SYSTEM AND METHOD FOR RAILWAY RIGHT-OF-WAY OCCUPANCY DETECTION
20240010249 ยท 2024-01-11
Assignee
Inventors
- Glen F. Dargy (Shellsburg, IA, US)
- James Hanlon, JR. (Grapevine, TX, US)
- Lee Olson (Cedar Rapids, IA, US)
Cpc classification
International classification
Abstract
A rail crossing occupancy detection system and method includes a plurality of LIDAR sensors operable to detect objects in one or more areas of interest within a field of interest, such as the areas including and surrounding a rail crossing, station, platform, or other railway right-of-way area. The field of interest is divided into one or more areas of interest, with one or more LIDAR sensors positioned to detect the presence of one or more objects within each of the one or more areas and to provide alerts based on the detection and behavior of the objects such as movement or other parameters associated with the objects.
Claims
1. A system for railroad right-of-way occupancy detection, comprising: one or more LIDAR sensors operable to detect one or more objects of interest in a field of interest; and logic and control circuitry in communication with the LIDAR sensors, wherein the logic and control circuitry is operable to determine information associated with the one or more detected objects within the field of interest.
2. The system of claim 1, wherein the field of interest comprises one or more areas of interest.
3. The system of claim 2, wherein the fields of view of the one or more LIDAR sensors overlap with the one or more areas of interest.
4. The system of claim 1, wherein the field of interest comprises an at-grade crossing, a station, a platform, a bridge, a tunnel, other railroad right-of-way area, area adjacent to a railroad right-of-way area, and combinations thereof.
5. The system of claim 1, wherein the information associated with the one or more detected objects comprises behaviors of interest.
6. The system of claim 5, wherein behaviors of interest comprises velocity, direction, location, duration, and combinations thereof.
7. The system of claim 1, wherein the logic and control circuitry is further operable to generate alerts, generate notifications, generate an event log, and combinations thereof upon detection of an object.
8. The system of claim 1, wherein the logic and control circuitry is configured to detect a crossing gate malfunction.
9. The system of claim 1, wherein the logic and control circuitry is configured to detect a vehicle incursion into the field of interest.
10. The system of claim 1, wherein the logic and control circuitry is configured to detect an object entering and/or exiting the field of interest.
11. The system of claim 1, wherein the logic and control circuitry is configured to detect a near-miss of a train with an object.
12. The system of claim 1, wherein the logic and control circuitry is configured to detect a collision of a train with an object.
13. The system of claim 1, wherein the logic and control circuitry is configured to detect loitering of an object within the field of interest.
14. The system of claim 1, wherein the logic and control circuitry is configured to detect a suspicious object within the field of interest.
15. A method of railroad right-of-way occupancy detection, comprising: providing one or more LIDAR sensors operable to detect one or more objects of interest in a field of interest; and providing logic and control circuitry in communication with the LIDAR sensors, wherein the logic and control circuitry is operable to determine information associated with the one or more detected objects within the field of interest.
16. The method of claim 15, wherein the field of interest comprises one or more areas of interest.
17. The method of claim 16, wherein the fields of view of the one or more LIDAR sensors are arranged to overlap with the one or more areas of interest.
18. The method of claim 16, wherein the field of interest comprises an at-grade crossing, a station, a platform, a bridge, a tunnel, or other railroad right-of-way.
19. The method of claim 15, wherein the information associated with the one or more detected objects comprises behaviors of interest.
Description
DESCRIPTION OF THE DRAWINGS
[0013] Illustrative embodiments of the invention are described in detail below with reference to the attached drawing figures, and wherein:
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DETAILED DESCRIPTION
[0026] As required, detailed embodiments of the present invention are disclosed herein; however, it is to be understood that the disclosed embodiments are merely exemplary of the invention, which may be embodied in various forms. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the present invention in virtually any appropriately detailed structure.
[0027] The present invention is directed to a system and method for rail crossing occupancy detection. Looking first to
[0028] LIDAR sensors L1 through L7 are operable to detect objects within their respective fields of view and, as depicted in
[0029] In the exemplary embodiment as depicted in
[0030] Looking back to
[0031] It should be understood that the areas 112, 114, 116, 118, 120, 122, 124, 126, and 128 as just described are virtual areas corresponding to the areas of interest within the field of interest, and that there is not necessarily a one-to-one correspondence between the field of view of a particular LIDAR sensor and an area of interest. For example, areas 112, 114, and 116 are all within the field of view of LIDAR sensor L1, and thus a single LIDAR sensor may be employed to cover and detect objects within all of those areas. Or, as seen in
[0032] Thus, the LIDAR sensors are preferably positioned to cover the entire field of interest, with the various areas of interest defined within that field of interest regardless of which physical LIDAR sensor (or sensors) include that area within its field of view.
[0033] With the LIDAR sensors positioned to cover the field of interest and the logic and control circuitry of the object detection subsystem in communication with the LIDAR sensors, objects within any of the areas, and movement or motion of objects within the areas can be detected and various occupancy detection scenarios can be implemented as will now be described.
[0034] The system and structure as just described can detect objects and conditions by monitoring specific areas of interest within a field of interest and iteratively track the state of objects within those areas and determine what has changed since the last iteration. In various embodiments, the system and method for rail crossing occupancy detection can be employed for train detection, gate malfunction detection, vehicle intrusion detection, object detection, near miss detection, train/object collision detection, loitering detection, suspicious object detection, and detection of other objects and events as will now be described.
Train Detection
[0035] In one exemplary embodiment, the system and method of the present invention may be configured to detect a train traveling along a railway by tracking the state of objects within three defined areas-for example, with reference to
[0036] A method of detecting a train travelling in those zones is depicted generally as numeral 240 in
[0037] At block 242, upon detection of an object within the region of interest, the system uniquely identifies the object by identifying features and parameters associated with the object, such as the size of the object, the shape of the object, the position of the object, the velocity of the object (if moving), and other parameters associated with the object. At block 244, based on the detected object and its parameters, the system determines and classifies the object as a train. At bock 246, if the detection of the train within the region is the first detection (i.e., the system had not, on previous iterations, identified a train within the region), then at block 248 the system sends a notification alert that a train has entered the region and sets an internal state parameter noting that a train has been detected entering the regionwith the state parameter of entering used on subsequent iterations of the logic to track further movement of the train. It should be understood that detection of a train entering from either side of the crossing may be accomplished, for example a train entering either of zone 126 or 128 may be detected, with the object detection subsystem and logic and control circuitry operable to distinguish between the two and to further determine the direction in which the train is travelling based on which zone it enters first.
[0038] If, at block 246, the system has already initially detected a train entering the region as just described (i.e., the state parameter is set to entering), at block 250 the system continues to monitor the areas of the region of interest to determine movement of the detected train beyond the entering status and to detect any transition of the train within the region of interest.
[0039] It should be understood, as noted above, that the logic implemented by the object detection subsystem is iterative, and that multiple samples per second may be captured by the logic and control circuitry so that movement of an object (such as a train) may be initially detected, tracked as the object traverses across the various monitored areas within the region of interest, and detected as the object eventually leaves the region, with the state parameter providing one or more states of the object/train within the region.
[0040] For example, as just described, the system may detect a train entering the region (e.g., the system initially had no detection of a train, then a train enters the region and the state changes to entering), may track as the train continues to occupy the region (e.g., a train may take seconds or minutes to travel through the crossing area), and may track and detect as the train prepares to leave the region (e.g., the train has traversed the region but is still detected in the final area of the region), and may detect that the train has exited the region (e.g., no train is detected within any area of the region). This iterative monitoring and state determination allows for complex scenarios implemented by the object detection subsystem and logic and control circuitry to monitor movement of a train within the monitored region beyond a simple object present and object not present detection as in the prior art.
[0041] It should be further understood that the iterative monitoring of the present invention allows calculation of additional parameters associated with the object/train for example, velocity, direction, and acceleration may be calculated based on the iterative parameters sampled by the object detection subsystem.
[0042] Looking still to
[0043] If, at block 252, the previous state of the system was occupying (i.e., the system had previously detected a train occupying the region, then at block 256, upon detection of the train transitioning to the final area within the region (e.g., referring to
[0044] Once a detection occurs and/or a state is set as described above, the logic is iteratively repeated, with subsequent changes in the state of detection of the train/object updated as described above.
[0045] Thus, it can be seen that the object detection subsystem and logic and control circuitry can monitor a region of interest and detect the initial entry of a train (or other object) into the region, track the train as it continues to occupy the region, and detect when the train leaves the region. It should be understood that the detection as just described is exemplary, and that other detection scenarios having more or fewer areas within a region may be implemented by the system of the present invention.
[0046] It should be further understood that the object detection subsystem and logic and control circuitry may include error detection capabilities to alert a user of an anomaly or potential malfunction. For example, in the scenario as just described, if the current state of the system is none (i.e., no train or object currently detected) and the system detects a train or object in zone 118, without ever having detected a train entering the region through zone 126, that anomaly may be flagged and reported to an operator. Similarly, any other variances or logical anomalies may be detected and reported.
Gate Malfunction Detection
[0047] Looking to
[0048] The logic flow is depicted generally in
[0049] With the gates identified, the iterative logic continues to monitor the position and movement of the identified gates, and detects various gate malfunction scenarios: a crossing gates do not lower scenario in blocks 266, 268, and 270; a crossing gates do not raise scenario in blocks 272, 274, and 276; and a crossing gates lower unexpectedly scenario in blocks 278 and 280 as will now be described.
[0050] To detect a crossing gates do not lower malfunction, at block 266, the system first determines that a train has been detected within the region of interest (as described above, a train entering, occupying, or exiting the region is a detected train within the region). At block 268, the system determines, based on parameters iteratively monitored for each identified gate, whether any of the gates did not move to the completely lowered position withing a predetermined amount of time. If so, at block 270, the system sends a gate malfunction alert identifying the gate(s) at issue. Thus, the system can not only detect and report that a gate did not lower at all, but can also detect and report that a gate lowered too slowly.
[0051] To detect a crossing gates do not raise malfunction, at block 272, the system first determines that a train has been detected within the region of interest (as described above). At block 274, the system determines, based on parameters iteratively monitored for each identified gate, whether any of the gates did not move to the completely raised position withing a predetermined amount of time. If so, at block 276, the system sends a gate malfunction alert identifying the gate(s) at issue. Thus, the system can not only detect and report that a gate did not raise at all, but can also detect and report that a gate raised too slowly.
[0052] To detect a crossing gates lowers unexpectedly malfunction, at block 278, the system first that a train has not been detected within the region of interest (as described above) and further detects that an identified gate is in the lowered position (or alternatively, is not in the completely raised position). At block 280, they system sends a gate malfunction alert identifying the gate(s) at issue.
Vehicle Turning onto Rail Detection
[0053] Turning to
[0054] The logic flow for the detection is depicted in
[0055] At block 358, as the logic iterates the system keeps track of the amount of time in which the object remains in the region of interest. If the object remains longer than a predetermined allowable time, then at block 368 the system sends an alert of the persistence of the object within the region.
[0056] Preferably, the system sends an alert specific to the type of object detected, such as a vehicle, pedestrian, box, etc. so that a user may respond appropriately to the detection and alert.
[0057] With the logic and detection scenarios set forth,
[0058] Looking to
[0059] Looking to
[0060] Looking to
[0061] And, looking to
[0062] The system would likewise generate an alert, signal or other alarm to notify of the vehicle incursion and positioning between the lowered gates.
[0063] As described, the system and method of the present invention may be configured to detect and alert to various other scenarios, several of which will now be described with respect to
Object Entering Track Detection
[0064] Looking to
[0065] In further embodiments, the system may further determine if the object is a train, a vehicle, a cyclist, a pedestrian, or other object and provides an appropriate alert. And in further embodiments, the object detection system may provide two-dimensional map coordinates of the detected object, or two-dimensional projection coordinates.
Near Miss Detection
[0066] Turning to
[0067] At block 410, the system detects and identifies an object entering a region of interest. At block 412, the system classifies the detected object, and at block 414, the system detects the object exiting the region of interest. At bock 416, the system detects a train within the region of interest within a predetermined amount of time from the time the detected object exited the region of interest. At block 420, the system sends a near miss alert to a user.
[0068] In further embodiments, the system further determines if the object is a train, a vehicle, a cyclist, a pedestrian, or other object and provides an appropriate alert. And in further embodiments, the object detection system provides two-dimensional map coordinates of the detected object, or two-dimensional projection coordinates.
Train/Object Collision Detection
[0069] Turning to
[0070] At block 430, the system detects and identifies an object entering a region of interest. At block 432, the system classifies the detected object. At block 434, the system detects a train entering a zone associated with the railway track in the region of interest while the detected object is still within that zone. Finally, at block 436, the system sends a train/object collision alert.
[0071] In further embodiments, the system further determines if the object is a train, a vehicle, a cyclist, a pedestrian, or other object and provides an appropriate alert. And in further embodiments, the object detection system provides two-dimensional map coordinates of the detected object, or two-dimensional projection coordinates.
Loitering Detection
[0072] Looking to
[0073] To detect loitering within a field of interest, the system generally detects that the discrete average speed of one or more objects within the field of interest over a predetermined time period is less than a predetermined set speed threshold, and provides an alert.
[0074] At block 440, the system detects and identifies an object within a region of interest. At block 442, the system classifies the object as a person. At block 444, the system determines whether the detected person has remained in the region of interest (or a zone within the region of interest) for longer than a predetermined amount of time. At block 446, the system sends a loitering alert to a user.
[0075] And in further embodiments, the object detection system provides two-dimensional map coordinates of the detected person, or two-dimensional projection coordinates.
Suspicious Object Detection
[0076] Turning to
[0077] To detect a suspicious object within a field of interest, the system generally detects that the discrete average speed of an object within the field of interest over a predetermined time period is less than a predetermined set speed threshold, and determines that the physical dimensions of the detected object are consistent with a suspicious object.
[0078] At block 450, the system detects and identifies an object within a region of interest. At block 452, the system classifies the object as a non-train, non-person object based on detected physical characteristics of the object. At block 454, the system determines whether the detected object has remained within the region of interest for longer than a predetermined time, and at block 456, the system sends a suspicious object alert to a user.
[0079] In further embodiments, the system further determines if the object is a train, a vehicle, a cyclist, a pedestrian, or other object and provides an appropriate alert. And in further embodiments, the object detection system provides two-dimensional map coordinates of the detected object, or two-dimensional projection coordinates.
[0080] Finally,
[0081] Looking to
[0082] Looking to
[0083] Second, third, fourth, and fifth areas 312, 313, 314, 315 are defined to encompass each of the crossing gates and to detect the position of each of the gates. As seen in the depicted scenario of
[0084] Finally, turning to
[0085] It is to be understood that while certain forms of the present invention have been illustrated and described herein, it is not to be limited to the specific forms or arrangement of parts described and shown. It should be further understood that with various areas defined within the field of interest that the system of the present invention can detect various objects, movement of objects, and positions of objects within those areas to determine unsafe conditions such as incursion of objects into the rail crossing region and to generate alerts or warnings in response. In addition, the system can similarly provide reports, alerts, and the like to confirm that the system is operating normally or as expected.