CZ20011464A3 - Method for determining driving times and driving time prognoses in a transport system by making use of cellular telephone positioning and a system for making the same - Google Patents

Abstract

A traffic network is topologically defined together with its individual section (1) to (n) and node points, minimum specified speeds Vset 1 to n of mobile telephones moving within these sections are defined for the selected traffic network and its individual sections (1) to (n). From all positioned mobile telephones, a set of mobile telephones located close to or directly within the defined sections (1) to (n) of the traffic network is topologically evaluated. From the set of mobile telephones located close to or directly within the defined sections (1) to (n) of the traffic network, subsets (MT1 to n) of mobile telephones moving within defined sections (1) to (n) at speeds Vmob 1 to n are topologically evaluated, with the subsets (MT 1 to n) of mobile telephones moving at speeds V mob 1 to n including all telephones meeting the condition Vmob for the section in question >Vset for the section in question, ans subsequent mathematical evaluation of travel times between node points of sections 1 to n of the traffic network.

Description

Technical field

The invention relates to a method for determining travel times and travel time forecasts in a transport network using mobile phone positioning and a system for carrying out the method.

BACKGROUND OF THE INVENTION

In particular, the following technological equipment is used to determine travel times in the road transport network:

- sensing of passing vehicles by means of induction loops

- sensing of passing vehicles using video cameras with evaluation and registration of license plate

- scanning of passing vehicles by video cameras with evaluation of transport parameters (speed, dimensions of the vehicle, ...)

- scanning of passing vehicles by means of lasers

- sensing of passing vehicles by means of radar sensors

- sensing of passing vehicles by means of infrared sensors

- sensing of passing vehicles by means of sound sensors

All of the above technologies have the following disadvantages:

- They require the establishment of costly special infrastructure at transport network checkpoints

- Checkpoints must be numerous - thousands of checkpoints for a medium-sized European state.

- All of the above devices, except for license plate video recognition, are not able to perform directional counts (ie where the vehicle goes through multiple checkpoints, since the vehicle remains anonymous only with traffic data such as speed, vehicle category, passenger or freight etc.). )

Some travel time traffic information providers combine checkpoint devices with dedicated identification devices that provide additional location and motion information as a supplement to fixed checkpoint information while serving as a traffic news receiver for the provider. However, these services use only high-end means of transport and the following disadvantages result:

- the set of onboard identification devices is limited

-2-on-board identification devices are mainly installed in passenger cars of a higher category, which have very reduced traffic at night and information on night traffic is then severely limited

SUMMARY OF THE INVENTION

The disadvantages of the known solutions are overcome by the method of determining travel times and travel time forecasts in the transport network using the mobile phone positioning according to the invention, which is based on the topological definition of the transport network and its sections with nodal points. Nodal points are understood as eg towns, municipalities, intersections, etc., the section is a route between nodal points. For the selected transport network and its individual sections, the minimum set speeds of moving mobile phones along these sections are defined. Moving mobile phone refers to the movement of persons with mobile phones in vehicles. A set of mobile phones adhering to defined sections of the transport network is topologically evaluated from all positioned mobile phones. From a plurality of mobile phones adhering to defined sections of the transport network, a subset of moving mobile phones along the defined speed segments V _mob i n is evaluated topologically, and all mobile phones meeting the condition V _mob are included in the subset of moving mobile phones at Vm _{Ob 1 to n} respective section> In the _settings of the current section, and then mathematically evaluate travel times between nodes of transport network.

According to a further embodiment of the invention, the forecasts of these travel times between the individual nodes of the transport network are processed and evaluated from the evaluated travel times between the nodes of the transport network using knowledge of the elapsed behavior of the transport network and supplemented with known current transport conditions, especially traffic congestion. , accidents, closures.

The system for carrying out the method comprises a communication and computing device of the mobile telephone network operators, which comprises a network of GSM base radio stations and a stationary central dispatching center for evaluating the positioning of the mobile phones. The communication and computing device of mobile phone network operators is assigned an evaluation device for topological evaluation of moving mobile phones assigned to the transport network, from which the evaluated data of moving mobile phones are passed to the computing device for evaluation and forecasting travel times between nodes of the transport network.

Among the main advantages of the invention is the socially requested information about travel times provided to the traveling public, which is well measured and predicted by this invention, even for a large and complicated transport network. In order to obtain driving times, it is not necessary to equip the vehicles with any additional identifiers - eg transponders, but it is sufficient to monitor a sufficient number of mobile phones of persons present in moving means of transport. Furthermore, it is not necessary to set up an extensive and expensive special network of traffic control points to measure and predict traffic flow behavior. The present invention suffices for these purposes

-3 with completion of a high-quality computing center of the evaluation device for the topological evaluation of moving mobile phones assigned to the transport network and the computing center of the device for the evaluation and forecasting of travel times. Both of these units are based on computers and high-quality dedicated software. Moreover, the existing network of mobile phone operators is better used for this new purpose.

The widespread distribution of travel time information has great socio-economic benefits especially when the traveling public loses their productive time by traveling in a complicated section of the transport network due to congestion, etc. With timely information it is possible to choose a substitute route or reorganize the work program and do not enter the complicated section at all in a complicated time. Furthermore, the travel time forecast can be used to more accurately plan the travel time required for travel on the transport network. The informed traveling public is not exposed to the necessity of scheduling with a large margin, nor is it exposed to the stresses and losses caused by possible underestimation of the time consuming movement on the transport network. In this way, work productivity can be directly promoted and unnecessary waste of time can be avoided, which can then be spent on work, entertainment and relaxation. Selected information according to the dynamic travel time model can be provided to the traveling public, for example in the form of radio broadcasting, information boards, pagers or GSM phones. The calculation of a specific travel time can also be provided on the basis of a demand mode, when the user requests a specific travel time between selected points of the transport network.

Overview of the drawings

Giant. 1 schematically illustrates a transport network with nodal points; FIG. 2 illustrates a transport network of FIG. 1 with sections between nodal points and minimum set mobile phone speed parameters for individual sections of a transport network; Fig. 4 shows the transport network with the positioning mobile telephones adhering to the individual sections of the network with the speed of mobile phone movement greater than the set parameter of the minimum speed of mobile phones for the individual sections; Fig. 5 shows the transport network for calculation 6 shows the historically measured travel time of one section of the transport network according to FIG. 5; FIG. 7 shows a system for carrying out the method.

Examples

Giant. 1 to 4 characteristically illustrate a procedure for selecting moving mobile phones over a transport network to determine travel times between individual nodes of the transport network. The movement of mobile phones is to be understood as the movement of persons with mobile phones in means of transport.

-4Fig. 1 and 2 illustrate a topologically defined transport network, e.g., with seven sections 1 to 7 and their nodes A, B, C, D, E. Node points are cities, municipalities, intersections, etc. GSM base station transmitters 11, 1 on this selected transport network, they monitor the positioning of all MT mobile phones and the data is collected in the evaluation device 12 of the mobile network operators (FIG. 7). For that selected transport network for each of its individual section 1-7 between node points A, B, C, D and E define the minimum speed setting _sett is from ₁ to 7 moving mobile telephones, ie., For segment 1, between for node points A and C, speed V _nas t 1 is set, for section-2 between node points B and C, speed V _nas t 2 is set, for section 3 between node points C and D is set speed V _n and _S t 3 etc. ., up to section 7 between node points D and E is set in the _NAS t 7.

The _wizard Iaz velocity for individual sections 7 1-7 a specific absolute velocity set for the time period and the transport network. Its value is subject to many influences and is obtained statistically and empirically to match the minimum speed of the traffic flow in a given section and time. Depending on the time - rush hour, afternoon rush, saddle, accident, congestion, its value will be adjusted by the system. Thus, this condition serves as a filter for the selection of mobile phones in moving vehicles.

Of all coated mobile phones MT, a set MT1 to MT7 of mobile phones sliding to defined sections 1 to 7 between nodes A, B, C, D, E of the transport network is topologically evaluated in the evaluation device 12 associated with the device 11 . These sets MT1 to MT7 are shown in Figure 3 with a solid black square. For section 1 mobile phones 1.1, 1.2 to 1.n are included in MT1, for section 2 mobile phones 2.1, 2.2 to 2.n are included in MT2, and up to section 7 mobile MTs 7.1, 7.2 to 7.n

From the sets MT1 to MT7 of mobile phones interconnected for each defined section 1 to 7 of the transport network, subsets MT1.1 to MT1.7 of moving mobile phones are evaluated topologically in the evaluation device 12 at the speed V _mO b 1 to 7, for each section 1 to 7 it holds that V _mO b of the relevant section> V _nas t of the relevant section, ie Vm _Ob 1> V _set 1, Vmob 2> V _set 2 to V _mob 7> V _{set 7} . Do these subsets MT1.1 to MT1.7 not already covered by mobile phones indicated in Fig. 4, black square crossed that each section meets the conditions in the relevant section _mob> In _setting the appropriate section.

Of subsets MT1.1 to MT1.7 of mobile telephones moving individual sections 1 to 7 defined by the transport network and satisfying the conditions in the respective section mot> _us t relevant section is then in computing equipment 13 mathematically evaluate the running time slots 1-7 between individual nodes A, B, C, D, E of the transport network.

The journey time t _A c of section 1 is calculated from the subset MT1.1 of the moving mobile phones between nodes A and C (Fig. 4) according to the following procedure:

1. Exclude outliers from the data set V _mO bi to V _m ob n for section 1 The standard statistical test shall be used to exclude:

Student's test with alpha = 0.95

By eliminating outliers, vehicle speeds significantly different from conventional ones are eliminated. These are in particular:

- vehicles with low speed compared to normal - these can be vehicles with low operating speed, but it can also be caused by interruption of travel between route points

- vehicles with a significant increase in the normal cruising or authorized speed

2. The set of non-excluded data is subjected to a median calculation to obtain the most probable velocity V _me and the movement of vehicles in a given section. 1 The median is chosen because it gives more information about the mean speed of the vehicles while normal arithmetic mean really mean vehicle speed. The travel time t _A c between points A and C is then calculated:

section length 1 t _AC --------------------- V med 1

Similarly, the travel time of each section of the transport network between two nodes is calculated.

Example of calculation of travel time on a route longer than just between two nodes of the transport network, eg on the route given by nodes A, B, C, E, ie on three marked sections 5, 2, and 4 of the transport network. The driving time t _ABC E is evaluated - the route is marked with a thick line (fig. 5). After determining the subsets MT1.5, MT1.2 and MT1.4 of moving mobile phones by section, the procedure is as in the previous example for a simple calculation between two node points. Subsequently, however, can not be only a mathematical sum of the travel time T _AB + T _BC + TCE individual sections 5,2 and 4, but it is necessary to calculate, with the vehicle setting out on ABCE route at time t AB section will complete at time t _AB , but it does not enter BC until after t _{AB has} elapsed. For this reason, it is not possible to start from the current driving time tec, but it is necessary to use historical data according to the graph shown in Fig. 6. In this graph, whose horizontal coordinate shows the time of day t in hours and the vertical coordinate shows the travel time t _B c of section 2 in minutes, we can see the historically measured and calculated travel time tec. which usually has two peaks in the course of 24 hours - morning peak 20 and afternoon peak 21. Furthermore, there is a noon saddle 22, which reduces travel time. These waveforms depend on the density of traffic given time on that particular day. If we compare the standard course of this dependence between two comparable days (eg between two Mondays - 1st weekdays of the week), we find a great agreement, provided that on any of these days there is no significant anomaly caused, for example, by the winter calamity section of the transport network.

-6In Fig. 6, travel time tec is predicted according to historical graphs of computational travel time t _B c for a given time of the day td = t + UbFor explanation - measuring travel time in the transport network in a given section provides information about usual travel time - eg Monday period 8:00 to 9:00 between points B and C - t _B c. If these historical data are corrected for unexpected traffic anomalies such as accidents, poor passability or congestion in a given section, the total travel time can be calculated according to the formula:

AbABCE ⁼ tAB + tec at Time td = t + tab tcE at time td = t + tab + tbc

While the time in time td = t + tab + tbc is determined similarly as time tsc in time td = t + tab ·

The above formula can be applied to any route between individual points in the transport network with a high percentage probability on shorter combined sections, with decreasing probability on sections longer and longer. It therefore already includes an element of forecasting the overall travel time.

Claims (3)

PATENT CLAIMS 1. A method of determining travel times and travel time forecasts in a transport network using cell phone positioning, characterized in that a topology is defined for a transport network and its node-point sections (1) to (n) for a selected transport network and its individual sections (1) to (n) define the minimum set speeds V _n 1 to n of moving mobile phones along these sections, from all coated mobile telephones / topologically evaluate a plurality of mobile phones adhering to the defined sections (1) to (n) a transport network, from a plurality of mobile phones slipping along defined sections (V to (n) of a transport network), a subset of moving mobile phones along defined sections (1y to / n) is evaluated topologically at a velocity V _mO b 1 to n, moving mobile phones at speeds V _mO b 1 to n are included all mobile phones meet condition Vm _{Ob of the} relevant section> V _{set of} the section and then the travel times between the node points of the sections (Ijt to (n) of the transport network) are mathematically evaluated. Method according to claim 1, characterized in that a prediction of these travel times between these nodes of the transport network is processed from the evaluated travel times between the nodes of the transport network using knowledge of the elapsed behavior of the transport network and supplemented with known current traffic conditions. congestion, passability, accidents, closures. 3. A system for carrying out the method according to items 1 and 2 comprising communication and computing devices of mobile phone network perimeters, which evaluates coated mobile phones, characterized in that the communication and computing device (11) of mobile network operators comprises an evaluation device (12) For topical evaluation of moving mobile phones assigned to the network, the mobile data are evaluated by the computing device (13) for evaluating and predicting travel times between nodes. i · // .. · transport networks. ^of