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    • 专利摘要:
    Method and system to monitor the mobility of vehicles and people, and computer program that implements the method The method includes: a) performing a plurality of detections of mobile devices (Mv, Mp) by receiving and acquiring identification information contained in wireless signals, and b) process the identification information acquired to: b1) calculate the mean and standard deviation of the number of total detections within a given integration interval; and b2) determine that mobile devices (Mv) whose number of detections is equal to or less than the value resulting from the sum of the values of the mean and standard deviation calculated are associated to vehicles of interest (V1, V2). The system includes processing means adapted to implement the method of the present invention. The computer program includes code instructions that implement the steps of the method of the present invention.
    公开号:ES2674293A1
    申请号:ES201700026
    申请日:2016-12-28
    公开日:2018-06-28
    发明作者:Juan José MARTINEZ DURÁ；Javier MARTINEZ PLUMÉ；Ramón Vicente CIRILO GIMENO；Antonio GARCIA CELDA；Federico ZOMEÑO BREITENSTEIN
    申请人:Universitat de Valencia；
    IPC主号:
    专利说明:

    Method V system to monitor the mobility of vehicles V people. and computer program that implements the method
    Technical sector
    The present invention generally concerns, in a first aspect, a method for monitoring the mobility of vehicles and people, which comprises determining what
    10 mobile devices are associated to vehicles of interest, and more particularly to a method that allows such determination to be carried out even in low-speed urban environments and for routes less than 1000 meters.
    A second aspect of the present invention concerns a system for monitoring the mobility of vehicles and people, which includes processing means adapted to implement the method of the first aspect.
    A third aspect of the present invention concerns a computer program, which implements the steps of the method of the first aspect of the present invention.
    Prior art
    Various methods for monitoring the mobility of vehicles and people are known in the state of the art, comprising the features included in the preamble of the
    Claim 1 of the present invention, ie comprising:
    a) perform a plurality of detections of mobile devices within a detection area, by receiving and acquiring, by a detector device disposed in a known position of a path, of identification information related to said
    30 mobile devices contained in wireless signals transmitted from them according to at least one short or long range wireless technology, and
    b) determine which mobile devices, among said plurality of detected mobile devices, are associated with vehicles of interest, by performing a processing 35 of said acquired identification information.

    In general, the majority of proposals known in the state of the art propose to carry out said step b) simply by filtering the information acquired based on the speed associated with the mobile devices with which it is associated, considering that if it is for Below an exclusion limit, which is generally fixed, the mobile device is carried by a pedestrian and if it is above it is on board a vehicle. Such is the case of the method described in W02010012844A1.
    Such proposals (such as the one made in W0201 0012844A 1) are only valid for non-urban environments or for very long routes within urban environments, where the distances between sensors is greater than 1.6 km (as described in Malinovskiy , Wu, Wang, & Lee, 2010 yen Araghi, Christensen, Krishnan, & Lahrmann, 2012), with the aim that the travel times between the different means of transport are significant and those corresponding to vehicles can be differentiated which correspond to pedestrians.
    However, for short distances in urban environments, with reduced vehicle speeds, due to road speed limitations and the presence of traffic lights, this type of proposal does not work properly, since travel times and Average speeds are very similar between pedestrians and motor vehicles, so an important problem arises that is to be able to differentiate between different means of transport, mainly motorized and pedestrian.
    To correct this problem, a more elaborate proposal is known which is described in the patent ES2424397B 1, which describes a method comprising determining which of the mobile devices detected twice are associated with vehicles from the acquired identification information, Carry out step b) by establishing a dynamically limited speed limit based on the speeds of mobile devices that have been determined associated with vehicles, and identify mobile devices that move slowly below the exclusion speed limit, and monitor the Mobile device traffic that does not move slowly.
    However, the proposal made in ES2424397B1 has a number of limitations, such as the need for mobile devices on board vehicles to be vehicle-specific, such as GPS devices designed for vehicles (such as a TomTom® device or device Parrot®), which is a problem if a minimum number of vehicles carrying one of such devices is not detected.
    There is therefore a need to offer an alternative to the state of the art that covers the gaps found therein, by providing a method that offers results in terms of the determination made in stage b) more efficient than those They offer the known methods.
    Explanation of the invention.
    To this end, the present invention concerns a method for monitoring the mobility of vehicles and people, which comprises, in a known manner, the realization of the following 10 steps:
    a) perform a plurality of detections of mobile devices within a detection area, by receiving and acquiring, by a detector device disposed in a known position of a path, of identification information related to said
    15 mobile devices contained in wireless signals transmitted from them according to at least one short or long range wireless technology, and
    b) determine which mobile devices, among said plurality of detected mobile devices, are associated with vehicles of interest, by performing a processing 20 of said acquired identification information.
    Unlike the methods known in the state of the art, in that proposed by the first aspect of the present invention, said step b) comprises:
    25 b1) calculate the mean and standard deviation of the number of total detections performed by at least said detector device within a given integration interval; Y
    b2) determine that mobile devices whose number of detections, by the detection device and within said determined integration interval, are associated with vehicles of interest is equal to or less than the value resulting from the sum of the values of said mean and said standard deviation.
    The problem described in the state of the art is solved by the method proposed by the first aspect of the invention, offering good results, in terms of the determination made in step b), even in urban environments with distances between the sensors less than 1000m, with traffic lights on the route of vehicles in environments
    Low-speed urban areas (30km / h) where travel times and pedestrians are very similar and there are no significant differences that can be used to make the classification.
    According to an exemplary embodiment, said detector device is arranged5 at a point j of a route, and:
    - said step a) also comprises previously carrying out a plurality of detections of mobile devices within another detection area, by receiving and acquiring, by another detector device arranged in a known position of
    10 said route or another route, at a point i of said route prior to said point j, of identification information related to mobile devices contained in wireless signals transmitted from them according to at least said short or long range wireless technology; Y
    15 - the method comprises checking whether the identification information acquired by the detector device provided at point j of said route corresponds to the same mobile device as that acquired by the other detector device provided at point i, and if so determine that there is a transit within said route between point i and j for said mobile device and assign said transit ij to said mobile device.
    20 Preferably, said step b) is carried out for each mobile device to which the corresponding i-j transit or other different transit has been assigned.
    The detection areas are, in general, between 100 and 300m, for short-range technologies (preferably not less than 250m), and larger for long-range ones.
    According to an embodiment of the method proposed by the first aspect of the present invention, it comprises, for each of the mobile devices determined as associated with vehicles of interest, to calculate a travel time such as that elapsed between the
    30 minus the time when at least one of the detections of the mobile devices has occurred within said other detection area and at least the moment in which at least one of the detections of the mobile devices has occurred within said area detection.
    According to an example of embodiment, the method comprises including information associated with said plurality or each of said pluralities of detections, including at least the acquired identification information and the times in which each detection has been performed, in a respective set of data (or register) called a detection interval that temporarily covers the time between the first and the last time a mobile device has been detected in step a) plus a correction value, which is set to
    5 function of the scope of work and the minimum separation between the sensors.
    According to an embodiment, said correction value is a time value of less than 1 minute, for interurban environments, and 30 seconds, for urban environments.
    For an exemplary embodiment, the method of the first aspect of the present invention comprises creating said detection range for at least the detector device located at point jo the one referred to as another detector device disposed at point i of the route, by corresponding processing means.
    The method of the first aspect of the present invention comprises, according to one embodiment, creating said detection range for at least the detection device of point j and another detection interval for the other detection device of point i, or vice versa.
    According to an embodiment example, the method of the first aspect of the present invention
    20 comprises generating a record of each of said detection intervals (i.e. of the data sets so named herein) and of the detections included therein, by the processing means of the corresponding detector device and send it to a remote computing entity, which will, in general, be responsible for carrying out the processing of the data received to implement the
    The rest of the steps of the method of the first aspect of the present invention, although for other examples of embodiment such remote computing entity is dispensed with and the steps of the method are implemented in one of the detection devices (communicated with each other), or in Another computing entity.
    According to one embodiment, the method of the first aspect of the present invention comprises performing said travel time calculation by said remote computing entity.
    For a preferred embodiment, the method of the first aspect of the present invention comprises selecting from among the travel times calculated for mobile devices associated with vehicles of interest, those that are within a range
    delimited by a lower threshold value and a higher threshold value.
    For an implementation of said preferred embodiment, the method comprises5 calculate said lower threshold value and said upper threshold value based on a valueof global travel time TTij which in turn is a function of different time values ofprevious trips, where the lower threshold value is equal to a portion of the time value ofTTij global trip and the upper threshold value is equal to a multiple of the travel time value
    global TTij greater than 1.
    10 According to a variant of said implementation, the lower threshold value is equal to substantially half of the global travel time value TTij and the upper threshold value
    it is equal to substantially double the value of the global travel time TTij.
    Advantageously, the method of the first aspect of the present invention comprises recalculating the value of said global travel time TTij from each selected travel time, applying the following expression:
    20 where p € [0.1, o.s] and TT¡ ' Is the last travel time selected.
    For an exemplary embodiment, the method of the first aspect of the present invention comprises dynamically generating an origin-destination matrix with the selected travel times and related data, including at least mobile devices, detection intervals, geographical positioning, wireless signal quality
    25 received, identification information acquired, transits and routes associated with them.
    According to an exemplary embodiment of the method of the first aspect of the present invention, the acquired identification information comprises a media access control address (MAC).
    For an exemplary embodiment, the method of the first aspect of the present invention comprises performing the detections of step a) by receiving and acquiring identification information contained in wireless signals transmitted from them according to two or more wireless short technologies. or long range different.

    A second aspect of the present invention concerns a system for monitoring the mobility of vehicles and people, which comprises, in a manner known per se:
    - at least one detector device disposed in a known one-way position, which includes a local electronic system and short or long-range wireless technology media, adapted to detect a plurality of mobile devices circulating within an area of detection, by receiving and acquiring identification information related to said mobile devices contained in wireless signals transmitted from them according to at least one short or long range wireless technology, and
    - processing means operatively connected to at least said detection device to receive the acquired identification information, and adapted to process it to determine which mobile devices, among said plurality of detected mobile devices, are associated with vehicles of interest.
    Unlike the systems known in the state of the art, in that proposed by the second aspect of the present invention, in a characteristic way, the processing means are adapted to at least perform the sub-steps b1) and b2) of the method of the first aspect of the present invention.
    For an exemplary embodiment of the system of the second aspect of the present invention, said detector device is disposed at a point j of a route, and in the system it comprises at least one other detector device disposed in a known position of said route. or in another way, at a point i of the aforementioned route prior to point j, which includes a local electronic system and short or long-range wireless technology media, also adapted to detect a plurality of mobile devices circulating inside of another detection area, by receiving and acquiring identification information related to mobile devices contained in wireless signals transmitted from them according to at least said short or long range wireless technology.
    The system of the second aspect of the present invention comprises, for one embodiment, a remote computing entity operatively connected with local electronic systems of the detecting devices.
    According to an example of embodiment of the system of the second aspect of the present invention, processing means of at least one of the local electronic systems or of said remote computing entity are adapted to implement the steps of the method of the first aspect according to any of the embodiments above
    5 described.
    According to one embodiment, said detecting devices comprise respective means of communication of long-range wireless technology and / or connection to a wired network, to at least communicate with each other bidirectionally.
    10 For an exemplary embodiment, the short-range wireless technology communication means are adapted to work with at least two different short-range wireless technologies, for which they comprise at least one horizontal polarization antenna and one vertical polarization antenna for each short-range technology with which 15 work.
    A third aspect of the present invention concerns a computer program, which includes code instructions that when executed in a computer implement the steps of the method of the first aspect of the present invention, according to any of its
    20 examples of realization.
    Brief description of the drawings
    The above and other advantages and features will be more fully understood from
    25 of the following detailed description of some examples of embodiment with reference to the attached drawings, which should be taken by way of illustration and not limitation, in which:
    Figure 1 is a schematic view of the system of the second aspect of the present invention arranged in a road in which vehicles and pedestrians circulate, representative of an embodiment of both the method and the system of the present invention.
    Figure 2 is a graph showing the MAC detections made (higher rectangles, one of them indicated as "Raw data" »with respect to the detection intervals (medium height rectangles, one of them indicated as" Raw intervals ") 35 for transits (lower rectangles, one of them indicated as" Transits "),
    with respect to a day of detection in a test installation of three sensors, according to an embodiment of the system and method proposed by the invention.
    Figure 3 is a graph showing the valid transits (using the + symbol), the
    5 filtered (by the symbol x), as well as three curves: an intermediate corresponding to theglobal travel time progressively recalculated from valid transits, ahigher resulting from multiplying by 2 the values of the intermediate and determining a thresholdupper, and a lower one resulting from dividing by 2 the values of the intermediate and thatdetermines a lower threshold, to filter transits that are outside the marked limits
    10 by the upper and lower thresholds, according to an embodiment of the method of the first aspect of the present invention.
    Figure 4 is a flow chart illustrating the different stages of the method proposed by the first aspect of the present invention, for an exemplary embodiment, including the essential stages thereof corresponding to the determination of the vehicles of interest.
    Figure 5 is a relative flow chart illustrating the steps carried out by the method proposed by the first aspect of the present invention, in particular in the
    20 detector device, to create the detection interval, according to an embodiment example.
    Figure 6 is a flow chart illustrating the steps carried out by the method proposed by the first aspect of the present invention, in particular in the detector device, to close the detection intervals, according to an embodiment example.
    Figure 7 is a flow chart illustrating the steps carried out by the method proposed by the first aspect of the present invention, for the calculation of the destination origin matrix (OID) and travel times, according to an example of realization.
    30 Detailed description of some embodiments
    An exemplary embodiment of the system of the second aspect of the present invention is illustrated in Figure 1, for which it includes:
    35-two detector devices Sj, Si, arranged in respective known positions of a track e, or points i, j (where i is a point prior to point j within a route), where each detector device Sj, If includes a local electronic system and media of short or long range wireless technology (not illustrated), adapted to detect a plurality of mobile devices Mv, Mp that circulate within respective areas of detection of the e-path, by receiving and acquisition of identification information
    5 related to mobile devices Mv, Mp contained in wireless signalstransmitted from them according to one or more short-range wireless technologies(Bluetooth, WiFi, etc.) or long range (eg 3G); Y
    - a remote computing entity R operatively connected to the local electronic systems 10 of the detecting devices Si, Sj.
    Also shown in Figure 1 are two vehicles of interest V1, V2 carrying on-board respective mobile devices Mv, and a pedestrian P carrying a mobile device Mp.
    The main objective of the method proposed by the first aspect of the present invention, implemented in the system of the second aspect, is to be able to distinguish with great precision the vehicles of interest V1, V2 from the pedestrians P (or other vehicles that do not they are of interest, such as bicycles or vehicles of people who carry out negotiations within the monitored route, remaining a long time within it).
    In this regard, the different steps of the method proposed by the first aspect of the present invention are illustrated in the flowchart of Figure 4, for an exemplary embodiment, which are explained below.
    25 According to the flowchart of Figure 4, a detection interval is first created (ie opened and closed) in the detector device or sensor Sj (arranged at a point j at the exit of the network or route or at an intermediate point thereof) where stage a) has been carried out.
    30 It should be understood that what has been referred to herein as a detection range is actually a set of data included within a time interval.
    The detection interval does not have a fixed value, it begins at the first detection or acquisition of identification information of the mobile devices Mv, Mp, which in this case is a MAC, and ends (that is, closes) when that MAC it has not been re-registered on that sensor after a preset time, that is, it is determined as the interval
    of detection existing between the first and last time that a mobile device Mv, Mp has been detected in step a) of the method plus a correction value, which is set according to the scope of work and the minimum separation between sensors In a way that ensures that a vehicle cannot make a path between two sensors without first
    5 have closed the detection interval on the source sensor. As a reference, environment times are taken per minute for interurban environments and 30 seconds for urban environments.
    Below is an excerpt of the data included in the data sets here called sensor detection intervals, for an exemplary embodiment. The fields are as follows:
    Field 1: MAC of the detected device.
    15 Field 2: Indicates if it is BT (Bluetooth) or WiFi, in the case of BT the device's CoD is registered.
    Field 3: "timestamp" of the first device detection.
    20 Field 4: "timestamp" of the last device detection.
    Field 5: maximum value of the RSSI (for the acronym in English "Received Signal Strength Indicator") detected.
    25 Field 6: "timestamp" in which the detection of the highest RSSI value has been performed.
    Field 7: number of detections within the detection range.
    The steps to open and increase the detection interval are illustrated in Figure 5, according to
    30 an exemplary embodiment, starting with the detection of the MAC, the verification of whether there is a detection interval for said MAC, and in case the creation of the corresponding detection interval is not so. If on the contrary one already exists for the detected MAC, this is added to it.
    35 In turn, the steps to close the detection intervals are illustrated in Figure 6, according to an example of embodiment. In this case, every 30 seconds (value taken as an example), for all open detection intervals it is checked whether (t -tfi)> to, where t is the current time, tfi is the time of the last detection of the MAC of the detection interval analyzed, and to is a constant and its value is set (for an embodiment) for the time that a vehicle would need at free speed (without retentions, or conditions that reduce its speed) to exit the area of sensor detection, circulate along the route or study network and be re-detected by the same sensor. In this case, it corresponds to the previously called correction value.
    As illustrated in Figure 6, the detection intervals once closed are sent to a central server (or remote computing entity R in Figure 1), where the remaining steps of the method of the present invention will be performed. This implies a substantial improvement in the consumption of the bandwidth of the communications network and in the reduction of the processing needs at the central server level, compared to the case in which each of the messages were sent to the central server separately. acquired information (MAC and associated information, if applicable) in each detection.
    Figure 2 confirms what has been said in the previous paragraph, in the form of a graph in which the results of an investigation carried out by the present inventors can be seen applying the method of the present invention, where the graph shows the MAC detections made (higher rectangles, one of them indicated as "Raw data" »with respect to the detection intervals (medium height rectangles, one of them indicated as" Raw intervals ") for transits (lower rectangles, one of they are indicated as "Transits"), with respect to a detection day in a test installation of three sensors This information has been obtained in a motorway installation of 3 acquisition devices, ie detection devices or sensors Si, Sj, distributed on the route or sensed network The data is for a full day of sensing.
    The following table shows the total numerical results obtained in the aforementioned investigation, which shows how shipments from the sensor to the Central Server are reduced by 84.5%.
    Raw Data Sensor Interval data
    Bluetooth detection
    62,384 9,678
    100% 15.5%
    The detection interval aims to associate each mobile device Mv, Mp (associated with a vehicle or person) with a single record in the detection device Si, Sj that includes all the possible information of that device Mv, Mp in its path by the detection zone of the detection device Yes, Sj. The algorithm that has been followed for its creation has been the following, for an embodiment example:
    The time t ~ is the time in which the MAC associated with the mobile device Mv, Mp has been detected for the first time, the following detections of the MAC are associated with the time tf, it is compared with t ~, if it is fulfilled that tf -t ~ <K it is considered that the new detection of the same MAC is part of the current detection interval, with K being a constant time that is set according to the detection zone. If K seconds pass since the last detection the interval would close and its limits would be [t ~, tf].
    Following the flowchart of Figure 4, as can be seen in this, after each time the mentioned creation of a detection interval is performed in the sensor Sj, it is checked whether during the detection interval created there is the same information of acquired identification, which in this case is a MAC, in the sensor i, and if so it is determined that there is a transit within said route between point i and j for the mobile device Mv, Mp and is created, that is to say assigns said transit ij to the corresponding mobile device Mv, Mp. At that time, the transits between the Sj sensor and the Si sensor (input sensor or intermediate point of the route or network) are closed.
    After that, sub-steps b1) and b2) of the method of the invention are carried out, ie the calculation
    of the mean ND and the standard deviation O ij of the number of total detections ND
    performed by the detector device Sj within a given integration interval.
    Subsequently, for all existing transits in the given integration interval, sub-stage b2) is carried out, that is, it is checked whether the number of detections
    ND associated with each transit is greater than ND + to ij 'and if not, the transit is classified
    as associated to a vehicle of interest. If so, traffic is classified as associated with a pedestrian (or a vehicle that is not of interest).
    The travel time of the vehicles of interest TT¡t and the TTil pedestrians is then calculated, and with the results of such calculations the values of respective origin / destination matrices (0/0) of vehicles M jv and pedestrians are increased Mit
    To carry out each of said travel time calculations, the time Tj associated with one of the detections in the sensor Sj is subtracted from the time Ti associated with one of the detections in the sensor Si. The detections to be included in said subtraction depend on the example of embodiment, in some cases they will be the detections associated with the maximum value of the RSSI in each sensor Sj, Yes, in other cases (for example when the distance between sensors is reduced) work The first detection in each Sj sensor, Si, and even in other cases, corresponding to urban traffic, is worked with the last detection in a Sj sensor and with the first one of the other Si, in order to exclude the effect of traffic lights.
    Figure 7 illustrates the steps carried out by the method proposed by the first aspect of the present invention, for the calculation of travel times and also of the 0/0 matrix, according to an embodiment example.
    The flowchart of Figure 7 begins with, beginning with the steps already indicated in that of Figure 4, that is, the creation (including its closure) of the detection interval in the sensor Sj, and for each time it is created one of such detection intervals in the sensor Sj, the closing of the transits between the sensor Sj and the sensor Si. After that, the travel time TTit of the traffic is calculated, in this case (although it has not been indicated in Figure 7) only of those associated with vehicles of interest (although, alternatively, the diagram of Figure 7 could be applied to the traffic associated with any vehicle).
    Next, it is checked whether the travel time TT¡t is within a range defined by a lower threshold value, in this case equal to half the value of TTij, and a higher threshold value, in this case equal to twice the value of TTij, where TTij is a global travel time value TTij that initially is equal to the free flow travel time.
    Those travel times where TTt / that are within the aforementioned range and their transits
    Associates are selected and considered valid, and those that are not discarded.
    The overall travel time TTij is in turn a function of different values of previous travel times, as illustrated in Figure 7 which shows how after considering a transit as valid TTij is recalculated according to the following expression:
    TT'J = TTt / * p + TT'J * (1 - ~)
    5 where pE [0.1, 0.5] YTT {/ is the last travel time selected.
    Subsequently, the values of an O / O matrix are increased with the travel times selected TT {/ and related data, where Mj is the component of the 0/0 matrix that corresponds to the itinerary between the Si sensor and the Sj sensor.
    10 The procedure in the diagram in Figure 7 is repeated for all detection intervals that are created.
    The results of another study carried out by the present inventors implementing the present invention are illustrated in Figure 3, two detection devices having been arranged in particular 109 km apart from each other.
    In Figure 3, the intermediate curve corresponds to the global travel time TTij which is progressively recalculated as indicated above, the upper curve sets the said upper threshold and the lower one the lower threshold, both of which also vary with time.
    20 for its dependence on TTij. Valid transits, that is, those between both thresholds have been indicated by the + symbol, while the filtered ones have been indicated by the x symbol and are discarded when considered abnormal.
    Finally, it should be noted that for the conception of the present invention, in particular the
    25 of its main characteristics based on the determination of whether a mobile device is associated with a vehicle of interest in the mean and the standard deviation of the number of total detections made by the detector device within a given integration interval, the present inventors performed a study in the city of Valencia that aimed to determine the use made by motor vehicles of its
    30 historic center, and it lasted for 18 days. That is, if it was a residential use, or on the contrary it was to shorten the movement within the city by crossing it from one side to the other. For this, 5 detecting devices were arranged in different locations, defining different paths.
    In the manual measurements that were made to characterize these two types of transport, an average hourly intensity of 660 pedestrians and 616 vehicles was recorded, that is, the number of vehicles and pedestrians was very similar. In order to be able to define a procedure that allowed distinguishing between a pedestrian and a motor vehicle, it was performed
    5 the hypothesis that a pedestrian should be registered for longer and more times on each sensor.
    The number of detections that were recorded in each sensor for each MAC was studied and the average value and its standard deviation were calculated, the values obtained were the 10 indicated in the following table:
    Average No. Detections Typical deviation
    16.1 17.1
    Tests were also carried out with devices of which the inventors knew their MAC, carrying out the tours by car and on foot. The data obtained were the following:
    15 • EI1 00% of the transits made on foot had a number of detections greater than 60, with an average of 80.1 detections and a standard deviation of 16.
    • Only 3.5% of vehicles exceeded the average number of detections plus the standard deviation of value 33. The average value was 8.3 detections and the standard deviation of 8.5. In all cases the values of the number of detections
    20 were less than 40 detections.
    Therefore, the criterion was set, to discriminate between a route made by a vehicle or by a pedestrian, that a transit corresponded with a motor vehicle if the number of detections was below average plus the standard deviation.
    In order to validate the previous hypothesis, the results obtained in
    25 classification. When analyzing the filtering files, it was noted that there were MAC addresses that had been registered many times throughout the study period, so it was assumed that they corresponded to residential vehicles or used to manage the monitored area.
    The results obtained were very positive, allowing to distinguish not only between vehicles and pedestrians, but also to obtain the classification of motor vehicle transits based on the use they make of the historic center of Valencia, either passing through or residential / management.
    Therefore, the results obtained allowed us to verify that the hypothesis made for the classification of transits created based on whether they are associated with a pedestrian or a vehicle was correct, and resulted in the creation of the method proposed by the present invention, especially sub-stages bl) and b2).
    The technical characteristics of each of the sensors or detection devices used in the study are presented below, each of which had a range of up to 300 m, according to the present invention:
    SENSORIZATION INTERFACES 2 Bluetooth interface 2 Wi-Fi interface.
    CHARACTERISTICS OF THE AERIALS 4 antennas, 2 horizontal polarization and 2 vertical polarization Frequency: 2400-2500MHz Gain: 2 x 12dBi Horizontal beam width: 90 "Vertical beam width: 30" Two interfaces for connecting external antennas (1 BT + 1 WIFI)
    3G / 4G SIM COMMUNICATIONS: 4 bands GSM, GPRS, EDGE: 850, 900, 1800 and 1900 MHz 2 bands UMTS and HSPA: 900 and 2100 MHz. UMTS 384Kbps up / down.
    EDGE (class 12) 237Kbps up / downHSPA + 14.4Mbps down / 5.76Mbps up.100 Mbps Ethernet
    POSITIONING
    5 GPS + Glonass.
    OTHER FUNCTIONALITIES
    NTP time service.FTP service
    10 WebConfig (local or remote access; even via W¡ · Fi) Configurable as a communications gateway. Bus 1xl2C and 2xUART and 3xGPIOS to connect more sensors or devices.
    POWER SUPPLY 15 AC 11 OV-240V, 50/60 Hz 0.3A DC 6V-36V (PoE).
    OPERATING TEMPERATURE
    - 40 ° C - + 60 ° C. P environment
    20 DIMENSIONS 270 x 270 x 110 mm
    SEALING 25 IP 67 waterproof case.
    Waterproof cable gland RJ45 and power.
    PROCESSING AND MEMORY SPECIFICATIONS
    ARM 7 processor
    5 RAM RAM 512 kb
    8 Mb ROM
    Each sensor has three long-range telecommunications devices, which allows the same system to coexist with several detection devices that communicate by different means:
    • 3G / 4G SIM:4 bands GSM, GPRS, EDGE: 850, 900, 1800 and 1900 MHz
    2 UMTS and HSPA bands: 900 and 2100 MHz. UMTS 384Kbps up / down.
    EDGE (class 12) 237Kbps up / down
    15 HSPA + 14.4Mbps down / 5.76Mbps up.
    • 100 Mbps Ethernet via RJ 45 connection
    • WIFI
    With respect to the power supply, this allows the connection of the detection device 20 to a wide variety of electrical supply elements, since it allows the feeding in direct, alternating current and through the Ethernet communications network
    • AC 11 OV-240V, 50/60 Hz 0.3A
    • DC 6V-36V
    • PoE through RJ45
    A person skilled in the art could introduce changes and modifications in the described embodiments without departing from the scope of the invention as defined in the appended claims.
    权利要求:
    Claims (20)
    [1]
    1.-Method to monitor the mobility of vehicles and people, which includes performing the following stages:
    a) perform a plurality of detections of mobile devices (Mv, Mp) within a detection area, by receiving and acquiring, by a detector device (Si) disposed in a known position of a path (C), of identification information related to said mobile devices (Mv, Mp) contained in wireless signals
    10 transmitted from them according to at least one short or long range wireless technology, and
    b) determine which mobile devices (Mv, Mp), among said plurality of mobile devices (Mv, Mp) detected, are associated with vehicles of interest (V1, V2), by performing a processing of said identification information acquired
    the method being characterized in that said step b) comprises:
    b1) calculate the mean and standard deviation of the number of total detections performed by at least 20 said detector device (Sj) within a given integration interval; Y
    b2) determine that mobile devices (Mv) are associated with vehicles of interest (V1, V2) whose number of detections, by the detection device (Si) and within said determined integration interval, is equal to or less than the resulting value of the sum
    25 of the values of said mean and said standard deviation.
    [2]
    2. Method according to claim 1, wherein said detector device (Si) is arranged at a point j of a route, and in which:
    - said step a) also comprises previously carrying out a plurality of detections of mobile devices (Mv, Mp) within another detection area, by means of reception and acquisition, by another detector device (Si) arranged in a known position of said route (C) or another way, at a point i of said route prior to said point j, of identification information related to mobile devices (Mv, Mp) contained in signals
    35 wireless transmitted from them according to at least said short or long range wireless technology; Y
    - because the method comprises checking whether the identification information acquired by the detector device (Sj) corresponds to the same mobile device (Mv, Mp) as that acquired by the other detector device (Si), and if so to determine that there is a transit within said route between point i and j for said mobile device (Mv, Mp) and assign said transit ij to said mobile device (Mv, Mp).
    [3]
    3. Method according to claim 2, wherein said step b) is carried out for each mobile device (Mv, Mp) to which said i-j transit or other transit has been assigned.
    [4]
    4. Method according to any one of the preceding claims, comprising, for each of said mobile devices (Mv) determined as associated to vehicles of interest (V1, V2), calculate a travel time (TTit) as the elapsed between at least the moment in which at least one of the detections of the mobile devices (Mv, Mp) has occurred within said other detection area (and at least the moment in which at least one of the detections has occurred of the mobile devices (Mv, Mp) within said detection area.
    [5]
    5. Method according to any one of the preceding claims, which includes including information associated with said plurality or each of said pluralities of detections, including at least the acquired identification information and the times at which each detection has been made, in a respective set of data called a detection interval that temporarily covers the time between the first and the last time a mobile device (Mv, Mp) has been detected in said stage a) plus a correction value.
    [6]
    6. Method according to claim 5, wherein said correction value is a time value of less than 1 minute, for interurban environments, and 30 seconds, for urban environments.
    [7]
    7. Method according to claim 6, which comprises creating said detection interval for at least said detector device (Sj) or said other detector device (Si), by means of corresponding processing means.
    [8]
    8. Method according to claim 7, which comprises creating said range of
    detection for at least said detector device (Sj) and another detection interval for said other detector device (Si), or vice versa.
    5. Method according to claim 7 or 8, which comprises generating a record of eachone of said detection intervals and the detections included therein, byof the processing means of the corresponding detector device (Sj, Si) and send it toa remote computing entity (R).
    10. Method according to claim 9 when it depends on 4, which comprises performing at least said travel time calculation (TT¡t) by said remote computing entity (R).
    [11]
    11. Method according to claim 4 or any one of claims 5 to
    15 10 when they depend on 4, which includes selecting from among the travel times (TT¡n calculated for mobile devices (Mv) associated with vehicles of interest (V1, V2), those that are within a range defined by a lower threshold value and an upper threshold value.
    12. Method according to claim 11, which comprises calculating said lower threshold value and said upper threshold value based on a global travel time value TTij which in turn is a function of different values of previous travel times, where the lower threshold value is equal to a portion of the global travel time value TTij and the upper threshold value is equal to a multiple of the global travel time value TTij greater than 1.
    [13]
    13. Method according to claim 12, wherein the lower threshold value is equal to half of the global travel time value TTij and the upper threshold value is equal to twice the
    TTij global travel time value.
    14. Method according to claim 12 or 13, which comprises recalculating the value of said global travel time TTij from each selected travel time, applying the following expression:
    35 where p € [0.1. 0.5] YTT {/ is the last travel time selected.
    [15]
    15. Method according to any one of claims 11 to 14, which comprises dynamically generating an origin-destination matrix with travel times
    selected (TTt /) and related data, including at least mobile devices
    (Mv), detection intervals, geographical positioning, quality of the wireless signals received, identification information acquired, transits and routes associated therewith.
    [16]
    16. Method according to any one of the preceding claims, wherein the identification information acquired comprises an access control address to the medium.
    [17]
    17. Method according to any of the preceding claims, which comprises detecting stage a) by receiving and acquiring identification information contained in wireless signals transmitted from them according to at least two different short or long range wireless technologies .
    [18]
    18.-System to monitor the mobility of vehicles and people, which includes:
    - at least one detector device (Sj) disposed in a known one-way position (C), which includes a local electronic system and short or long-range wireless technology media, adapted to detect a plurality of mobile devices (Mv, Mp) circulating within a detection area, by receiving and acquiring identification information related to said mobile devices (Mv, Mp) contained in wireless signals transmitted from them according to at least one short or long range wireless technology , Y
    - processing means operatively connected to at least said detector device (Sj) to receive said acquired identification information, and adapted to process it to determine which mobile devices (Mv, Mp), among said plurality of mobile devices (Mv, Mp) detected , are associated with vehicles of interest (V1, V2);
    the system being characterized in that said processing means are adapted to at least carry out the following sub-steps b1) and b2) of the method according to any one of the preceding claims:

    b1) calculate the mean and standard deviation of the number of total detections made by
    at least said detector device (Sj) within a given integration interval; Y
    b2) determine that mobile devices (Mv) whose number of detections, by the detection device (Sj) and within said determined integration interval, are equal to or less than the resulting value are associated with vehicles of interest (V1, V2) of the sum of the values of said mean and said standard deviation.
    [19]
    19. System according to claim 18, wherein said detector device (Sj) is disposed at a point j of a route, and wherein the system comprises at least one other detector device (Si) disposed in a position known from said path (C) or from another path, at a point i of said path prior to said point j, which includes a local electronic system and short or long range wireless technology communication means, also adapted to detect a plurality of mobile devices (Mv, Mp) that circulate within another detection area, by receiving and acquiring identification information related to said mobile devices (Mv, Mp) contained in wireless signals transmitted from them according to at least said technology Wireless short or long range.
    [20]
    20. System according to claim 18 or 19, comprising a remote computing entity (R) operatively connected with local electronic systems of the detecting devices (Si, Sj).
    [21 ]
    21. System according to any one of claims 18 to 20, wherein processing means of at least one of the local electronic systems or said remote computing entity (R) are adapted to implement the steps of the method according to any one of claims 1 to 17.
    [22]
    22. System according to any one of claims 19 to 21, wherein said detecting devices (Si, Sj) comprise respective means of communication of long-range wireless technology and / or connection to a wired network, for least communicate with each other bidirectionally.
    [23]
    23. System according to any one of claims 19 to 22, wherein the short-range wireless technology communication means are adapted to work with at least two different short-range wireless technologies, for which
    they comprise at least one horizontal polarization antenna and one vertical polarization antenna for
    every short-range technology they work with.
    [24]
    24.-Computer program, which includes code instructions that when executed in 5 a computer implement the steps of the method according to any one of claims 1 to 17.
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    同族专利:
    公开号 | 公开日
    ES2674293B2|2018-10-24|
    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    US20090153364A1|2007-12-17|2009-06-18|Motorola, Inc.|Method and apparatus for vehicle traffic time calculation|
    WO2009086565A1|2008-01-03|2009-07-09|Stanley Young|Monitoring a mobile device|
    ES2424397A2|2010-07-28|2013-10-01|Traffic Network Solutions, S.L.|A method and a system for monitoring traffic of vehicles|
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    ES201700026A|ES2674293B2|2016-12-28|2016-12-28|Method and system to monitor the mobility of vehicles and people, and computer program that implements the method|ES201700026A| ES2674293B2|2016-12-28|2016-12-28|Method and system to monitor the mobility of vehicles and people, and computer program that implements the method|
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