METHOD, DEVICE AND COMPUTER PROGRAM FOR CONTROLLING THE FLOW OF ROAD PARTICIPANTS

Description

[0001] The invention relates to a method for controlling the inflow of a plurality of road users who are moving within a defined traffic area along a route towards a capacity-limited infrastructure.

[0002] The invention also relates to a computer program and a device for this purpose.

[0003] Within a transport network, where road users move within a traffic area, the infrastructures where these users begin or end their transport routes often represent a bottleneck, as these infrastructures can typically only process road users sporadically. This means that road users can only leave or arrive at the infrastructures one at a time.

[0004] Airports that are heavily frequented represent a bottleneck for the landing of commercial aircraft as road users, since each commercial aircraft is only allowed to land on the runway assigned to it within a certain time window.

[0005] For this reason, appropriate measures are necessary to manage infrastructure congestion in such capacity-limited systems. Depending on the specific system, two different types of measures are generally conceivable in practice. The first type involves storing the excess traffic that cannot currently use the infrastructure in a defined area upstream of the infrastructure itself. In aviation, this is done using holding patterns or route extensions (e.g., trombones). However, this has the disadvantage that the necessary detours result in unnecessary fuel consumption, leading to unnecessary environmental damage and increased costs. A similar situation arises in shipping when a port, being a capacity-limited infrastructure, becomes congested.The ships then have to wait in a certain area outside the port, e.g., the German Bight, until they are allowed to enter. This waiting time also results in unnecessary fuel consumption and thus additional environmental pollution, as maintaining position in shipping requires energy.

[0006] The second type of measure actively intervenes in the influx of arriving road users, adjusting the flow to the capacity-limited infrastructure. Excess road users are stored on the limited infrastructure and thus shifted to the route structure. This control is usually based on 4D trajectories, where waypoints must be reached at specific target times. However, in practice and in a real-world environment, such control systems encounter disruptions and inaccuracies in planning and implementation. If left uncorrected, these disruptions and inaccuracies in the road user flow lead to fluctuations and, consequently, to congestion or the failure to utilize available time slots on the limited infrastructure.Therefore, road users must constantly compensate for disruptions and inaccuracies to adhere to the plan as precisely as possible, thus ensuring the flow of traffic. The constant corrections required trigger continuous acceleration and deceleration of road users, increasing energy consumption and wear and tear. Furthermore, the measures required to maintain the plan, and their sheer number, lead to a significantly increased workload and complexity for those involved (e.g., traffic controllers).

[0007] From DE 602 06 785 T2 a method for managing the flight of a large number of aircraft is known by estimating the utilization of the system resource and continuously adjusting it by means of an objective function.

[0008] From DE 10 2004 050 988 A1, a pre-tactical control device for traffic management is known, which is intended for connection with a tactical control system for assigning traffic event times in order to comply with the target times of means of transport at defined traffic junctions. Target times for traffic events of individual means of transport at the defined traffic junctions are set within a pre-tactical control time horizon that is longer than a tactical control time horizon of the tactical control system and that includes at least one assigned traffic event time. The target times are then fed into the tactical control system as control parameters.

[0009] WO 2007 / 110 194 A1 discloses a method for the optimized use of the airside capacities of an airport, whereby a current operating capacity of the airport and a current traffic demand are calculated in order to determine an optimal use of the available resources.

[0010] It is therefore an object of the present invention to provide an improved method for controlling the inflow of road users onto a capacity-limited infrastructure, which takes into account the disadvantages of the methods known from the prior art.

[0011] The problem is solved by the inflow control method according to claim 1 according to the invention. Advantageous embodiments of the invention are then found in the corresponding dependent claims.

[0012] According to claim 1, a method for controlling the flow of traffic from a plurality of road users moving towards a capacity-limited infrastructure within a defined traffic area is proposed. The method comprises the following steps: Providing a temporal division of the traffic space into a plurality of time periods starting from the capacity-limited infrastructure, wherein each time period defines a time window that specifies the duration until arrival at the capacity-limited infrastructure, and each time period is assigned a maximum capacity, determining a utilization indicator at a specific time for each time period depending on position information of the road users and the maximum capacity of the respective time period, and controlling the road users depending on the utilization indicators of the time periods.

[0013] The defined traffic area is therefore first divided into time periods, resulting in multiple time segments on a time scale based on the capacity-limited infrastructure. These time segments define a time window indicating the duration until arrival at the capacity-limited infrastructure. Each time segment is also assigned a maximum capacity. This capacity is related to the maximum capacity of the capacity-limited infrastructure and, if applicable, the time distance of the respective time segment from the capacity-limited infrastructure. The maximum capacity could, for example, represent the maximum number of road users permitted in the respective time segment. Alternatively, the maximum capacity could be a key performance indicator derived from the positional information of the road users.

[0014] The defined traffic space encompasses those road users who are moving towards the capacity-limited infrastructure and thus constitute the influx of traffic to that infrastructure. Each road user can move towards the capacity-limited infrastructure along an individual route.

[0015] Subsequently, a utilization indicator is determined for each time period to ascertain the utilization level of that period in relation to the traffic participants approaching the capacity-limited infrastructure. This utilization indicator is calculated based on the traffic participants' positional information and the maximum capacity of the respective time period. Such positional information could, for example, represent a predicted remaining time until arrival at the capacity-limited infrastructure. Specifically, this positional information represents an estimate of the traffic participant's position on the timescale, relative to the capacity-limited infrastructure, which forms the basis for defining the time periods. In particular, the positional information represents the remaining flight time.

[0016] Based on the utilization indicator for each time period, traffic participants are managed accordingly to prevent future overloading of the capacity-limited infrastructure. Managing traffic participants means varying the speed and / or route of at least one traffic participant, thereby altering the flow of traffic onto the infrastructure.

[0017] To manage the flow of road users onto the capacity-limited infrastructure, appropriate measures are taken when the capacity is exceeded for at least one time period. These measures reduce the utilization rate in one or more time periods. Advantageously, road users in the inflow are selected who possess particularly suitable characteristics for implementing these measures. Such characteristics include the breadth of the road user's distribution across the timescale or a special status of the road user, such as still being at the departure airport. The measures applied to the selected road users can result in a shift on either side of the timescale. This leads either to an acceleration or a deceleration of the road user.Depending on the extent of the capacity overrun, individual traffic participants or multiple traffic participants in the influx may be subject to necessary measures of varying intensity. This approach significantly reduces the number of interventions in air traffic, as not every inaccuracy and disruption requires subsequent intervention.

[0018] The inventor recognized that in transport systems with capacity-limited infrastructure, corresponding disruptions and inaccuracies in traffic flow often balance themselves out over time, meaning that constantly compensating for these effects largely represents an ineffective consumption of resources. By dividing the traffic space into time slots and monitoring their utilization, these overcompensation effects can be avoided, thus preventing the ineffective consumption of resources in such transport systems. By proactively adjusting the behavior of road users in relation to the divided time slots, the performance of the capacity-limited infrastructure can be optimally utilized.

[0019] The temporal division of the traffic area can be provided by an electronic processing unit. This unit receives the current time as an additional input parameter, at which the occupancy indicator for each time period is to be determined. Furthermore, information regarding road users is provided as an input parameter to identify individual road users for determining the occupancy indicator. The determination of the occupancy indicator can also be carried out using the electronic processing unit. Controlling road users based on the determined occupancy indicator for each time period can also be performed using the electronic processing unit, for example, by automatically generating and sending control commands to the road users.

[0020] The control of road users based on the occupancy indicators of the time periods is achieved, in particular, by ensuring that the occupancy indicators do not exceed a certain threshold and preferably by ensuring that road users are distributed essentially homogeneously within their respective time periods. If the occupancy indicator is defined as the percentage occupancy of the respective time period, then the control of road users is achieved in such a way that the occupancy indicator does not exceed 100% in any given time period.

[0021] According to one embodiment, it is provided that for each road user, position information is determined indicating the time period in which the respective road user is located at the specific time, whereby the utilization indicator for the respective time period is determined as a function of the maximum capacity assigned to the time period and a number of road users in the relevant time period based on the position information of the road users.

[0022] In this relatively simple configuration, the predicted arrival time on the capacity-limited infrastructure is determined for each road user at a given time as position information, and based on this, each road user is assigned to the corresponding time slot. The number of road users in a time slot is then compared with the maximum capacity assigned to that time slot to determine whether the maximum capacity has been exceeded. If so, appropriate measures are taken to redistribute the road users to other time slots by accelerating, decelerating, or changing their route.

[0023] According to one embodiment, it is provided that for each road user, a probability distribution is provided as position information, indicating the probability that the respective road user is located at a certain time on a time scale starting from the capacity-limited infrastructure, whereby the utilization indicator for the respective time period is determined as a function of the maximum capacity assigned to the time period and the probability distribution of the road users.

[0024] This method uses a probability distribution to determine the distribution of road users across time periods. This distribution describes the probability of a road user being at a specific location on the timescale at a specific time. At the time of the study, it is possible to determine the probability of each road user being in the considered time period. By combining all the probabilities of all road users in a given time period, the capacity utilization indicator for that period can be determined.

[0025] Essentially, for the defined time periods on the time scale, starting from the capacity-limited infrastructure, a corresponding utilization indicator is determined for a selected time period, which is based on the integral of the part of the probability distribution in the relevant time period.

[0026] According to one embodiment, the probability distributions are based on or determined based on stochastic data about the road users approaching the capacity-limited infrastructure.

[0027] These stochastic data can be based on past observations. From this stochastic data, the probability distribution can then be determined, so that for each point on the timescale, the probability of a given road user being at a specific point on the timescale at a certain time can be specified. Such a probability distribution can be derived from past flight data and the associated flight times.

[0028] According to one embodiment, it is provided that, in order to control the road users, a control command is generated for at least one road user and transmitted to the road user in question.

[0029] Such control commands can be, for example, voice commands issued by a controller of the capacity-limited infrastructure or other infrastructure to the relevant traffic participants (e.g., VHF radio communication). It is also conceivable that the control commands are digital data packets transmitted to the relevant traffic participants via a digital radio link. The control commands are then either executed automatically by the respective traffic participant or implemented by the pilot.

[0030] According to one embodiment, it is provided that at least one road user is controlled by changing his speed and / or his route depending on the occupancy indicators of the time periods.

[0031] According to one embodiment, the subdivision is provided in such a way that the time windows of the time periods become increasingly larger, starting from the capacity-limited infrastructure.

[0032] This results in increased sensitivity to fluctuations in the number of road users during defined time periods of inflow as approaching the infrastructure.

[0033] According to one embodiment, the road users are aircraft, in particular commercial aircraft, and the capacity-limited infrastructure is an airport, and / or the road users are ships and the capacity-limited infrastructure is a port.

[0034] The problem is also solved according to the invention with the computer program according to claim 9. The problem is also solved according to the invention with the device according to claim 10.

[0035] The invention is explained by way of example with reference to the attached figures. They show: Figure 1: Schematic representation of a capacity-limited infrastructure in the form of an airport; Figure 2: Schematic representation of the temporal division; Figure 3: Schematic representation of a probability distribution at a specific time.

[0036] Figure 1 Figure 10 shows a highly simplified schematic representation of a capacity-limited infrastructure 10, which in the exemplary embodiment of the Figure 1 This represents an airport. The capacity-limited infrastructure 10 includes a runway 11. The air traffic participants 20 are located within a controlled airspace 100.

[0037] For this purpose, an electronic computing unit 30 is located in the approach control system 12, or in the inflow monitoring unit. This unit performs inflow control according to the method of the present invention and controls the inflow of traffic participants 20 onto the runway 11 of the capacity-limited infrastructure 10 in such a way as to reduce or completely minimize the need for holding patterns. The approach control system is so extensive that one or more Area Control Centers (ACCs) are involved in its operation.

[0038] Figure 2The diagram shows the temporal division of traffic area 100 into a total of four time periods: A1, A2, A3, and A4. The first time period, A1, is located immediately before the capacity-limited infrastructure 10 and extends from it to the outer boundary where the second time period, A2, begins. From there, the second time period, A2, extends to the beginning of the third period, A3, which is then followed by the fourth period, A4. It can be seen that, starting from the capacity-limited infrastructure 10, the time periods become longer with increasing distance from the infrastructure 10. This makes the entire process more tolerant of fluctuations with increasing distance from the infrastructure 10, so that small fluctuations no longer immediately lead to an intervention in the traffic flow.

[0039] Each time period An is assigned a maximum capacity, which specifies how many road users are permitted within that period. Furthermore, each time period is assigned a time window, which defines the duration until arrival at the capacity-limited infrastructure 10. For example, the first time period A1 might be assigned a time window of 0 to 10 minutes, while the second time period A2 might be assigned a time window of 10 to 30 minutes. The third period A3 would then be assigned a time window of 30 to 60 minutes, and the fourth period A4 a time window of 60 to 120 minutes.

[0040] As the distance from the capacity-limited infrastructure 10 increases, the time window also becomes larger for each time period. In principle, it can be stipulated that the capacity allocated to each time period is selected depending on the size of the time window assigned to that period, which in turn is based on the maximum performance of the capacity-limited infrastructure.

[0041] Assuming we are on runway 11 ( Figure 1 Given the limited capacity of infrastructure 10, one road user 20 can land every 3 minutes, resulting in a capacity of 3 road users for a 10-minute time window. Therefore, for the first time segment A1, which has a 10-minute time window, the maximum capacity is 3 road users.

[0042] The second time period, in turn, has a length of 20 minutes, so that, based on the capacity of infrastructure 10, a total of 6 road users may be included, since a maximum of 6 road users can land on runway 11 of infrastructure 10 within 20 minutes.

[0043] At a specific time when a majority of road users 20 are approaching infrastructure 10, a capacity factor is determined for this time period, indicating how busy the respective time period A n is. This capacity factor is determined based on the maximum capacity of the respective time period and position information of the road users. The position information of the road users is specified in relation to the approach to the infrastructure.

[0044] In a simple implementation, the actual position of the road user can be used to determine the approximate arrival time at the infrastructure. From this, the remaining travel time on the road user's route can then be determined, thus enabling its classification within the respective time segment.

[0045] It is also conceivable that the capacity utilization indicator is determined as positional information based on a probability distribution for each road user. This probability distribution indicates the likelihood that a road user will be located at a specific point in time on the time scale on which the time intervals are divided.

[0046] Such a probability distribution applies to a road user at a specific time in Figure 3shown. The x-axis represents the time scale 40, on which the individual time periods A n are subdivided, starting from the capacity-limited infrastructure 10. The y-axis represents the probability between 0 and 1. The in Figure 3 The probability distribution shown indicates the probability that the road user is located within the time scale at a specific time.

[0047] In the exemplary embodiment of the Figure 3 The road user in question has the highest probability in the first third of the third time period A 3. After that, the probability flattens out on both sides of the time scale.

[0048] At the time of analysis, such probability distributions are provided for each road user under consideration. These probability distributions can be created, for example, using stochastic data about the road users in the past. This can be defined, for instance, based on existing flight routes for each road user.

[0049] To determine a utilization indicator based on the probability distribution of each traffic participant, the probabilities of the individual traffic participants within each time period are integrated to calculate the utilization indicator. In other words, the proportion of aircraft within a given time period is determined from the integral of the portion of the probability distributions that correspond to that time period.

[0050] This determines a fictitious number of aircraft in the respective time periods based on the probability distributions, on the basis of which the utilization indicator can then be determined taking into account the maximum capacity assigned in the respective time period. Reference symbol list

[0051] 10 Capacity-limited infrastructure 11 Runway 12 Approach control 20 Traffic participants 30 Electronic computing unit 40 Time scale A n time intervals 100 Traffic area

Claims

1. Method for controlling the flow of a plurality of traffic participants (20) moving within a defined traffic area (100) toward a capacity-limited infrastructure (10), the method comprising the following steps: - providing a temporal segmentation of the traffic area (100) into a plurality of time segments (An ) starting from the capacity-limited infrastructure (10), wherein each time segment (An) defines a time window that indicates the duration until arrival at the capacity-limited infrastructure (10), and a maximum capacity is assigned to each time segment (An ), - determining a load factor index at a specific point in time for each time segment (An ) depending on position information of the traffic participants (20) and the maximum capacity of the respective time segment (An ), and - controlling the traffic participants (20) depending on load factor index of the time segments (An).

2. Method according to claim 1, characterized in that the position information determined for each traffic participant (20) is the time segment (An ) in which the respective traffic participant (20) is located at the specific point in time, whereby the load factor index for the respective time segment (An) is determined as a function of the maximum capacity assigned to the time segment (An) and a number of traffic participants (20) in the relevant time segment (An) based on the position information of the traffic participants (20).

3. Method according to claim 1, characterized in that for each traffic participant (20), a probability distribution is provided as position information, which indicates the probability that the respective traffic participant (20) is located on a time scale (40) starting from the capacity-limited infrastructure (10) at a certain point in time, wherein the load factor index for the respective time segment (An) is determined as a function of the maximum capacity assigned to the time segment (An) and the probability distribution of the traffic participants (20).

4. Method according to claim 3, characterized in that the probability distributions are based on stochastic data about the traffic participants (20) in the inflow to the capacity-limited infrastructure (10) or are determined based thereon.

5. Method according to claim 1, characterized in that, in order to control the traffic participants (20), a control command is generated for at least one traffic participant (20) and transmitted to the traffic participant (20) concerned.

6. Method according to one of the preceding claims, characterized in that at least one traffic participant (20) is controlled by changing their speed and / or their route depending on the load factor index for the time segments (An).

7. Method according to one of the preceding claims, characterized in that the segmentation is provided in such a way that the time windows of the time segments (An) become increasingly larger starting from the capacity-limited infrastructure (10).

8. Method according to one of the preceding claims, characterized in that the traffic participants (20) are flying objects, in particular commercial aircraft, and the capacity-limited infrastructure (10) is an airport, and / or that the traffic participants (20) are ships and the capacity-limited infrastructure (10) is a port.

9. Computer program with program code means, designed to carry out the method according to one of the preceding claims when the computer program is executed on a data processing system.

10. Device with an electronic computing unit designed to carry out the method according to one of claims 1 to 8.