METHOD FOR LOCATING AND/OR MEASURING THE SPEED OF A VEHICLE

Abstract

A system for the geolocation of vehicles traveling on a guideway comprises the vehicles and markers distributed episodically along the guideway. The vehicles are equipped with a sensor for detecting a physical characteristic of the markers, and a computer for supplying location information as a function of signals delivered by the sensor. The computer stores a database comprising a recording of the distribution of the markers on the guideway. The markers having a physical characteristic detectable by the sensors. The markers each belong to one and only one class among a plurality of classes of physical objects, and the physical characteristic of all the markers of a class have the same property during detection by one of the sensors. The markers are randomly distributed on the guideway, with an ordered recording of the class to which each of the markers arranged on the guideway is stored in the database. Each of the recordings is associated with location information relative to the physical position of the marker on the guideway.

Claims

1. A system for the geolocation of vehicles traveling on a guideway, comprising: vehicles equipped with a sensor for detecting a physical characteristic of markers distributed episodically on the guideway, and a computer for supplying location information as a function of the signals delivered by the sensor and storing a database comprising a recording of a distribution of the markers on the guideway; and markers having a physical characteristic detectable by the sensors, the markers distributed over the guideway; wherein, the markers each belong to one and only one class among a plurality of classes of physical objects, the physical characteristic of all the markers of a class having the same property during detection by one of the sensors, and the markers are randomly distributed on the guideway, with an ordered recording of the class to which each of the markers arranged on the guideway belongs in the database, each of the recordings being associated with location information relative to the physical position of the marker on the guideway.

2. The system of claim 1, wherein the physical characteristic is magnetic induction.

3. The system of claim 2, wherein the markers are conductive masses and the sensors comprise a transmitter coil powered by an alternating electric current and by a receiver coil detecting the magnetic field induced by a conductive marker to produce an electric current processed to provide a signal when in proximity to a conductive marker.

4. The system of claim 2, wherein, the markers are magnetic masses and the sensors are constituted by a receiver coil detecting the magnetic field induced by a magnetic marker to produce an electric current processed to provide a signal when in proximity to a magnetic marker.

5. The system of claim 1, wherein the physical property is a length in a direction of a trajectory of the vehicle on the guideway.

6. The system of claim 5, wherein the classes of the plurality of classes correspond to ranges of the length with no overlap between the ranges.

7. The system of claim 6, wherein the markers are positioned between the rails forming the guideway.

8. The system of claim 7, wherein the database also comprises the recordings of distances separating two consecutive markers.

9. The system of claim 8, wherein the distribution of the markers on the guideway is periodic.

10. The system of claim 9, wherein the vehicles further comprise a second geolocation means, and the computer is configured to apply a consistency verification process between geolocation information calculated as a function of the signals delivered by the sensor and information supplied by the second geolocation means.

11. A method for geolocating vehicles equipped with a sensor for detecting a physical characteristic of markers, traveling on a guideway comprising a distribution of markers having a physical characteristic detectable by the sensors, wherein in the method comprises recording, during the movement, a sliding window of the property of the physical characteristic of each of the markers detected by the sensor of the vehicle, and comparing the sequence recorded during the movement of the vehicle with the sequences recorded in a database containing an ordered recording of the class to which each of the markers arranged on the guideway belongs in a database, each of the recordings being associated with location information relative to the physical position of the marker on the guideway.

12. The method of claim 11, further comprising, after processing a sequence of properties read by the sensor: recording in a buffer memory of the following sequence recorded in the database, recording in a buffer memory of the previous sequence shifted by the reading by the sensor of the property of the next marker, and comparing these two sequences to validate the location in the event of conformity or to order signaling in the event of a difference.

13. The system of claim 1, wherein the markers are positioned between the rails forming the guideway.

14. The system of claim 1, wherein the database also comprises recordings of distances separating two consecutive markers.

15. The system of claim 1, wherein the distribution of the markers on the guideway is periodic.

16. The system of claim 1, wherein the vehicles further comprise a second geolocation means, and the computer is configured to apply a consistency verification process between geolocation information calculated as a function of the signals delivered by the sensor and information supplied by the second geolocation means.

17. A system for geolocation of vehicles traveling on a guideway, comprising: markers distributed along the guideway, each of the markers having a common physical characteristic that varies among the markers, each marker belonging to one and only one class among a plurality of classes correlated to variations of the common physical characteristic, the sequence of categories of markers along the guideway being random; and at least one vehicle configured to travel along the guideway, the at least one vehicle comprising: a sensor configured to detect the physical characteristic of each of the markers as the vehicle passes adjacent the respective marker; and a computer configured to receive a signal from the sensor, the signal corresponding to the detected physical characteristic, and to identify the category to which each marker respectively belongs as the vehicle passes adjacent the respective marker, the computer configured to record sequences of the detected categories of markers identified by the computer, the computer further storing the random sequence of categories of markers along the guideway, the computer configured to compare the recorded sequences with the stored random sequence of categories of markers along the guideway and determine a location of the vehicle along the guideway.

18. The system of claim 17, wherein the markers are metal members having variable lengths, and wherein the sensor comprises a sensor configured to detect the presence of the metal members in proximity thereto.

19. The system of claim 18, wherein the vehicle further comprises a speed sensor for determining a speed of the vehicle, and wherein the computer is configured to use the determined speed of the vehicle and the sensor to determine the length of each metal member as the vehicle passes adjacent each metal member.

20. The system of claim 19, wherein the speed sensor comprises a sensor configured to detect a rotational speed of a wheel of the vehicle.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present disclosure will be described in more detail with reference to non-limiting example embodiments specifying the aforementioned advantages and considerations. A more specific description of the present disclosure is illustrated by the accompanying drawings, where:

[0044] FIG. 1 shows a schematic view of a section of guideway according to the present disclosure;

[0045] FIG. 2 shows a view of the sequences of signals processed by the computer;

[0046] FIG. 3 shows a schematic view of a section of guideway with a vehicle according to the present disclosure in a first position;

[0047] FIG. 4 shows a schematic view of a section of guideway with a vehicle according to the present disclosure in a second position;

[0048] FIG. 5 shows a schematic view of a section of guideway with a vehicle according to the present disclosure in a third position;

[0049] FIG. 6 shows a schematic view of a section of guideway with a vehicle according to the present disclosure in a fourth position;

[0050] FIG. 7 shows a schematic view of a section of guideway with a vehicle according to the present disclosure in a fifth position; and

[0051] FIG. 8 shows a schematic view of the digital processing operations.

DETAILED DESCRIPTION

[0052] The positioning system will be described below according to a non-limiting example where the markers are metallic masses, the physical property taken into account is the length along the trajectory of the vehicle (1), and the sensors are inductive sensors and autonomous shuttle vehicles traveling on a dedicated track with guide rails. The vehicles are also equipped, according to a preferred option, with a second location system, for example, an odometer taking into account the rotation of one of the wheels of the vehicle, or possibly radio transmitter balises arranged along the guideway, or even a GPS system, the data of which in the uncovered area will be extrapolated from data provided by, for example, an inertial unit.

[0053] The guideway can form a single closed loop, or on the contrary have multiple branches.

[0054] This detailed description that follows may be directly transposed to other implementations, which form an integral part of the present disclosure: for example, the vehicles could be rail vehicles for transporting people or freight, or trams, or handling vehicles traveling on dedicated tracks without rails. The markers could be optical markers detected by an optical sensor, mechanical markers detected by feelers or equivalent sensors, radiofrequency tags, etc.

[0055] Embodiment with metal markers and an inductive sensor

[0056] The solution described below is advantageous because the markers are particularly robust, easy to install and replace on the guideway, economical and resistant to vandalism because of low market value, and easy to firmly attach to the track.

[0057] The inductive characteristic is also advantageous because it does not require contact or special atmospheric conditions. Detection is robust irrespective of the lighting, humidity or pollution conditions, and withstands most forms of jamming.

[0058] FIG. 1 shows the environment of the present disclosure, namely a vehicle (1) moving on rails (10, 20). The rails (10, 20) have markers that can be attached to the crosspieces, attached to the rail or placed on a fixed support relative to the rail (10, 20). These markers (101 to 104) are passive, i.e., they are not supplied with energy. The length of the markers (101 to 104) along the axis of movement of the vehicle (1) on the rail is variable.

[0059] The markers (101 to 104) must be located far enough from the rail to avoid disturbances. The markers (101 to 104) can be positioned inside or outside the rails (10, 20). It is also possible to arrange several rows of markers (101 to 104) on the track. In the figure, the markers (101 to 104) are positioned, for example, along the left rail (10).

[0060] The rail vehicle (1) has at least one inductive sensor (21) positioned above the row of metal markers (which may be magnetic or metal pads). If several rows of markers are present, the rail vehicle (1) has at least as many inductive sensors (21).

[0061] The rail vehicle (1) also has a means of obtaining speed information, for example, using a toothed wheel speed sensor (22) as shown in FIG. 1, or by any other means (GPS data, speed obtained by an engine speed observer, coupling between several speed sensors, etc.). This speed information must be sampled sufficiently to be refreshed several times during the passage of the vehicle (1) above a marker (101 to 104).

[0062] According to this embodiment described in detail, the property retained, namely the length, is also advantageous because it is easy to segment the assembly into classes of lengths without overlap, while accepting a tolerance for manufacturing and for reading. For example, lengths of between 50 and 300 millimeters can be provided, with a tolerance of 10 mm (or a relative tolerance), and a segmentation into six classes: [0063] C1 [40 mm to 60 mm] [0064] C2 [90 mm to 110 mm] [0065] C3 [140 mm to 160 mm] [0066] C4 [190 mm to 210 mm] [0067] C5 [240 mm to 260 mm] [0068] C6 [290 mm to 310 mm]

[0069] It is easy to read the “length” property by an inductive sensor detecting the presence or absence of a metallic mass, combined with a determination of the length as a function either of a movement sensor, for example, odometric, or as a function of the speed and the time elapsing between a rising edge and a falling edge of magnetic flux detection.

[0070] Physically, these markers take the form of a rectangular steel metal pad that can be screwed or glued to a crosspiece of a track segment, between the two rails (10, 20), in an identical lateral position for each marker, for example, X centimeters from the left rail (20).

[0071] These markers (101 to 104) are randomly distributed along the track.

[0072] The property (length) of the marker to be implanted is determined without a predictive model, by a random draw or possibly by a chaotic sequence generator.

[0073] To obtain a high resolution, it is preferable to provide a marker on each crosspiece (11 to 16), but omitting one or more crosspieces does not prevent the proper functioning of embodiments of the present disclosure. Similarly, the presence of a parasitic metal mass, for example, a metal can, on the track does not prevent the correct operation of the system.

[0074] Randomization means that the properties of two consecutive markers are chosen at random. Thus, a class C2 marker will be between any two markers of class C.sub.i and C.sub.j.

[0075] The sequence of classes on the track is recorded in an ordered database. It can be a simple ordered list of the property of successive markers, of type C4, C2, C3, C4, . . . for a sequence formed by a marker (101) of 200 mm followed by a marker (102) of 100 mm, followed by a marker (103) of 150 mm, followed by a marker (104) of 200 mm, etc.

[0076] It is not necessary for two or more markers to belong to different classes.

[0077] Moreover, when the markers are distributed with an approximately constant spacing, it is not necessary to record the location coordinates of each of the markers, the positioning being able to be deduced from its rank in the ordered list.

[0078] To facilitate exploitation, however, an alternative involves recording the property and position of each marker in the database, for example, by reference to an origin position constituting the zero point, in the form of its distance with respect to this origin point according to a trajectory following the center line of the guideway.

[0079] This implantation of the markers (101 to 104) on the guideway will form a virtual “coded” line (50) formed by an alternating presence and absence of the characteristic read by the vehicle, with variable properties alternating with absences of the characteristic, which are also variable.

[0080] Assuming that the inter-distance between two crosspieces is constant, and that each crosspiece (11 to 16) carries a marker, the sum between the presence and the absence of induction will correspond to a constant length, and will provide the sensor (21) of the vehicle (1) traveling on the track with information coded according to a pulse width modulation (PWM) technique, commonly used to exploit robust discrete state signals.

[0081] The vehicle (1) comprises an inductive sensor (21) formed by, for example, a component placed under the chassis of the vehicle and comprising a first winding powered by an alternating current to emit a magnetic field. When a conductive or magnetically permeable target, in particular, a marker (101 to 104), is close to the winding, the impedance of the winding varies, and the measurement of this impedance and of the exceeding of a threshold value makes it possible to generate a binary signal indicating the presence or absence of metallic mass.

[0082] Inductive sensors produce an oscillating magnetic field at the end of their detection head. This field is generated by an inductor and a capacitor mounted in parallel. When a metallic conductive body is placed in this field, eddy currents arise in the mass of the metal; there is disturbance of this field that leads to a reduction in the amplitude of the oscillations as the metal object approaches, until complete blockage occurs. This variation is exploited by an amplifier that delivers a binary output signal.

[0083] Those skilled in the art know multiple solutions of variable inductance and variable reluctance sensors generally produce an electrical signal proportional to the conductive mass and the distance of a conductive or magnetically permeable object with respect to a coil.

[0084] When the vehicle is stationary, the sensor (21) remains in the same state depending on the presence or absence of a marker under the vehicle (1), and more precisely under the head of the sensor (21).

[0085] When the vehicle (1) moves at a speed V, the sensor (21) will detect a marker n whose “property” is a length L for a duration T.sub.i=L.sub.i/V.

[0086] The instantaneous movement speed of the vehicle (1) is known by, for example, an odometric sensor (22) or any other usual means for measuring the instantaneous speed of a vehicle. By measuring the time interval T.sub.i separating a rising edge and a falling edge of the signal supplied by the inductive sensor (21), the property of the marker is determined, namely its length Li equal to T.sub.i/V.

[0087] Similarly, the time interval separating a falling edge and a rising edge of the signal supplied by the inductive sensor (21), and the distance D2 separating two consecutive markers (101, 102) is determined.

[0088] The sequences taken into account have a length of N markers, such that the sequences of length N (or greater than N) produced are orthogonal or quasi-orthogonal in the sense that: [0089] Any sub-sequence extracted from the total sequence is unique, thus ensuring the uniqueness of positioning. [0090] Any subsequence extracted from the total sequence exhibits minimal correlation with all other subsequences, thus ensuring robustness to measurement inaccuracies.

[0091] See, for example, Dines, L. L. “A Theorem on Orthogonal Sequences.” Transactions of the American Mathematical Society, vol. 30, no. 2, American Mathematical Society, 1928, pp. 439-46, https://doi.org/10.2307/1989131.

[0092] N is determined according to the total number of markers, the number of property classes by a combinatorial calculation. For example, with the six classes of lengths referred to above, and sequences of 10 consecutive markers, one has a million unique sequences.

[0093] FIG. 2 shows the timing diagram of the signals supplied by the two sensors (21, 22) present on the vehicle (1):

[0094] The odometer comprises an incremental encoder (22) that counts the number of revolutions of the wheel with a certain precision (typically 100 pitches per revolution: one pitch is approximately equal to 12 mm) and supplies a rectangular signal (30) whose periodicity is representative of the instantaneous speed. The periodicity is constant when the vehicle (1) is moving at a constant speed.

[0095] The inductive sensor (21) provides a second rectangular signal (40) whose level is 1 if it is above a marker (101 to 104) and zero otherwise.

[0096] The combination of the two sensors makes it possible to measure the length of the markers in number of pitches as well as the distance between markers in number of pitches.

[0097] An electronic system makes it possible to store these two lengths d1 and d2 in a memory of adjustable size. The circuit is known in advance and recorded in another reference memory that will allow the electronics to define its position.

[0098] FIGS. 3 to 7 illustrate an example of acquisition of the signals from the sensors (21) and (22).

[0099] In FIG. 3, the vehicle (1) passes over the first marker (102): it measures d1=10 pitches (approximately 12 cm) and stores the value (10 pitches) in memory in a first register.

[0100] In FIG. 4, the vehicle (1) passes over the start of the second marker (103): it measures d2=154 pitches (approximately 185 cm) and stores the value (154 pitches) in memory in a second register.

[0101] In FIG. 5, the vehicle (1) passes over the end of the second marker (103): it measures d1=5 pitches (approximately 6 cm) and stores the value (5 pitches) in memory in a third register.

[0102] In FIG. 6, the vehicle (1) passes over the start of the third marker (104): it measures d2=150 pitches (approximately 180 cm) and stores the value (154 pitches) in memory in a fourth register.

[0103] And so on.

[0104] The values are in fact recorded in memory in binary (for example, on 8 bits) in a shift register composed of N values, N corresponding to the number of measurements taken into account in a sliding window of N increments, and recorded in a memory of FIFO type. This processing requires very few resources and can be executed by a very simple microcontroller.

[0105] One then proceeds to a process involving a hash of these data: Only the most representative values are kept to form a binary word on N bits (for example, a word on 32 bits) to produce a binary sequence coding the absolute position of the capsule (deletion of useless bits).

[0106] During synchronization (search for the initial state during start-up), the closest binary word is searched in the table compared with the table. This synchronization involves validating the position resulting from the exploitation of the signals supplied by the sensors (21, 22) making it possible to calculate sliding sequences, with the sequences recorded in the database constituted during the implantation of the markers or during a reset step.

[0107] Once synchronized, it is checked at the next pad that the read state is close to the expected state. To do this, it suffices to read the following sequence in the table and to check, during the acquisition of the signals, that the sequence obtained by the exploitation of the signals from the sensors (21, 22) is compliant. It is thus possible to produce location information very simply by incremental reading of the positions recorded in the database, by synchronizing with the signals supplied by the sensors (21, 22).

[0108] FIG. 8 shows how reading a succession of markers of different lengths L1 to L4 makes it possible to find the position P1 to P7 of the vehicle (1) on the guideway. The set of markers (101 to 104) of different lengths forms a set of accessible states with knowledge of the possible transitions between states. The read lengths of markers (101 to 104) correspond to the succession of past markers (101 to 104) modified by the measurement error. These read marker lengths (101 to 104) are the input data of the positioning algorithm (60). From the measurements (Step 62) and knowledge of the positioning (Step 63) of the markers (101 to 104) on the guideway, the algorithm (Step 64) finds the most probable state P3 (Step 65) among the known possible states (Step 61), and therefore the position (Step 66) of the mobile on track.

[0109] Depending on the algorithm used, this determination can be made in two ways: [0110] by memorizing a fixed number of markers and finding this pattern in the set of existing patterns. In this case, the algorithm can be, for example, a search for a maximum in a convolution calculation, or any other method making it possible to find the sequence produced in a deterministic manner. [0111] by a probabilistic method giving the probability of being located at each point of the network or only the most probable point. The use of a probabilistic algorithm for determining the state may be, for example, a Viterbi algorithm, a Kalman filter, or any other method making it possible to find the sequence carried out in the most probable manner.

[0112] The successive steps of positioning on the track are therefore: [0113] 1. Detecting the presence of markers (101 to 104). [0114] 2. Coupling the speed measurement with the detection of the presence of markers (101 to 104) in order to determine the length of the markers (101 to 104). This speed measurement can come from a wheel rotation speed sensor or from any other method of obtaining a sufficiently sampled speed measurement to allow the length of the crosspiece to be measured, for example, coupling the speed measurements of several axles, a speed measurement given by a GPS, a speed obtained by an engine speed observer, etc. [0115] 3. Reading the succession of markers (101 to 104) in order to define a succession of words in a code. [0116] 4. Using this succession of words to determine the markers (101 to 104) read in the entire network code. This determination can be made in two ways, either by memorizing a fixed number of markers (101 to 104) and finding this pattern in all the existing patterns, or by a probabilistic method giving the probability of being located in each network point. [0117] 5. Linking the position in the code to the absolute position on the network.

[0118] This positioning system can be adapted or supplemented with the distance measurement between two markers (101 to 104). In this case, the positioning algorithm takes as input data can be completed to use as input data the distance between two markers (101 to 104) in addition to the length of the markers (101 to 104). This algorithm can also be adapted to use only the distance between markers (101 to 104).