FORM 2
THE PATENTS ACT, 1970
(39 of& 1970) THE PATENTS RULES, 2003 COMPLETE SPECIFICATION
[See section 10, Rule 13] OBSTACLE DETECTION DEVICE AND OBSTACLE DETECTION METHOD;
MITSUBISHI ELECTRIC CORPORATION, A CORPORATION ORGANISED
AND EXISTING UNDER THE LAWS OF JAPAN, WHOSE ADDRESS IS 7-3,
MARUNOUCHI 2-CHOME, CHIYODA-KU, TOKYO 1008310, JAPAN
THE FOLLOWING SPECIFICATION PARTICULARLY DESCRIBES THE
INVENTION AND THE MANNER IN WHICH IT IS TO BE PERFORMED.
2
DESCRIPTION
Field
[0001] The present invention relates to an obstacle
5 detection device and an obstacle detection method for
detecting an obstacle on a route of a train.
Background
[0002] Patent Literature 1 discloses that a vehicle
10 traveling along a laid groove-shaped track includes an
obstacle detection means such as a stereo optical system
and a laser radar transmission and reception device, and
detects an obstacle in a surrounding using the obstacle
detection means. The vehicle described in Patent
15 Literature 1 is a so-called automobile that travels on a
general road surface with its own tires.
Citation List
Patent Literature
20 [0003] Patent Literature 1: Japanese Patent Application
Laid-open No. 2001-310733
Summary
Technical Problem
25 [0004] By installing the obstacle detection means
described in Patent Literature 1 in a train, the train can
detect an obstacle on the route. However, a train
traveling on rails with wheels has a longer braking
distance than an automobile traveling on a general road
30 surface with tires. When the obstacle detection means
described in Patent Literature 1 is installed in a train, a
range to be monitored must be extended farther at a longer
distance than when the means is installed in an automobile,
3
according to the longer braking distance. For this reason,
there has been a problem that the amount of calculation is
larger than when it is installed in an automobile. The
obstacle detection means described in Patent Literature 1
5 can reduce the amount of calculation by lowering the
resolution of an image. However, lowering the resolution
of an image causes a deterioration in obstacle detection
accuracy, which has also been problematic.
[0005] The present invention has been made in view of
10 the above circumstances, and an object thereof is to
provide an obstacle detection device capable of detecting
an obstacle without deteriorating the accuracy while
reducing the amount of calculation.
15 Solution to Problem
[0006] In order to solve the above-mentioned problems
and achieve the object, the present invention provides an
obstacle detection device installed in a train, the
obstacle detection device comprising: a sensor to monitor
20 surroundings of the train and generate a range image that
is a result of monitoring; a storage unit to store map
information including position information of structures
installed along a railroad track on which the train
travels; a correction unit to correct, using the range
25 image acquired from the sensor and the map information
stored in the storage unit, first train position
information that is information acquired from a train
control device and indicates a position of the train, and
to output second train position information that is a
30 result of correction; and a monitoring condition
determination unit to determine a monitoring range of the
sensor using the second train position information and the
map information.
4
Advantageous Effects of Invention
[0007] According to the present invention, the obstacle
detection device can achieve the effect of detecting an
5 obstacle without deteriorating the accuracy while reducing
the amount of calculation.
Brief Description of Drawings
[0008]
10 FIG. 1 is a diagram illustrating an exemplary
configuration of an obstacle detection device according to
a first embodiment.
FIG. 2 is a flowchart illustrating an obstacle
detection process of the obstacle detection device
15 according to the first embodiment.
FIG. 3 is a flowchart illustrating a process in which
a correction unit according to the first embodiment
corrects the position of a train.
FIG. 4 is a diagram illustrating an example of the
20 monitoring range of the obstacle detection device according
to the first embodiment.
FIG. 5 is a diagram illustrating an example of
identifying the positional relationship between a train and
a track-side structure in the obstacle detection device
25 according to the first embodiment.
FIG. 6 is a diagram illustrating an example in a case
where the processing circuitry owned by the obstacle
detection device according to the first embodiment is
configured with a processor and a memory.
30 FIG. 7 is a diagram illustrating an example in a case
where the processing circuitry owned by the obstacle
detection device according to the first embodiment is
configured with dedicated hardware.
5
FIG. 8 is a flowchart illustrating a process in which
a correction unit according to the second embodiment
corrects the position of a train.
5 Description of Embodiments
[0009] Hereinafter, an obstacle detection device and an
obstacle detection method according to embodiments of the
present invention will be described in detail with
reference to the drawings. The present invention is not
10 necessarily limited by these embodiments.
[0010] First Embodiment.
FIG. 1 is a block diagram illustrating an exemplary
configuration of an obstacle detection device 20 according
to the first embodiment of the present invention. The
15 obstacle detection device 20 is a device that is installed
in a train 100 and detects an obstacle located in a
traveling direction of the train 100. The obstacle
detection device 20 is connected to a train control device
10 and an output device 30. The train control device 10
20 and the output device 30 are also devices installed in the
train 100. The obstacle detection device 20 includes a
sensor 21, a storage unit 22, a correction unit 23, a
monitoring condition determination unit 24, and an obstacle
determination unit 25.
25 [0011] The sensor 21 detects an object around the train
100. Objects include structures such as traffic signals,
masts for overhead contact lines, railroad crossings,
stations, bridges, and tunnels, which have been installed
by the railroad company. Among them, traffic signals,
30 masts for overhead contact lines, and railroad crossings
are track-side structures that are each installed alongside
a railroad track. Objects also include an obstacle that
hinders the operation of the train 100. An obstacle is,
6
for example, an automobile that has entered a railroad
track area while a railroad crossing gate is closed, a
rockfall from a cliff, a passenger who has fallen from a
station platform, a wheelchair in an area of the railroad
5 crossing, or the like. The sensor 21 is an instrument
capable of detecting these structures and obstacles, for
example, a stereo camera including two or more cameras, a
Light Detection And Ranging (LIDAR) device, a Radio
Detection And Ranging (RADAR) device, and the like. The
10 sensor 21 may have a configuration with two or more
instruments. In the present embodiment, the sensor 21
includes a stereo camera and a LIDAR device. In the sensor
21, the stereo camera and the LIDAR device detect the
surroundings of the train 100, generate a range image from
15 the resultant data, and output the generated range image to
the correction unit 23 and the obstacle determination unit
25. A range image is a monitoring result obtained by
monitoring the surroundings of the train 100 by the sensor
21, and includes one or both of a two-dimensional image and
20 a three-dimensional image including range information. The
sensor 21 is installed in the leading car of the train 100.
In a case where the train 100 is composed of a plurality of
cars, the leading car is changed depending on the traveling
direction, and so the sensors 21 are installed in the cars
25 at both ends. For example, in a case where the train 100
is a 10-car train composed of cars No. 1 to No. 10, the car
No. 1 or the car No. 10 serves as a leading car depending
on the traveling direction. In this case, the sensors 21
are installed in the car No. 1 and the car No. 10 of the
30 train 100. The obstacle detection device 20 uses the
sensor 21 installed in the leading car in the traveling
direction of the train 100.
[0012] The storage unit 22 stores map information
7
including position information of railroad tracks on which
the train 100 travels and position information of
structures installed by the railroad company. Position
information of railroad tracks and structures can be
5 expressed as a distance in kilometers from a position used
as a point of origin, expressed in latitude and longitude,
expressed by coordinates using three-dimensionally measured
point groups, or expressed in other appropriate method, or
it may also be expressed using any combination of these
10 methods. In a case where position information of railroad
tracks and structures is expressed by three-dimensional
coordinate values, for example, map information can be
created using a mobile mapping system (MMS) or the like.
Structures measured three-dimensionally using the MMS can
15 be expressed by the coordinates of points that constitute
each structure, but the coordinates of one of the points
that constitute each structure may be used as a
representative value. One point Pi that constitutes a
three-dimensionally measured structure can be expressed as
20 a three-dimensional coordinate value Pi (xi, yi, zi) with
use of the coordinate values of three axes in the x-axis
direction, the y-axis direction, and the z-axis direction.
The storage unit 22 stores, for example, data on the
coordinate values of three axes in the x-axis direction,
25 the y-axis direction, and the z-axis direction as a
representative value of each structure. In addition, the
storage unit 22 stores, for example, data on the coordinate
values of three axes in the x-axis direction, the y-axis
direction, and the z-axis direction for a position of each
30 interval defined on the railroad track expressed as a
distance in kilometers. With regard to the x-axis
direction, the y-axis direction, and the z-axis direction,
for example, use can be made of a plane orthogonal
8
coordinate system in which the x and y axes can be
represented on the horizontal plane and the z-axis can be
represented in a height direction with respect thereto.
Alternatively, for example, another coordinate system may
5 be used in which an arbitrary point is set as the origin,
and the eastward, northward, and vertically upward
directions are set as the x-axis direction, the y-axis
direction, and the z-axis direction, respectively with use
of the point of origin of a distance in kilometers as the
10 origin. For units of data indicating the coordinate values
of each point, meters (m) or the like can be used, but the
present invention is not limited thereto. The storage unit
22 can hold the position coordinates of the railroad track
expressed by three-dimensional coordinate values by holding
15 the three-dimensional coordinate value for each distance in
kilometers on the railroad track, for example, for every
one-meter point. In the present embodiment, the storage
unit 22 stores position information of railroad tracks and
structures in the form of combination of a distance in
20 kilometers and three-dimensional coordinate values. The
storage unit 22 may store the map information during a
process in which the train 100 travels and/or store the map
information that has been measured in advance.
[0013] The correction unit 23 acquires, from the train
25 control device 10, train position information indicating
the position of the train 100, as described later. The
correction unit 23 corrects the train position information
of the train 100 acquired from the train control device 10
using the range image acquired from the sensor 21 and the
30 map information stored in the storage unit 22. The
correction unit 23 outputs the corrected train position
information of the train 100 to the monitoring condition
determination unit 24. Note that the train position
9
information of the train 100 that the correction unit 23
acquires from the train control device 10 is referred to as
first train position information, and the train position
information of the train 100 that is a correction result
5 obtained by the correction unit 23 is referred to as second
train position information.
[0014] The monitoring condition determination unit 24
determines the monitoring range of the sensor 21 with
respect to the traveling direction of the train 100 using
10 the second train position information acquired from the
correction unit 23 and the map information stored in the
storage unit 22. The monitoring condition in the first
embodiment is the monitoring range of the sensor 21.
[0015] The obstacle determination unit 25 determines the
15 presence or absence of an obstacle in the traveling
direction of the train 100 based on the range image
acquired from the sensor 21. When the obstacle
determination unit 25 determines that an obstacle is
included in the range image, the obstacle determination
20 unit 25 generates obstacle detection information that is
information indicating that an obstacle has been detected,
and outputs the generated obstacle detection information to
the output device 30. The obstacle detection information
may be information merely indicating only the fact that an
25 obstacle has been detected, or may include information on
the position where the obstacle has been detected.
[0016] The train control device 10 detects the position
of the train 100 using a beacon installed on the ground, a
transponder (not illustrated), a speed generator, and the
30 like mounted on the train 100. The train control device 10
outputs the detected position of the train 100 to the
correction unit 23 as first train position information.
The method of detecting the position of the train 100 in
10
the train control device 10 is commonly used as in the
conventional art. Although the train control device 10
detects the position of the train 100 based on the moving
distance on the railroad track from an absolute position
5 indicated by a beacon, the first train position information
may contain an error due to the effect of some error in
calculating the moving distance, slip and skid caused by
wheels (not illustrated) of the train 100, or the like.
[0017] In response to acquiring obstacle detection
10 information from the obstacle determination unit 25, the
output device 30 outputs information indicating that an
obstacle has been detected to a motorman of the train 100
or the like. The output device 30 may display that an
obstacle has been detected to the motorman of the train 100
15 or the like via a monitor or the like, or may output a
sound indicating that an obstacle has been detected via a
loudspeaker or the like.
[0018] Next, an operation of the obstacle detection
device 20 detecting an obstacle will be described. FIG. 2
20 is a flowchart illustrating an obstacle detection process
of the obstacle detection device 20 according to the first
embodiment. In the obstacle detection device 20, in order
to detect an object around the train 100, the sensor 21
detects the surroundings of the train 100 in the traveling
25 direction of the train 100, and generates a range image
(step S1). On an initial stage, any monitoring range of
the sensor 21 is not determined by the monitoring condition
determination unit 24, and therefore the sensor 21 performs
detection in a range of −90° to +90° in the horizontal
30 direction with the traveling direction of the train 100
being 0°, or in the maximum range within which monitoring
can be realized, and generates a range image. The sensor
21 outputs the generated range image to the correction unit
11
23. Note that the monitoring range of the sensor 21 is set
to extend in the horizontal direction in one example, but
may be set to extend in the vertical direction or extend in
both the horizontal direction and the vertical direction.
5 [0019] The correction unit 23 acquires the first train
position information of the train 100 from the train
control device 10 (step S2). The correction unit 23
searches the map information stored in the storage unit 22
based on the first train position information acquired from
10 the train control device 10, and extracts the map
information in the monitoring range of the sensor 21, that
is, a range included in the range image (step S3). The
correction unit 23 may extract the map information in a
specified range centered on a position indicated by the
15 first train position information, or may acquire
information on the traveling direction of the train 100
from the train control device 10 and extract the map
information in a specified range on the traveling direction
side of the train 100, specifically, the above-mentioned
20 range of −90° to +90°. The correction unit 23 compares the
range image with the extracted map information, and
identifies the position of a structure included in the
range image. Specifically, the correction unit 23
determines which of the structures in the extracted map
25 information an object included in the range image
corresponds to, and selects a position in the map
information of a structure in the map information having
been determined to correspond to the object, thereby to
identify the position of the structure. The correction
30 unit 23 corrects the position of the train 100 based on the
identified position of the structure. The structure may be,
for example, a track-side structure whose accurate position
is possibly known by the railroad company. The correction
12
unit 23 generates second train position information
obtained by correcting the position of the train 100
indicated by the first train position information, and
outputs the second train position information to the
5 monitoring condition determination unit 24 (step S4).
[0020] Here, the process of step S4, that is, the
process of correcting the position of the train 100 in the
correction unit 23 will be described in detail. FIG. 3 is
a flowchart illustrating a process in which the correction
10 unit 23 according to the first embodiment corrects the
position of the train 100. FIG. 4 is a diagram
illustrating an example of the monitoring range of the
obstacle detection device 20 according to the first
embodiment. FIG. 5 is a diagram illustrating an example of
15 identifying the positional relationship between the train
100 and a track-side structure in the obstacle detection
device 20 according to the first embodiment. FIG. 4 shows
that, in the traveling direction of the train 100 equipped
with the obstacle detection device 20, a traffic signal 300,
20 a railroad crossing 400, and a station 500 are installed
alongside a railroad track 200, and a tunnel 600 is built
beyond the station 500. A monitoring range 700 represents
the monitoring range of the sensor 21, and an obstacle 800
is an obstacle such as a rockfall present on the railroad
25 track 200. In FIG. 4, the traveling direction of the train
100 is a direction indicated by an arrow 900.
[0021] The correction unit 23 detects a structure from
the range image acquired from the sensor 21 (step S11).
Using the range image acquired from the sensor 21, the
30 correction unit 23 can recognize that a structure exists at
a certain position even though the type of a structure
cannot be identified. In a case where the sensor 21 is a
stereo camera and a LIDAR device as described above, the
13
correction unit 23 can recognize that a structure is
included in the range image obtained by the sensor 21 using
a conventional general method. In a case where track-side
structures are targeted as structures, the sensor 21 can
5 easily detect a track-side structure because the track-side
structure is a traffic signal, a mast for overhead contact
lines, a railroad crossing, or the like. Therefore, it is
assumed that the range image includes some track-side
structure. When the correction unit 23 detects a plurality
10 of structures from the range image acquired from the sensor
21, the correction unit 23 selects as a target the
structure closest to the train 100, for example, from among
the structures detected from the range image, and
identifies the position of the selected structure.
15 [0022] The correction unit 23 uses the range image
acquired from the sensor 21 to identify the positional
relationship between the train 100 and the successfully
detected structure (step S12). The positional relationship
means a relative position between the train 100 and the
20 successfully detected structure. Specifically, the
correction unit 23 obtains a distance r and an angle θ in
the horizontal direction with respect to the traveling
direction from the train 100 to the structure. The
correction unit 23 can compute the distance r and the angle
25 θ from the train 100 to the structure using the range image
in a conventional general method. The correction unit 23
searches the map information based on the relative position
of the structure whose positional relationship has been
identified, and extracts information on the structure
30 located around the relative position from the map
information (step S13). For example, based on the first
train position information and the position information of
the railroad track included in the map information, the
14
correction unit 23 converts the position of the train 100
that is based on the first train position information into
a three-dimensional coordinate value, and extracts, from
the map information, a three-dimensional coordinate value
5 of a point located around the position at the distance r
and the angle θ based on the three-dimensional coordinate
value of the position of the train 100.
[0023] The correction unit 23 identifies the position of
the structure whose positional relationship has been
10 identified from the range image by using the position of
the structure indicated by the extracted map information
(step S14). For example, the correction unit 23 identifies
the position of the structure whose positional relationship
has been identified from the range image by using the
15 three-dimensional coordinate value of the structure
extracted from the map information. In the example of FIG.
4, the traffic signal 300 and the railroad crossing 400
that are track-side structures are provided as structures,
and the correction unit 23 identifies the positional
20 relationship of the traffic signal 300 that is closest to
the train 100. The accurate position of the traffic signal
300 is recorded in the map information by using a threedimensional
coordinate value. The correction unit 23
identifies the position of a structure whose positional
25 relationship has been identified from the range image, that
is, the position of the traffic signal 300 in the example
of FIG. 4, using the position of the traffic signal 300
indicated by the map information, that is, the threedimensional
coordinate value thereof.
30 [0024] The correction unit 23 identifies the position of
the train 100 based on the identified position of the
traffic signal 300, and corrects the position of the train
100 (step S15). Because the correction unit 23 knows the
15
positional relationship between the train 100 and the
traffic signal 300 from the distance r and the angle θ, the
correction unit 23 fixes the position of the traffic signal
300 at the three-dimensional coordinate value, and corrects
5 the position of the train 100 using the distance r and the
angle θ. That is, the correction unit 23 corrects the
first train position information. In the example of FIG. 4,
a straight line in the opposite direction of the traveling
direction of the train 100 is drawn leftward from the
10 traffic signal 300. The corrected train 100 is located at
the position of the angle θ and the distance r from the
traffic signal 300 with respect to this straight line.
[0025] The correction unit 23 sets the corrected
position of the train 100 as second train position
15 information, and outputs the second train position
information to the monitoring condition determination unit
24 (step S16).
[0026] Let us now return to the explanation of the
flowchart in FIG. 2. The monitoring condition
20 determination unit 24 determines the monitoring condition
of the sensor 21 with respect to the traveling direction of
the train 100, that is, the monitoring range 700, using the
second train position information acquired from the
correction unit 23 and the map information stored in the
25 storage unit 22 (step S5). Because the monitoring
condition determination unit 24 can grasp the shape of the
railroad track 200 from the position information of the
railroad track 200 included in the map information, the
monitoring condition determination unit 24 determines the
30 monitoring range 700 of the sensor 21 such that the
railroad track 200 in the traveling direction of the train
100 is covered by the range 700. The shape includes the
curvature and gradient of the railroad track, the width of
16
the track, and the like. By determining or limiting the
monitoring range 700 of the sensor 21 as illustrated in FIG.
4, the monitoring condition determination unit 24 can
reduce the amount of calculation for the sensor 21 as
5 compared to the case of step S1. Further, by limiting the
monitoring range 700 of the sensor 21, the monitoring
condition determination unit 24 can reduce the amount of
calculation for the obstacle determination unit 25 as
compared to the case of using the range image obtained in
10 step S1.
[0027] Here, let us consider the case in which the
monitoring condition determination unit 24 determines the
monitoring range 700 of the sensor 21 using the first train
position information. When the monitoring condition
15 determination unit 24 determines the monitoring range 700
of the sensor 21 with respect to the traveling direction of
the train 100 using the first train position information
including some error and the map information, the
monitoring condition determination unit 24 must determine
20 the monitoring range 700 of the sensor 21 in consideration
of the positional error of the train 100. Therefore, the
monitoring condition determination unit 24 needs to set a
larger monitoring range 700 than when using the second
train position information. This is because when the
25 sensor 21 performs long-range monitoring, a slight error in
the position of the train 100 leads to a large difference
in distance in a faraway place. Especially in a place
where the train 100 is approaching a curve or a slope,
there is a large difference in distance. In the present
30 embodiment, by using the second train position information
in which the position of the train 100 has been corrected,
the monitoring condition determination unit 24 can make a
monitoring range 700 of the sensor 21 smaller and reduce
17
the amount of calculation for the sensor 21 and the
obstacle determination unit 25 as compared to the case of
using the first train position information.
[0028] The monitoring condition determination unit 24
5 outputs the determined monitoring condition, that is,
information on the monitoring range 700, to the sensor 21.
The information on the monitoring range 700 may be, for
example, information on the direction and range in which
the sensor 21 performs detection, or may be information
10 indicating, by an angle, the range in which the sensor 21
performs detection.
[0029] The sensor 21 performs detection based on the
monitoring condition acquired from the monitoring condition
determination unit 24, that is, the monitoring range 700,
15 and generates a range image (step S6). The sensor 21
outputs the generated range image to the correction unit 23
and the obstacle determination unit 25. The sensor 21 may
detect a wide area covering the monitoring range 700 and
use only the detection result included in the monitoring
20 range 700.
[0030] The obstacle determination unit 25 determines
whether or not there is an obstacle, that is, whether or
not any obstacle is included in the range image acquired
from the sensor 21 (step S7). The obstacle determination
25 unit 25 can determine whether or not any obstacle is
included in the range image using the range image acquired
from the sensor 21 with a method similar to that in the
correction unit 23 described above. If there is an
obstacle, that is, if the range image includes an obstacle
30 (step S7: Yes), the obstacle determination unit 25 outputs,
to the output device 30, obstacle detection information
indicating that an obstacle has been detected (step S8).
In response to acquiring the obstacle detection information
18
from the obstacle determination unit 25, the output device
30 outputs, to the motorman or the like, information
indicating that an obstacle has been detected in the
traveling direction of the train 100.
5 [0031] If there is no obstacle, that is, the range image
does not include any obstacle (step S7: No), or after the
process of step S8, the obstacle detection device 20
returns to step S2 to repeatedly perform the abovementioned
process. Specifically, the correction unit 23
10 performs a process of steps S2 to S4 every time a range
image generated by the sensor 21 in step S6 is acquired.
In step S3, the correction unit 23 may acquire information
on the monitoring range 700 from the monitoring condition
determination unit 24 and extract the map information
15 within the monitoring range 700. The monitoring condition
determination unit 24 performs the process of step S5 every
time the second train position information is acquired.
[0032] Note that the above-mentioned method of
determining whether or not the range image includes an
20 obstacle in the obstacle determination unit 25 is one
example, and another method may be used. For example, in a
case where the train repeatedly travels on the same route,
the obstacle determination unit 25 holds, as a past range
image, a range image for the last travel or a range image
25 when no obstacle has been detected. The obstacle
determination unit 25 compares the latest range image and
the held range image at one and the same train position,
and if there is some difference, that is, when an object
that is not included in the held range image is detected in
30 the latest range image, the obstacle determination unit 25
determines that the latest distance image includes an
obstacle.
[0033] Further, when there is an obstacle, the obstacle
19
determination unit 25 may output obstacle detection
information to the output device 30 and output a brake
instruction for stopping or decelerating the train 100 to
the train control device 10. When acquiring the brake
5 instruction from the obstacle determination unit 25, the
train control device 10 performs control to stop or
decelerate the train 100.
[0034] Next, the hardware configuration of the obstacle
detection device 20 will be described. In the obstacle
10 detection device 20, the sensor 21 is a stereo camera and a
LIDAR device as described above. The storage unit 22 is a
memory. The correction unit 23, the monitoring condition
determination unit 24, and the obstacle determination unit
25 are implemented by processing circuitry. That is, the
15 obstacle detection device 20 includes a processing circuit
that can correct the position of the train 100 and detect
an obstacle. The processing circuit may be a memory and a
processor that executes a program stored in the memory, or
may be of dedicated hardware.
20 [0035] FIG. 6 is a diagram illustrating an example of a
case where the processing circuitry of the obstacle
detection device 20 according to the first embodiment is
configured with a processor and a memory. In a case where
the processing circuitry is configured with the processor
25 91 and the memory 92, each function of the processing
circuitry of the obstacle detection device 20 is
implemented by software, firmware, or a combination of
software and firmware. Software or firmware is described
as a program and stored in the memory 92. In the
30 processing circuitry, the processor 91 reads and executes
the program stored in the memory 92, thereby implementing
each function. That is, the processing circuitry includes
the memory 92 for storing programs that can result in the
20
correction of the position of the train 100 and the
detection of an obstacle being realized. It can also be
said that these programs correspond to a means to cause a
computer to execute the procedures and methods for the
5 obstacle detection device 20.
[0036] The processor 91 may be a central processing unit
(CPU), a processing device, an arithmetic device, a
microprocessor, a microcomputer, or a digital signal
processor (DSP). The memory 92 corresponds to a non10
volatile or volatile semiconductor memory, a magnetic disk,
a flexible disk, an optical disc, a compact disc, a mini
disc, a digital versatile disc (DVD), or the like.
Examples of the non-volatile or volatile semiconductor
memory include a random access memory (RAM), a read only
15 memory (ROM), a flash memory, an erasable programmable ROM
(EPROM), an electrically EPROM (EEPROM, registered
trademark), and the like.
[0037] FIG. 7 is a diagram illustrating an example of a
case where the processing circuitry owned by the obstacle
20 detection device 20 according to the first embodiment is
configured with dedicated hardware. In a case where the
processing circuitry is configured with dedicated hardware,
the processing circuitry 93 illustrated in FIG. 7
corresponds, for example, to a single circuit, a composite
25 circuit, a programmed processor, a parallel programmed
processor, an application specific integrated circuit
(ASIC), a field programmable gate array (FPGA), or any
combination thereof. The functions of the obstacle
detection device 20 may be implemented by the processing
30 circuitry 93 separately for each function or collectively
in whole.
[0038] Note that a part of each function of the obstacle
detection device 20 may be implemented by dedicated
21
hardware, and the other part thereof may be implemented by
software or firmware. In this manner, the processing
circuitry can implement the above-described functions using
dedicated hardware, software, firmware, or any combination
5 thereof.
[0039] As described above, according to the present
embodiment, in the obstacle detection device 20, the
correction unit 23 corrects the position of the train 100
detected by the train control device 10, and the monitoring
10 condition determination unit 24 determines the monitoring
range 700 of the sensor 21 based on the corrected position
of the train 100. As a result, the obstacle detection
device 20 can limit the monitoring range 700 by accurately
identifying the position of the train 100, and thus can
15 detect the obstacle 800 without deteriorating the accuracy
while minimizing the amount of calculation.
[0040] Second Embodiment.
Although the obstacle detection device 20 corrects the
position of the train 100 in the first embodiment, the
20 corrected position of the train 100 may not be on the
railroad track 200 due to some factor such as the accuracy
of the sensor 21. In the second embodiment, the obstacle
detection device 20 corrects the position of the train 100
in two steps. The difference from the first embodiment
25 will be described.
[0041] The configuration of the obstacle detection
device 20 in the second embodiment is similar to the
configuration of the obstacle detection device 20 of the
first embodiment illustrated in FIG. 1. The obstacle
30 detection process of the obstacle detection device 20 is
also similar to the process of the flowchart of the first
embodiment illustrated in FIG. 2. The second embodiment is
different from the first embodiment in content of the
22
process of step S4 of the flowchart illustrated in FIG. 2,
that is, the process of correcting the position of the
train 100 in the correction unit 23. FIG. 8 is a flowchart
illustrating a process in which the correction unit 23
5 according to the second embodiment corrects the position of
the train 100. The flowchart illustrated in FIG. 8 is
obtained by adding the process of steps S21 and S22 to the
flowchart of the first embodiment illustrated in FIG. 3.
[0042] After the process of step S15, the correction
10 unit 23 determines whether or not the result of correction,
that is, the corrected position of the train 100 is on the
railroad track 200, based on the position information of
the railroad track 200 included in the map information of
the storage unit 22 (step S21). If the three-dimensional
15 coordinate value of the corrected position of the train 100
is the same as the three-dimensional coordinate value of
any position on the railroad track 200, the correction unit
23 can determine that the corrected position of the train
100 is on the railroad track 200. If the corrected
20 position of the train 100 is not on the railroad track 200
(step S21: No), the correction unit 23 fixes the position
of the traffic signal 300 to maintain the relationship of
the distance r and the angle θ with respect to the traffic
signal 300, and further corrects the position of the train
25 100 by moving the position of the train 100 onto the
railroad track 200 (step S22). For example, the correction
unit 23 moves the position of the train 100 by rotating the
position of the train 100 around the traffic signal 300.
If the corrected position of the train 100 is on the
30 railroad track 200 (step S21: Yes), or after the process of
step S22 is performed, the correction unit 23 sets the
corrected position of the train 100 on the railroad track
200 as second train position information, and outputs the
23
second train position information to the monitoring
condition determination unit 24 (step S16).
[0043] As described above, according to the present
embodiment, in the obstacle detection device 20, the
5 correction unit 23 is configured to correct the position of
the train 100 detected by the train control device 10, and
if the corrected position of the train 100 is not on the
railroad track 200, further correct the position of the
train 100 so that the position is made onto the railroad
10 track 200. As a result, the obstacle detection device 20
can limit the monitoring range 700 by more accurately
identifying the position of the train 100 than in the first
embodiment, and thus can detect the obstacle 800 without
deteriorating the accuracy while minimizing the amount of
15 calculation.
[0044] Third Embodiment.
In the first embodiment, the obstacle detection device
20 limits the monitoring range 700 of the sensor 21 because
the obstacle detection device 20 corrects the position of
20 the train 100 and does not have to consider the positional
error of the train 100. In the second embodiment, the
obstacle detection device 20 adjusts or determines the
monitoring range 700 and the resolution of the sensor 21
based on a structure included in the monitoring range 700.
25 The difference from the first embodiment will be described.
[0045] The configurations of the obstacle detection
device 20 and the train 100 according to the second
embodiment are similar to those of the first embodiment.
Herein assumed is that the traveling direction of the train
30 100 is in the situation illustrated in FIG. 4.
[0046] Near the railroad crossing 400 where people,
automobiles, and the like cross the railroad track 200, the
probability of existence of an object that can obstruct the
24
passage of the train 100 is higher than in a part of the
railroad track 200 without being associated with the
railroad crossing 400, e.g. a part of the railroad track
200 near the traffic signal 300. For this reason, in a
5 specified range covering the railroad crossing 400, the
monitoring condition determination unit 24 determines the
monitoring conditions of the sensor 21 to make the
monitoring range 700 of the sensor 21 wider and make the
resolution of the sensor 21 higher than normal, that is, as
10 compared to a part of the railroad track 200 without being
associated with the railroad crossing 400. The monitoring
conditions in the second embodiment are the monitoring
range 700 of the sensor 21 and the resolution of the sensor
21. A specified range may be set individually depending on
15 the traffic volume of each railroad crossing 400 or the
like, or may be set uniformly for all railroad crossings
400. In a case where a specified range is set for the
railroad crossing 400 or the like in the second embodiment,
the monitoring condition determination unit 24 modifies,
20 according to the specified range, the monitoring range 700
determined in the method of the first embodiment. In
addition, there may be a possibility for a passenger to
fall from a platform near the station 500. For this reason,
in a specified range covering the station 500, the
25 monitoring condition determination unit 24 determines the
monitoring conditions of the sensor 21 such that the
monitoring range 700 of the sensor 21 is made wider and the
resolution of the sensor 21 is made higher than normal,
that is, as compared to a part of the railroad track 200
30 without being associated with the station 500. A specified
range may be set individually depending on the number of
passengers at each station 500 or the like, or may be set
uniformly for all stations 500. The monitoring condition
25
determination unit 24 can increase the resolution of the
sensor 21, for example, by determining the monitoring
condition of the sensor 21 such that the spatial resolution
of the sensor 21 is made shorter than normal or the
5 sampling rate of the sensor 21 is made higher than normal.
“Normal” or a normal time means a situation in which the
sensor 21 performs detection near the traffic signal 300,
for example. The sensor 21 can detect a smaller obstacle
800 with its resolution increasing.
10 [0047] The sensor 21 requires a larger amount of
calculation when performing detection near the railroad
crossing 400 or near the station 500 than when performing
detection in a part of the railroad track 200 without being
associated with the railroad crossing 400 or the station
15 500. However, depending on the settings of the monitoring
range 700 and the resolution of the sensor 21 realized by
the monitoring condition determination unit 24, it can be
expected for the sensor 21 to have a smaller amount of
calculation than in step S1 of the flowchart illustrated in
20 FIG. 2 of the first embodiment. Similarly, the obstacle
determination unit 25 can also be expected to have a
smaller amount of calculation.
[0048] On the other hand, in the tunnel 600 where the
railroad track 200 is enclosed in a closed space, the
25 probability of existence of an object that can obstruct the
passage of the train 100 is lower than in a part of the
railroad track 200 without being associated with the tunnel
600, e.g. a part of the railroad track 200 near the traffic
signal 300. For this reason, in a specified range covering
30 the tunnel 600, the monitoring condition determination unit
24 determines the monitoring conditions of the sensor 21
such that the monitoring range 700 of the sensor 21 is made
narrower and the resolution of the sensor 21 is made lower
26
than at a normal time, that is, as compared to a part of
the railroad track 200 without being associated with the
tunnel 600. A specified range may be set individually for
each tunnel 600, or may be set uniformly for all tunnels
5 600. The monitoring condition determination unit 24 can
make the resolution of the sensor 21 lower, for example, by
determining the monitoring condition of the sensor 21 so as
to make the spatial resolution of the sensor 21 coarser
than normal or make the sampling rate of the sensor 21
10 lower than normal.
[0049] The sensor 21 can have a much smaller amount of
calculation when performing detection in the tunnel 600
than when performing detection in a part of the railroad
track 200 without being associated with the tunnel 600.
15 Similarly, the obstacle determination unit 25 can also have
a much smaller amount of calculation in that case.
[0050] The monitoring condition determination unit 24
may adjust the resolution of the sensor 21 regardless of
the situation for the traveling direction of the train 100.
20 For example, the monitoring condition determination unit 24
may increase the resolution of the sensor 21 when the
monitoring range 700 of the sensor 21 can be made narrower
than a specified first range. The amount of calculation of
the sensor 21 increases as the resolution becomes higher,
25 but if the amount of increase for the amount of calculation
is smaller than the amount of decrease for the amount of
calculation caused by limiting the monitoring range 700,
the resolution of the sensor 21 can be improved while the
amount of calculation of the sensor 21 is reduced, so that
30 a smaller obstacle can be detected. Alternatively, the
monitoring condition determination unit 24 may reduce the
resolution of the sensor 21 when the monitoring range 700
of the sensor 21 becomes wider than a specified second
27
range.
[0051] As described above, according to the present
embodiment, in the obstacle detection device 20, the
monitoring condition determination unit 24 is adapted to
5 adjust the resolution of the sensor 21 according to the
situation for the traveling direction of the train 100. As
a result, the obstacle detection device 20 can increase the
resolution of the sensor 21 or further reduce the amount of
calculation of the sensor 21 according to the situation for
10 the traveling direction of the train 100.
[0052] The configurations described in the abovementioned
embodiments correspond to examples of the
contents of the present invention, and can be combined with
other publicly known techniques and partially omitted
15 and/or modified without departing from the scope of the
present invention.
Reference Signs List
[0053] 10 train control device; 20 obstacle detection
20 device; 21 sensor; 22 storage unit; 23 correction unit;
24 monitoring condition determination unit; 25 obstacle
determination unit; 30 output device; 100 train; 200
railroad track; 300 traffic signal; 400 railroad
crossing; 500 station; 600 tunnel; 700 monitoring range;
25 800 obstacle.
28
We Claim:
1. An obstacle detection device installed in a train, the
obstacle detection device comprising:
5 a sensor to monitor surroundings of the train and
generate a range image that is a result of monitoring;
a storage unit to store map information including
position information of structures installed along a
railroad track on which the train travels;
10 a correction unit to correct, using the range image
acquired from the sensor and the map information stored in
the storage unit, first train position information that is
information acquired from a train control device and
indicates a position of the train, and to output second
15 train position information that is a result of correction;
and
a monitoring condition determination unit to determine
a monitoring range of the sensor using the second train
position information and the map information.
20
2. The obstacle detection device according to claim 1,
wherein
the correction unit detects a structure installed
alongside the railroad track from the range image,
25 identifies a relative position between the train and the
structure detected, identifies a position of the structure
based on the position information of structures included in
the map information, and identifies the position of the
train based on the relative position to correct the first
30 train position information.
3. The obstacle detection device according to claim 2,
wherein
29
the storage unit further stores position information
of the railroad track, and
the correction unit determines, based on the position
information of the railroad track included in the map
5 information, whether or not the position of the train
indicated by the result of correction of the first train
position information is on the railroad track, sets the
result of correction as the second train position when the
position of the train is on the railroad track in the
10 determination, but further moves the position of the train
indicated by the result of correction of the first train
position information onto the railroad track to set the
position moved onto the railroad track as the second train
position when the position of the train is not on the
15 railroad track in the determination.
4. The obstacle detection device according to any one of
claims 1 to 3, wherein
the monitoring condition determination unit determines
20 the monitoring range of the sensor and a resolution of the
sensor based on a structure included in the monitoring
range.
5. The obstacle detection device according to claim 4,
25 wherein
when a railroad crossing is included in the monitoring
range of the sensor, the monitoring condition determination
unit makes the monitoring range wider than normal and makes
the resolution higher than normal in a specified range
30 including the railroad crossing,
when a station is included in the monitoring range of
the sensor, the monitoring condition determination unit
makes the monitoring range wider than normal and makes the
30
resolution higher than normal in a specified range
including the station, and
when a tunnel is included in the monitoring range of
the sensor, the monitoring condition determination unit
5 makes the monitoring range narrower than normal and makes
the resolution lower than normal in a specified range
including the tunnel.
6. The obstacle detection device according to any one of
10 claims 1 to 5, comprising
an obstacle determination unit to determine presence
or absence of an obstacle based on the range image acquired
from the sensor, wherein
when determining that the range image includes an
15 obstacle, the obstacle determination unit outputs
information indicating that the obstacle has been detected.
7. The obstacle detection device according to any one of
claims 1 to 5, comprising
20 an obstacle determination unit to determine presence
or absence of an obstacle based on the range image acquired
from the sensor, wherein
when determining that the range image includes an
obstacle, the obstacle determination unit outputs a brake
25 instruction to the train control device.
8. An obstacle detection method for an obstacle detection
device installed in a train,
the train including a storage unit to store map
30 information including position information of structures
installed along a railroad track on which the train travels,
the obstacle detection method comprising:
a monitoring step for a sensor to monitor surroundings
31
of the train and generate a range image that is a result of
monitoring;
a correction step for a correction unit to correct,
using the range image acquired from the sensor and the map
5 information stored in the storage unit, first train
position information that is information acquired from a
train control device and indicates a position of the train,
and to output second train position information that is a
result of correction; and
10 a monitoring condition determination step for a
monitoring condition determination unit to determine a
monitoring range of the sensor using the second train
position information and the map information.
15 9. The obstacle detection method according to claim 8,
wherein
in the correction step, the correction unit detects a
structure installed alongside the railroad track from the
range image, identifies a relative position between the
20 train and the structure detected, identifies a position of
the structure based on the position information of
structures included in the map information, and identifies
the position of the train based on the relative position to
correct the first train position information.
25
10. The obstacle detection method according to claim 9,
wherein
the storage unit further stores position information
of the railroad track, and
30 in the correction step, the correction unit determines,
based on the position information of the railroad track
included in the map information, whether or not the
position of the train indicated by the result of correction
32
of the first train position information is on the railroad
track, sets the result of correction as the second train
position when the position is on the railroad track in the
determination, but further moves the position of the train
5 indicated by the result of correction of the first train
position information onto the railroad track to set the
position moved onto the railroad track as the second train
position when the position is not on the railroad track in
the determination.
10
11. The obstacle detection method according to any one of
claims 8 to 10, wherein
in the monitoring condition determination step, the
monitoring condition determination unit determines the
15 monitoring range of the sensor and a resolution of the
sensor based on a structure included in the monitoring
range.
12. The obstacle detection method according to claim 11,
20 wherein
in the monitoring condition determination step,
when a railroad crossing is included in the monitoring
range of the sensor, the monitoring condition determination
unit makes the monitoring range wider than normal and makes
25 the resolution higher than normal in a specified range
including the railroad crossing,
when a station is included in the monitoring range of
the sensor, the monitoring condition determination unit
makes the monitoring range wider than normal and makes the
30 resolution higher than normal in a specified range
including the station, and
when a tunnel is included in the monitoring range of
the sensor, the monitoring condition determination unit
33
makes the monitoring range narrower than normal and makes
the resolution lower than normal in a specified range
including the tunnel.
5 13. The obstacle detection method according to any one of
claims 8 to 12, comprising
an obstacle detection step for an obstacle
determination unit to determine presence or absence of an
obstacle based on the range image acquired from the sensor,
10 wherein
in the obstacle determination step, when determining
that the range image includes an obstacle, the obstacle
determination unit outputs information indicating that the
obstacle has been detected.
15
14. The obstacle detection method according to any one of
claims 8 to 12, comprising
an obstacle detection step for an obstacle
determination unit to determine presence or absence of an
20 obstacle based on the range image acquired from the sensor,
wherein
in the obstacle detection step, when determining that
the distance image includes an obstacle, the obstacle
determination unit outputs a brake instruction to the train
25 control device.