SYSTEM AND METHOD FOR RAILWAY RIGHT-OF-WAY OCCUPANCY DETECTION

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.

Description

FIELD

The present invention relates generally to the field of railroads, and more particularly to a system and method for detecting trains, vehicles, people, or other objects within a railway right-of-way region, detecting and calculating parameters associated with the detected objects, and providing alerts and/or control signals based on the detected objects and their associated parameters.

BACKGROUND

Systems and methods of detecting the presence or absence of objects are known in the art, and such detection has been applied to the field of railroads. For example, U.S. Pat. No. 9,376,129 discloses the use of RADAR sensors to detect a blocked rail crossing by detecting the presence or absence of an object in the crossing area. Similar detection of the presence or absence of objects in an area has been used in the field of trespasser detection (i.e., detection of the presence of an unexpected object in an area) and in the field of traffic counting (i.e., detection and counting of the presence of vehicles or people in a particular area).

While such systems and methods are useful, they are also rudimentary, typically only detecting the presence or absence of an object in a defined area and taking a particular action in response—e.g., keeping a running tally of objects entering the defined area (i.e., traffic counting), or generating an alert or signal indicating the presence or absence of an object in the defined area (i.e., blocked rail crossing detection).

Thus, it can be seen that there remains a need in the art for an improved system and method for detecting and monitoring objects in a rail crossing area and providing responses tailored to the detected object or objects.

SUMMARY

Embodiments of the invention are defined by the claims below, not this summary. A high-level overview of various aspects of the invention are provided here for that reason, to provide an overview of the disclosure, and to introduce a selection of concepts that are further described in the detailed description section below. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in isolation to determine the scope of the claimed subject matter. In brief, this disclosure describes, among other things, a system and method for detecting objects in a rail crossing area and providing outputs, actions, and responses based on the detected objects and parameters and information associated with the detected objects.

In one embodiment, a rail crossing occupancy detection system and method includes a plurality of LIDAR sensors positioned and operable to detect objects in one or more areas of a field of interest (FOI) being monitored, such as the region including and surrounding a rail crossing. The region is divided into one or more areas of interest (AOI), with one or more LIDAR sensors positioned to detect the presence of one or more objects within each of the one or more areas. For example, the region being monitored may be a rail crossing area, with multiple areas within that region monitored, such as the rail track, the crossing gates, and the roadway within, and outside of, the crossing gates. Thus, while the system monitors the entire rail crossing region, that region is subdivided into multiple areas, each of which includes one or more LIDAR sensors associated with that area for detecting objects and parameters and information associated with the objects.

In one aspect, the plurality of LIDAR sensors are connected and integrated into an object detection subsystem which includes logic and control circuitry to communicate with and receive data from each of the sensors. The logic and control circuitry may include processors, memory, and power supply circuitry, and is configured to define various regions and areas of coverage by various combinations of the LIDAR sensors. In another aspect, the object detection subsystem generates three-dimensional object location data for each detected object-such as trains, crossing gates, vehicles, people, and other objects-from image data captured by the LIDAR sensors.

In a further aspect, the system and method of the present invention derives one or more parameters and/or information associated with detected objects, such as an object's speed, direction of movement, and size, i.e., objects of interest (OOI) and behaviors of interest (BOI). Thus, both static and moving objects may be detected, and moving objects may be tracked as they traverse through the rail crossing area or through one or more areas of the region.

In another aspect, the occupancy system and method may be deployed in any railway right-of-way region or area, such as at-grade crossings, stations, platforms, bridges, tunnels, trespasser problem areas, or any other area within or near a railway right-of way in which monitoring for objects of interest and/or behaviors of interest is required or desired.

In further embodiments, the type of object is identified by comparison of the parameters and information associated with the object to a database of known objects and parameters. For example, a train may be identified by its size, its position above and along the tracks within a region, and by its direction of travel within the area. Similarly, vehicles, people, and other objects may be identified by comparing their physical size and features (speed, movement patterns, etc.) with a database of known objects and their associated parameters.

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.

DESCRIPTION OF THE DRAWINGS

Illustrative embodiments of the invention are described in detail below with reference to the attached drawing figures, and wherein:

FIG. 1 is a top plan view of a system in accordance with an exemplary embodiment of the present invention deployed in a rail crossing region.

FIG. 2 is a schematic block diagram of a system in accordance with an exemplary embodiment of the present invention.

FIG. 3 is a flow diagram of a method of train detection in accordance with an exemplary embodiment of the present invention.

FIG. 4 is a flow diagram of a method of gate malfunction detection in accordance with an exemplary embodiment of the present invention.

FIG. 5 is a flow diagram of a method of detecting vehicle incursion into the railway in accordance with an exemplary embodiment of the present invention.

FIGS. 6A, 6B, 6C, and 6D depict areas and objects within a railway crossing region in a vehicle incursion detection scenario as also described with respect to FIG. 5.

FIG. 7 is a flow diagram of a method of detecting an object entering a rail track in accordance with an exemplary embodiment of the present invention.

FIG. 8 is a flow diagram of a method of detecting a near miss in accordance with an exemplary embodiment of the present invention.

FIG. 9 is a flow diagram of a method of detecting a train/object collision in accordance with an exemplary embodiment of the present invention.

FIG. 10 is a flow diagram of a method loitering detection in accordance with an exemplary embodiment of the present invention.

FIG. 11 is a flow diagram of a method of suspicious object detection in accordance with an exemplary embodiment of the present invention.

FIGS. 12A, 12B, and 12C depict areas and objects within a railway crossing region in a train in crossing region without gates lowered scenario.

DETAILED DESCRIPTION

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.

The present invention is directed to a system and method for rail crossing occupancy detection. Looking first to FIGS. 1 and 2, an exemplary embodiment of the system of the present invention is depicted. As seen in FIG. 1, a plurality of LIDAR sensors L1 through L7 are positioned around a region of interest 98, a rail crossing. As seen in the figure, the rail crossing comprises a railway 20 extending across a roadway 21 to allow a train to pass over the roadway. The railway includes two rails 22 supported by a plurality of ties 24. Crossing gates 26a, 26b, 26c, and 26d raise and lower to block and unblock the roadway 21 to prevent vehicles from entering the railway when a train is approaching and/or to act as a visual indication that a train is approaching or is present on the railway. It should be understood that in alternative embodiments that other signals, such as warning lights and the like, may be employed in addition to, or in place of, the crossing gates. It should be further understood that other configurations of crossing gates, such as single gates on each side of the railway, are within the scope of the present invention.

LIDAR sensors L1 through L7 are operable to detect objects within their respective fields of view and, as depicted in FIG. 2, are connected to logic and control circuitry to form an object detection subsystem 100. Looking to FIG. 2, the object detection subsystem 100 includes logic and control circuitry 102 comprised of one or more processors 104, memory 106, database 108 and control logic 110.

In the exemplary embodiment as depicted in FIG. 2, the output of the object detection subsystem 100 is used to control and/or signal various devices, such as signage 111a, alert devices 111b such as audio or visual alerts, reports 111c, crossing signals 111d, and crossing gates 111e based on logical and algorithmic programming in the control logic 110. In alternative embodiments, the output of the object detection subsystem 100 may be directed to an external computer or controller which includes its own control logic to determine actions to take and devices to control in response to data provided by the object detection subsystem 100.

Looking back to FIG. 1, LIDAR sensors L1 through L7 are positioned such that their fields of view encompass the entire field of interest (FOI), in this case the railway crossing region. Within the field of interest, various areas of interest are defined in which the detection of objects is desired. For example, in FIG. 1, area 112 is an area of the roadway outside of the first and second crossing gates 26a, 26b, area 114 is the area surrounding and including the first crossing gate 26a, area 116 is the area surrounding and including the second crossing age 26b, area 118 is the area of the railway 20 crossing the roadway 21, area 120 is the area surrounding and including the third crossing gate 26c, area 122 is the area surrounding the fourth crossing gate 26d, and area 124 is the area of the roadway outside of the third and fourth crossing gates. Track zones, or areas 126, 128, located on either side of the crossing zone, allow detection of a train (or other object) travelling along the railway into or away from the crossing zone.

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 FIG. 1, LIDAR sensor L2 may encompass only area 112 within its field of view. Regardless of the number of LIDAR sensors used, the logic and control circuitry within the object detection subsystem will virtually mesh all of the separate LIDAR signals, accounting for overlap as necessary, with the various separate areas of interest defined as logical subsets within the entire LIDAR viewing profile.

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.

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.

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

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 FIG. 1, track zones 126, 128, and crossing zone 118 are monitored by the LIDAR detectors in the manner as previously described to detect a train (or other object) travelling along the railway 20.

A method of detecting a train travelling in those zones is depicted generally as numeral 240 in FIG. 3. Looking to FIG. 3 in conjunction with FIG. 1, to detect a train (or other object) travelling along a railway, the system as previously described is first initialized, with the region of interest defined and the appropriate LIDAR sensors covering the area(s) within the region of interest monitored by the object detection subsystem 100. The system iteratively cycles thorough the covered areas (the track zones 126, 128 and crossing zone 118) to detect whether an object, or a change in state of a previously detected object, has occurred, with detection of train accomplished by implementing the following logic.

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 region—with 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.

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.

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.

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.

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.

Looking still to FIG. 3, at block 250, the system detects the train transitioning to an area within the region of interest beyond the zone in which the train entered. For example, with reference to FIG. 1, a train entering the region at zone 126 will transition to zone 118 and then to zone 128. Thus, once the train is detected transitioning from zone 126 to zone 118, at block 212 the system determines that if the previous state was “entering” then at block 254 the state of the system is set to “occupying” and an alert of that event is sent.

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 FIG. 1, the train has previously moved from zone 126 to zone 118, and now moves to zone 128) at block 258 the system sets the state to “exiting” and sends an alert of that event.

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.

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.

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

Looking to FIG. 4 in conjunction with FIG. 1, in another exemplary embodiment, the system and method of the present invention are deployed to detect a malfunction of a crossing gate. In this exemplary embodiment, the system is configured to monitor the position of crossing gates within the region of interest, for example, zones 114, 116, 120, and 122 are monitored to detect the position and/or movement of crossing gates 26a, 26b, 26c, and 26d, respectively, with the train “entering”, “occupying”, and “exiting” states also operating as described above with respect to the train detection scenario.

The logic flow is depicted generally in FIG. 4 as numeral 260. At block 261, if the state of the gate detection is “none” (i.e., no gates have yet been identified classified), then at 262, the system initially detects an object (i.e., the gate) in each of the areas within the region, that is, the gates 26a, 26b, 26c, and 26d. At block 264, the system classifies the detected object in each region as a gate, and thus will subsequently track the position and/or movement of each gate.

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.

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.

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.

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

Turning to FIG. 5, in conjunction with FIG. 1, in another exemplary embodiment, the system and method of the present invention are used to detect a vehicle (or other non-train object) turning onto the rail track. As seen in FIG. 1, various zones or areas within the entire region of interest 98 are defined, with several zones (126, 118, and 128 associated with the railway 20) and other zones (112, 118, and 124 associated with the roadway 21), with zone 118 encompassing both the railway 20 and the roadway 21.

The logic flow for the detection is depicted in FIG. 5 generally as numeral 350. At block 352, with an initial state of an object undetected, the system detects and identifies an object within the region. At block 354, the system classifies the detected object as a “non-train” object, thus any car, motorcycle, or other non-train object may be detected. At block 356, the system detects that the non-train object is within any area in which only trains would be expected, for example, zones 126 and 128 of FIG. 1, which are zoned on the railway 20. Upon detection of an object in these zones, the system sets a state parameter to “object”, and at block 362 the system sends an alert of the detected non-train object on the railway.

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.

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.

With the logic and detection scenarios set forth, FIGS. 6A, 6B, 6C, and 6D depict the various scenarios as just described with respect to the logic flow diagram of FIG. 5 in which the system and method of the present invention detect that a vehicle is present between closed crossing gates. An alert and/or other action would be generated in response to such detection.

Looking to FIG. 6A, a railway crossing region—the field of interest in this scenario-is depicted generally as numeral 200. The railway crossing region includes a roadway 202 allowing vehicles to cross the rail track 204, with crossing gates 206a, 206b, 206c, 206d positioned on each side of the roadway 202, the crossing gates normally operable to close/lower when a train is approaching the crossing region to deter vehicles from entering the crossing region and to raise when the train has sufficiently cleared the crossing region. Signal/warning lights are included with each crossing gate mechanism to provide a visual indication of the presence or approach of a train.

Looking to FIG. 6B, an area 208 is defined by the system to detect objects in the area where the rail track 204 crosses the road 202. Thus, as depicted, a vehicle 210 has entered that area 208 and is detected by the system. As can also be seen in FIG. 6B, the crossing gates are each detected within an area corresponding to each gate, with the system detecting that all of the crossing gates are in the lowered/closed position. Thus, the system determines that a vehicle has entered the crossing area with all gates, down, thus the vehicle 210 is between the closed/lowered crossing gates.

Looking to FIG. 6C, the system detects that the vehicle has entered the area 212 defining the rail track crossing the roadway—i.e., that the vehicle between the gates has moved from the roadway on one side of the track and onto the track.

And, looking to FIG. 6D, the system detects that the vehicle 210 has entered area 214, i.e., the roadway area on the opposite side of the track, indicating that the vehicle has crossed the track. As also seen in FIG. 6D, the system can provide a signal to allow the crossing gate to raise to allow the vehicle 210 to exit from the area.

The system would likewise generate an alert, signal or other alarm to notify of the vehicle incursion and positioning between the lowered gates.

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 FIGS. 7, 8, 9, 10, and 11.

Object Entering Track Detection

Looking to FIG. 7, in another exemplary embodiment, the system and method of the present invention are used to detect an object entering the track. At block 400, the system detects and identifies an object within the region of interest. At block 402, the system determines that the object is not a train, and at block 404 the system detects that the object is within a zone, area, or region associated with railway track. Finally, at block 406, the system sends an alert of the object detected entering the track.

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

Turning to FIG. 8, in another exemplary embodiment, the system and method of the present invention are used to detect a near miss condition. To detect a near miss, the system generally detects that a train is present and that an object is located within a predetermined distance threshold from the detected train, and provides an alert.

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.

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

Turning to FIG. 9, in another exemplary embodiment, the system and method of the present invention are used to detect a collision between a train and an object. To detect a train/object collision, the system generally detects that a train is present (as described previously) and that a detected object is within the area occupied, or zone extents, of the train, and provides an alert.

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.

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

Looking to FIG. 10, in another exemplary embodiment, the system and method of the present invention are used to detect loitering within the field of interest.

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.

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.

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

Turning to FIG. 11, the system and method of the present invention are used to detect suspicious objects within the field of interest.

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.

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.

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.

Finally, FIGS. 12A, 12B, and 12C depict a scenario in which the system and method of the present invention detect that a train is present on the railway while one or more of the crossing gates are not lowered. An alert and/or other action would be generated in response to such detection.

Looking to FIG. 12A, a railway crossing region is depicted generally as numeral 300. The railway crossing region includes a roadway 302 allowing vehicles to cross the rail track 304, with crossing gates 306a, 306b, 306c, 306d positioned on each side of the rail track 304, the crossing gates normally operable to close/lower when a train is approaching the crossing region to deter vehicles from entering the crossing region and to raise when the train has sufficiently cleared the crossing region. Signal/warning lights are included with each crossing gate mechanism to provide a visual indication of the presence or approach of a train.

Looking to FIG. 12B, a first area 308 is defined by the system to detect objects in the area where the rail track 304 crosses the road 302. Thus, as depicted, a train 310 entering that first area 308 is detected by one or more LIDAR sensors defining that first area. In other embodiments, objects other than a train may likewise be detected, such as a survey vehicle, repair equipment, and the like.

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 FIG. 12B, a train is entering the rail track crossing the road (and thus is detected in area 308). At the same time, the system detects that all of the crossing gates—as detected in areas 312, 313, 314, and 315—are in the up/not-lowered position. Thus, an alert, signal or other alarms would be generated to notify of the gate malfunction or incursion of a train without a corresponding gate closure.

Finally, turning to FIG. 12C, the second, third, fourth and fifth areas 312, 313, 314, 315 are more clearly visible, with the train exiting the rail track crossing area 308, and detected in the crossing exit area 316.

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.

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; andlogic 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; andproviding 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.