MX2008003361A - Method and apparatus for optimizing a train trip using signal information - Google Patents

Abstract

One embodiment of the invention includes a system for operating a railway network comprising a first railway vehicle (400) during a trip along track segments(401/412/420). The system comprises a first element (65) for determining travel parameters of the first railway vehicle (400), a second element (65) for determining travel parameters of a second railway vehicle (418) relative to the track segments to be traversed by the first vehicle during the trip, a processor (62) for receiving information from the first (65) and the second (65) elements and for determining a relationship between occupation of a track segment (401/412/420) by the second vehicle (418) and later occupation of the same track segment by the first vehicle (400) and an algorithm embodied within the processor (62) having access to the information to create a trip plan that determines a speed trajectory for the first vehicle (400), wherein the speed trajectory is responsive to the relationship and further in accordance with one or more operational criteria for the first vehicle (400).

Description

METHOD AND APPARATUS TO OPTIMIZE THE TRAIN OF A TRAIN USING SIGNAL INFORMATION Cross Reference with Related Requests The present application is a continuation in part of the application claiming the benefit of the North American Patent Application entitled System and Method of Optimization of Travel for a train, presented on March 20, 2006, and with a number of assigned application 11 / 385,354, which is incorporated herein by reference. Field of the Invention The embodiments of the present invention relate to the optimization of train operations, and more particularly, to use tracking and switching signals in conjunction with train monitoring and control operations to improve efficiency, while satisfying at the same time programming restrictions. BACKGROUND OF THE INVENTION A locomotive is a complex system with numerous subsystems, each subsystem is interdependent with other subsystems. An operator on board a locomotive, applies traction and braking effort to control the speed of the locomotive and its load of wagons to ensure a safe arrival and in time to the desired destination. Speed control must also be carried out to maintain the forces in-train within acceptable limits, avoiding this form excessive coupling forces and the possibility of breaking a train. To carry out this function and comply with the prescribed operating speeds that may vary with the location of the train in the lane, the operator must generally have extensive experience in locomotive operation on the specific terrain with several groups of wagons, ie , different types and numbers of wagons. However, even with sufficient knowledge and experience to ensure safe operation, the operator generally can not operate the locomotive to minimize fuel consumption (or other operating characteristics, eg emissions) during a journey. Multiple operating factors affect fuel consumption, including, for example, emission limits, fuel characteristics / emissions of the locomotive, size and load of the wagons, weather, traffic conditions and operating parameters of the locomotive. An operator can operate a train more effectively and efficiently (through the application of traction and braking efforts), if it provides control information that optimizes the performance during a trip, while complying with a required program (time of arrival) and using a minimum amount of fuel (or optimizing other operating parameters), despite the various variables that affect performance. Therefore, it is desired that the operator operates the train under the guidance (or control) of an apparatus or process that announces the application of traction or braking efforts to optimize one or more operating parameters. Brief Description of the Invention According to one embodiment, the present invention includes a system for operating a rail network comprising a first rail vehicle during a journey along rail segments. The system comprises a first element for determining travel parameters of the first railway vehicle, a second element for determining travel parameters of a second railway vehicle in relation to the rail segments that will be crossed by the first vehicle during the journey, a processor for receive information from the first and the second elements and to determine a relationship between the occupation of a lane segment through the second vehicle and the subsequent occupation of the same lane segment by the first vehicle, and an algorithm presented within the processor having access to the information to create a route plan that determines a speed trajectory of the first vehicle, wherein the speed trajectory responds to the relation and in addition is in accordance with one or more criteria of operation of the first vehicle. According to another modality, the present invention includes a method for operating a rail vehicle during a journey along rail segments of a rail network. The method includes determining the vehicle's travel parameters, determining the travel parameters of other vehicles that cross the network and executing an algorithm that responds to the vehicle's travel parameters, and the travel parameters of the other vehicles to optimize the performance of the vehicle according to one or more criteria of vehicle operation. Yet another embodiment includes a computer software code for operating a rail vehicle during a journey along rail segments of a rail network. The software code comprises a software module for determining vehicle travel parameters, a software module for determining travel parameters of other vehicles that traverse the network, and a software module for executing an algorithm that responds to the travel parameters of the vehicle and the travel parameters of other vehicles to optimize the performance of the vehicle according to one or more criteria of vehicle operation. BRIEF DESCRIPTION OF THE DRAWINGS A more particular description of the aspects of the present invention described herein will refer to the specific embodiments thereof that are illustrated in the accompanying drawings. It will be understood that these drawings illustrate only typical embodiments of the present invention and will therefore not be construed as limiting their scope, the modes will be described and explained with additional specificity and detail through the use of the accompanying drawings in which: Figure 1 shows an example illustration of a flow diagram of an embodiment of the present invention; Figure 2 illustrates a simplified model of the train that can be used; Figure 3 illustrates an exemplary embodiment of elements of the present invention; Figure 4 illustrates an exemplary embodiment of a fuel usage / travel time curve; Figure 5 illustrates an example mode of decomposition by segmentation to plan a route; Figure 6 illustrates an exemplary embodiment of a segmentation example; Figure 7 illustrates an exemplary flow chart of one embodiment of the present invention; Figure 8 shows an example illustration of a dynamic screen to be used by the operator; Figure 9 shows another example illustration of a dynamic screen to be used by the operator; Figure 10 shows another example illustration of a dynamic screen to be used by the operator; and Figures 11A and 11B illustrate blocks and lane signals and a locomotive speed path as it relates to the embodiments of the present invention. Detailed Description of the Invention Reference will now be made in detail to the embodiments consistent with aspects of the present invention, examples of which are illustrated in the accompanying drawings. Whenever possible, the same reference numbers are used throughout the drawings to refer to the same or similar parts. The embodiments of the present invention attempt to overcome certain disadvantages in the art by providing a system, method and method implemented in computer to determine and implement a train driving strategy, which includes a group of locomotives and a plurality of railway lines, monitoring and controlling (either directly or through actions suggested by the operator), a train operation to improve certain operating parameters objectives, while satisfying programming and speed restrictions. The present invention also applies to a train that includes a plurality of groups of locomotives separated from the main locomotive group and that can be controlled through the train operator (referred to as a train with distributed power).

Those skilled in the art will recognize that an apparatus, such as a data processing system, including a CPU, memory, I / O, program store or bus connection, and other suitable components, can be programmed or otherwise designed. to facilitate the practice of the modalities of the method of the present invention. Said system may include means of suitable programs to execute the methods of these modalities. In other embodiments, an article of manufacture, such as a pre-recorded disc or other similar computer program product, for use with a data processing system, includes a storage medium and a program recorded therein to direct the data processing system to facilitate the practice of the methods of the present invention. Said apparatus of manufacturing articles are also within the spirit and scope of the present invention. Broadly speaking, aspects of the present invention teach a method, apparatus and program for determining and implementing a train driving strategy to improve certain operating parameters while satisfying programming and speed constraints. To facilitate understanding of the present invention, a description is made below with reference to specific implementations thereof.

The present invention is described within the general context of computer executable instructions, such as program modules, executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. who perform particular tasks or implement particular abstract data types. For example, the software programs provided in the present invention can be encoded in different languages, for use with different processing platforms. In the description that follows, examples of the present invention are described within the context of a web portal that employs a web browser. However, it will be appreciated that the principles encompassing the present invention can also be implemented with other types of computer software technology. In addition, those skilled in the art will appreciate that the embodiments of the present invention can be practiced with other configurations of computer systems, including portable devices, multiprocessor systems, programmable or microprocessor-based consumer electronics, minicomputers, mainframes and the like. The modalities are also practiced in a distributed computing environment, where tasks are carried out through remote processing devices that are linked through a communication network. In the distributed computing environment, program modules can be located on both local and remote computer storage media including memory storage devices. These local and remote computing environments may be contained entirely within the locomotive, or within adjacent locomotives in a group or outboard, on the road or in central offices where wireless communications are provided between the computing environments. The term locomotive group means one or more locomotives in succession, connected together to provide driving capacity and / or braking without wagons between the locomotives. A train can comprise one or more groups of locomotives. Specifically, there may be a main group and one or more remote groups, such as a first remote group in the middle of the wagon line and another remote group at the end of the train position. In each group of locomotives there may be a first locomotive or main locomotive and one or more locomotives. Although a group is usually considered as successive connected locomotives, those skilled in the art will recognize that also a group of locomotives can be recognized as a group even with at least one wagon separating the locomotives, such as when the group is configured for distributed power operation, wherein the acceleration commands and braking are relieved from the main locomotive to the remote wagons through a radio link or physical cable. For this purpose, the group of term locomotives should not be considered a limiting factor, when multiple locomotives are described within the same train. Referring now to the drawings, the embodiments of the present invention will be described. The embodiments of the present invention can be implemented in various ways, including in the form of a system (including a computer processing system) a method (including a computerized method, an apparatus, a computer-readable medium, a program product). in computer, a graphical interface of the user, including a web portal or a data structure fixed in a tangible form in a computer readable memory .. Various embodiments of the present invention are described below: Figure 1 shows an illustration of a diagram Example flow of the present invention As illustrated, the instructions are specific to the entry to plan a route either on board or from a remote location, such as a dispatch center 10. Such entry information includes, but is not limited to, train position, group composition (such as locomotive models), locomotive traction power performance of the traction transmission of the locomotive, fuel consumption of the engine as a function of the output power, cooling characteristics, projected route path (degree and curvature of rail effective as a function of landmarks or a component of "grade effective "to reflect the curvature after standard railroad practices), marking and loading of wagons (including effective drag coefficients, desired travel parameters including, but not limited to, time and location of start, final location, time of route, identification of crew (user and / or operator), expiration time of change of crew and route of travel. This data can be provided to the locomotive 42 according to various techniques and processes, such as, but not limited to, manual entry of the operator into the locomotive 42 through an on-board display, which links to a data storage device. , such as a hard card, hard disk drive and / or USB drive or transmitting information through a wireless communication channel of a central location or on board the path 41, such as a lane signaling device and / or apparatus to on the road, to the locomotive 42. The load characteristics of the locomotive 42 and the train 31 (for example, drag) can also change on the route (for example, with the altitude, ambient temperature and condition of the rails and wagons ), originating the updating of a plan to reflect said changes in accordance with any of the methods described above. The update data that affect the route optimization process can be supplied through any of the methods and techniques described herein and / or through autonomous real-time collection of locomotive / train conditions. Such updates include, for example, changes in the characteristics of the locomotive or train detected by monitoring equipment in or outboard of the locomotive (s) 42. A lane signal system indicates certain lane conditions and provides instructions to the operator of a train to reach the signal. The signaling system, which is described in more detail below, indicates, for example, a permissible speed for the train in a rail segment and provides stop and run instructions to the train operator. The details of the signal system, including the location of the signals and the rules associated with different signals, are stored in the on-board database 63. Based on the input of specification data in the embodiments of the present invention, an optimal route plan minimizes the use of fuel and / or generated emissions subject to speed limit restrictions and a desired start and end time, is computed to produce a travel profile 12. The profile contains the optimal speed and power settings (notch) that the The train must follow, expressed as a function of distance and / or time from the beginning of the course, limits of operation of the train, including but not limited to, maximum power and braking configurations of notches, speed limits as a function of location and the expected fuel used and emissions generated. In an example embodiment, the value of the notch configuration is selected to obtain acceleration change decisions, about every 10 to 30 seconds. Those skilled in the art will readily recognize that acceleration change decisions can occur at longer or shorter intervals, if needed and / or desired to follow an optimum speed profile. In a broad sense, it should be apparent to those skilled in the art that the profiles provide power settings for the train, whether at the train level, group level and / or individual locomotive level. As used in the present invention, the power comprises braking power, driving power and air brake power. In other preferred embodiments, instead of operating in traditional independent notch power configurations, the present invention determines a desired power configuration, from a continuous range of power settings, to optimize the speed profile. Therefore, for example, if an optimum profile specifies a notch configuration of 6.8, instead of a notch configuration of 7, the locomotive 42 operates in 6.8.

By allowing the intermediate power configurations, additional efficiency benefits can be provided, as described below. The procedure for computing the optimum profile can include any number of methods for computing a power sequence that operates the train 31, to minimize the fuel and / or emissions subject to the operating and programming restrictions of the locomotive, as shown in FIG. summarized form later. In some situations the optimum profile can be sufficiently similar to a previously determined profile, due to the similarity of train configurations, route and environmental configurations. In these cases it may be sufficient to recover the previously determined conduction path of the database 63 and operate the train accordingly. When a previous plan is not available, methods to computerize a new plan include, but are not limited to, direct calculation of the optimal profile using differential equation models that approximate the physical motion of the train. According to this process, a quantitative objective function is determined, commonly comprising the function a weighted sum (integral) of model variables that correspond to a range of fuel consumption and generated emissions plus a term to penalize excessive variations in acceleration.

An optimal control formulation is established to minimize the quantitative target function subject to restrictions including, but not limited to, speed limits and minimum and maximum power settings (acceleration). Depending on the planning objectives at any time, the problem can be established to minimize fuel subject to restrictions on emissions and speed limits, or to minimize emissions subject to restrictions on fuel usage and time of arrival. It is also possible to establish, for example, a goal to minimize total travel time without restrictions on total emissions or fuel usage, where such relaxation of restrictions is permitted or required for the mission. Throughout the document, equations and objective objective functions are presented to minimize the fuel consumption of the locomotive. These equations and functions are only for illustration, since other equations and objective functions can be used to optimize the fuel consumption or to optimize other operating parameters of the locomotive / train according to the different functions. Mathematically, the program that will be solved can be considered more precisely. The basic physics are expressed by: dt 1 = 7,?) - Ga (x) -? (?);? (0) = 0.0; v (Tf) = 0.0 dt where x is the position of the train, v is the speed of the train, t is the time (in miles, miles per hour and minutes or hours as appropriate) and u is the notch command entry (acceleration) plus, D denotes the distance that will be traveled, Tf the desired arrival time at distance D along the lane, Te is the tensile stress produced by the locomotive group, Ga is the gravitational drag (which depends on the length of the train, marking of train and terrain of route) and R is the net speed that depends on the drag of the group of locomotives and combination of trains. The initial and final speeds can also be specified, but without loss of generality, they are taken here as zero (train stopped at the beginning and end of the route). The model is easily modified to include other dynamic factors such as delay between a change in acceleration u and a resultant tensile or braking stress. All these performance measures can be expressed as a linear combination of any of the following: Tr 1. min F (u (t)) dt - Minimize total fuel consumption 2. ™ T / - Minimize travel times 3. min («, -«, _,) 2 - Minimize notch driving (constant entry in the form of pieces) 4 · min. { duldtfdt ~ Minimize notch driving (continuous entry) 5. replace the fuel term F () in (1) with a term that corresponds to production of emissions. A commonly used and representative objective function is therefore mine, jF (u (t)) dt + aTf + a2 j (du / dt) 2 t (OP) The coefficients of the linear combination depend on the importance (weight) provided to each of the terms. It should be noted that in the equation (OP), u (t) is the optimization variable which is the continuous notch position. If an independent notch is required, for example, for older locomotives, the solution to the equation (OP) is made independent, which can result in lower fuel savings. The finding of a minimum time solution is used (ai is set to zero and a2 is set to zero or a relatively small value), to find a link lower than the travel time that can be achieved (Tf = Tfmin). In this case, both u (t) and Tf are optimization variables. The preferred mode solves the equation (OP) for various values of Tf with Tf > Tfmin with an a3 set to zero. In the latter case, Tf is treated as a restriction.

For those who are familiar with solutions to such optimal problems, it may be necessary to join the restrictions, for example, the speed limits along the trajectory: 0 < v < SL (x) or when a minimum time is used as the target, the union constraint may be such that an endpoint constraint must be maintained, for example, the total fuel consumed must be less than that in the tank, example, through: where WF is the remaining fuel in the tank in Tf. Those skilled in the art will readily recognize that the equation (OP) can be presented in other forms and that the previous version is an exemplary equation for use in one embodiment of the present invention. The reference to emissions within the context of the present invention, is generally directed to cumulative emissions produced in the form of nitrogen oxides (???), unburned and particulate hydrocarbons. Through design, each locomotive must comply with EPA emission standards, and therefore in an embodiment of the present invention that optimizes emissions, this can refer to the total emissions of the emission, for which there is no specification EPA The operation of the locomotive according to the optimized route plan, always complies with EPA emission standards. If a key objective during the tour is to reduce emissions, the formulation of optimal control, the equation (OP), is amended to consider this travel objective. A key flexibility in the optimization process is that any or all travel objectives may vary by geographic region or mission. For example, for a high priority train, the minimum time may be the only target on a route due to the priority of the train. In another example broadcast, the output may vary from state to state, along the planned route of the train. To solve the resulting optimization problem, in an exemplary embodiment the present invention transcribes a problem of optimal dynamic control in the time domain to a problem of mathematical static programming equivalent to N decision variables, wherein "N" depends on the frequency at which acceleration and braking adjustments are made and the duration of the journey. For physical problems, this N can be in thousandths. In one example mode, a train is traveling a lane extension of 172 miles in the Southwest of the United States. Using the present invention, an exemplary fuel consumption of 7.6% can be considered when compared to a determined path and followed in accordance with the aspects of the present invention, versus a path wherein the acceleration / velocity is determined by the operator, in accordance with standard practices. The improved savings are considered due to the optimization provided by the present invention which produces a driving strategy with both less drag loss and with little or no loss of braking compared to the travel controlled by the operator. To make the optimization described above computationally adaptable, a simplified model of the train can be employed, as illustrated in Figure 2, and set in the equations described above. A key refinement to the optimum profile is produced by deriving a more detailed model with the optimal power sequence generated, to test if any thermal, electrical and mechanical restrictions are violated, leading to a modified profile with speed versus distance that is as close as possible to a run that can be achieved without damaging the equipment of the locomotive or train, that is, by satisfying the additional constraints involved, such as thermal and electrical limits on the locomotive and forces on the train. Referring again to figure 1, once the route 12 starts, 14 power commands are generated to start the plan. Depending on the operating configuration of the embodiments of the present invention, a command causes the locomotive to follow the optimized power command 16, to achieve the optimum speed. One mode obtains real power speed information from the train's locomotive group. Due to the common approaches in the models used for the optimization, a closed circuit calculation of corrections to the optimized power can be obtained to track the desired optimal speed. Said corrections of the limits that operate the train, can be carried out automatically or through the operator, who always has the last control of the train. In some cases, the model used in optimization may differ significantly from the actual train. This can happen for many reasons, including but not limited to, taking and leaving overload, locomotives that fail on the route, errors in the initial database 63 and errors in the entry of data by the operator. For these reasons, a monitoring system uses data from the real-time train to estimate the parameters of the locomotive and / or train in real time 20. Subsequently the estimated parameters are compared with the parameters assumed when the route was initially created 22. With Based on any differences in the assumed and estimated values, the route can be re-planned 24. Normally, the route is re-planned if significant savings can be considered from a new plan.

Other reasons for a route to be re-planned include guidelines from a remote location, such as a dispatch and / or a request from the operator for a change in objectives to be consistent with the objectives of global movement planning. Such global movement planning objectives may include, but are not limited to, other train programs, time required to dissipate tunnel escape, maintenance operations, etc. Another reason may be due to a failure on board a component. Strategies for re-planning can be grouped into incremental and larger adjustments depending on the severity of the interruption, as described in more detail below. In general, a "new" plan must be derived from a solution to the optimization problem (OP) equation described above, although often faster approximate solutions can be found, as described in the present invention. In operation, the locomotive 42 will continuously monitor the efficiency of the system and will continuously update the route plan based on the actual measured efficiency, provided that said update can improve the performance of the route. Refitting computations can be carried out entirely within the locomotive (s) or can be carried out completely or partially at a remote location, such as an office or processing facilities on the road, where wireless technology can communicate from new plan to the locomotive 42. An embodiment of the present invention can also generate efficiency trends to develop data of the locomotive fleet with respect to efficiency transfer functions. Fleet-wide data can be used when determining the initial route plan, optimization negotiation across the network can be used when considering locations of a plurality of trains. For example, as illustrated in Figure 4, the fuel usage negotiation curve, real time reflects the capacity of a train on a particular route at a current time, updated from assembly averages collected from many trains. similar in the same route. Therefore, a central dispatch facility that collects type 4 loops from many locomotives, can use this information to better coordinate the general movements of the train to achieve an advantage throughout the system in fuel use and performance. Many events during area operations can motivate the generation of a new or modified plan, including a new or modified route plan that retains the same route objectives, for example, when a train is not in a program for a planned meeting or phase with another train, and therefore must cover the lost time.

Using the real speed, power and location of the locomotive, we compare a planned arrival time with an estimated arrival time of that moment (anticipated) 25. Based on a difference in the times, as well as the difference in parameters ( detected or changed by the dispatcher or operator) the plan is adjusted 26. This adjustment can be made automatically in response to a policy of the railway company to handle departures from the plan or manually as the on-board operator and dispatcher jointly decide the best method to return to the plan. A plan can always be updated, but when the original objectives (such as but not limited to the arrival time) remain the same, additional changes can be factorized concurrently, for example, new future speed limit changes, which may affect the feasibility of recovering the original plan, in such cases if the original route plan can not be maintained, or in other words, the train does not have the capacity to fulfill the objectives of the original route plan, as described in the present invention, other route plans may be presented to the operator, remote installation and / or dispatch. A new plan can also be developed when you want to change the original objectives. Said re-planning may be carried out at any time previously planned, manually, at the discretion of the operator or dispatcher, or autonomously when the predefined limits are exceeded, such as the operating limits of the train. For example, the execution of the current plan is to run late for more than a specific threshold value, such as thirty minutes, a mode of the present invention can re-plan the course to accommodate the delay, despite the consumption of Increased fuel as described above, or give notice to the operator and dispatcher to see to what extent the lost time can be regained, if possible, (for example, which is the minimum remaining time or the maximum fuel that It can be saved within a time constraint.Alternatively other activators can be considered for the new plan based on the fuel consumed or the power group's vitality, including but not limited to the time of arrival, loss of horsepower due to equipment failure and / or equipment temporary malfunction (such as operation with too much heat or too cold) and / or detection of gross configuration errors, as in the load of the assumed train. That is, if the change reflects damage in the performance of the locomotive for the course of that moment, these can be factored into the models and / or equations used in the optimization process. Changes in plan objectives may also suffer from the need to coordinate events when the plan for a train compromises the ability of another train to meet the objectives and arbitrariness at a different level, and arbitrariness is required in a different level, for example, the dispatch office. For example, the coordination of meetings and phases can be optimized in an additional way through train-to-train communications. Therefore, as an example, if an operator knows that it is plotted in a program to reach a place for an encounter and / or pass, the communications of the other train can warn the operator of the delay of the train (and / or dispatch). The operator can enter information pertaining to the arrival with an expected delay to recalculate the train's travel plan. In one embodiment, the present invention is used at a high level or network level, to allow an office to determine which train should slow down or accelerate, if it appears that a meeting time restriction and / or can not be met. scheduled pass. As described in the present invention, this is achieved through trains that transmit data to the dispatch, to organize by priorities as each train must change its planning objective. A choice can be made either based on the program or benefits in fuel savings, depending on the situation. For any of the new plans initiated manually or automatically, the embodiments of the present invention may present more than one route plan to the operator. In an exemplary embodiment, the present invention presents different profiles to the operator, allowing the operator to select the arrival time and also understand the corresponding impact of fuel and / or emission. Said information may also be provided to the dispatch for similar considerations, either as a simple list of alternatives or as a plurality of negotiation curves, as illustrated in Figure 4. In one embodiment the present invention includes the ability to learn and adapt to key changes in the train and power group that can be incorporated into either the current plan and / or future plans. For example, one of the activators described above is losing horsepower. When horsepower builds up over time, either after the loss of horsepower or when a run is started, a transition logic is used to determine when a desired horsepower power is achieved. This information can be stored in the database of the computer 61 to be used in optimizing either future routes or the route of that moment, if the loss of horsepower occurs again later. Figure 3 illustrates an example embodiment of elements of the present invention. A locator element 30 determines a location of the train 31. The locating element 30 comprises a GPS sensor or a sensor system that determines the location of the train 31. The systems of said systems may include, but are not limited to, apparatus on the edge of the train. path, such as identification labels of automatic radio frequency equipment (RF AEI) dispatch and / or video-based determinations. Another system can use a tachometer on board a locomotive and distance calculations from a reference point. As previously described, a wireless communication system 47 can also be provided to allow communications between trains and / or to a remote location, such as a dispatch. Information regarding travel locations can also be transferred from other trains through the communication system. A rail characterization element 33 provides information regarding the one lane, mainly information of grade, elevation and curvature. The characterization element of the rail 33 may include an on-board rail integrity database 36. The sensors 38 measure a tensile stress 40 applied by the locomotive group 42, acceleration configuration of the locomotive group 42, configuration information from locomotive group 42, locomotive group speed 42, individual locomotive configuration information, individual locomotive capacity, etc. In an exemplary embodiment, the configuration information of the locomotive group 42 can be loaded without the use of a sensor 38, although it is entered by other methods, as described above. In addition, the vitality of the locomotives in the group can also be considered. For example, if a locomotive in the group does not have the capacity above a power notch level 5, this information is used when optimizing the route plan. The localized element information can also be used to determine an adequate arrival time of the train. For example, if there is a train 31 that moves along lane 34 to a destination, and there is no train following it, and the train does not have to meet a fixed arrival time limit, the locator element, including but not limited to to the identification labels of automatic radio frequency equipment (RF AEI), dispatch and / or video-based determinations, can be used to determine the exact location of the train 31. In addition, the inputs of these signaling systems can be used to adjust the speed of the train. Using the on-board lane database, described below, and the locator element, such as GPS, one embodiment of the present invention adjusts the operator interface to reflect the state of the signaling system at the location of the locomotive. determined. In a situation where the signal states indicate operating costs of restrictive speeds, the glider may choose to slow down the train to conserve fuel consumption.The information of the locator element 30 can also be used to change the planning objectives as a function of the distance to a destination. For example, due to the inevitable uncertainties with respect to congestion along the route, the "fastest" time objectives in the early part of the route can be used as a protection against delays that statistically will occur later. In a particular route, these delays do not occur, the objectives in the later part of the route can be modified to exploit the lazy time accumulated in previous stages and thus be able to recover some fuel efficiency. A similar strategy can be invoked with respect to targets with emission restriction, for example, emission restrictions that apply when arriving in an urban area. As an example of the protection strategy, if a trip is planned from New York to Chicago, the system can provide an option to operate the train with lower speed either at the beginning of the route, halfway or at the end of the route . One embodiment of the present invention optimizes the route plan to allow a slower operation at the end of the route, since unknown restrictions may be developed and known during the course, such as but not limited to climatic conditions, maintenance of the lanes, etc. As another consideration, if the traditionally congested areas are known, the plan is developed with an option to increase driving flexibility around these regions. Accordingly, the embodiments of the present invention may also consider weighting / penalization as a function of time / distance in future experiences and / or based on known / past experiences. Those skilled in the art will readily recognize that such planning and re-planning taking into account considerations of weather conditions, lane conditions, other trains in the lanes, etc., may be considered at any time during the route, when the route plan it adjusts accordingly. Figure 3 also describes other elements that can be inserted in the embodiments of the present invention. A processor 44 operates to receive information from a locator element 30, the lane characterization element 33 and the sensors 38. An algorithm 46 operates within the processor 44. The algorithm 46 computes an optimized route plan based on parameters involving the locomotive 42, train 31, lane 34 and mission objectives, as described in the present invention. In an example embodiment, a route plan is established based on train performance models, as the train 31 moves along the lane 34, as a solution of the nonlinear equations derived from the applicable physics with assumptions of simplifications that are provided in the algorithm. The algorithm 46 has access to the information of the locating element 30, characterization elements 33 and / or sensors 38 to create a route plan that minimizes the fuel consumption of a group of locomotives 42, minimizes emissions of a group of locomotives 42, establish a desired travel time and / or ensure adequate operation time of the crew aboard the locomotive group 42. In an example embodiment, a driver or controller 51 is also provided. As described in the present invention, the controlling element 51 can control the train according to the route plan. In an exemplary embodiment described further in the present invention, the controlling element 51 autonomously takes decisions of the train operation. In another example mode, the operator may be involved with the direction of the train to follow or deviate from the route plan in its direction. In an embodiment of the present invention, the route plan can be modified in real time, as it is being executed. This includes creating the initial plan for a long distance travel, due to the complicity of the plan optimization algorithm. When the total length of a travel profile exceeds a certain distance, an algorithm 46 can be used to segment the mission, dividing the mission into coordinates to locate reference points. Although only one algorithm 146 is described, those skilled in the art will appreciate that more than one algorithm can be used, and that such multiple algorithms are linked to create the route plan. The coordinates for locating route reference points may include natural locations, where for the train 31, such as, but not limited to, dead ends of the simple main line to meet with opposite traffic or for a pass with a coming train behind the train at that time, a train station, an industrial dead-end where the wagons are taken or left and locations for planned maintenance operations. In such coordinates for locating reference points it may be required that the train 31 be in the location at a programmed time, stop or move with a speed within a specific range. The length of time from arrival to departure at the coordinates is called the stop time. In an exemplary embodiment, the present invention has the ability to break a longer path into small segments according to a systematic process. Each segment can be somewhat arbitrary in length, although it is usually selected in a natural location such as a significant stop or speed restriction, or in key coordinates or markers that define junctions with other routes. Due to the division or segment selected in this way, a driving profile is created for each segment of the lane as a function of travel time taken as an independent variable, as shown in figure 4. The fuel negotiation used / The travel time associated with each segment can be computed before the train 31 reaches that segment of the lane. Therefore, a total route plan can be created from the driving profiles created for each segment. One embodiment of the present invention optimally distributes the travel time between all travel segments, so that the total travel time required is satisfied and the total fuel consumed in all segments is minimized. In figure 6 a three-segment example path is described. Those skilled in the art will recognize, however, although segments are described, that the route plan may comprise a single segment representing the complete route. Figure 4 illustrates an exemplary embodiment of a fuel usage time / travel time curve. As mentioned above, said curve 50 is created when an optimum path profile is calculated for various travel times of each segment. That is, for a determined travel time 51, the fuel used 52 is the result of the computerized detailed driving profile as described above. Once the travel times for each segment are assigned, a power / speed plan for each segment is determined from the previously computerized solutions. If there are any speed restrictions of the coordinates between the segments, such as, but not limited to, a change in the speed limit, they are matched during the creation of the optimum path profile. If the speed restrictions change only with a single segment, the fuel usage / travel time curve 50 has to be re-computed only for the changed segment. This process reduces the time required to recalculate more parts, or segments, of the route. If the group of locomotives or train changes significantly along the route, for example, loss of a locomotive or lifting or leaving of wagons, then the driving profiles must be re-computed for all subsequent segments creating new cases of the curve 50. These new curves 50 are subsequently used together with new program objectives to plan the remaining route. Once the route plan is created as described above, a trajectory of speed and power versus distance allows the train to reach a destination with fuel and / or minimum emissions at the required travel time. There are several techniques to execute the route plan. As provided in more detail below, in an exemplary mode of a steering mode, the present invention displays control information to the operator. The operator follows the information to achieve the required power and speed as determined in accordance with the optimal route plan. Therefore, in this mode the operator is supplied with operating suggestions to be used in the driving of the train. In another exemplary embodiment, control actions to accelerate the train or maintain a constant speed are carried out through the present invention. However, when the train 31 must slow down, the operator is responsible for applying brakes, controlling the braking system 52. In another example embodiment, the present invention commands power and braking actions, as required to follow the trajectory. of desired speed-distance. Feedback control strategies are used to correct the sequence of power control in the profile, to take into account events such as, but not limited to, variations in the train load caused by winds in the front and / or winds in the the back part fluctuating. Another such error can be caused by an error in the parameters of the train, such as but not limited to mass and / or drag of the train, in comparison with assumptions in the optimized route plan. A third type of error can occur due to incorrect information in the database of lane 36. Another possible error can imply non-modeled performance differences due to the engine of the locomotive, thermal decrease of the traction motor and / or other factors. The feedback control strategies compare the actual speed as a position function with the speed in the desired optimal profile. Based on this difference, a correction is added to the optimum power profile to drive the actual speed towards the optimum profile. To ensure stable regulation, a compensation algorithm can be provided that filters feedback velocities in power corrections to ensure closed circuit performance stability. Compensation can include standard dynamic compensation as used by experts in the design of the control system to meet performance objectives. According to several aspects, the present invention allows the simplest and therefore fastest means to adapt the changes in the travel objectives, which is the rule and not the exception, in railway operations. In an example mode, to determine the optimal-fuel route from point A to point B, where there are stops along the way, and to update the route of the rest of the route once it has begun, you can use a suboptimal decomposition method to find an optimal path profile. When using modeling methods, the computation method can find the route plan with the specific travel time and initial and final speeds that satisfy all restrictions of speed limits and locomotive capacity., when there are stops. Although the following description is aimed at optimizing the use of fuel, it can also be applied to optimize other factors, such as but not limited to emissions, schedule, crew comfort and cargo impact. The method can be used at the beginning of the development of a route plan, and more importantly, to adapt to the changes in the objectives after a journey begins. As described in the present invention, one embodiment of the present invention employs a configuration, such as illustrated in the example flow chart illustrated in Figure 5, and in the form of a three segment example illustrated with detail in figure 6. As illustrated, the path can be broken into two or more segments, T1, T2 and T3, although as described in the present invention, it is possible to consider the path as a simple segment. As described in the present invention, segment boundaries may not result in segments of equal length. Rather, the segments use natural or mission specific limits. The optimal route plans are pre-computed for each segment. If the object of the route to be fulfilled is fuel use versus time of travel, fuel curves versus time of travel are generated for each segment. As described in the present invention, the curves can be based on other factors, where the factors are objectives that will be fulfilled with a route plan. When the travel time is the parameter that is being determined, the travel time of each segment is computed, while satisfying the general restrictions of the travel time. Figure 6 illustrates speed limits for a route 97 of 200 miles of three example segments. Changes of degree in the 200-mile course 98 are further illustrated. A combined graph 99 illustrates fuel curves used for travel segment in travel time. Using the optimal control configuration described above, the computation method of the present invention can find the route plan with specified travel time and initial and final speeds, to satisfy all constraints on speed limits and locomotive capacity when there are stops . Although the following detailed description is directed to optimize the use of fuel, it may apply to optimizing other factors as described in the present invention, such as, but not limited to, emissions. The method can accommodate desired stop times at stops and considers restrictions on prior arrivals and departures at a location, as required, for example, in single-lane operations, where the time of entry or transfer to an airport is important. death way. According to one embodiment, the present invention finds a fuel-optimal distance from the distance D0 to DM, travel in time T, with intermediate stops M-1 in Di, ..., DM-Í, and with times of arrival and exit at these stops, restricted by: ímin (/ ') = tarr (D ¡) < imax (/) - Af, tarr (D¡) + ?? / = tdep (D¡) = tmax (i) i = 1 M -1 where tarr (D¡), tdeP (Di), and Af, are the time of arrival, departure and minimum stop at the stop / 'th, respectively. Assuming that the optimization-fuel implies the minimization of the stoppage time, consequently tdep (D,) = tarr (D¡) ??, where the second previous lack of equality is eliminated. Assume for each i =,.,.,?, The fuel-optimal path of D (-i to D¡ for the time of travel t, Tmin (/ ') <t = fma (/') is known. that F, (t) is the corresponding fuel-use for this path If the travel time of D¡.ia D¡ is denoted as T, then the arrival time in D, is determined by where ?? 0 is defined as zero. The fuel-optimal path from D0 to DM for the travel time T is subsequently obtained by finding T,,? =? , ..., M, which minimizes u? W) Tmitt (i) = rl = Tmx (i) subject to '™ "(0 =? (Tj +?, _,) < (0 -?, / = 1 M - 1 Once the route is on the way, the emission of the fuel-optimal solution for the rest of the route (originally from D0 to DM at time T) is determined again, as the route is carried out, although the disturbances are exclude after the fuel-optimal solution. Let the current distance and velocity be xyv, respectively, where D (- <x = D¡) Also, let the current time from the start of the journey be fací- Subsequently, the fuel-optimal solution for the rest of the travel xa DM, which retains the original time of arrival in DM, are obtained by finding = '+ - ~ M, ^ | 0 cua | minimizes subject to rrain < *) < tÍK, + r7 + ¿(G, +?, _,) < f max (*) -Atk k = i + 1, ..., M - 1 ./-/+! Ai ("+ r (+ ¾ + á / ,,) = r Here, it is the fuel used for the optimal path from x to D, traveled at time t, within the initial velocity at x of y.

As described above, an example process allows more efficient replanting constructions of the optimal solution for a stop-to-stop route from split segments. For the path of D (-1 to D, with the time of travel T, a set of immediate points D, j =, ...,? -? Is chosen Allow Di0 = D; N¡ = D¡ Then express the use of fuel for the optimal path of D (-1 to D¡.

F, (0 =? Fy C ~ lU-l> V¡. > -1 > v¡,) where f, 7 (f,? ,,; - ?, v¡j) is the use of fuel for the path from D / y-1 to D¡¡, travel in time t, with initial and final velocities of yv ¡¡ Furthermore, t¡¡ is the time in the optimum path corresponding to the distance D (y) Through the definition tiN¡ - f, 0 = T¡ Since the train stops at D, 0 and DiN, ViO = ViNi = 0. The above expression allows the function Fj (t) to be determined in an alternative way by first determining the functions (,; (·), 1 = j = Nj, later finding r, y, 1 < j = N¡ y ??, = j = N¡, which minimizes? Subject to 7 = 1 ) V) j = V / ü = ¼ = o By choosing D (for example in speed restrictions or meeting points), vmax - vmin can be minimized thus minimizing a domain through which (,; () needs to be known, based on the division described above, a simpler suboptimal re-planning method than the one described above restricts the re-planning to times where the train is at the distance points D¡¡, 1 = / '= M, 1 = j = N¡. At point D, and , the new optimal path of D¡¡ to DM can be determined by finding r, - *, j < k = N¡, v¡k, j < k < N¡ yy xmn, i < m < M , 1 < n < Nm, vmn, < m < M, 1 < n < n < n < N >, which minimizes subject to 'm¡n (») = +? A +? (G "+? G,".,) < tmn (n) -Atn n = / +?,.,.,? - 1 where A further simplification is obtained by waiting for a re-computation of Tm, i < m = M, until the distance point D¡ is reached. In this way at points D, between D, .f and D ,, the above minimization needs to be carried out only through j < k = N¡, vik, j < k < N¡ T is incremented as necessary to adapt any real travel time longer than D (-ia D¡¡, to the planned one.This increment is later compensated if possible, through the recum of Tm, i <m = M , at the distance point D¡¡ With respect to the closed loop configuration described above, the total input energy required to move a train 31 from a point A to a point B consists of the sum of four components, specifically the difference in kinetic energy between points A and B, the difference in potential energy between points A and B, the loss of energy due to friction and other drag losses, and the energy dissipated by the application of the brakes. Start and end velocities (eg stationary) are equal, the first component is zero, and the second component is independent of the driving strategy, so it is sufficient to minimize the sum of at least s two components, then a constant velocity profile minimizes drag loss. Subsequently, a constant speed profile also minimizes the total energy input when there is no need to brake to maintain constant speed. However, if braking is required to maintain constant speed, applying braking only to maintain constant speed will probably increase the total energy required due to the need to refill the energy dissipated by the brakes. There is a possibility that some braking can actually reduce the use of total energy, if the additional brake loss is greater than the compensation for the decrease in drag caused by braking, reducing the variation in speed. After completing a new planning from the collection of the events described above, the new optimum notch / speed plan can be followed using the closed circuit control described here. However, in some situations there may not be enough time to carry out the decomposed planning per segment described above, and particularly when there are critical speed restrictions that must be respected, an alternative may be preferred. One embodiment of the present invention accomplishes this with an algorithm referred to as "intelligent crossover control". The intelligent crossover control algorithm is an efficient process for generating, in flight, a suboptimal energy-efficient (therefore fuel-efficient) prescription for driving train 31 through known terrain. This algorithm assumes knowledge of the position of train 31 along lane 34 at all times, as well as the knowledge of the degree and curvature of the lane, versus position. The method depends on a mass-point model for the movement of the train 31, whose parameters can be estimated in the form of adaptation from online measurements of the movement of the train, as described above. The intelligent crossover control algorithm has three main components, specifically a modified speed limit profile that serves as an efficient guide and an energy around speed limit reductions; an adjustment profile of ideal acceleration or dynamic braking configuration that attempts to balance, minimizing variations in speed and braking; and a mechanism for combining the last two components to produce a notch command, using a velocity feedback circuit to compensate for mismatches of modeled parameters when compared to reality parameters. Intelligent crossover control can accommodate strategies in the embodiments of the present invention, without active braking (i.e., the driver is signaled and assumed to provide the requisite braking) or a variant that provides active braking. With respect to the crossover control algorithm that does not control dynamic braking, the three example components are a modified speed limit profile that serves as an efficient guide and an energy around speed limit reductions, a notification signal that notifies the operator when braking must be activated, an ideal acceleration profile that attempts to balance minimizing variations in speed and notifying the operator to apply braking and a mechanism that uses a feedback loop to compensate for mismatches of the model parameters to the parameters real. Also included, in accordance with aspects of the present invention, is a method for identifying key parameter values of the train 31. For example, with respect to the train mass estimate, a Kalman filter and a minimum method can be used. resource squares to detect errors that can develop over time. Figure 7 illustrates an exemplary flow chart of the present invention. As previously described, a remote installation, such as a dispatch center 60 may provide information to be used in the present invention. As illustrated, said information is provided to an executive control element 62. The executive control element 62 is also provided with a modeling information database of the locomotive 63, a lane information database 36 such as , but not limited to, lane grade information and speed limit information, estimated train parameters such as, but not limited to, train weight and drag coefficients, and fuel range tables of a range estimator. fuel 64. The executive control element 62 provides information to the integrator 12, which is described in greater detail in figure 1. Once a route plan has been calculated, the plan is provided to a driving advertiser, operator or controller element 51. The route plan is also provided to the executive control element 62 so that it can compare the route when other new data is provided. As described above, the driving advertiser 51 can automatically adjust a notch power, either a pre-set notch setting or an optimal, continuous notch power value. In addition to providing a speed command to the locomotive 31, a screen 68 is provided so that the operator can see what the glider has recommended. The operator also has access to the control panel 69. Through the control panel 69, the operator can decide whether to apply the recommended notch power. For this purpose, the operator can limit a directed or recommended power. That is, at any time the operator always has the final authority with respect to the power configuration for the operation of the locomotive group, including whether brakes are applied if the plan recommends decreasing the speed of the train 31. For example, if In dark territory, or when the information of the team on the edge of the road can not transmit information electronically to a train, and rather the operator observes visual signals of the equipment on the road, the operator enters commands based on information contained in the base of Lane data and visual signals from the team on the road. Based on how the train is working 31, the information regarding fuel measurements is supplied to the fuel range estimator 64. Since direct measurement of fuel flows is not normally available in a group of locomotives, all fuel information consumed at a point in the route and the projections in the future if the optimal plans are followed, use calibrated physical models, such as those used in the development of the optimal plans. For example, such anticipations may include, but are not limited to, the use of measured gross horsepower and known fuel characteristics to derive the cumulative fuel used. The train 31 also has a locator apparatus 30 such as a GPS sensor, as described above. Information is supplied to the train parameter estimator 65. Such information may include, but is not limited to, GPS sensor data, traction / braking effort data, braking state data, speed of any changes in speed data. . With the information regarding grade information and speed limit, information of train weight and drag coefficients is provided to the executive control element 62. An embodiment of the present invention may also allow the use of continuously variable power through optimization planning, and implementation of closed circuit control. In a conventional locomotive, the power is normally quantified to eight independent levels. Modern locomotives may consider a continuous variation in horsepower that can be incorporated into the optimization methods described above. With continuous power, the locomotive 42 can further optimize the operating conditions, for example, by minimizing the auxiliary loads and power transmission losses, and fine-tuning the horsepower regions of the engine of optimum efficiency or points of increased emission margins. The example includes, but is not limited to, minimizing cooling system losses, adjusting alternator voltages, adjusting engine speeds, and reducing the number of energized axles. In addition, the locomotive 42 can utilize the on-board rail database 36, and the predicted performance requirements to minimize auxiliary loads and power transmission losses to provide optimum efficiency for the target fuel consumption / emissions. Examples include, but are not limited to, reducing a number of energized axles in flat terrain and previously cooling the engine of the locomotive before entering a tunnel. One embodiment of the present invention also utilizes the on-board rail track database 36 in the expected performance to adjust the performance of the locomotive, such as to ensure that the train has sufficient speed as it arrives at a mountain and / or tunnel . For example, it can be expressed as a speed restriction in a particular location that becomes part of the generation of the optimal plan created to solve the equation (OP). In addition, the embodiment of the present invention may incorporate train handling rules, such as, but not limited to, traction force ramp ranges, maximum braking force ramp ranges. These can be incorporated directly into the formulation for an optimum path profile or alternatively incorporated into the closed-loop regulator used to control the application of power to achieve the target velocity. In a preferred embodiment of the present invention, said mode is installed only on a front locomotive of the train assembly group. Even though the embodiment of the present invention does not depend on data or interactions with other locomotives, it can be integrated with a group administrator, such as described in US Patent No. 6,691,957 and in Patent Application No. 10/429, 596 (belonging to the Assignee and both are incorporated as reference), functionality and / or functionality of the group optimizer to improve efficiency. The interaction with multiple trains is not excluded as illustrated in the example of the arbitration of the dispatch of two trains "independently optimized" described here. One embodiment of the present invention can be used with groups in which the locomotives are contiguous, for example, with one or more locomotives from the front, others in the middle and at the rear of the train. These configurations are called distributed power, where the standard connection between the locomotives is replaced by radio link or an auxiliary cable to externally link the locomotives. When operating in distributed power, the operator in a main locomotive can control the operating functions of the remote locomotives in the group through a control system, such as a distributed power control element. In particular, when operating in distributed power, the operator can command each group of locomotives to operate at a different notch power level (or one group can be driven and the other can be braked) where each individual part in the group of locomotives operate the same notch power. Trains with distributed power systems can operate in different modes. One mode is where all the locomotives in the train operate in the same notch command. Therefore, if the main locomotive is commanding the N8 drive, all the units in the train will be commanded to generate the driving power - N8. Another mode of operation is "independent" control. In this mode, the locomotives or groups of locomotives distributed along the train can be operated in different powers of driving or braking. For example, as a train passes over the top of a mountain, the main locomotives (on the descending slope of the mountain) can be placed in braking, while the locomotives in the middle or at the end of the train (in the ascending slope of the mountain) may be in conduction. This is done to minimize the tensile forces to the mechanical couplers that connect the wagons and the locomotives. Traditionally, the operation of the distributed power system in the "independent" mode requires that the operator will manually command each locomotive or set of remote locomotives through a screen in the main locomotive. Using the physics-based planning model, ten configuration information, on-board railroad database, on-board operation rules, location determination system, real-time closed-circuit power / braking control and sensor feedback, the system must automatically operate the distributed power system in "independent" mode. When operating in the distributed power, the operator in a main locomotive can control the operating functions of the remote locomotives in the remote assembly through a control system, such as a distributed power control element. Therefore when operating in a distributed power, the operator can command each set of locomotives to operate at a different notch power level (or one set can be in driving and the other can be in braking) where each individual locomotive in the set of locomotives operates in the same notch power. In an exemplary embodiment, with the embodiment of the present invention installed in the train, preferably in communication with the distributed power control element, when a notch power level of a set of remote locomotives is desired as recommended by the optimized route plan, the modality of the present invention will communicate this power configuration to the set of remote locomotives for its implementation. As described later, braking applications are implemented in a similar way. When operating with distributed power, the previously described optimization problem can be improved to allow additional degrees of freedom, since each of the remote units can be controlled independently from the main unit. The value of this is that they can be incorporated into the performance function, objectives or additional restrictions that refer to forces in train, assuming that the model reflects the train forces that are also included. Therefore, various aspects of the present invention may include the use of multiple throttle controls to better handle train forces, as well as fuel consumption and emissions. In a train that uses a group manager, the main locomotive in a group of locomotives can operate in a different notch power configuration than the other locomotives that are in the group. The other locomotives in the group operate in the same notch power configuration. The embodiment of the present invention can be used together with the group administrator to command the notch power settings for the locomotives in the group achieved. Therefore, since the group administrator divides a group of locomotives into two groups, the main locomotive and the towing units, the main locomotive will be commanded to operate at a certain notch power and the locomotives will be commanded to operate in another certain notch power. In an exemplary embodiment, the distributed power control element may be the system and / or apparatus in which this operation is carried out. Likewise, when a group optimizer is used with a group of locomotives, the embodiment of the present invention can be used together with the group optimizer to determine the notch power for each locomotive in the locomotive group. For example, it is assumed that a route plan recommends a notch power setting of four for the locomotive group. Based on the location of the train, the group optimizer will take this information and subsequently determine the notch power setting for each locomotive in the group. In this implementation, the efficiency of the configuration of the notch power configurations with respect to the intra-rail communication channels is improved. In addition, as described above, the implementation of this configuration can be carried out using the distributed control system. In addition, as described above, the embodiment of the present invention can be used for continuous corrections and re-planning with respect to when the train group uses braking based on input aspects of interest, such as but not limited to, railroad crossings, grade changes, arrival at dead roads, arrival at deposit fields and arrival at fuel stations where each locomotive in the group may require a different braking option. For example, if the train is reaching a mountain, the main locomotive may have to enter a braking condition while remote locomotives, which have not reached the mountain peak, may have to remain in a driving state. Figures 8, 9 and 10 show exemplary illustrations of dynamic displays for use by the operator. Figure 8 provides a travel profile 72. A location 73 of the locomotive is provided within the profile. Information such as train length 105 and carriage number 106 is provided on the train. Elements are also provided with respect to the grade of rail 107, curve and elements on board road 108, including location of bridge 109 and speed of train 110. Screen 68 allows the operator to see such information and also see when the train It is along the route. Information corresponding to distance and / or estimated time of arrival is provided to locations such as intersections 112, signals 114, speed changes 116, landmarks 118 and destinations 120. A time-of-arrival management tool 125 is also provided to allow the user to determine the fuel savings that are being made during the journey. The operator has the ability to vary arrival times 127 and witness how this affects fuel savings. As described in the present invention, those skilled in the art will recognize that fuel savings is an example of only one objective that can be reviewed with a management tool. For this purpose, depending on the parameter that is being seen, other parameters can be seen, described here and evaluated with a management tool that is visible to the operator. The operator is also supplied with information regarding how much the train is being operated by the crew. In example modalities, the time and distance information can be illustrated as the time and / or distance until a particular event and / or location can provide a total elapsed time.

As illustrated in Figure 9, an example screen provides information regarding group data 130, a graph of events and situations 132, a time-of-arrival management tool 134, and action keys 136. It is provided also on this screen, information similar to that described above. This screen 68 also provides action keys 138 to allow the operator to plan again, as well as disengage 140 from the embodiment of the present invention. Figure 10 illustrates another example mode of the screen. Typical data of a modern locomotive including air brake condition 72, analog speedometer with digital inserts 74 and information regarding the tensile force in pounds force (or traction amperes for CD locomotives) are visible. An indicator 74 is provided to show the current optimum speed in the plan being executed, as well as an accelerometer graph to supplement the reading in mph / minute. The new important data for an optimal plan execution is in the center of the screen, including a rolling strip graph 76 with optimal velocity and notch configuration versus distance compared to the history of that moment of these variables. In this example mode, the train location is derived using the locator element. As illustrated, the location is provided by identifying how far the train is from its final destination, an absolute position, an initial destination, an intermediate point and / or an operator input. The graph of the tape provides a top view of the changes in speed required to follow the optimal plan, which is useful in manual control, and monitors the plan versus the real during automatic control. As described in the present invention, such as when in the steering mode, the operator can either follow the notch or the speed suggested by the embodiment of the present invention. The vertical bar provides a graph of a real desired notch, which is also displayed digitally below the ribbon graph. When using continuous notch power, as described above, the screen will simply round off the closest independent equivalent, the screen can be a similar screen so that an analog equivalent or a percentage or horsepower / actual traction will be displayed. Critical information is displayed on the route status on the screen, and shows the grade in which the train is at that moment, either by the main locomotive 88, a location anywhere along the train or an average in the length of the train. Also described is a distance traveled in plan 90, cumulative fuel used 92, where the distance to the next stop is planned 94, the time of arrival of that moment and projected 96 expected will be at the next stop. Screen 68 also shows the maximum possible time to the possible destination with the available computerized plans. If a later arrival is required, a new plan can be carried out. The delta plan data shows the state of expenses for fuel and programming or corresponding to the optimal plan at that moment. Negative numbers mean less fuel or an early arrival compared to the plan, positive numbers show more fuel or a late arrival compared to the plan, and usually in the negotiation in opposite directions (when you slow down to save fuel you will causes the train to arrive late and vice versa). Every time you are screens 68 provide the operator with a screenshot of where you are with respect to the split plan instituted at that time. This plan is for illustrative purposes only, since there are many other ways to deploy / transport this information to the operator and / or dispatch. For this end, the information described above can be intermixed to provide a different display to those described. Other features that may be included in the embodiment of the present invention include, but are not limited to, allowing the generation of records and data reports. This information can be stored on the train and downloaded to an outboard system at some point in time. Downloads can occur through manual and / or wireless transmission. This information can also be seen by the operator through the locomotive screen. The data may include information such as, but not limited to, operator inputs, the time system is operational, fuel saved, fuel imbalance through the locomotives on the train, off-course train journeys, diagnostic emissions from the system such as the GPS sensor is working well. Since the route plan must take into consideration the operating time of the allowable crew, the modality of the present invention may take such information into consideration as a planned route. For example, if the maximum time a crew can operate is eight hours, then the route should be modeled to include a stopping location for a new crew to take the place of that crew. Said locations of specified stops may include, but are not limited to, train stations, meeting / passing locations, etc. If, as the travel progresses, the travel time may be exceeded, the mode of the present invention may be mastered by the operator to meet the criteria as determined by the operator. Finally, regardless of the operating conditions of the train, such as but not limited to a high level load, low speed, train expansion conditions, etc., the operator remains in control to command a speed and / or operation condition. of the train. According to different aspects of the present invention, the train can operate in a plurality of operations. In an operation concept, the embodiment of the present invention can provide commands to command the proportion, dynamic braking. Subsequently, the operator manages all other train functions. In another operation concept, the embodiment of the present invention can provide commands to command only the propulsion. The operator then handles dynamic braking and all other functions. In yet another operating concept, the embodiment of the present invention can provide commands to command propulsion, dynamic braking and application of air brakes. The operator handles all other train functions. The embodiments of the present invention can also notify the operator of the next issues of interest of the actions that will be taken. Specifically, the forecasting logic of the mode of the present invention, the continuous corrections and re-planning to the optimized route plan, the tracking database, the operator can be notified of upcoming junctions, signals, changes of grade, braking actions, dead lanes, train stations, fuel stations, etc. This notification may occur in audible form and / or through the operator interface. Specifically, using the physics-based planning model, the train configuration information, the on-board tracking database, the on-board operation rules, the location determination system, the power control / circuit brake closed in real time and sensor feedback, the system must submit and / or notify the operator the required actions. The notification can be visual and / or audible. Examples include notifying crossovers that require the operator to activate the locomotive's horn and / or bell, notification of "silent" junctions that do not require the operator to activate the horn or bell of the locomotive. In another example mode, using the physics-based planning model described above, the train configuration information, the on-board tracking database, the on-board operation rules, the location determination system, the control Power / real-time closed loop braking and sensor feedback, the embodiment of the present invention can present the operator with information (eg, a gauge on the screen) that allows the operator to see when the train will arrive at the various locations such as shown in figure 9. The system must allow the operator to adjust the route plan (target arrival time). This information (actual estimated arrival time or information needed for outboard derivation) can also be communicated to the dispatch center to allow the dispatcher or dispatch system to adjust the target arrival times. This allows the system to adjust quickly and optimize for the appropriate objective function, (for example, negotiation between speed and fuel usage). Multiple railway vehicles (locomotives, or wagons, trains, maintenance vehicles on the road and other energized vehicles) operate through a railway line within fixed or mobile segments (referred to as railway blocks) with a real or synthetic signal at a block entry point indicating a current state of the block. The signal notifies an operator of the rail vehicle that is arriving at the block, whether the block is allowed to enter or not, and if so, can give notice of a restricted speed at which the block can be entered. The speed of entering the block is normally determined in response to a state of the subsequent block (s) along the path or travel of that vehicle moment. A block signal comprises a signal aspect (a visual element such as a light with color or an arm position) that provides a signal indication. The indication gives notice to the operator of the vehicle if the block can be entered and can give additional notice of the speed of the vehicle as the vehicle enters and travels through the block. For example, the indication can command the vehicle to immediately reduce the speed when entering the block or at a specific location within the block. The indication can also command speed limits for the next block. A block occupancy detector detects whether a vehicle occupies a block and the associated control components configure the block signals that precede the occupied block correspondingly. There are many different types of block signal aspects, each having unique indications associated with the aspects. For example, signals with light may comprise a simple color controlled light for an on or off state or multi-colored lenses illuminated through a single light, wherein the movement of the lenses is controlled to place the desired lens color. in the front of the light. Other light signals include multiple lights that operate with multiple colored lenses and flashing lights. Although the operator of the vehicle will visually perceive the aspect of the signal as the vehicle arrives at the aspect, several components on board also communicate the appearance to the operator. The electrical components near the entrainment signal generate an electrical signal representative of the signal aspect. As the vehicle passes through or in close proximity to these components, the electrical signal is transferred to a lifting coil located in the locomotive. The operator is thus presented with an indication of the signal aspect inside the cab of the locomotive. Other signaling systems include a wireless communication link between the railway signal and the locomotive. A vehicle that arrives at a block occupied by another vehicle, you will see (normally) a red aspect that indicates that the vehicle must stop for a moment in the block. A vehicle that reaches an unoccupied block (a clear block) can usually see a green appearance that indicates that the vehicle can enter the block at its current speed. Several configurations of the yellow aspects indicate entry with restricted speed and crossing with restricted speed through the block. For example, a railway segment comprising first and second blocks in series with a first vehicle arriving at the first block and a second vehicle occupying the second block. The first vehicle that is arriving from the first block may be allowed, but at a restricted speed that allows the first vehicle to stop safely if it reaches the entry point of the second block before the second vehicle leaves the second block. Therefore, the vehicles that cross the railway network block by block with entry to each controlled block, avoids a situation where two vehicles occupy the same block. Rail switches that can direct a vehicle that arrives along two or more railroad branches can also be protected with a signal. A switch signal indicates the status of the block defined by the branches of the switch and may also indicate the position of the switch, allowing the operator of the arriving vehicle to determine if the switch conforms to the desired railroad branch. The signal aspects of the block (and switch signal aspects) and the associated indication, accurately indicate the actual time status of the block (and the switch) based on the occupation state of the block. However, to control the railroad and the movement of individual vehicles in the network, it may be necessary for a dispatcher to adjust the block signals and switch signals according to projected future locations of the vehicles traversing the network. These predictions of future vehicle locations are becoming less precise, as predictions extend to the future. The unpredictable nature of vehicle movement can cause the dispatcher to conservatively adjust the signals, resulting in reduced efficiency across the railroad. The uncertainty of these future block and switch signal anticipations is due to many uncontrollable causes that include, but are not limited to, environmental conditions such as weather, snow, ice and storms.; mechanical failures of equipment such as wagons, locomotives, railroad tracks, and equipment along the road; crew operating behaviors such as vehicle handling and speed configuration; maintenance efforts such as road repairs and road side equipment and vehicle accidents and diverting traffic jams. As a result, the status of any block signal or switch signal of a railroad segment where at least two vehicles cross or use the same rail segment is known precisely only for the past states, up to and including the current state. The path optimizer modes described above slow down the vehicle or stop it based on the state of the next block or switch signal in the vehicle's travel path. Generally, the travel optimizer algorithm reduces the speed in a range that minimizes fuel consumption, allowing the vehicle to reach the desired speed at the desired railroad location as required to enforce block occupancy rules and traffic restrictions. speed. For example, if a first vehicle is shown with a restricted indication as it enters a block, the standard vehicle control rules require the vehicle to slow down at a designated speed, so that it can stop safely before entering the vehicle. next block in the case that a second vehicle that occupies at that time the next block, has not evicted said block when the first vehicle arrives at the entry point of the block.

According to other modalities of the route optimizer, the state of the block signals is anticipated or determined in a probabilistic manner and the vehicle's speed trajectory is controlled in accordance with the future block states, thus optimizing the fuel consumption , at the same time increasing the performance of the network. Whether the current state of the following signals (eg, one, two, three or more) is known (as determined by their respective block occupations), and the location, speed, arrival time and / or address of travel of other vehicles that can intercept the trajectory of the vehicle (for example, travel parameters) are known, the route optimizer probabilistically determines the future state of the signals that the vehicle will find. In response to this, the travel optimizer modifies the vehicle's speed trajectory (traction and braking effort applications) based on the determined probability that the successive block signals will change / be erased before the vehicle reaches those signals . Since a probabilistic determination can not definitively determine the future state of the successive signals, the travel optimizer also controls the vehicle's speed path to allow the vehicle to be safely stopped or to slow down, if a state The real time signal presented to the vehicle differs from the anticipated state. A probabilistic determination may indicate that the rail blocks along the path of travel of the vehicle can be cleared as a vehicle reaches said blocks, allowing unimpeded entry to the cleared block. Multiple parameters and network conditions of the vehicle and the railroad must be considered in the determination of this probability. If the determined probability is relatively high, the vehicle is controlled according to a speed trajectory that responds to the anticipated block states. Generally, the travel optimizer may not use anticipated future block occupations with a low probability to control the vehicle.

For example, it is assumed that a front block is normally occupied, although it is determined with a relatively high probability that the block will be cleared when the vehicle reaches the entry point of the block. In this way, the vehicle's travel optimizer determines the speed trajectory of the vehicle according to the anticipation that the block will be clear. The fuel consumption of the vehicle is optimized in this way during this travel interval. However, the speed trajectory should also consider the possibility that the front block is not clear, as anticipated. Recognition that this condition is less likely than a block cleared, the speed path includes a delayed generation of a speed reduction, that is, the speed reduction is delayed to a later time or a forward rail location that provides enough distance / time to stop or slow down the vehicle as required, if the block ahead is not clear. However, the delayed generation of the speed reduction may require a more aggressive braking application to slow down or stop the vehicle. Although it is recognized that the probability that it is necessary, in fact, a more aggressive braking application is low. Therefore, the route optimizer of one mode optimizes the fuel consumption during the course of a vehicle, while satisfying the rules of occupation of the block. If the anticipations to future block occupations are wrong, some fuel optimization can be considered. In addition, the application of these probabilistic concepts throughout the rail network will improve fuel efficiency for most vehicles for most of their encounters with anticipated railroad occupations. Although the fuel consumption of individual vehicles may not always be optimized, the fuel consumption in the whole railway will be improved. The events that are closest in time can be anticipated with greater precision, and therefore can be implemented in a trajectory of the path optimizer with greater reliability. For example, for a railroad network including a first and second series block, if a vehicle is almost clear of the second block, then it may not be necessary to decrease the speed of the vehicle of interest, as it enters the first block since it is It is likely that the vehicle ahead will clear the second block before the vehicle of interest reaches the entry point of the second block. The travel optimization algorithm correspondingly modifies the speed trajectory of the vehicle of interest based on the probability that the signal will be clear, allowing to travel through the block at a maintained speed. In one embodiment, the path optimizer uses a threshold value probability to determine the velocity path. For example, if the probability that the front block is cleared is greater than a predetermined threshold value probability, then the speed path is determined by assuming a direct clear block, with permits to stop or slow down the vehicle as required. , but future events have been anticipated. In another modality, instead of using a probability threshold value, the determined probability controls the time / rail location in which the speed reduction is initiated. A lower probability that the front block will clear (that is, the vehicle will be able to see a green indication and therefore is allowed to enter the block at its current speed) will result in a previous speed reduction start ( for example, location of time / railroad). The time / rail location where the speed reduction begins responds to the probability. A higher probability that the front light block will clear, results in a delayed generation of the speed reduction. The time / rail location where the speed reduction begins again responds to the probability value. However, the time / rail location to initiate the speed reduction is always determined to allow compliance with the railroad signals, as the vehicle finds them in real time. The operation information, such as location of the vehicles, their speed and path of travel, which is required to determine the probabilities described above can be supplied through a wireless communication link, for example, from a track dispatch center. rail, to be used by an on-board travel optimizer. As an alternative, the information can be supplied through other communication links between the locomotive and the dispatch center. In a railway network, with communication links between operating vehicles, the information can be supplied directly between the vehicles in the same path. The information can be provided through vehicles that are ahead of the vehicle of interest. For example, a vehicle that is ahead can warn either its speed, position and estimated time to vacate the block. Alternatively, if the vehicle ahead provides either the location, speed, speed path (based on grade / rail information) distance to the next block, the route optimizer algorithm that runs on board the vehicle of interest , can computerize the anticipated state of the next block. Even in another modality, the vehicle of interest can estimate the time in which the next block can be cleared based on the type of vehicle that is ahead, for example, passenger, high priority or low priority. The information from which the probability of a block that is ahead can be determined, can also be supplied through signals directly to the vehicles. Depending on the location where the optimization algorithm is executed, the operation information can be transferred in said location by wireless, wired, radio frequency, acoustic, energy line conveyor, optical and manual operator techniques. According to another modality, the path optimizer uses knowledge of past experiences or commonly encountered indications of signals that come back to anticipate the state of these signals and develop a speed trajectory according to these anticipations. If there is a relatively high probability (based on past experience) that the signal will clear, it may not be necessary for the vehicle to slow down. Rather, the reduction in speed (either through the application of braking effort or reduction of tractive effort) can be delayed at a later time or location of the railway. At that moment, the location of time or railway track of the state of the real-time signal is determined and a decision is made regarding the control of the vehicle, for example, if the signal has not been cleared, the speed begins to decrease of the vehicle as required to stop at the desired location or if the signal has been cleared, the vehicle is allowed to pass through the block at its speed. Figures 11A and 11B illustrate the concepts described for a railroad train. A train 400 in block 401 and traveling in a direction indicated by arrow 404, approaching a yellow signal aspect 408 at an entry point of a block 412 and a red signal aspect 414 at an entry point of a block 420. A train 418. which runs in a direction indicated by arrow 423, appears to be near an exit of block 420. Figure 11B illustrates a speed path 440 of a train 400 when the information regarding the state of the blocks 412 and 420 is not known by the train 400, as it passes through the block 401. The speed values established in the abscissa and time, distance or location are established in the ordinate. As can be seen, according to a path segment 440A, the train decreases the speed S1 until it reaches a speed S2 in the signal 408. The speed S2 is slow enough to allow the train to decelerate so that it can be stopped at the entry point of block 420 (signal aspect 414) if train 418 has not left block 420, when train 400 arrives at the entry point. A different deceleration function or path segment 440B can be employed in block 412 so that speed S3 is zero in signal aspect 414. Alternatively, path segments 440A and 440B can be similar, each trajectory segment (and speed S2) according to the required practices of the railway and / or each speed trajectory can be determined based on the type and priority of trains 400 and 418, their speed and direction of travel and the speed value S1. The speed paths 440A and 440B may alternatively be non-linear. In one embodiment, wherein the route optimizer anticipates future signal aspects based on future block occupancies, if there is a relatively high probability that the block 420 is cleared before the train 400 arrives at the block entry point ( signal aspect 414), train 400 is controlled in accordance with an example speed trajectory 444. This trajectory allows train 400 to maintain its speed S1 along a path segment 444C until a point (or time) ) 444B is reached, time in which train 400 begins to decelerate along path 444A if block 420 is not cleared at that time. If block 420 is clear at point 444B, then train 400 continues in a speed path 444D. The point 444B is selected to allow the train 400 to reach the speed S2 in signal aspect 408, decelerating according to the speed path 444A, and can also selectively respond to the probability that the train 418 clears the block 420 before the train 400 arrives at the signal aspect 414. For example, the deceleration start point 444B moves back in time (allowing a less aggressive deceleration or braking effort to arrive at the speed S2 in the aspect of signal 408) that responds to a relatively low probability that block 420 is clear. The deceleration start point 444B moves forward in time (requiring a more aggressive deceleration or braking effort to reach the speed S2 in the signal aspect 408) that responds to a relatively high probability that the block 420 remains clear. If point 444B is the last point or time at which the train can begin to decelerate to reach speed S2 at signal aspect 408, and there is a relatively low probability that block 420 will clear before train 400 Arrive at signal aspect 408, efficient rail and train operation, suggesting an earlier start of deceleration to conserve fuel. As an alternative to moving the deceleration point 444B or in addition to this, the slope of the path segment 444A can be controlled in response to the determined probability. It should be noted that the speed path 444 decelerates the train 400 to the speed S2 at the same point or time as the speed path 440, but requires more aggressive braking, as indicated by the magnitude of the segment of the trajectory line 444A, which for the segment of the trajectory line 440A. However, in a situation where the point 444B is selected based on a relatively high probability, that although the train 400 is going through the speed path 444C (for example, before beginning its speed reduction at point 444B in path 444) block 420 will be cleared, it is highly probable that train 400 is allowed to pass through clear signal 414, and therefore, in fact, no speed reduction is required. Although the speed reduction in the trajectory 400 must be somewhat unusual, since the braking is more aggressive than commonly used, it is recognized that this trajectory is unlikely to be implemented since the probability that the train 418 leaves the block 420 and clear signal 414 before train 400 reaches the entry point of block 420, it is quite high. However, in the event that the train 418 does not clear the block 420 as intended, the train 400 slows down to the correct speed S2 in the correct location and the safety of the train is not compromised. Each of the various velocity paths and the segments thereof (and the speed S2) as set forth in Figure 11B, can be determined in accordance with the required practices of the railway and / or each speed path can be determined based on the type and priority of trains 400 and 418 and the speed value S1. The trajectories of speed can be nonlinear, increasing in speed with time or decreasing in speed with time, depending on the determined probabilities, train operations and other train parameters.

Although the probability-determined characteristics of the present invention can be described with respect to the quantified probability value, other modalities can use the probability range or estimate the qualitative ones of the probability or possibility, especially since it is recognized that a plurality of factors exist, including factors that vary with time, which affect the travel of train 418 through block 420 and therefore impact the likelihood that train 418 will clear block 420 before the desired time. In another embodiment, the speed of the vehicle through a block responds to a block output speed determined in a probabilistic manner (or switching pass speed). That is, the speed is reduced in a first range that responds to a relatively high probability that the next block is not cleared in time, and the speed is reduced (or maintained or even increased) in a second range that responds to a relatively high probability that the next block will be clear in time. Therefore, the speed reduction range and the target speed at the end of the speed reduction range, responds to the probability that the next block is cleared before the train 400 reaches the entry point of the block. A speed trajectory 448 illustrated in Figure 11 B illustrates said different deceleration range, as compared to the speed trajectory 444, and can be implemented according to a lower probability that the block 420 is clear, than the probability associated with the speed trajectory 444. The braking and speed control mechanisms described here attempt to limit fuel consumption and reduce braking efforts that respond to determined or estimated probabilities of future occupancy of the block along the trajectory of the travel of the vehicle. This technique reduces the "hurry up and wait" scenario, common in the daily operations of railroads. In another embodiment, the probability that train 418 clears block 420 is determined continuously or at a plurality of time points during path segment 444C. As the calculated probability increases, the point 444B at which the speed reduction begins can be moved forward in time and as the probability at point 444B decreases, it can move backward in time. According to another modality, the performance of the vehicle can be improved if the route optimizer considers the information with respect to previous operations in the same track segment, in the development of an optimized route plan for the route of that moment. For example, information is provided to the path optimizer with respect to the following conditions, during previous travels in the same rail segment: signal states, operator actions, unexpected vehicle or rail conditions and vehicle congestion. This information is used to develop the statistical bases for planning the route, assuming that high priority events will occur as in the past. For example, if certain signal aspects of the previous routes in the railway segment were found to be 90%, the railway optimizer assumes that the same signals will be presented in the course of that moment, and correspondingly develops the speed trajectory. During the planned route, the route optimizer reviews the signal aspects in real time with sufficient time allocated to allow the vehicle speed to be safely decreased in case the signal aspects are not as anticipated. Therefore, despite its probabilistic basis, the trajectory includes sufficient margin (time and / or distance) to safely control the vehicle under circumstances where the real-time events differ from the anticipated events. As a result of these statistical considerations, on an aggregate basis, the travel optimizer improves vehicle efficiency. That is, although the optimization of each route may not be improved because the signal aspects are different from what was anticipated and the vehicle may therefore need to slow down or stop along an "inefficient" speed trajectory. Vehicle efficiency will be improved for most vehicle tours, that is, overall operational efficiency is improved. Because vehicle and rail conditions may be different from those assumed by the path optimizer in the generation of the speed trajectory, there may be unnecessary braking applications that result in increased fuel consumption. Similarly, as certain conditions (for example, vehicle congestion) occur during almost every vehicle run on a particular rail segment, another mode of the route optimizer considers this statistical information in the development of the speed path. Therefore, according to another embodiment of the present invention, the trip plans are generated without base in the worst case or best case efficiency, but rather based on the most probable operating conditions or in a range of conditions of probable operations, considering the statistical nature of these conditions. While certain modalities of the route optimizer use only independent data to develop the speed trajectory, this modality provides an improvement of using additional statistical information that can offer, at least in the aggregate, improved performance. For each switching signal or block there is a typical configuration most likely depending on the traffic patterns of the vehicle such as time of day, season, type of traffic, etc. If the most probable configuration can be determined, the vehicle speed is adjusted so that an optimum block / switching output speed is achieved. Instead of determining the average configuration, other statistical parameters (such as a two sigma limit) can be used depending on the variations of the signal configuration from the average and the amount of improvement in fuel efficiency that can be achieved . According to another embodiment of the present invention, the overall speed of the mission is calculated to optimize an operation parameter within blocks and optimize the output speed of a block. That is, if a planning tool adds a time regulator to the end of a route block, then in the logic interface of the block and the time regulator, the overall speed can be optimized to allow the use of the time regulator for a lower block velocity that prevents the insertion of a large velocity transition. Therefore, time regulators, when used, can be considered in previously set speed paths to minimize large velocity transitions, i.e., higher braking applications. In another modality, the arbitrariness between two vehicles competing for the same rail resource is considered by the route optimizer. The vehicle that provides the most efficient operating result is selected to use the resource, thus optimizing the fuel consumption and / or efficiency of the network, since it is unlikely that the speed trajectory of both vehicles could be optimized For example, when two vehicles arrive at an intercept where each one requires the use of a single railroad segment, the arbitrariness mechanism determines which of the two selections will result in a more optimized rail network. The optimization algorithm determines the best choice based on operating parameters of individual vehicles and the parameters of the rail network. The fuel efficiency of the vehicle, the maximum allowed rail speed, the average rail speed, the order of priority to arrive at the destination are some of the factors that are considered through the optimization algorithm. Likewise, the results of previous encounters with similar vehicles through similar railway segments can also be considered by the algorithm. For example, a previous encounter may have produced excessive incremental braking for one of the vehicles or caused one of the vehicles to exceed an acceleration limit. The determination of priority may also be based on local, regional or network levels and may include, but is not limited to, cargo, arrival time, fuel efficiency, time for a required crew change, crew change point, vitality of individual vehicles, emission requirements, etc. The optimization algorithms are generally known and can use any of the following techniques to optimize the function: achievement of the approximation, search tables, closed form solutions, Kalman filters, Taylor time series, expansions and any combination of these techniques. The data to be used in the optimization algorithms described above (which can be executed either on board the vehicle or in a dispatch center) can be provided by a manual data transfer from an outboard, such as a dispatch center for the local, regional or global vehicle. If the algorithms are executed in a team that is on the edge of the road, you can transfer necessary data to it passing the vehicles or through a dispatch center. Data transfer can also be carried out automatically using data transfer equipment and outboard computers, on board or on the edge of the road. Any combination of manual data transfer and automatic data transfer with computer implementation anywhere in the rail network can be adapted according to the teachings of the different embodiments of the present invention. The present invention contemplates multiple options for the processor to computerize the optimization data, including the processing of the algorithm in the locomotive of the vehicle to be used, within the equipment on the edge of the road, outboard (in a center-dispatch model) or at another location in the rail network. The execution can be pre-programmed, processed in real time or conducted through a designated event, such as a change in the operation parameters of the vehicle or locomotive, this is operation parameters related to either the vehicle of interest or other vehicles which can be intercepted by the vehicle of interest. The methods and apparatuses of the embodiments of the present invention offer improved locomotive fuel efficiency and network efficiency (at local, regional and global levels). The optimization technique also provides the ability to negotiate efficiency, speed and priorities. Since the techniques of the embodiments of the present invention are scalable, they provide an immediate rail network benefit even if they are not implemented throughout the network. They can be considered local negotiations without the need to consider the entire network. Later vehicles will find a better time of little activity at a higher average speed. As a result, more vehicles can be carried along the same railway track, without additional resource costs for the railway. Although the various embodiments of the present invention have been described in what is currently considered to be a preferred embodiment, various variations and modifications will be appreciated by those skilled in the art. For example, although it is described within the context of a railway network through which operate trains comprising locomotives and wagons, the teachings of the present invention also apply to other rail-based systems and vehicles that include, but are not limited to, interurban trains, for mobilizing people and trams. Correspondingly, it is intended that the present invention not be limited to the specific illustrative modalities, but be interpreted within its spirit and total scope of the appended claims.

Claims (65)

1. CLAIMS 1. A system for operating a railroad network comprising a first railroad vehicle along the route along railroad segments, wherein the system comprises: a first element for determining travel parameters of the first railroad vehicle; a second element for determining travel parameters of a second railway vehicle relative to the railroad segments that will be traversed by the first vehicle during the journey; a processor for receiving information of the first and second elements and for determining a relation between the occupation of the railroad segment by the second vehicle, and the subsequent occupation of the same railroad segment by the first vehicle; and an algorithm presented within the processor that has access to the information to create a route plan that determines a velocity path of the first vehicle, where the velocity trajectory responds to the ratio, and also in accordance with one or more criteria of operation for the first vehicle. The system as described in claim 1, characterized in that the relationship comprises a probability that the second vehicle occupies the railroad segment where the first vehicle arrives at an entry point of the railroad segment. 3. The system as described in claim 2, characterized in that the probability indicates whether the occupation of the second vehicle of a railway segment will affect the occupation of the first vehicle of the same railway segment, in accordance with the route plan . The system as described in claim 1, characterized in that the probability determines a time in which the speed of the first vehicle is reduced to avoid occupying a railroad segment concurrently with the occupation of the same segment of road. railway by the second vehicle. The system as described in claim 4, characterized in that a range in which the speed of the first vehicle is reduced, allows the first vehicle to achieve a desired speed at a later time. The system as described in claim 1, characterized in that the speed path comprises a speed reduction time and a speed reduction range, wherein a subsequent speed reduction time or a speed reduction range. higher respond to a relationship comprising a lower probability and a previous speed reduction time or a lower speed reduction range respond to a relationship comprising a greater probability. The system as described in claim 1, characterized in that the relationship determines a railway track location where the speed of the first vehicle is reduced to avoid occupying the railroad segment concurrently with the occupation of the same segment of railway track by the second vehicle. The system as described in claim 7, characterized in that a range is reduced in which the speed of the first vehicle allows the first vehicle to achieve a desired speed at an entry point for the railroad segment occupied by the vehicle. second vehicle. The system as described in claim 1, characterized in that the travel parameters comprise one or more of location, speed, travel plan, type, arrival time, direction of travel and priority. The system as described in claim 1, characterized in that the relationship comprises a probability that the second vehicle occupies the railroad segment when the first vehicle arrives at the entry point of the railroad segment, and where a probability lower than a predetermined probability threshold value is determined by the speed trajectory, as if the occupation of a rail segment by the second vehicle does not interfere with the occupancy of the same segment by the first vehicle. 11. The system as described in claim 1, characterized in that the processor is on board the first vehicle and the second element supplies the travel parameters of the second vehicle by wired, wireless, radio location, radiofrequency, acoustic, conveyor power line, optical and manual. The system as described in claim 1, characterized in that the speed path comprises a speed path of a railroad segment, immediately behind a railroad segment occupied concurrently by the second vehicle. The system as described in claim 1, characterized in that the velocity path that changes over time responds to time-variant changes in the relation. The system as described in claim 1, characterized in that the relationship responds in addition to the previous operation of vehicles tgh the railway segments. 15. The system as described in claim 1, characterized in that the relationship responds in addition to conditions of the railway and an operation condition of each of the first and second vehicles. 16. The system as described in claim 1, characterized in that the relationship responds in addition to the railroad signals that indicate the occupation of the vehicle of a railway segment. 17. The system as described in claim 16, characterized in that the probability also responds to the most probable indication of the railway signals. 18. The system as described in claim 1, characterized in that the speed path additionally responds to a relative priority between the first and second vehicles. The system as described in claim 1, characterized in that the second element determines a real-time location of the second vehicle in relation to railway segments, and the processor determines an anticipated location of the second vehicle that responds to a location of real time and travel parameters of the second vehicle. 20. The system as described in claim 1, characterized in that it further comprises a controller element for autonomously directing the vehicle to follow the speed path. 21. The system as described in claim 1, characterized in that an operator steers the vehicle according to the speed path. 22. The system as described in claim 1, characterized in that the algorithm autonomously determines the probability and updates the velocity path that responds to the information received from the first and second elements. 23. The system as described in claim 1, characterized in that the railway track segments comprise one or more railway track blocks, and wherein the second element determines the location of the second vehicle relative to the railway track blocks. , and wherein the algorithm optimizes the performance of the first vehicle that responds to the presence of the second vehicle in the railway blocks comprising railroad segments of the first vehicle's route. 24. The system as described in the claim 23, characterized in that the algorithm optimizes the performance of the first vehicle that responds to anticipated future locations of the second vehicle relative to the railroad blocks comprising railroad segments of the first vehicle's travel. 25. The system as described in claim 24, characterized in that the algorithm optimizes the performance of the first vehicle that responds to a probability associated with anticipated future locations of the second vehicle. 26. The system as described in the claim 24, characterized in that the speed path provides adequate control of the first vehicle if a real future location of the second vehicle is different from that anticipated. 27. The system as described in claim 24, characterized in that the anticipated future locations respond to past locations of the second vehicle during previous journeys through the railroad segments. The system as described in claim 24, characterized in that anticipated future locations of the second vehicle, respond to one or more railroad conditions of that time or future and operation parameters of that moment or future of the second vehicle. 29. The system as described in claim 1, characterized in that the speed path comprises an exit velocity of the first vehicle to exit each rail segment. 30. The system as described in claim 1, characterized in that the second element determines the location of the second vehicle in response to location information provided from a remote site or an edge equipment. The system as described in claim 1, characterized in that the first and second railway vehicles comprise a first respective train, which further comprises a first locomotive and first wagons, and a second train further comprising a second locomotive and second cars. 32. A system for operating a railroad network comprising a rail vehicle during a journey by the vehicle along railroad segments that respond to a location of other vehicles relative to the railroad segments, in where the system comprises: a first element for determining vehicle travel parameters; a second element to determine travel parameters of other vehicles; a processor that operates to receive information of the first and second elements; and an algorithm that is used within the processor that has access to the information to create a route plan that optimizes the vehicle's performance in response to the vehicle's travel parameters and the travel parameters of the other vehicles and in accordance with one or more criteria of vehicle operation. 33. The system as described in claim 32, characterized in that one of the path parameters of the other vehicles comprise locations of the other vehicles, wherein the system further comprises signals indicating a state of occupation of the track segments. rail for the location of the other vehicles relative to the railroad segments, and where the second element determines the location of the other vehicles in response to the signals. 34. The system as described in claim 32, characterized in that the travel parameters of the vehicle comprise the location of the vehicle or a time from which the vehicle's journey began, and where the travel parameters of other vehicles comprise speed , location, direction of travel and relative priority. 35. The system as described in claim 32, characterized in that the processor determines a probability that one or more vehicles occupy a railroad segment that affects the occupation by the vehicle of the same railroad segment according to the plan of the railroad. travel. 36. The system as described in the claim 32, characterized in that the processor determines a time in which the vehicle speed is reduced to avoid occupying the railroad segment concurrently with the occupation of the same railroad segment by another vehicle. 37. The system as described in claim 32, characterized in that the processor determines a range in which the vehicle speed is reduced to allow the vehicle to achieve a desired speed at a later time. 38. The system as described in claim 32, characterized in that the route plan comprises a time or location of railroad in which the speed reduction begins and a range of reduction of vehicle speed. 39. The system as described in the claim 32, characterized in that the processor determines a probability that one of the other vehicles occupies a railroad segment that affects the occupation of the vehicle of the same railroad segment according to the route plan, and where the processor modifies the plan of travel in response to probability. 40. The system as described in the. claim 39, characterized in that the route plan comprises a time in which the vehicle will start a speed reduction in a range of speed reduction, and where a later time at which the speed reduction begins or a greater range of speed Speed reduction, respond to a first probability and at an earlier time in which speed reduction or a lower range of speed reduction begins, responds to a second probability lower than the first probability. 41. The system as described in claim 32, characterized in that the processor determines the location of a railway track at or at the time when the vehicle speed is reduced to prevent entry into the railroad segment occupied by the vehicle. one of the other vehicles. 42. The system as described in claim 41, characterized in that a range in which the vehicle speed is reduced allows the vehicle to achieve a desired speed at an entry point of a railroad segment occupied by one of the others. vehicles. 43. The system as described in claim 32, characterized in that the processor is on board the vehicle and the second element supplies the travel parameters of the other vehicles through wired, wireless, radio location, radiofrequency, acoustic processes , transporters of power lines, optical and manual. 44. The system as described in claim 32, characterized in that the processor modifies the route plan with time that responds to the time variation parameters of the other vehicles. 45. The system as described in claim 32, characterized in that the travel parameters of the vehicle and the travel parameters of the other vehicles comprise a relative priority between the vehicle and the other vehicles. 46. The system as described in claim 32, characterized in that the second element determines a real time location of the other vehicles that respond to the travel parameters of the other vehicles, and the processor determines an anticipated location of the other vehicles. vehicles that respond to the travel parameters of the other vehicles. 47. The system as described in the claim 32, characterized in that the vehicle comprises a train that further comprises a first locomotive and first wagons, wherein each of the other vehicles comprises a locomotive. 48. A method for operating a rail vehicle during a journey along railroad segments of a railroad network, wherein the method comprises: determining vehicle travel parameters; determine travel parameters of other vehicles that cross the network; and executing an algorithm that responds to the vehicle's travel parameters and the travel parameters of the other vehicles, to optimize the vehicle's performance in accordance with one or more criteria of vehicle operation. 49. The method as described in the claim 48, characterized in that the travel parameters of the vehicle comprise a location of the vehicle or a time from which the vehicle's journey began, and where the travel parameters of other vehicles comprise one or more of the relative location of the railroad segments. , speed, automatic route plan, arrival time, direction of travel and priority. 50. The method as described in claim 48, characterized in that the railway network also comprises signals indicating the status of railway segments that respond to the location of the other vehicles relative to the railway segments, and wherein the step of determining the travel parameters of the other vehicles further comprises determining a condition of the signals to determine a location of the other vehicles. 51. The method as described in claim 48, characterized in that the execution step determines a probability that the occupancy of the segment of travel by one of the vehicles affects the occupation of the same segment of railway track by the vehicle and optimizes the vehicle performance additionally, according to the probability. 52. The method as described in claim 51, characterized in that one or more of a vehicle speed, a time or rail location where the vehicle speed is reduced and a range of speed reduction, respond to the probability. 53. The method as described in claim 48, characterized in that the execution step further comprises determining a vehicle speed path that responds to the travel parameters of the other vehicles. 54. The method as described in the claim 53, characterized in that the execution step further comprises determining an anticipated future location of the other vehicles, and where the vehicle's speed trajectory responds to it. 55. The method as described in the claim 54, characterized in that the execution step further comprises determining a real-time location of the other vehicles and modifying the speed path, if the real-time location is different from the anticipated location. 56. The method as described in claim 48, characterized in that the execution step further comprises determining anticipated future locations of the other vehicles, determining a probability that an anticipated future location of the other vehicles in relation to the railroad segment affects the occupation of the same segment of railway track by the vehicle, and optimizes the performance of the vehicle according to the probability. 57. The method as described in the claim 56, characterized in that the anticipated future locations of the other vehicles respond to past locations of the other vehicles during previous journeys through the railroad segments. 58. The method as described in claim 48, characterized in that the vehicle comprises a train that further comprises a locomotive and wagons. 59. A computer software code for operating a rail vehicle during a journey along railroad segments of the railroad network, wherein the software code comprises: a software module for determining the travel parameters of the railroad. vehicle; a software module to determine the travel parameters of other vehicles that cross the network; and a software module for executing an algorithm that responds to the vehicle's travel parameters and to the travel parameters of other vehicles to optimize the vehicle's performance in accordance with one or more criteria of vehicle operation. 60. The computer software code as described in claim 59, characterized in that it also comprises a software module to determine a probability that the occupation of a railroad segment through one of the other vehicles will affect the occupation of the railway segments by the vehicle during the journey and to optimize the performance of the vehicle additionally according to the probability. 61. The computer software code as described in claim 60, characterized in that it also comprises a software module for determining a train speed path that responds to the probability. 62. The computer software code as described in claim 61, characterized in that the parameters of the speed path comprise a range of speed reduction and a time or rail location, where the speed reduction begins. 63. The computer software code as described in claim 61, characterized in that the software module for executing the algorithm also anticipates a future location of the other vehicles and develops a route plan for the vehicle that responds to it. 64. The computer software code as described in claim 63, characterized in that the software module for executing the algorithm determines a real-time location of the other vehicles, determines any differences between the future location and the time location. real and modifies the route plan accordingly. 65. The computer software code as described in claim 63, characterized in that the route plan comprises a vehicle speed path.