NL2022249B1 - Method and system for determining movements of physical entities in a part of a geographic region - Google Patents
Method and system for determining movements of physical entities in a part of a geographic region Download PDFInfo
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- NL2022249B1 NL2022249B1 NL2022249A NL2022249A NL2022249B1 NL 2022249 B1 NL2022249 B1 NL 2022249B1 NL 2022249 A NL2022249 A NL 2022249A NL 2022249 A NL2022249 A NL 2022249A NL 2022249 B1 NL2022249 B1 NL 2022249B1
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/012—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from other sources than vehicle or roadside beacons, e.g. mobile networks
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
Abstract
In a method and system for determining movements of physical entities in a part of a geographic region comprising a plurality of geographic areas, numbers of movements of entities moving between areas during a predetermined time period are acquired based on time and location data of mobile stations. Based on census data associated with the areas, numbers of movements of entities moving within individual areas are determined. At least one of the areas is divided into zones and, based on census data associated with the zones, numbers of movements of entities moving between different zones and within zones are determined. Values of a travel parameter for the movements of entities related to the zones are determined and used to increase the number of movements related to the zones. The lower the value of the travel parameter of the movements is, the more the number of movements is increased.
Description
P33633NLOO/STR/ME Method and system for determining movements of physical entities in a part of a geographic region
FIELD OF THE INVENTION The invention relates to the field of traffic analysis methods and systems, in particular to a method and system for determining movements of physical entities in a part of a geographic region.
BACKGROUND OF THE INVENTION Knowledge about traffic flows in a geographic region during predetermined time periods is desired for many purposes, such as transportation infrastructure planning and maintenance, traffic flow regulation, traffic flow prediction, etc.
To perform traffic flow analysis or estimation, in the art transport models are built, comprising an origin-destination or OD matrix for a particular time interval and for a particular geographic region. Reference is e.g. made to “Modelling Transport” by Juan de Dios Ortúzar & Luis G. Willumsen, ISBN 978-0-470-76039-0, for a general introduction to transport models and the use of OD matrices. The geographic region is divided into a plurality of areas. Trips made from an origin, O, area to a destination, D, area, of the geographic region are represented as elements of the OD matrix. The OD matrix is a representation of numbers of physical entities (such as persons and vehicles, including freight vehicles) moving between different areas of the geographic region.
It is known to determine the movement of physical entities using data generated by mobile stations of a communication network, which mobile stations move together with the physical entities. In particular, mobile phones carried by people may provide time and location data which can be used to locate the physical entity and its movement in a time interval. Reference is made to N. Caceres, J. Wideberg, and F. Benitez “Deriving origin destination data from a mobile phone network”, Intelligent Transport Systems, IET, Vol. 1, No. 1, pp. 15-26, 2007, describing a mobility analysis simulation of moving vehicles along a highway covered by a plurality of GSM network cells. One vehicle may be associated with one or more mobile stations, depending on the number of passengers in the vehicle.
In a communication network, mobile stations communicate with a base station. The base station handles communication with mobile stations in a cell, which covers a geographic
-2- cell area. A mobile communication network comprises a plurality of cells, which may be described by a cell plan. The sizes of the cells may vary from less than 100 meters to many kilometers. Cells may overlap each other to some degree to provide full coverage over a geographic region covered by the cells. Movement of a mobile station can be detected if the mobile station is detected in different cells at different times.
Based on the cell plan and the coverage of the different base stations, an aggregate cell plan may be made, which reflects the smallest area sizes between which movements of mobile stations can be detected reliably. From the aggregate cell plan, an OD matrix of the movements of the mobile stations between different areas may be created. An OD matrix represents movements between geographic areas in a region, wherein an area may be associated with a municipality, a district, a city or part thereof. To arrive at an OD matrix which reproduces the movement of the total population of mobile stations, the values in the OD matrix need to be adjusted, e.g. based on subscription rates for specific providers and the number of inhabitants in the different cells or areas of the aggregate cell plan. Thus, a base weighted OD matrix may be obtained. Herein, wherever an OD matrix is referred to, a base weighted OD matrix is intended.
However, by relying on mobile station data, the sizes of the areas in the aggregate cell plan may be too large for a detailed traffic analysis. The level of spatial detail or granularity of the base weighted OD matrix may not be sufficient to determine numbers of physical entities moving on all traffic links directly from the mobile station data. Also short- distance trips are not present or at least under-represented in the base weighted OD matrix due to the sizes of the cells of the aggregate cell plan.
Accordingly, a need remains to improve methods and systems for traffic analysis, wherein in an efficient manner a high spatial detail can be obtained.
SUMMARY OF THE INVENTION The present invention provides a method and a system to estimate traffic, or movement of physical entities, in an efficient manner, and with a high spatial detail.
In a first aspect of this invention, a method for determining movements of physical entities in a part of a geographic region is presented. The geographic region comprises a plurality of geographic areas and a plurality of cells of a mobile communication network,
-3. wherein the areas do not overlap, and the cell do overlap. The method comprises the steps of: (a) acquiring, based on time and location data of mobile stations associated with the respective physical entities in the region during a predetermined time period, numbers of movements of the physical entities moving between different ones of the areas during the predetermined time period, wherein the mobile stations are associated with the respective cells of the mobile communication network; {b) determining, based on census data associated with the areas, numbers of movements of physical entities moving within individual areas during the predetermined time period; {c) dividing at least one of the areas into a plurality of zones and, based on census data associated with the zones, determining numbers of movements of physical entities moving between different ones of the zones within the same area; (d) determining values of a travel parameter for the movements of physical entities related to the zones, wherein each value is determined based on a travel time, or a travel distance, or a fixed value, or any combination thereof, wherein there is a positive correlation between the value and the travel time, and between the value and the travel distance; and (e) increasing, based on the determined values of the travel parameter, the number of movements related to the zones, wherein the lower the value of the travel parameter of the movements is, the more the number of movements is increased.
The method according to the invention, step (a), is based on time and location data acquired from a mobile communication network, instead of on a transport model. Within a secure environment of a telecom provider, time and location data of mobile stations may be derived from call detail records, CDRs (sometimes also referred to as call data records), and event detail records, EDRs (sometimes also referred to as event data records), of the mobile communication network.
A CDR contains data fields that describe a specific instance of a communication transaction, but does not include the content of that transaction. A CDR may contain attributes such as: the phone number of the subscriber originating the call (calling party, A-party), the phone number receiving the call (called party, B-party), the starting time of the call (date and time), the call duration, the billing phone number that is charged for the call, the identification of the telephone exchange or equipment writing the record, a unique sequence number identifying the record,
-4- additional digits on the called number used to route or charge the call, the disposition or the results of the call, indicating, for example, whether or not the call was connected, the route by which the call entered the exchange, the route by which the call left the exchange, call type (voice, SMS, etc.), any fault condition encountered.
Through EDRs, a variety of parameters of mobile station use like duration, data volume, web site/content accessed, quality of service per flow, per event, per ad etc. are recorded in real time.
The CDR and EDR data comprise all contact events between a mobile station and a base station, e.g. by initiating or receiving a call, sending or receiving a short message, SMS, or any data traffic.
Within the secure environment of at least one telecom provider, behind a fire wall of the telecom provider, this information is converted to representative levels, possibly taking into account information about other providers, ways of transport, etc., and assigned to the different areas, where there is a predetermined relationship between each base station and an area. The converted information is acquired from the telecom provider in the form of data representing an OD matrix by exporting the data from the secure environment.
Thus, part of the data aggregated in the mobile communication network may be processed, for security and privacy reasons, at a telecom provider, after which anonymized data may be acquired in, and further processed according to the method of the present invention, including steps (b) to (e) above.
The acquisition of data from the mobile communication network may be in real-time, or over a predetermined past time period, such as a part of an hour, one or more hours, one or more days, one or more weeks, or even longer, depending on the required topicality of the numbers of movements of the physical entities.
Based on the mobile communication network data, the present method may provide accurate determination of movements or flows of physical entities, such as vehicles, cars, bicycles, drones, persons, etc., in a certain time period, which may be a part of a day, or even a part of an hour. The method thus provides semi real-time determination of traffic flow, up to the detail of a single traffic link or part thereof.
-5.
In the present method, census data are applied. The census data comprise at least one set of data of the group of census data comprising a set of population data (such as representing (a distribution of) people living in a geographic area), a set of employment data (such as representing working places in a geographic area), a set of learning place data {such as representing (a distribution of) people learning in companies or going to school in a geographic area), a set of shop data (such as representing (a distribution of) shops in a geographic area), and a set of vehicle ownership data (such as (a distribution of) vehicles based or owned in a geographic area).
In traffic modelling, index numbers are used for each area to estimate the amount of traffic (number of movements of physical entities) which the area produces (the number of departures) or attracts (the number of arrivals). In the modelling, the index number is multiplied by a variable from the census data to estimate the traffic, or a linear combination of different index numbers multiplied by different variables may be made. This may be represented in a formula for the departures D; in area i, using index numbers a, az, ... (also referred to as trip end coefficients) with corresponding amounts of the census variables Xs, Mai, ...: Di=a Xyi+az Xo...
Similarly, a formula for the arrivals A; in area i, using index numbers by, bz, ... {also referred to as trip end coefficients) with corresponding amounts of the census variables Xs, Xai, ...: Ai= bi Xqi+b Xai...
The index numbers for the departures may differ from the index numbers of the arrivals.
As an example, during a morning rush, for the census variable residents, the index number for departures is high and for arrivals is low. By contrast, during an evening rush the index number for departures is low and for arrivals is high. As a further example, for the census variable working places, during a morning rush the index number for departures is low and for arrivals is high, and during an evening rush the index number for departures is high and for arrivals is low.
For a twenty-four hours period, index numbers for departures and arrivals may be equal.
The census data are applied in different steps of the present method.
In step (b), particular census data may be associated with particular areas, wherein for different areas different census data, or combinations of census data, may be used, in
-6- combination with intra-area coefficients representing the intra-area traffic. In step (b), no time and location data of mobile stations are used. In the present method, in particular step (c), at least one area is divided (disaggregated) into a plurality of, i.e. at least two, zones. A zone is a geographic area that may be suited to determine movements of physical entities on a particular transport link or part thereof extending in the zone. Based on census data associated with the zones, numbers of movements of physical entities moving between zones are determined. The total number of movements related to the at least one area remains the same as established before. Furthermore, numbers of movements of physical entities moving within individual zones may be determined. In step (c), particular census data may be associated with particular zones. For determining the number of movements of physical entities moving from zones to other zones within the same area, interzonal coefficients representing interzonal traffic may be used, or fractions of trip end coefficients of the associated area may be used, and no time and location data of mobile stations are used. For determining the number of movements of physical entities moving within a zone, intrazonal coefficients representing the intrazonal traffic may be used, or fractions of trip end coefficients of the associated area may be used, and no time and location data of mobile stations are used. In some embodiments of the method, the census data associated with zones may be identical to the census data associated with the area of which the zones form part.
The numbers of movements associated with a zone may be determined by associating a fraction (a number between zero and one) of the movements to or from or within an area comprising the zone, wherein the fraction may be determined by the census data. For example, if a zone has twice the population compared to another zone within the same area, twice the number of movements may be assigned to the zone with the larger population in comparison to the zone with the smaller population. For an area, the sum of the fractions of all zones of the area is equal to one. In step (d), a value of a travel parameter is determined. The travel parameter is a measure of a time and/or distance of one or more movements. The value of the travel parameter may be positively correlated to the travel time and/or travel distance of one or more movements, meaning that the longer the travel time and/or travel distance of the one or more movements is, the higher the value of the travel parameter is. A relationship between the value of the travel parameter and the travel time and/or travel distance of the one or more movements may be predetermined through a mathematical function or a look-up table. The values of the travel parameter for movements related to zones may be based on the time and location data of the mobile stations, and also may be based on a distances
-7- between different areas, on distances between different zones, and on distances between areas and zones.
The value of the travel parameter may be a linear or non-linear combination of travel time and travel distance. Additionally or alternatively, the value of the travel parameter may comprise a constant value component.
In step (e), based on the determined values of the travel parameter, the number of movements related to zones is increased, wherein the lower the value of the travel parameter of the movements is, the more the number of movements is increased (in other words: the increase of the number of movements related to zones is non-positively correlated to the value of the travel parameter of the particular movements), to thereby mare accurately determine movements of physical entities in a zone.
In an embodiment of the present method, step (c) further comprises the steps of determining numbers of movements of physical entities moving from zones of one of the areas to another area, and from zones of one of the areas to zones of another area, and from one of the areas to zones of another area. In addition to using census data, also time and location data of mobile stations may be used for determining the number of movements of the physical entities.
In an embodiment of the present method, in step (d), the movements of physical entities related to the zones may comprise any movements of movements between areas, movements within areas, movements between zones, movements within zones, and movements between areas and zones.
In an embodiment of the present method, the numbers of movements in one of the zones and between different zones within the predetermined time period are assigned to a transport link or a part thereof extending in said one of the zones.
In an embodiment of the present method, the numbers of movements are represented as elements of an origin-destination, OD, matrix. In particular, this embodiment comprises the steps of: associated with step (a), acquiring non-diagonal elements of the OD matrix representing numbers of movements of physical entities moving between different ones of the areas during the predetermined time period;
-8- associated with step (b), determining diagonal elements of the OD matrix representing numbers of movements of physical entities moving within individual areas during the predetermined time period; associated with step (c), disaggregating the OD matrix, and filling the disaggregated OD matrix with elements representing numbers of movements of physical entities moving between different ones of the zones within the same area; and associated with step (e), and based on the determined values of the travel parameter, increasing at least some of the elements of the disaggregated OD matrix to obtain an enhanced disaggregated OD matrix, wherein there is a positive correlation between the value and the travel time, and between the value and the travel distance.
In a second aspect of the invention, a system for determining movements of physical entities in a part of a geographic region is provided.
The geographic region comprises a plurality of geographic cells of a mobile communication network.
The system comprises an input component, a storage component, at least one processor, and an output component, wherein the input component, the storage component, the at least one processor, and the output component are operatively coupled.
In the system: the input component is configured to: acquire, based on time and location data of mobile stations associated with the respective physical entities in the geographic region during a predetermined time period, numbers of movements of physical entities moving between different ones of the areas during the predetermined time period, wherein the mobile stations are associated with the respective cells of the mobile communication network; the storage component is configured to: store census data; the at least one processor is configured to: determine, based on census data associated with the areas, numbers of movements of physical entities moving within individual areas during the predetermined time period; divide at least one of the areas into a plurality of zones and, based on census data associated with the zones, determine numbers of movements of physical entities moving between different ones of the zones within the same area; determine values of a travel parameter for the movements of physical entities related to the zones, wherein each value is determined based on a travel time, or a travel distance, or a fixed value, or any combination thereof,
-9- wherein there is a positive correlation between the value and the travel time, and between the value and the travel distance; and increase, based on the determined values of the travel parameter, the number of the movements related to the zones, wherein the lower the value of the travel parameter of the movements is, the more the number of movements is increased, and the output component is configured to: output a movements indicator indicating the number of movements of the physical entities in the part of the geographic region.
A system according to the second aspect of the invention may be used to obtain better insights in the traffic within a city or part thereof, and in other parts of geographic regions, and to determine for example whether, from a traffic perspective, certain areas in a city are strongly or weakly linked.
The system may also be used to obtain intensities of the traffic, to determine whether the current road system needs to be adjusted. Also, the traffic intensity may be linked to air quality and noise, facilitating traffic planning.
These and other aspects of the invention will be more readily appreciated as the same becomes better understood by reference to the following detailed description and considered in connection with the accompanying drawings in which like reference symbols designate like parts.
BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 depicts an example of a geographic region, showing an aggregate cell plan of a mobile communication network.
Figure 1a depicts an example of an aggregate cell plan.
Figure 2 illustrates an OD matrix of a geographic region comprising three areas, wherein numbers of movements between different areas are represented by off-diagonal OD matrix elements.
Figure 3 illustrates the OD matrix of the geographic region underlying Figure 2 and comprising three areas, wherein additionally numbers of movements within the three areas are represented by diagonal OD matrix elements.
Figure 4 depicts an example of the geographic region of Figure 1, further showing a plurality of zones in each cell of the aggregate cell plan of the mobile communication network.
-10- Figure 4a depicts the aggregate cell plan of Figure 1a, wherein some areas are divided into zones. Figure 5 illustrates a disaggregated OD matrix based on the OD matrix of Figure 3. Figure 6 depicts a decay curve. Figure 7 depicts a flow diagram of an embodiment of a method for determining movements of physical entities in a part of a geographic region Figure 8 depicts a block diagram of an embodiment of a system for determining movements of physical entities in a part of a geographic region.
DETAILED DESCRIPTION OF EMBODIMENTS Figure 1 shows a geographic region 1 delimited by a dashed line. The geographic region 1 is covered by a mobile communication network having a cell plan. Each cell of the mobile communication network is covered by a base station. The cell plan is mapped to an aggregate cell plan comprising a plurality of geographic areas 2 each delimited by a solid line, and each being associated to a different base station. The areas 2 are adjacent to each other, and do not overlap. Mobile stations within the geographic region 1 connect to one of the base stations, such that the location of the mobile station can be determined to be in one of the areas 2 corresponding to the respective base station. Upon movement of the mobile station, the mobile station may connect to different base stations, and a movement (indicated by a dashed line) of the mobile station from an origin area 2a to a destination area 2b may be established. Mobile stations are presumed to be associated with physical entities, such as persons, vehicles, etc., so that movement of a mobile station corresponds to movement of the associated physical entity. Thus, the time and location data of mobile stations associated with the respective physical entities in the geographic region 1 during a predetermined time period may indicate movement of the mobile station and its associated physical entity between different areas 2, 2a, 2b, so at the spatial level of the areas 2, 2a, 2b. If such movements of physical entities, sometimes also called intra-area trips, are determined, they may be grouped to form numbers of movements of physical entities moving from an origin area 2a to a destination area 2b during the predetermined time period. Time and location data of mobile stations are derived from call detail records, CDRs, and event detail records, EDRs, of the mobile communication network. This process may take place in a secure environment of one or more telecom providers, where numbers of movements of physical entities may be determined from the CDR and EDR data. The
-11 - numbers of movements constitute anonymous or anonymized data, and can be used outside the secure environment of the one or more telecom providers.
Figure 1a shows an exemplary geographic region 5 comprising three areas 10, 20, 30 for ease of explanation.
Figure 2 illustrates the construction of an OD matrix of the exemplary geographic region 5 of Figure 1a, comprising the three areas 10, 20, 30, wherein numbers of movements of physical entities, as evidenced by time and location data of mobile stations (not shown) associated with the physical entities, between different areas 10, 20, 30 are represented by off-diagonal OD matrix elements. In other words, all OD matrix elements with the exception of the diagonal OD matrix elements represent numbers of movements from an origin area to a destination area. The OD matrix comprises 3 rows (i=1... 3) and 3 columns (j=1... 3). A number of movements from an i" area to a j" area is represented by Ti, where the 15! area is area 10, the 2" area is area 20, and the 3" area is area 30. As an example, a number of movements from area 10 to area 20 is represented by T12. Within each area 10, 20, 30, movements cannot be detected by time and location data of the mobile stations, and therefore the diagonal OD matrix elements initially are equal to 0 (Ti; = 0 if i = j).
The OD matrix may be constructed inside the secure environment of a telecom provider, or aggregated from several preliminary OD matrices originating from different telecom providers.
As illustrated in Figure 3, according to the present invention, the diagonal OD matrix elements of the OD matrix of the exemplary geographic region according to Figure 1a and comprising three areas 10, 20, 30, are further determined. The diagonal OD matrix elements Ti; wherein i = j, represent the numbers of movements within the three areas 10, 20, 30. As an example, a number of movements within area 20 is represented by T22. The numbers of movements of physical entities moving within individual areas 10, 20, 30 during the predetermined time period are determined based on census data associated with the areas 10, 20, 30, wherein census data comprise at least one set of data of the group of census data comprising a set of population data (such as the number of people living in the individual areas, or the number of subscribers of one or more mobile communication networks in the individual areas), a set of employment data (such as the number of people working in the individual areas), a set of learning place data (such as the number of people learning in companies or going to school or university in the individual areas), a set of shop data (such as the number of people visiting shops in a geographic area), and a set of vehicle ownership
-12- data (such as the number of vehicles based or owned in a geographic area). Relationships between the census data and the number of movements within the individual areas 10, 20, 30 are based on existing transport modelling knowledge, e.g. as explained in “Modelling Transport” by Juan de Dios Ortúzar & Luis G. Willumsen, ISBN 978-0-470-76039-0.
Figure 4 shows the geographic region 1 of Figure 1, further showing a plurality of zones 3 in each area 2 of the aggregate area plan of the mobile communication network. Accordingly, at least one area 2 may be divided into a plurality of zones 3. Then, based on census data associated with the zones 3, numbers of movements of physical entities moving from zones 3 to other zones 3 within the same area 2, and numbers of movements of physical entities moving within the individual zones 3 are determined. This is reflected in a disaggregation of the OD matrix, as explained below by reference to Figure 5.
Figure 4a shows the exemplary geographic region of Figure 1a comprising three areas 10, 20, 30, wherein area 10 is divided into two zones 11, 12, area 20 remains undivided, and area 30 is divided into three zones 31, 32, 33. In the construction of the corresponding disaggregated OD matrix, accordingly the number of matrix elements increases, providing an improved granularity of the OD matrix, describing the number of movements in the geographic region, and the areas thereof, in more detail. In particular, numbers of movements of physical entities moving from zones of one of the areas to zones of another area, and from zones of one of the areas to zones of another area, and from one of the areas to zones of another area are determined.
The numbers of movements associated with a zone may be determined by associating a fraction (a number between zero and one) of the movements to or from or within an area with the zone, wherein the fraction is determined by the census data. For example, if one of the zones has twice the population compared to another zone within the same area, twice the number of movements may be assigned to the zone with the larger population in comparison to the zone with the smaller population. For an area, the sum of the fractions of all zones of the area is equal to one.
Figure 5 illustrates a disaggregation of the exemplary 3x3 OD matrix illustrated in Figure 3, as a result of dividing area 10 into zones 11, 12, and dividing area 30 into zones 31, 32, 33. An exemplary 6x6 disaggregated OD matrix results.
Using census data, the number of movements of physical entities of the areas 10, 20, 30 are disaggregated by applying fractions f and g based on such census data of the zones 11, 12, 31, 32, 33 being origin or destination zones, respectively, so that zones 11 and 12 as origin zones of area 10 are associated with fractions f1: and f:2, respectively, and zones 31,
-13- 32 and 33 as destination zones of area 30 are associated with fractions f31, f32 and fss, respectively. Zones 11 and 12 as destination zones of area 10 are associated with fractions 1: and giz, respectively, and zones 31, 32 and 33 as destination zones of area 30 are associated with fractions g3:, g:2 and gss, respectively. The fractions f and g within an area 10,30 sum up to 1. The exemplary disaggregated OD matrix comprises 6 rows (y = 1 ... 8) and 6 columns (z=1... 6). A number of movements from an y" area or zone to a z!" area or zone is represented by X,,. As an example, a number of movements from zone 11 to area 20 is represented by Xi4 20, wherein X31.29 = f11 * g20 * T12. Here, since area 20 is not divided, g29 =
1. The total number of movements of physical entities per origin-destination pair of the areas 10, 20, 30 remains the same in the disaggregated OD matrix, for example: T1s = Z(i = 11 to 12) (Z(j = 31 to 33) (Xi). The disaggregated OD matrix is enhanced by determining values of a travel parameter t for the movements of physical entities related to the zones 3, 11, 12, 31, 32, 33. Here, a value of the travel parameter t may be representative for a travel time or travel distance for the movements of physical entities related to zones. Other choices, e.g. incorparating both the travel time and the travel distance into the value of the travel parameter t are also possible. The enhancement comprises increasing, based on the determined values of the travel parameter t, the number of the movements related to the zones, wherein the lower the value of the travel parameter t is, the more the number of movements is increased. The movements of physical entities related to zones comprise movements between areas, within areas, between zones, within zones, and between areas and zones.
In the disaggregated OD matrix, the relevant numbers of movements are multiplied by a factor F > 1, as illustrated in Figure 6, which is non-positively correlated with the value of the travel parameter t. Other non-positively correlated relationships between the factor F and the value of the travel parameter t are possible.
Accordingly, an enhanced disaggregated OD matrix is obtained. Using a common transport modelling technique, the numbers of movements in and between zones during said predetermined time period are assigned to a transport link or part thereof extending in the zone. In the art, e.g. in “Modelling Transport” by Juan de Dios Ortúzar & Luis G. Willumsen, ISBN 978-0-470-76039-0, these assignments to transport links or parts thereof may be referred to as an ‘assignment procedure’.
-14 - As illustrated in Figure 7, the method as explained above comprises the following steps.
In a step 41, based on time and location data of mobile stations associated with the respective physical entities in the geographic region during a predetermined time period, numbers of movements of the physical entities moving from areas to other areas during the predetermined time period are acquired. The mobile stations are associated with the respective cells of a mobile communication network.
In a step 42, based on census data associated with the areas, numbers of movements of physical entities moving within individual areas during the predetermined time period are determined.
In a step 43, at least one of the areas is divided into a plurality of zones and, based on census data associated with the zones, numbers of movements of physical entities moving from zones to other zones within the same area, and numbers of movements of physical entities moving within the individual zones are determined.
In a step 44, a value of the travel parameter t for the movements of physical entities related to the zones is determined. Each value is determined based on a travel time, or a travel distance, or a fixed value, or any combination thereof, wherein there is a positive correlation between the value and the travel time, and between the value and the travel distance.
In a step 45, based on the determined values of the travel parameter, the number of movements related to the zones is increased, wherein the lower the value of the travel parameter of the movements is, the more the number of movements is increased.
In an optional step 46, the numbers of movements in one of the zones and between different zones within the predetermined time period are assigned to a transport link or a part thereof extending in said one of the zones.
Figure 8 shows a block diagram of an embodiment of a system 50 for determining movements of physical entities in a part of a geographic region, for implementing the method explained above with reference to Figure 7, on a computer system. As before, the geographic region comprises a plurality of geographic areas of a mobile communication network.
The system 50 comprises an input component 51, a storage component 52, at least one processor 53, and an output component 54, wherein the input component 51, the storage component 52, the at least one processor 53, and the output component 54 are operatively coupled as indicated by solid lines. In particular, the input component 51 is coupled to the at least one processor 53 to provide input data to the at least one processor 53 for processing of the input data by the at least one processor 53. The storage component
-15- 52 is coupled to the at least one processor 53 to input stored data to the at least one processor 53 for processing of the stored data by the at least one processor 53. The output component 54 is coupled to the at least one processor 53 to receive output data from the at least one processor 53.
In some embodiments, the terms input component, storage component and output component indicate software, possibly implemented in firmware, the software comprising computer instructions which, when loaded in the at least one processor 53, cause the at least one processor 53 to perform an input function, storage function or output function, respectively, as explained below.
In other embodiments, the terms input component, storage component and output component indicate a combination of hardware and software, possibly implemented in firmware, the software comprising computer instructions which, when loaded in the at least one processor 53, cause the at least one processor 53 to perform an input function, storage function or output function, respectively, as explained below.
In all embodiments, the at least one processor 53 comprises hardware and software.
The input component 51 is configured to acquire, based on time and location data of mobile stations associated with the respective physical entities in the geographic region during a predetermined time period, numbers of movements of physical entities moving from areas to other areas during the predetermined time period. The mobile stations are associated with respective cells of a mobile communication network.
The storage component 52 is configured to store census data. The at least one processor 53 is configured to determine, based on data acquired by, and received from the input component 51, and based on census data associated with the areas, and received from storage component 52, numbers of movements of physical entities moving within individual areas during the predetermined time period; divide at least one of the areas into a plurality of zones and, based on census data associated with the zones, and received from storage component 52, determine numbers of movements of physical entities moving from zones to other zones within the same area, and numbers of movements of physical entities moving within the individual zones; determine values of a travel parameter for the movements of physical entities related to the zones, wherein each value is determined based on a travel time, or a travel distance, or a fixed value, or any combination thereof, wherein there is a positive correlation between the value and the travel time, and between the value and the travel distance; and increase, based on the determined values of the travel parameter, the number of the movements related to the zones, wherein the lower the value of the travel parameter of the movements is, the more the number of movements is increased.
-16 - The output component 54 is configured, based on the output of the at least one processor 53, to output a movements indicator indicating the number of movements of the physical entities in the part of the geographic region. In a basic form, the movements indicator is a number.
As explained in detail above, in a method and system for determining movements of physical entities in a part of a geographic region comprising a plurality of geographic areas, numbers of movements of entities moving between areas during a predetermined time period are acquired based on time and location data of mobile stations. Based on census data associated with the areas, numbers of movements of entities moving within individual areas are determined. At least one of the areas is divided into zones and, based on census data associated with the zones, numbers of movements of entities moving between different zones and within zones are determined. Values of a travel parameter for the movements of entities related to the zones are determined and used to increase the number of movements related to the zones. The lower the value of the travel parameter of the movements is, the more the number of movements is increased.
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 can 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. Further, the terms and phrases used herein are not intended to be limiting, but rather, to provide an understandable description of the invention.
The terms "a"/"an", as used herein, are defined as one or more than one. The term plurality, as used herein, is defined as two or more than two. The term another, as used herein, is defined as at least a second or more. The terms including and/or having, as used herein, are defined as comprising (i.e., open language, not excluding other elements or steps). Any reference signs in the claims should not be construed as limiting the scope of the claims or the invention.
The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.
A single processor or other unit may fulfil the functions of several items recited in the claims.
Claims (12)
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