Procedure and system for a common driving strategy for vehicle trains

Abstract

System (4) for controlling a vehicle train comprising at least one lead vehicle and one further vehicle, each of which has a positioning unit (1) and a wireless communication unit (2), wherein the system (4) comprises an analysis unit (7) configured to: - receive a driving profile for each of several vehicles fkin in the vehicle train along a road segment for a road ahead of the vehicle, wherein each driving profile contains target values ​​bi and associated positions pi for the relevant vehicle fken along the road segment;- to analyze the driving profiles in order to determine a selected driving profile as a position-based driving strategy for the vehicles in the train, wherein the vehicles in the train are then controlled according to the position-based driving strategy, with the target values ​​being target speeds, and the analysis unit (7) is configured to: - determine a difference Δv for each driving profile that indicates the largest difference between a maximum speed vmax and a minimum speed vmina; - compare the differences Δv for the different driving profiles with each other; - based on the comparison, determine a selected driving profile that has the largest difference Δv.;

Description

Technical field The present invention relates to a system and a method for controlling a vehicle train. The vehicle train comprises at least one lead vehicle and one further vehicle, each of which has a positioning unit and a wireless communication unit. Background of the invention Traffic intensity on Europe's main transport routes is high, and further increases are expected. The growing transport of people and goods not only exacerbates traffic problems in the form of congestion but also requires ever-increasing amounts of energy, ultimately leading to a rise in emissions of greenhouse gases, for example. One potential solution to these problems is to allow vehicles to travel closer together, a practice known as "vehicle platooning." The term "vehicle platooning" is used here to refer to a number of vehicles traveling close together, operating as a single unit. These shorter distances allow more traffic to share the road, and the energy consumption of each individual vehicle is reduced due to the lower resistance.The vehicles in the platoon are driven with at least one automated control system for vehicle speed and one for automated control of its direction of travel. This reduces the workload for drivers, such as truck drivers, thereby reducing accidents based on faulty human decisions, and enables a reduction in fuel consumption. Studies show that the fuel consumption of the lead vehicle in the platoon can be reduced by 2 to 10%, and that of the following vehicle by 15 to 20%, compared to the fuel consumption of a single vehicle. This is the case under conditions where the distance between the vehicles is 8-16 meters, and the speed at which they travel is 80 km / h. The reduced fuel consumption results in a corresponding reduction in CO2 emissions. Drivers are already exploiting this well-known fact, resulting in reduced road safety. A fundamental question regarding vehicle platooning is how to reduce the time gap between vehicles from the recommended 3 seconds to between 0.5 and 1 second without compromising road safety. Distance sensors and cameras reduce the need for rapid driver reaction times. This is a type of technology already used in systems such as ACC (Adaptive Cruise Control) and LKA (Lane-keeping Assistance). However, a limitation is that distance sensors and cameras require a clear view of the target, making it difficult to detect events occurring more than a few vehicles ahead in the queue.Another limitation is that the speed control system cannot act proactively, i.e., the speed control system cannot react to events occurring further ahead in the traffic that will affect the traffic rhythm. One way to enable vehicles to act proactively is to allow them to communicate and exchange information. An evolution of the IEEE 802.11 standard for WLAN (WLAN networks), known as "802.11p," allows for the wireless transmission of information between vehicles and between vehicles and infrastructure. Different types of information, such as vehicle parameters and strategies, can be transmitted to and from vehicles. The development of communication technology has thus made it possible to design vehicles and infrastructure that can interact and act proactively. Vehicles can be controlled as a single unit, enabling shorter distances between them and improved overall traffic flow. Today, many vehicles are equipped with a cruise control system to make driving easier for the driver. In this case, the desired speed can be set by the driver, for example, using a control on the dashboard. The cruise control system then influences the vehicle's steering system to accelerate and decelerate as needed to maintain the set speed. If the vehicle is equipped with an automatic transmission, the system automatically shifts gears to maintain the desired speed. When cruise control is used in hilly terrain, it attempts to maintain the preset speed on uphill sections. This sometimes results in the vehicle accelerating over the crest of the hill and potentially into a subsequent downhill section, requiring it to brake to maintain the preset speed. This is a fuel-wasting driving style. Varying the vehicle's speed in hilly terrain can save fuel compared to the fuel consumption of a vehicle using a conventional cruise control system.If the upcoming topology is made known by the vehicle having map data and positioning equipment, such systems can be made more robust and can change the vehicle's speed before events occur. This is achieved by what is known as "predictive cruise control," abbreviated as "LAC." The situation becomes more complex, however, when a fuel-optimized driving strategy needs to be developed for a complete train. Additional aspects must be considered, such as maintaining optimal spacing and physically feasible speed profiles for all vehicles with varying masses and engine capacities. Another consideration for a train traveling through varying topography is that if a lead vehicle loses speed on an incline, it will resume its preset speed after the climb. The following vehicles, still on the incline, are then forced to accelerate uphill, which is not fuel-efficient. Furthermore, this is not always possible, creating gaps in the train that must then be closed. This results in oscillations within the train.A similar behavior is observed on downhill sections when the lead vessel begins to accelerate due to its large mass. The following vessels are then forced to accelerate before reaching the downhill section as they attempt to maintain a constant distance to the vessels ahead. After the downhill section, the lead vessel begins to brake to return to its preset speed. The following vessels, still on the downhill section, are then forced to brake to avoid a collision, a process that is not fuel-efficient. A similar problem arises when negotiating curves. For an individual vehicle, it's possible to calculate the maximum speed it should maintain through the curve. This maximum speed is based on factors such as driver comfort, center of gravity, rollover risk, and curvature, using a predictive cruise control system. However, it's not always clear how a train of vehicles should navigate the curve. If the lead vehicle needs to slow down to negotiate the curve, it will resume its preset speed afterward. The following vehicles, still within the curve, will then be forced to accelerate, which may not be possible without putting them at risk, such as running off the road. Several documents describe control strategies for vehicle trains. JP 2010-176353A addresses the problem of keeping a vehicle train together when the road has a gradient. The control strategy employed utilizes an acceleration error due to the road gradient. US 2013 / 0041576A1 describes various procedures for driving a vehicle train and generally states that other measures can be used to optimize fuel consumption. Further control strategies for train sets and / or for vehicles are disclosed in documents DE 10 2010 013 647 A1 , DE 10 2008 026 686 A1 , DE 10 2010 054 241 A1 , DE 10 2007 046 763 A1 and US 6 032 097 A . The object of the invention is to provide a system that, in a more efficient manner than previously suggested solutions, can control a vehicle train in the event of variations in the design of the upcoming roadway, such as at least one hill and curve. Brief description of the invention According to a first aspect, the problem described above is solved at least partially by a method for controlling a train of vehicles comprising at least one lead vehicle and one other vehicle, each of which has a positioning unit and a wireless communication unit. The method comprises providing a driving profile for at least one vehicle fkin to the train along a road segment for the road ahead of the vehicle, wherein the driving profile contains target values ​​bi and associated positions pi for the vehicle fken along the road segment in order to determine a position-based driving strategy for the vehicles in the train based on at least the driving profile for vehicle fk, and subsequently controlling the vehicles in the train according to the position-based driving strategy. Thus, all vehicles in the train essentially follow the same driving profile with the same target values ​​(bi) at the same points (pi). This means that the driving strategy is not time-based. When each vehicle is at or within point pi, the following vehicles receive a target value (bi). A suitable control unit in the vehicle then controls the vehicle according to the target value (bi). This avoids the problem of unnecessary braking on downhill sections or impossible acceleration on uphill sections. The driving strategy is therefore based on an optimal speed profile for the entire train, which is point-based. When driving on hills or around curves, small changes in spacing are permitted to achieve optimal fuel consumption. When driving around curves, this avoids a situation where the lead vehicle's acceleration after a curve is simultaneously followed by the other vehicles in the curve, which can be uncomfortable for the driver and potentially poses a risk of overturning and other safety hazards. Instead, the other vehicles follow the lead vehicle's change in speed at the same position along the road where the lead vehicle initiated the speed change. In this way, the other vehicles also exit the curve before they accelerate. By creating a common driving profile that applies to the entire train, a well-organized train is achieved, taking into account what is best for the entire train when traveling uphill and around a curve, or uphill and around a curve. The vehicles can be kept together, which demonstrably results in fuel savings compared to splitting the train. The common profile is created, for example, by calculating an optimal LAC speed profile for each individual vehicle. Then, it is determined which vehicle needs to make the greatest changes in speed to travel up the upcoming hill in a fuel-efficient manner, and that vehicle's driving profile becomes the jointly selected driving profile. The selected driving profile can be transferred to all vehicles in the train, and each individual vehicle can follow it.In this way, each vehicle in the train can follow the same driving profile, having started from the same point along the road, i.e., not at the same time. The invention provides a driving strategy that ensures the train remains cohesive, i.e., it minimizes disturbances in the form of gaps that arise due to the saturation of control signals and are subsequently closed. The invention can manage variations in topography with few and simple control actions. It achieves a method for determining a common regulation for the vehicles in the train that does not require such complex calculations and is therefore easier to implement in real time than other computational solutions. According to a second aspect, the task described above is at least partially solved by a system for controlling a vehicle train. The vehicle train comprises at least one lead vehicle and one other vehicle, each of which has a positioning unit and a wireless communication unit. The system further comprises an analysis unit configured to receive a driving profile for at least one vehicle fkin in the vehicle train along a road segment for the road ahead of the vehicle, wherein the driving profile contains target values ​​bi and associated positions pi for the vehicle fken along the road segment; to determine a position-based driving strategy for the vehicles in the vehicle train based on at least the driving profile for vehicle fk, and subsequently to control the vehicles in the vehicle train according to the position-based driving strategy. According to a third aspect, the problem is solved at least partially by a computer program P in a system, wherein the computer program P comprises program code to cause the system to perform one of the procedural steps described in this application. According to a fourth aspect, the problem is solved at least partially by a computer program product, wherein the computer program P comprises program code stored on a medium readable by a computer to perform one of the process steps described in this application. Preferred embodiments are described in the independent claims and in the detailed description. Brief description of the attached drawings The invention is described below with reference to the accompanying drawings, wherein: Fig. 1 shows an example of a vehicle train traveling uphill. Fig. 2 shows an example of a vehicle train traveling around a curve. Fig. 3 shows an example of a vehicle in a vehicle train. Figs. 4A-4D show different examples of the system's construction. Fig. 5 shows a flowchart for the method according to one embodiment of the invention. Detailed description of preferred embodiments of the invention Definitions LAC (look-ahead cruise control): a cruise control system that uses information about the topography of the upcoming road and calculates an optimal driving profile for the vehicle. Also known as a "predictive cruise control system". LAP (look-ahead cruise control for platoons): a cruise control system that uses information about the topography of the upcoming road and calculates an optimal driving profile for all vehicles in a platoon. Also known as a "predictive cruise control system for platoons." The control strategy is determined, for example, by dynamic programming. vk: the speed of vehicle f in the platoon with N vehicles. dk,k+1: the distance between vehicle fk and the vehicle behind it fk+1 in the platoon. ak: the gradient at vehicle fk. V2V communication (vehicle-to-vehicle): wireless communication between vehicles, also known as vehicle-to-vehicle communication. V2I communication (vehicle-to-infrastructure): wireless communication between vehicles and infrastructure, such as road junctions and computer systems. Fig. 1 depicts a train of N heavy vehicles fk, traveling up a hill with small gaps dk, k+1 between the vehicles. The gradient for vehicle fk as it travels over the hill is represented as ak. Each vehicle fk can be equipped with a receiver and a transmitter for wireless signals, some of which are shown with an antenna. The vehicles fk in the train can thus communicate with each other via V2V communication or through other devices, such as mobile communication units, an application in a communication unit, or a server. They can also communicate with the infrastructure in the form of V2I communication. The different vehicles fk carry different masses m. Fig. 2 shows a train of vehicles with N=6 heavy vehicles fk, which, similar to the example shown in Fig. 1, travels with small gaps dk k+1 between the vehicles, but instead travels around a curve. In this case as well, each vehicle fi is equipped with a receiver and a transmitter 2 (Fig. 3) for wireless signals and can communicate via V2V and V2I communication. The curve is shown there with a radius of curvature r. Each vehicle train has a lead vehicle, i.e., the first vehicle f1. Each vehicle fkin in the train has, for example, a unique vehicle identity and a train identity common to the entire train, in order to maintain knowledge of which vehicles are members of the train. Data transmitted wirelessly between the vehicles in the train can be tagged with these identities, allowing the vehicle from which the received data originated to be determined. Figure 3 shows an example of a vehicle f in the vehicle train and illustrates how it can be equipped. The vehicle fk is equipped with a positioning unit 1 that can determine the position of vehicle fk. The positioning unit 1 can be configured to receive signals from a satellite navigation system, such as GNSS (Global Navigation Satellite System), e.g., GPS (Global Positioning System), GLONASS, Galileo, or Compass. Alternatively, the positioning unit 1 can be configured to receive signals, e.g., from one or more detectors in the vehicle that measure relative distances to, e.g., a road intersection, nearby vehicles, or similar objects with known positions. Based on these relative distances, the positioning unit 1 can determine the position of its own vehicle fk. A detector can also be configured to detect a signature, e.g.,The positioning unit 1 can be configured to determine its own position by detecting the signature at a road intersection, where the signature represents a specific position. Alternatively, the positioning unit 1 can be configured to determine the signal strength in one or more signals from multiple base stations or road intersections, etc., with known positions, and thereby determine the position of the vehicle fkb using triangulation. The position of vehicle fk can be determined in this way. Of course, the technologies described above can be combined to determine the position of vehicle fkzu. The positioning unit 1 is configured to generate a positioning signal containing the position of vehicle fkzu and to transmit this signal to one or more units within the vehicle fkzu.The vehicle fkist, as mentioned above, is also equipped with a wireless communication unit 2. Unit 2 is configured to operate as both a receiver and transmitter of wireless signals. Unit 2 can receive at least one wireless signal from other vehicles and wireless signals from infrastructure surrounding the vehicle fkherum, and it can transmit at least one wireless signal to other vehicles and wireless signals to the infrastructure surrounding the vehicle fkherum. The wireless signals can include vehicle parameters from other vehicles, such as their mass, developed torque, speed, and also more complex information, such as the currently used driving profile, driving strategy, etc. The wireless signals can also contain information about the environment, such as the gradient a of the road, the radius of curvature r, etc. The vehicle fk can also be equipped with one or more detectors 3 to detect the environment, e.g.,with a radar unit, a reader unit, a gradient measuring device, etc. These detectors are generally labelled as a detector unit 3 in Fig. 3, but can consist of several different detectors positioned at different locations in the vehicle. The detector unit 3 is configured to determine a parameter, such as a relative distance, speed, gradient, lateral acceleration, rotation, etc., and to generate a detector signal containing the parameter. The detector unit 3 is further configured to transmit the detector signal to one or more units in the vehicle fk. The vehicle may also be equipped with a map unit that can provide map information about the upcoming road. The map unit may, for example, be part of the positioning unit 1. The driver may, for example,specify a final position and the map unit can then, provided it has knowledge of the vehicle's current position, provide relevant map data about the upcoming road between the current position and the final destination. The vehicle communicates internally between its different units, for example, via a bus such as a CAN bus (Controller Area Network), which uses a message-based protocol. Examples of other communication protocols that can be used include TTP (Time-Triggered Protocol), FlexRay, etc. Signals and data, as described above, can be exchanged between different units in the vehicle in this way. Alternatively, signals and data can be exchanged wirelessly, for example, between the different units. There is also a System 4, either fully or partially integrated into the vehicle fk, which will be described below with reference to Figures 4A-4D, which depict different examples of System 4. The dashed lines in the drawings indicate that this is a case of wireless data transmission. System 4 is generally used for controlling the vehicle train and for establishing a common driving strategy for the entire train, based on information about the upcoming road. System 4 thus implements a type of cooperative speed control system, a LAP, for the vehicle train. System 4 is particularly useful for the vehicle train when it is driving uphill or around a curve, or uphill and around a curve.By creating a common driving profile that applies to the entire train, a well-organized train is achieved, taking into account what is best for the entire train when driving up a hill and around a bend, or up a hill or around a bend. System 4 comprises an analysis unit 7, which is configured to receive a driving profile for at least one vehicle fkin in the train along a road segment for a road ahead of the vehicle. The driving profile contains target values ​​bi for the vehicle fkin positions along the road segment. The driving profile may, for example, have been determined for an existing speed control system such as a LAC or another form of predictive speed control system and forwarded to the analysis unit 7. The target values ​​bi may be, for example, target speeds vi, target accelerations ai, or target separation distances. The analysis unit 7 is further configured to determine a position-based driving strategy for the vehicles in the train based on at least the driving profile for vehicle fk. The vehicles in the train are subsequently controlled according to the driving strategy.According to one embodiment, the analysis unit 7 is configured to generate a driving strategy signal that specifies the position-based driving strategy and to transmit the driving strategy signal via unit 2 to all vehicles in the train, after which the vehicles in the train are controlled according to the driving strategy. According to another embodiment, the vehicles in the train are controlled according to the driving strategy as determined, which is explained in more detail below. Thus, a driving profile for a single vehicle fk can be achieved by using a predefined driving profile designed by a predictive cruise control system located in the vehicle or another external unit. Predictive cruise control is a predictive control scheme that has knowledge of some of the disturbances, in this case the road topography, that are yet to come. Optimization is performed with respect to a criterion, and this optimization involves predicting the behavior of the system. Here, an optimal solution to the problem is sought along a limited road segment, which is obtained by shortening the segment of the complete driving session. The road segment typically has a length of 2 km.The goal of optimization is to minimize the energy and time required for the driving session while maintaining the vehicle's speed within a predetermined range. This optimization can be performed, for example, using Model Predictive Control (MPC) or a Linear Quadratic Regulator (LQR) to minimize fuel consumption and time in a cost function J, based on a nonlinear dynamics model and fuel consumption model for the vehicle fk, with limitations on the input control signals and limits on the maximum absolute deviation, e.g., 5 km / h, from the road speed limit. An example of how such optimization can be performed is described in "Look-ahead control of heavy vehicles," E. Hellström, Linköping University, 2010.A vehicle model describing the principal forces acting on a vehicle in motion is described in this publication, according to: where α describes the gradient of the road, cD and cr are characteristic coefficients, g describes gravity, ρadie is the air density, rw is the wheel radius, and it, if, ηf are constants specific to the transmission and gearbox. The acceleration mass of the vehicle mt(m,Jw,Je,it,if,ηt,ηf) depends on the gross mass m, wheel inertia Jw, engine inertia Je, the gear ratio and efficiency of the gearbox it,ηc, and the final gear ratio and efficiency if, ηf. The predictive cruise control (LAC) system increases the vehicle's speed in advance as it approaches a steep incline, thus achieving at least a partially higher average speed while traveling uphill. Similarly, the speed is reduced before the vehicle enters a steep downhill section. The system allows the vehicle's speed to drop to a minimum on an uphill section and regain the lost speed after the vehicle has crested the hill, i.e., once on a level road.If an uphill section is followed by a downhill section, the speed can be maintained at a lower level on the uphill section to avoid having to brake on the downhill section if the vehicle's speed becomes too high, and instead utilize the potential energy the vehicle gains from its weight on the downhill section. This saves time and fuel. A low gradient of road α can be described as follows: where αu is the steepest gradient at which speed can be maintained on an uphill section at maximum engine speed, and αl is the steepest gradient at which a heavy vehicle can maintain a constant speed by coasting without the need for braking. Steep hills are defined as road segments with a gradient outside the interval in (2). According to one embodiment, the system 4 comprises at least one segment unit 5 and a driving profile unit 6. The segment unit 5 is configured to determine a road segment for at least one vehicle fkin in the vehicle train using position data and map data for an upcoming road, wherein the road segment contains one or more properties of the upcoming road. The road segment can be subdivided into multiple road segments. For example, a property can be that a road segment in the road segment is classified as a steep incline or decline with a gradient outside the interval in (2). The driving profile unit 6 is configured to determine a driving profile for at least one vehicle fkin in the vehicle train based on properties of the road segment, wherein the driving profile contains one or more target values ​​bi and the associated positions pi for the vehicle fken along the road segment. The target values ​​bi can be, for example,B. Target speeds vi, target accelerations ai, or target separation distances disein. The system 4 can thus be configured to independently determine one or more driving profiles for the vehicles in the train, e.g., by the driving profile unit 6 determining an optimal driving speed profile in the same way as the LAC described above. System 4 can be configured to activate when the road exhibits specific characteristics, such as a steep gradient or a small radius of curvature (a tight bend). These characteristics are reflected in the driving profile, which is set by the generated target values, and also as features of the road segment. The vehicles in the convoy normally adhere to a road speed limit, also known as the "preset speed" (vset), which is the highest speed permitted by the road's speed limit. On hills, bends, and other road surfaces, it may be appropriate to adjust the speed to improve fuel efficiency or to enhance or maintain safety. Reducing speed on a bend with a small radius of curvature may also be advisable.An equation expressing the maximum vehicle speed, based on the vehicle's mass and the curve's radius of curvature, can be used to calculate the vehicle's maximum speed in the curve. The LAC calculates at least one of fuel-optimal and time-optimal target values ​​for exemplary target speeds via at positions pi, and these target speeds vi can differ from the preset speed vset to achieve economical or safe driving, or economical and safe driving. According to one embodiment, the analysis unit 7 is used to compare the target speeds vi with a preset speed vset and to determine a difference Δv between vi and vset.Analysis Unit 7 remains configured to compare Δv with a threshold value and initiate the determination of the position-based driving strategy if Δv exceeds the threshold. In this way, the train can be controlled according to the common driving strategy in selected situations or along specific road segments, while in other cases the vehicles in the train can be controlled based on their individual driving profiles. Once the train has completely exited the curve or reached the crest or bottom of the hill, all vehicles in the train can revert to their individual driving profiles. Fig. 4A shows an example of System 4, where System 4 is positioned in the vehicle f1, e.g., in the lead vehicle f1. In this case, System 4 can be part of a control unit in the vehicle f1. System 4 is shown here as comprising a segment unit 5 and a driving profile unit 6, which provide a driving profile for the vehicle f1 to the analysis unit 7. Map and position data are then transmitted, e.g., via the internal network in the vehicle f1 to the segment unit 5. Alternatively, an existing LAC in the vehicle f1 can provide a driving profile for the vehicle f1 to the analysis unit 7. System 4 can instead be positioned in an external unit, such as a road intersection or a computer system. In this case, position data, etc., can be transmitted to the external unit via V2I. According to the example shown in Fig.As schematically illustrated in Figure 4A, the analysis unit 7 determines that the driving profile for vehicle f1 is the selected driving profile for the entire train. The driving strategy is transmitted to the vehicles in the train via a wireless signal. The driving strategy includes, for example, a message indicating that all vehicles in the train, except the lead vehicle, must measure the behavior of the vehicle in front of them and adjust their own speed accordingly to maintain the distance di,j between the vehicles. The vehicles can, for example, use radar to determine the speed of the vehicle in front. In this way, the vehicles in the train will follow the speed profile of the lead vehicle f1 without needing to be consciously aware of the speed profile itself. According to one embodiment, the vehicles in the train are arranged in a specific sequence such that the most constrained vehicle is positioned at the front of the train as the lead vehicle f1, and the remaining vehicles are arranged in descending order such that the least constrained vehicle is located at the rear of the train. This ensures that all vehicles in the train can follow the driving profile of the lead vehicle. The most constrained vehicle is, for example, the vehicle with the greatest mass, the lowest available engine torque, or a combination of both. According to one embodiment, the analysis unit 7 is configured to receive a driving profile for each of the multiple vehicles in the train. In this embodiment, the analysis unit 7 is configured to analyze the driving profiles in order to determine a selected driving profile as a position-based driving strategy for the vehicles in the train. The selected driving profile can then be, for example, passed on to all vehicles in the train, whereby each individual vehicle in the train will then follow the same selected driving profile at the same positions. Before the driving profile is transmitted to the vehicles, the positions in the driving profile can be mapped to current positions along the upcoming road, so that the vehicles in the train can be controlled with respect to, for example, their speed according to target values ​​based on the same current positions along the road. This is the case in all embodiments described in this application. Several methods are available for determining a selected driving profile. For example, the selected driving profile can be determined to be the driving profile chosen for the most restricted vehicle in the train. Examples of the most restricted vehicle have been described above. The most restricted vehicle can also be determined to be the vehicle exhibiting the greatest speed fluctuations in its driving profile in and around, or in or around, an approaching incline or curve, or both an incline and a curve.To determine which driving profile should be selected, the analysis unit 7 is configured to calculate a difference Δv for each driving profile that specifies the largest difference between a maximum speed vmax and a minimum speed vmin. This difference Δv is then compared between the different driving profiles, and based on this comparison, the selected driving profile with the largest difference Δv is chosen. The maximum speed vmax is one of the speed targets vi in ​​the driving profile, and the minimum speed vmin is one of the target speeds vi in ​​the driving profile at or near an approaching hill or curve, or at or near an approaching hill and curve. Figure 4B shows an example of System 4, where a driving profile is determined for each vehicle fk. The driving profiles are subsequently transmitted to the analysis unit 7 to determine a position-based driving strategy based on a selected driving profile. In this case, the analysis unit 7 is located in an external unit, and the different driving profiles are transmitted to the analysis unit via V2I communication. After the analysis unit 7 has determined a selected driving profile, the driving strategy is transmitted to the vehicles in the train via V2I communication, i.e., by one or more wireless signals. The driving strategy includes, for example,A message indicating that all vehicles in the train, except the lead vehicle, must measure the speed of the vehicle in front of them and adjust their own speed accordingly to maintain the distance di,j between the vehicles. The vehicles can, for example, use radar to determine the speed of the vehicle ahead. The driving strategy also includes a message to the lead vehicle f1 that it must follow the selected driving profile, and the current driving profile if it is not already the lead vehicle's driving profile. In this case, the vehicles in the train will follow the selected speed profile without needing to be aware of the speed profiles of the vehicles they are following.Alternatively, the selected driving profile can be passed on to all vehicles in the train, whereby each individual vehicle in the train will then follow the same selected driving profile. Figure 4C shows another example, where the analysis unit 7 in system 4 is positioned in a vehicle, here in the lead vehicle f1. As in the example in Figure 4B, a driving profile is determined for each of the vehicles in each of the vehicles fk. The driving profiles are transmitted to the analysis unit 7 via V2V communication to determine a position-based driving strategy based on a selected driving profile. After the analysis unit 7 has determined a selected driving profile, the driving strategy is transmitted to the vehicles in the train via V2V communication, i.e., by one or more wireless signals, and is passed as a message or signal to the vehicle fk in which the analysis unit 7 is located, in this case f1. The driving strategy in this case can be the same as in the example illustrated in Figure 4B.The vehicles in the train subsequently control their speed according to the selected driving profile. Figure 4D shows an example of how a position-based strategy can be determined sequentially. Each vehicle fk is equipped with an analysis unit 7k or a part of the analysis unit 7. The final vehicle fN determines its driving profile and transmits it to the analysis unit 7N-1 in the vehicle fN-1 immediately preceding it. Vehicle fN-1 determines its driving profile, and the two driving profiles are compared in the analysis unit 7N-1 to determine which of the driving profiles is the most constrained. Thus, the analysis unit 7 is configured here to sequentially compare differences Δv. The manner in which this can be performed has been described previously. The most constrained driving profile of the two is subsequently transmitted to the next vehicle fN-2 immediately preceding it for continued comparison.Following a final comparison in the lead vehicle, a selected driving profile was determined that requires the greatest changes in speed. The lead vehicle follows this selected driving profile, and the other vehicles in the train follow the speed of the vehicle immediately in front of them in the train without further communication, e.g., radar detection, as previously explained. Alternatively, the other vehicles in the train can be informed of the same selected driving profile, which they then follow. The analysis unit 7, the driving profile unit 6, and the segment unit 5 can comprise or consist of one or more processor units and one or more memory units. A processor unit can consist of a CPU (Central Processing Unit). A memory unit can comprise volatile or non-volatile memory, or it can comprise both volatile and non-volatile memory, such as flash memory or RAM (Random Access Memory). The processor unit can be part of a computer or computer system, such as an ECU (Electronic Control Unit) in a vehicle 2. Figure 5 shows a flowchart for a method for controlling the vehicle train described above. The method can be implemented as program code in a computer program P. The computer program is shown in Figures 4A-4D as part of the analysis unit 7, and thus the computer program P is stored in a memory unit that can be part of the analysis unit 7. The program code can cause the system 4 to execute one of the steps according to the method when executed on a processor unit in the system 4. The method will now be explained with reference to the flowchart in Figure 5. The method comprises receiving a driving profile for the at least one vehicle fkin in the vehicle train along a road segment for a road ahead of the vehicle, wherein the driving profile contains target values ​​bi and associated positions pi for the vehicle fkin along the road segment (A1). The target values ​​bi can be, for example,B. Target speeds vi, target accelerations ai, or target separation distances. According to one embodiment, the method includes providing a driving profile for each of the multiple vehicles in the vehicle train. A driving profile can be obtained, for example, by determining a road segment for at least one vehicle fkin in the vehicle train using position data and map data for an upcoming road, wherein the road segment contains one or more properties of the upcoming road, and by determining a driving profile for at least one vehicle fkin in the vehicle train based on properties of the road segment, wherein the driving profile contains target values ​​bi and the associated positions pi for the vehicle fk along the road segment. The method also includes determining a position-based driving strategy for the vehicles in the vehicle train based on at least the driving profile for vehicle fk(A2).The vehicles in the train are subsequently controlled according to the position-based driving strategy (A3). According to one embodiment, step (A3) comprises transferring the position-based driving strategy to all vehicles in the train, after which the vehicles in the train are controlled according to the position-based driving strategy. According to one embodiment, (A1) comprises analyzing the driving profiles to determine a selected driving profile as a position-based driving strategy for the vehicles in the train. The analysis can be performed, for example, if the driving profile includes target speeds vium, which determine a difference Δv for each driving profile that specifies the largest difference between a maximum speed vmax and a minimum speed vmina, comparing the differences Δv for the different driving profiles with each other, and determining a selected driving profile that exhibits the largest difference Δv based on the comparison. According to one embodiment, the step of comparing the difference Δv is performed sequentially, for example, in each vehicle. According to one embodiment, the method includes a step prior to step A1 or A2, which, if the driving profile includes target speeds vium, compares the target speeds vi with a preset speed vset, determines a difference Δv between vi and vset, compares Δv with a threshold value and initiates the determination of a position-based driving strategy if Δv should exceed the threshold value. Further embodiments that can be used as methods have been described in connection with the description of the system. The invention also includes a computer program product comprising the program code P, which is stored on a medium readable by a computer to execute the method steps described above. The computer program product can, for example, be a CD. The present invention is not limited to the preferred embodiments described above. Various alternatives, modifications, and equivalents may be used. For this reason, the embodiments mentioned above do not limit the scope of the invention, which is defined by the accompanying patent claims.

Claims

System (4) for controlling a vehicle train comprising at least one lead vehicle and one further vehicle, each of which has a positioning unit (1) and a wireless communication unit (2), wherein the system (4) comprises an analysis unit (7) configured to: - receive a driving profile for each of several vehicles fkin in the vehicle train along a road segment for a road ahead of the vehicle, wherein each driving profile contains target values ​​bi and associated positions pi for the relevant vehicle fken along the road segment;- to analyze the driving profiles in order to determine a selected driving profile as a position-based driving strategy for the vehicles in the train, wherein the vehicles in the train are then controlled according to the position-based driving strategy, with the target values ​​being target speeds, and the analysis unit (7) is configured to: - determine a difference Δv for each driving profile that indicates the largest difference between a maximum speed vmax and a minimum speed vmina; - compare the differences Δv for the different driving profiles with each other; - based on the comparison, determine a selected driving profile that has the largest difference Δv.; System according to claim 1, wherein the analysis unit (7) is configured to:- generate a driving strategy signal that specifies the position-based driving strategy, and- transmit the driving strategy signal to all vehicles in the train, wherein the vehicles in the train are then controlled according to the position-based driving strategy. System (4) according to one of the preceding claims, wherein the analysis unit (7) is configured to compare the differences Δv sequentially. System (4) according to one of the preceding claims, wherein the target values ​​are target speeds, and the analysis unit (7) is configured to: - compare the target speeds with a preset speed vset and determine a difference Δv between vi and vset; - compare Δv with a threshold value, and initiate the determination of the position-based driving strategy if Δv should exceed the threshold value. System (4) according to any of the preceding claims, comprising: - a segment unit (5) configured to determine a road segment for at least one vehicle fkin in the vehicle train using position data and map data for an upcoming road, wherein the road segment contains one or more properties of the upcoming road; - a driving profile (6) configured to determine a driving profile for at least one vehicle fkin in the vehicle train based on properties of the road segment, wherein the driving profile contains one or more target values ​​bi and associated positions pi for the vehicle fken along the road segment. Method for controlling a vehicle train comprising at least one lead vehicle and one further vehicle, each of which has a positioning unit (1) and a wireless communication unit (2), the method comprising: - providing a driving profile for each of several vehicles fkin in the vehicle train along a road segment for a road ahead of the vehicle, wherein each driving profile contains target values ​​bi and associated positions pi for the relevant vehicle fken along the road segment;- to analyze the driving profiles in order to determine a selected driving profile as a position-based driving strategy for the vehicles in the train, wherein the vehicles in the train are then controlled according to the position-based driving strategy, with the target values ​​being target speeds, and the analysis includes the following: - to determine a difference Δv for each driving profile that indicates the largest difference between a maximum speed vmax and a minimum speed vmina; - to compare the differences Δv for the different driving profiles with each other; - based on the comparison, to determine a selected driving profile that has the largest difference Δv.; Method according to claim 6, comprising forwarding the position-based driving strategy to all vehicles in the train. Method according to claim 6 or 7, wherein the step of comparing differences is performed sequentially. A method according to any one of claims 6 to 8, wherein the target values ​​are target speeds, and the method further comprises: - comparing the target speeds with a preset speed vset and determining a difference Δv between vi and vset; - comparing Δv with a threshold value, and initiating the determination of a position-based driving strategy if Δv should exceed the threshold value. A method according to any one of claims 6 to 9, comprising providing a driving profile by: - ​​determining a road segment for at least one vehicle fkin in the vehicle train using position data and map data for an upcoming road, wherein the road segment contains one or more properties of the upcoming road; - determining a driving profile for at least one vehicle fkin in the vehicle train based on properties of the segment, wherein the driving profile contains target values ​​bi and the associated positions pi for the vehicle f along the road segment. Computer program (P) in a system (4), wherein the computer program (P) comprises program code to cause the system (4) to perform one of the steps according to claims 6 to 10. Computer program product comprising program code stored on a medium readable by a computer to perform the method steps according to any one of claims 6 to 10.

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