As another example of generating the position / speed correction information 158, if the determination result in STEP 206 is yes for the characteristic sound expression template of FIG. 4 and the characteristic sound history table of FIG. 5 corresponding to station A, the data constituting the position / speed correction information 158 will be as follows: ·Time: 15:16:00 Vehicle position: The distance in kilometers corresponding to the target stop position at Station A Vehicle speed: zero Acceleration: Positive (because the velocity changes from zero to positive)

[0074] Here, with regard to time, the timing of the master controller handle powering operation sound is stored as the departure time, but if the master controller handle powering operation sound is not detected, it is also possible to store a time estimated from the timing of other detected characteristic sounds. For example, since it is generally 1 to 3 seconds between the master controller handle powering operation sound and the compressed air discharge sound, if the master controller handle powering operation sound is not detected but the compressed air discharge sound is, the time 1 to 3 seconds before the compressed air discharge sound is detected can be used.

[0075] Note that the explanation so far has focused on characteristic sounds that are generated when a train stops at and departs from a station, but the locations at which trains stop and depart are not limited to stations. The driving assistance device described above can also be applied to other locations where there are predetermined stopping locations. Examples of characteristic sounds that are generated when a train stops at a location other than a station include the sound of the air brake sliding and the sound of the master controller handle braking. Examples of characteristic sounds that are generated when a train departs from a location other than a station include the sound of the master controller handle powering and the sound of compressed air being discharged.

[0076] Next, an example of the processing executed by the driving support content generation unit 109 will be described with reference to FIGS. 8, 9, and 10. FIG. FIG. 8 is a diagram showing an example of a flowchart of the processing executed by the driving support content generation unit 109. FIG. 9 is a schematic diagram showing an example of driving pattern data generated by the driving support content generation unit 109 in the form of a speed graph between stations. 10 is a diagram showing an example of driving pattern data in the form of a table, where the driving pattern data is composed of time, position, speed, reception state, and power consumption.

[0077] The flowchart shown in FIG. 8 is executed by the driving support content generation unit 109, and therefore the description of the entity that performs each of the following processing steps will be omitted. 9 is a speed graph with the horizontal axis representing the position and the vertical axis representing the speed. Here, two stations, Station A and Station B, are set, and an example of processing executed by the driving assistance content generation unit 109 will be described along the process of a train traveling from Station A to Station B.

[0078] The position of station A is assumed to be x1, and the position of station B is assumed to be x4. Assuming that the reception condition 154 deteriorates near the station due to the influence of roofs, etc., the reception condition 154 is assumed to be "deteriorated" in the sections x1 to x2 and x3 to x5 at the positions shown in FIG. 9. In other sections, the reception condition 154 is assumed to be "good." As for the driving assistance device, it is assumed that the power is turned on while the train is stopped at station A.

[0079] First, when the train stops at station A and the driving support device is turned on, the GPS satellites have not been acquired and the reception status 154 is in the "deteriorated" state. Therefore, in the flowchart shown in Figure 8, the determination in STEP 801 is yes, and the process proceeds to the next STEP 807.

[0080] Next, in the determination of STEP 807, there is no driving pattern data before the reception condition deteriorated, i.e., before the power was turned on in this case, so the result is no. Therefore, the process proceeds to STEP 811, but because there is no speed data, power consumption estimation is not performed.

[0081] In the example of driving pattern data shown in Figure 10, the range is from 9:14:00 to 9:14:59. The reception condition 154 is "deteriorating," and there is no data on position or speed, so power consumption cannot be estimated. For this reason, no data exists because it is not written into the driving pattern data.

[0082] At the timing when the train departs from station A, the position and speed correction information 158 is input to the driving support content generation unit 109. Here, the input position and speed correction information 158 is as follows. ·Time: 9:15:00 Vehicle position: x1 Vehicle speed: zero Acceleration Positive / Negative: Positive

[0083] At this stage, the reception state 154 continues to be "deteriorating," so in the flowchart shown in Fig. 8, processing continues in the order of STEP 801 → STEP 807 → STEP 811. At this stage, there is no data at that time.

[0084] When the train departs from station A and travels to position x2, the reception condition 154 changes from "deteriorating" to "good." At this timing, the determination in STEP 801 in the flowchart shown in FIG.

[0085] Next, in STEP 802, the on-track position 152 (x2), estimated speed 153, and reception status 154 ("good") are written into the travel pattern data. This timing corresponds to the data at 9:15:11 in Figure 10. At this stage, there is still no data before 9:15:10.

[0086] Since the reception condition 154 has changed from "deteriorating" to "good," the determination in the following STEP 803 is "yes," and the process proceeds to STEP 804. Here, the driving assistance content generation unit 109 determines "yes" in STEP 804 because there is position and speed correction information 158 received at the time the train departs from station A.

[0087] In the next step 805, a complementary pattern is generated. The complementary pattern is time-series data consisting of time, position, and speed. Here, based on the time, position, and speed related to the departure from Station A included in the latest position and speed correction information 158 and the time, position, and speed at the timing when the reception condition 154 changed from "deteriorating" to "good," time-series data that complements these is generated.

[0088] One example of a method for generating a complementary pattern is to search a database that stores past driving data (time, location, and speed) for data that matches certain conditions. The conditions here are the location of the start point and finish point of the section to be complemented, the speed, and the driving time between them.

[0089] To adopt this method, it is necessary to acquire in advance driving data from commercial operations on the target route and section using a vehicle information device or the like that can grasp the position and speed, and store it in a database. In addition to actual driving data from the past, virtual driving data created by computer simulation can also be stored in this database to prepare candidates for driving patterns to be adopted as supplementary patterns.

[0090] In STEP 806, the complementary pattern generated in STEP 805 is applied to the section where the reception condition is "deteriorated" and where position and speed data are missing, and the driving pattern data is updated. The data in the range indicated by the thick frame 1001 in Fig. 10 is the applied complementary pattern. In the speed graph shown in Fig. 9, the speed pattern from x1 to x2 (dashed line) corresponds to the complementary pattern.

[0091] In the next step 811, the updated driving pattern data is referenced and the power consumption is estimated for the range in which the speed data exists, which corresponds to the range from 9:15:00 to 9:15:11 shown in Fig. 10 (the range indicated by the thick frame 1004 in Fig. 10).

[0092] Here, an example of a method for estimating power consumption from speed data is the following method. a) In accordance with the equation of motion, the force acting on the train in the direction of travel is calculated from the train weight and the acceleration calculated from the time difference of the speed data. b) The force in the direction of travel calculated in a) above is taken into account, along with the running resistance calculated from the train's weight, speed data, and track conditions such as gradient, to determine the driving force generated by the train's drive unit. c) The power is calculated from the driving force and speed calculated in step b) above, and the power consumption is calculated by taking into account the loss of efficiency in the path from the energy source to the generation of the power.

[0093] While the train is traveling from x2 to x3, the reception condition 154 remains "good." Therefore, the processing flow for this section is STEP 801 → STEP 802 → STEP 803 → STEP 811 in the flowchart shown in Fig. 8. In the travel pattern database shown in Fig. 10, this corresponds to the data from 9:15:11 to 9:17:30.

[0094] When the train passes position x3, the reception status 154 becomes "deteriorating." The processing flow at this timing proceeds in the order of STEP 801 → STEP 807 → STEP 808 in the flowchart shown in FIG. 8. Until new position and speed correction information 158 is received, the determination in STEP 808 is no, and the process proceeds to STEP 811. During this period, there is no data in the bold frame 1002 in FIG. 10, and the corresponding power consumption cannot yet be estimated (the range shown by the bold frame 1005 in FIG. 10).

[0095] At the time when the train stops at position x4, that is, station B, the position and speed correction information 158 is input to the driving support content generation unit 109. Here, the input position and speed correction information 158 is as follows. ·Time: 9:17:42 Vehicle position: x4 Vehicle speed: zero Acceleration Positive / Negative: Negative Since new position and speed correction information 158 has been received, the determination in STEP 808 is yes.

[0096] In the next step 809, a complementary pattern is generated. Here, based on the time, position, and speed related to the stop at station B included in the latest position and speed correction information 158 and the time, position, and speed at the timing when the reception condition 154 changed from "good" to "worsened" before that, time series data that complements these is generated.

[0097] 101 In STEP 810, the driving pattern data is updated using the generated complementary pattern. That is, the data within the range indicated by the thick frame 1002 in Fig. 10 is the complementary pattern. Also, in the speed graph shown in Fig. 9, the speed pattern from x3 to x4 (dashed line) corresponds to the complementary pattern.

[0098] In the next step 811, the updated driving pattern data is referenced and the power consumption is estimated for the range in which speed data exists, which corresponds to the range from 9:17:31 to 9:17:42 shown in Fig. 10 (the range enclosed by the bold frame 1005 in Fig. 10).

[0099] While the train is stopped at station B, the reception status 154 continues to be "deteriorating." In FIG. 8, the process proceeds from STEP 801 to STEP 807 to STEP 808. Here, since no new position and speed correction information 158 is received until the train departs, the determination in STEP 808 is "no." The process proceeds to STEP 811, but during this time there is no data, and the corresponding power consumption cannot yet be estimated.

[0100] Subsequently, at the timing when the train departs from position x4, that is, station B, the position and speed correction information 158 is input to the driving assistance content generation unit 109. The position and speed correction information 158 input here is as follows. ·Time: 9:18:10 Vehicle position: x4 Vehicle speed: zero Acceleration Positive / Negative: Positive Since new position and speed correction information 158 has been received, the determination in STEP 808 is yes.

[0101] In the next STEP 809, a complementary pattern is generated. Here, based on the time, position, and speed of the train departing from station B included in the latest position and speed correction information 158 and the time, position, and speed of the train stopping at station B, whose position and speed are most recently known, time series data is generated to complement these. That is, the complementary pattern in this case is data in which the position remains at station B and the speed is zero.

[0102] Next, in STEP 810, the travel pattern data is updated using the generated complementary pattern. The data from 9:17:43 to 9:18:10 shown in FIG. 10 is the complementary pattern. In the following STEP 811, the updated travel pattern data is referenced, and the power consumption is estimated for the range in which the speed data exists. Here, since the train is stopped, the estimated power consumption is zero.

[0103] When the train departs from station B and travels to position x5, the reception condition 154 changes from "deteriorating" to "good." The subsequent processing is the same as the processing when the train travels to x2 described above. In the flowchart shown in FIG. 8, processing is performed in the order of STEP 801 → STEP 802 → STEP 803 → STEP 804 → STEP 805 → STEP 806 → STEP 811.

[0104] That is, using position / speed correction information 158 related to departure from station B, a supplementary pattern for the range enclosed by the thick frame 1003 in FIG. 10 is generated in STEP 805, and the travel pattern data is updated in STEP 806. In the speed graph shown in FIG. 9, the speed pattern from x4 to x5 (dashed line) corresponds to the supplementary pattern. Furthermore, for the section where the speed data has been supplemented, power consumption is estimated and reflected in the travel pattern data in STEP 811 (the range enclosed by the thick frame 1006 in FIG. 10). [Example]

[0105] Example 2 is a driving assistance device that detects obstacles on a track on which a vehicle is traveling and notifies the driver of the detection result. Here, obstacle detection is an important function for maintaining safe and secure operation in a situation where driver licenses are becoming unnecessary due to the advancement of automated driving.

[0106] The driving assistance device has a means for detecting obstacles, and this obstacle detection means is provided with multiple obstacle detection logics, and switches between the obstacle detection logics based on the vehicle position and vehicle speed estimated using GPS.

[0107] In the driving assistance device of Example 2, similarly to Example 1, in sections where the GPS reception is poor, the vehicle position and vehicle speed are estimated based on sound data inside and outside the vehicle collected by a sound collection unit provided in the driving assistance device. This makes it possible to supplement information on the vehicle position and vehicle speed in sections where the vehicle position and vehicle speed cannot be estimated using GPS in the obstacle detection logic switching process. This makes it possible to use the driving assistance device even in sections where the GPS reception is poor, leading to an improvement in the obstacle detection capability of the vehicle.

[0108] FIG. 12 is a diagram illustrating a functional configuration of a driving assistance device according to a second embodiment of the present invention and an overview of each function. The driving assistance device is composed of a GPS receiving unit 101, an on-track position estimation unit 102, a vehicle speed estimation unit 103, an operation unit 104, a route information management unit 105, a position and speed correction information generation unit 106, a sound collection unit 107, a characteristic sound detection unit 108, an obstacle detection logic unit 1209, a detection result transmission unit 1210, and an obstacle detection sensor unit 1211.

[0109] The components from the GPS receiving unit 101 to the characteristic sound detecting unit 108 of the driving assistance device according to the second embodiment are the same as those of the first embodiment shown in FIG. The following describes the obstacle detection logic unit 1209, the detection result transmission unit 1210, and the obstacle detection sensor unit 1211, which are components specific to the second embodiment.

[0110] The obstacle detection sensor unit 1211 uses a camera, laser radar, millimeter wave sensor, or the like as a sensor to constantly sense the track ahead of the vehicle and transmits the sensing result 1262 to the obstacle detection logic unit 1209. The obstacle detection sensor unit 1211 is assumed to be a device that is externally connected to a mobile terminal in which a driving assistance device is implemented, but this does not necessarily apply if a built-in function of the mobile terminal, such as a camera function, can be used.

[0111] The obstacle detection logic unit 1209 receives the on-track position 152 from the on-track position estimation unit 102, the estimated speed 153 from the vehicle speed estimation unit 103, the reception state 154 from the GPS reception unit 101, the position and speed correction information 158 from the position and speed correction information generation unit 106, and the sensing result 1262 from the obstacle detection sensor unit, and transmits the obstacle detection result 1261 to the detection result transmission unit 1210. The obstacle detection result 1261 is, for example, binary data indicating the presence or absence of an obstacle. Alternatively, the result may include a graded warning according to the degree of danger depending on the type of obstacle detected or the certainty of the detection result.

[0112] The obstacle detection logic unit 1209 determines whether an obstacle has been detected on the track ahead of the vehicle equipped with the driving assistance device based on the sensing result 1262. In this case, it has multiple detection logics for determining whether an obstacle has been detected, and switches between the multiple detection logics depending on the position and speed. Here, with regard to the position and speed used to switch the detection logic, if the reception condition 154 is "good", the on-track position 152 and estimated speed 153 are used, and if the reception condition 154 is "deteriorating", the position and speed information included in the position and speed correction information 158 is used.

[0113] One reason for the need to switch between multiple detection logics depending on the location is that, for example, the types of obstacles on the track that could potentially come into contact with a rail vehicle and cause an accident may vary depending on the location on the line. Specifically, within a station, this could be a person falling from the platform; at a railroad crossing, this could be an entering car, bicycle, or person; and near a residence, this could be a futon, etc. When the computational resources available for detection are limited, it is desirable from the perspective of obstacle detection accuracy to perform obstacle detection by preferentially using detection logic specialized for obstacles that are likely to occur depending on the location.

[0114] Furthermore, since the location where obstacle detection is prioritized may differ depending on the vehicle speed, it is expected that multiple detection logics will need to be switched depending on the vehicle speed. The maximum braking distance that a railway vehicle can brake when an obstacle is detected varies depending on the vehicle speed. The higher the vehicle speed, the longer it takes to stop, and therefore the longer the distance it will travel during that time. Therefore, the higher the vehicle speed, the more priority it needs to be given to detecting obstacles farther away from the vehicle. On the other hand, when the vehicle speed is low, or in the extreme case when the vehicle is stopped, the more priority it needs to be given to detecting obstacles closer to the vehicle. In this way, it is desirable from the perspective of obstacle detection accuracy to selectively use long-distance and short-distance detection logic depending on the speed.

[0115] The detection result transmission unit 1210 receives the obstacle detection result 1261 from the obstacle detection logic unit 1209 and transmits the detection result to the driver. Examples of means for transmitting the detection result to the driver include a display on the screen of a mobile terminal implemented in the driving assistance device and sound output from a sound output unit of the mobile terminal.

[0116] Furthermore, the detection result transmission unit 1210 may transmit the detection result received from the obstacle detection result 1261 to a braking / driving system of the railway vehicle (not shown). That is, the detection result transmission unit 1210 transmits the detection result to at least one of the crew and the braking / driving system. When the braking / driving system receives data indicating the presence of an obstacle as the obstacle detection result, it takes safety measures such as applying the necessary brakes, such as an emergency stop.

[0117] Furthermore, the obstacle detection logic unit 1209, the detection result transmission unit 1210, and the obstacle detection sensor unit 1211 of the second embodiment may be provided in a form in which they are installed together with the driving assistance content generation unit 109 and the driving assistance content transmission unit 110 of the first embodiment. This allows the driving assistance function of the second embodiment to be added to the driving assistance function of the first embodiment.

[0118] Although Examples 1 and 2 have been described above as embodiments of the present invention, the present invention is not limited to the above-described Examples, and various modifications are possible within the scope of the gist of the present invention. [Explanation of symbols]

[0119] 101 GPS receiver, 102 on-track position estimation unit, 103 vehicle speed estimation unit, 104 operation unit, 105 route information management unit, 106 position and speed correction information generation unit, 107 sound collection unit, 108 characteristic sound detection unit, 109 driving assistance content generation unit, 110 Operation support content transmission unit, 151 Latitude and longitude, 152 On-orbit position, 153 Estimated speed, 154 Reception status, 155 Track shape, 156 Route information, 157 Running station interval, 158 Position speed correction information, 159 Vehicle sound data, 160 Feature sound detection results, 161 Driving assistance content, 1001~1003: Data updated by complementary patterns in driving pattern data, 1004~1006 Power consumption estimation part based on updated data in driving pattern data, 1209 obstacle detection logic unit, 1210 detection result transmission unit, 1211 obstacle detection sensor unit, 1261 obstacle detection result, 1262 sensing result

Claims

1. A driving assistance device that provides driving assistance based on a vehicle position and a vehicle speed of a vehicle traveling on a track, a sound collection unit that collects sounds inside and outside the vehicle, including at least sounds generated from equipment mounted on the vehicle, as vehicle sound data, the sound collection unit being provided in a leading car of the vehicle; The vehicle position and the vehicle speed are estimated based on an appearance order of a plurality of characteristic sounds included in the vehicle sound data collected by the sound collection unit, The plurality of characteristic sounds are at least two of the following sounds: a sliding sound between the wheels and brake shoes when the air brakes of the vehicle are in use; an operating sound of the master controller handle of the vehicle; a warning sound for passengers when the doors of the vehicle are opened or closed; a door operation sound when the doors of the vehicle are opened or closed; a departure melody sound in the premises of the station where the vehicle stops; a sound that notifies confirmation that the doors of the vehicle are closed; and a sound of compressed air being discharged when the air brakes of the vehicle are released. A driving assistance device characterized by:

2. The driving assistance device according to claim 1, a GPS receiving unit for receiving GPS information; The vehicle position and the vehicle speed are calculated by In a period when the reception state of the GPS information is good, the estimation is made based on the GPS information received by the GPS receiving unit, and in a period when the reception state of the GPS information is poor, the estimation is made based on the appearance order of the plurality of characteristic sounds. A driving assistance device characterized by:

3. The driving assistance device according to claim 2, In the section where the reception state of the GPS information is poor, at least one of stopping and departing of the vehicle is estimated based on the order of appearance of the plurality of characteristic sounds. A driving assistance device characterized by:

4. The driving assistance device according to claim 3, The stop station is included in the section where the reception state of the GPS information is poor. A driving assistance device characterized by:

5. A driving assistance device according to any one of claims 1 to 4, The plurality of characteristic sounds are detected by pattern matching between the frequency analysis result of the vehicle sound data and the frequency analysis result of each of the plurality of characteristic sounds that is prepared in advance as a database. A driving assistance device characterized by:

6. A driving assistance device according to any one of claims 1 to 5, As the driving assistance, the history of the vehicle speed is visualized. A driving assistance device characterized by:

7. A driving assistance device according to any one of claims 1 to 6, As the driving assistance, an amount of power consumption while the vehicle is traveling is estimated based on the vehicle speed, and a history of the amount of power consumption is visualized. A driving assistance device characterized by:

8. A driving assistance device according to any one of claims 1 to 7, an obstacle detection unit that detects an obstacle on the track; the obstacle detection unit switches between a plurality of detection logics for detecting the obstacle depending on at least one of the vehicle position and the vehicle speed; As the driving assistance, a result of the obstacle detection by the obstacle detection unit is transmitted to at least one of a driver and a braking / driving system of the vehicle. A driving assistance device characterized by:

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