METHOD FOR CONTROLLING A POWERED SYSTEM BASED ON MISSION PLAN FIELD OF THE INVENTION [01] Embodiments of the invention relate to methods for controlling vehicles and other powered systems. BACKGROUND OF THE INVENTION [02] Certain powered systems (e.g., trains and other rail vehicles, marine vessels, stationary diesel powered power generation units, and mining vehicles, agricultural vehicles, and other off-highway vehicles) include a diesel-fueled unit as a power source. With respect to rail vehicle systems, the diesel-fueled unit may be a diesel internal combustion engine that is housed in a locomotive. The locomotive may be part of a train that includes other locomotives and a plurality of rail cars, such as freight cars. Locomotives are complex systems with numerous subsystems, with each subsystem being interdependent on other subsystems. [03] An operator is usually on board a locomotive to ensure the proper operation of the locomotive, and when there is a locomotive consist, the operator is usually on board a lead locomotive. A locomotive "consist" is a group of locomotives that are operated or controlled together for moving a train. In addition to ensuring proper operations of the locomotive, or locomotive consist, the operator is also responsible for determining operating speeds of the train and forces within the train. To perform this function, the operator generally must have extensive experience with operating the locomotive and various trains over the specified terrain. This knowledge is needed to comply with prescribed operating parameters, such as speeds, emissions, and the like that may vary with the train location along the track. Moreover, the operator is also responsible for ensuring that in-train forces remain within acceptable limits. [04] In marine applications, an operator is usually aboard a marine vessel to ensure the proper operation of the vessel, and when there is a vessel consist, the operator is usually in control of a lead vessel. As with the locomotive example cited above, a vessel consist is a group of vessels that operate together in carrying out a combined mission. In addition to ensuring proper operations of the vessel, or vessel consist, the operator also is responsible for determining operating speeds of the consist and forces within the consist. To perform this function, the operator generally must have extensive experience with operating the vessel and various consists over the specified waterway or mission. This knowledge is needed to comply with prescribed operating speeds and other mission parameters that may vary with the vessel location along the mission. Moreover, the operator is also responsible for ensuring that intra-vessel and inter-vessel forces and mission location remain within acceptable limits. [05] When operating a train, train operators typically call for the same notch settings when operating the train, which in turn may lead to a large variation in fuel consumption and/or emissions output, such as, but not limited to, NOx, C02, etc., depending on the number of locomotives powering the train. Thus, the operator usually cannot operate the locomotives so that the fuel consumption is minimized and emissions output is minimized for each trip, since the size and loading of trains vary, and locomotives and their power availability may vary by model type. [06] However, with respect to a locomotive, even with knowledge to ensure safe operation, the operator cannot usually operate the locomotive so that the fuel consumption and emissions are minimized for each trip. For example, other factors that must be considered may include emissions output, operator environmental conditions like noise/vibration, a weighted combination of fuel consumption and emissions output, etc. This is difficult to do because the size and loading of trains vary, locomotives and their fuel/emissions characteristics are different, and weather and traffic conditions vary. [07] Similar issues arise when an operator attempts to optimize the speed of a train. Though an operator may be skilled at operating various train configurations, ensuring an optimized mission speed is not uniformly possible across various train configurations. Furthermore, situations may arise where improper information is initially provided when establishing a mission plan. Though not detrimental to the operation of the train, having improper information may result in less than desirable performance. [08] A train owner usually owns a plurality of trains, wherein the trains operate over a network of railroad tracks. Since individual operators are required for each train, with operator skill levels varying from operator to operator, the number of factors relating to ensuring optimization of fuel use, emissions output, and speed, to ensure proper use of all resources in the network, increases exponentially. Because of the integration of multiple trains running concurrently within the network of railroad tracks, wherein scheduling issues must also be considered with respect to train operations, train owners would benefit from a way to optimize fuel efficiency and emissions output in real time so as to save on overall fuel consumption, while minimizing emissions output of multiple trains, and while meeting mission trip time constraints. BRIEF DESCRIPTION OF THE INVENTION [09] Embodiments of the invention relate to a system and method for controlling a powered system. The method comprises determining a mission plan for a powered system when a desired parameter of the mission plan is unobtainable and/or exceeds a predefined limit, so that optimized fuel efficiency, emission output, vehicle performance, and/or infrastructure and environment mission performance of the powered system is realized. The method further comprises identifying a desired parameter prior to creating a mission plan, where the desired parameter may be unobtainable and/or in violation of a predefined limit. An operator of the powered system and/or a remote monitoring facility of the desired parameter is notified. [010] In another embodiment, the method comprises creating a mission plan. A desired parameter in the mission plan that is unobtainable and/or exceeds a predefined limit is identified. A determination is made whether to temporarily exceed the predefined limit, identify an obtainable parameter proximate the desired parameter, and/or alert an operator and/or a remote monitoring facility for feedback on a course of action to take. [Oi 1] Other embodiments of the invention relate to a method for controlling a powered system by optimizing a range of an operating mode that a powered system encounters during a mission. The method comprises determining an amount of time the powered system enters a range of at least one operating mode prior to beginning a mission and/or while performing the mission. Notification is provided to an operator of the powered system and/or a remote monitoring facility regarding the amount of time the powered system enters the range of the at least one operating mode while performing the mission and/or will enter the range of the at least one operating mode prior to beginning the mission. [012] In another embodiment, the method comprises adjusting at least one operating parameter of the powered system to approximate a desired operating setting. The method may further comprise determining a minimum speed threshold and creating a mission plan using the minimum speed threshold. [013] Another embodiment relates to a method for determining a mission plan based on a target reference speed and/or a target reference power. The method comprises creating a mission plan with a target reference speed and/or a target reference power identified for an entire mission and/or a section of the mission. The target reference speed and/or the target reference power is adhered to and/or proximately adhered to. [014] Another embodiment also relates to a method for determining a mission plan based on a target reference speed and/or a target reference power. Here, the method comprises determining a reference target speed and a target reference power. A mission plan is created with the reference target speed and/or a target reference power determined for an entire mission and/or a section of the mission. The powered system is operated to provide power proximate the reference target speed. [015] Another embodiment relates to a method for minimizing a range of at least one operation mode of a powered system provided with a mission plan. The method comprises creating an original mission plan and identifying a time period of operation in the range of the at least one operation mode. The range of the at least one operating mode in the mission plan is identified. The mission plan is revised to provide for a power setting outside of the range of the at least one operation mode during a period the at least one operation mode is within a chosen range of a power operation period. [016] Another embodiment relates to a method for controlling a powered system having a first power generating unit and a second power generating unit, where power settings for the first power generating unit are decoupled from power settings for the second power generating unit. The method comprises developing a power operating plan which is independent of a coupled power setting, determining a power setting responsive to the power operating plan, and operating the first and/or second power generating units based on the determined power setting. BRIEF DESCRIPTION OF THE DRAWINGS [017] A more particular description of the invention briefly described above will be rendered by reference to specific embodiments thereof that are illustrated in the appended drawings. Understanding that these drawings depict only typical embodiments of the invention and are not therefore to be considered to be limiting of its scope, exemplary embodiments of the invention will be described and explained with additional specificity and detail through the use of the accompanying drawings in which: [018] FIG. 1 is a flowchart showing a method of trip optimization, according to an embodiment of the present invention; [019] FIG. 2 depicts a simplified mathematical model of a powered system that may be employed in connection with the present invention; [020] FIG. 3 is a schematic diagram of a powered system; [021] FIG. 4 depicts an exemplary embodiment of a fuel-use/travel time curve; [022] FIG. 5 depicts an exemplary embodiment of segmentation decomposition for trip planning; [023] FIG. 6 depicts another exemplary embodiment of a segmentation decomposition for trip planning; [024] FIG. 7 is a flowchart showing a method of trip optimization, according to another embodiment of the present invention; [025] FIG. 8 depicts an embodiment of a dynamic display for use by an operator; [026] FIG. 9 depicts another embodiment of a dynamic display for use by the operator; [027] FIG. 10 depicts another embodiment of a dynamic display for use by the operator; [028] FIG. 11 depicts a network of railway tracks with multiple trains; [029] FIG. 12 is a flowchart of a method for improving fuel efficiency of a train through optimized train power makeup, according to an additional embodiment of the invention; [030] FIG. 13 depicts a block diagram of exemplary elements included in a system for optimized train power makeup; [031] FIG. 14 depicts a block diagram of a transfer function for determining a fuel efficiency and emissions for a diesel powered system; [032] FIG. 15 is a flowchart depicting a method for determining a configuration of a diesel powered system having at least one diesel-fueled power generating unit; [033] FIG. 16 depicts an exemplary embodiment of a closed-loop system for operating a rail vehicle; [034] FIG. 17 depicts the closed loop system of FIG. 16 integrated with a master control unit; [035] FIG. 18 depicts an exemplary embodiment of a closed-loop system for operating a rail vehicle integrated with another input operational subsystem of the rail vehicle; [036] FIG. 19 depicts another exemplary embodiment of the closed-loop system with a converter which may command operation of the master controller; [037] FIG. 20 depicts another exemplary embodiment of a closed-loop system; [038] FIG. 21 is a flowchart illustrating a method for operating a powered system, according to an embodiment of the present invention; [039] FIG. 22 is a flowchart illustrating a method for operating a rail vehicle in a closed-loop process, according to an embodiment of the present invention; [040] FIG. 23 depicts a speed versus time graph comparing current operations to emissions optimized operation; [041] FIG. 24 depicts a modulation pattern compared to a given notch level; [042] FIG. 25 is a flowchart illustrating a method for determining a configuration of a diesel powered system; [043] FIG. 26 depicts a system for minimizing emission output; [044] FIG. 27 depicts a system for minimizing emission output from a diesel powered system; [045] FIG. 28 depicts a method for operating a diesel powered system having at least one diesel-fueled power generating unit; [046] FIG. 29 depicts a block diagram of an exemplary system operating a diesel powered system having at least one diesel-fueled power generating unit; [047] FIGS. 30-31 are flowcharts illustrating respective methods for determining a mission plan for a powered system, according to two embodiments of the present invention; [048] FIG. 32 is a flowchart illustrating a method for identifying a desired parameter in a mission plan that is unobtainable and/or exceeds a predefined limit; [049] FIG. 33 is a flowchart illustrating a method for optimizing a range of at least one operating mode of a powered system provided in a mission plan; [050] FIG. 34 is a flowchart illustrating a method for optimizing a range of at least one operating mode of a powered system provided in a mission plan; [051] FIG. 35 is a flowchart illustrating a method for determining a mission plan based on a maximum speed limit and/or a minimum speed threshold; [052] FIG. 36 is a flowchart illustrating a method for optimizing a range of an operating mode provided in a mission plan of a powered system; [053] FIG. 37 is a flowchart illustrating a method for determining a mission plan based on a maximum speed limit and/or a minimum speed threshold; [054] FIG. 38 is a flowchart illustrating a method for optimizing a range of an operation mode of a powered system provided with a mission plan; [055] FIG. 39 depicts a three dimensional graph illustrating an exemplary embodiment for providing decoupled power settings; [056] FIG. 40 depicts a three dimensional graph illustrating another exemplary embodiment for providing decoupled power settings; [057] FIG. 41 depicts a three dimensional graph illustrating another exemplary embodiment for providing decoupled power settings; [058] FIG. 42 depicts a flowchart illustrating an exemplary embodiment for providing decoupled power settings; and [059] FIG. 43 depicts a flowchart illustrating another exemplary embodiment for providing decoupled power settings. DETAILED DESCRIPTION OF THE INVENTION [060] Reference will now be made in detail to the embodiments consistent with the invention, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numerals used throughout the drawings refer to the same or like parts. [061] Though exemplary embodiments of the present invention are described with respect to rail vehicles, or railway transportation systems, specifically trains and locomotives having diesel engines, exemplary embodiments of the invention are also applicable for other uses, such as but not limited to off-highway vehicles, marine vessels, stationary units, and other vehicles such as agricultural vehicles and transport buses, each which may use at least one diesel engine, or diesel internal combustion engine. Towards this end, when discussing a specified mission, this includes a task or requirement to be performed by the diesel powered system. Therefore, with respect to railway, marine, transport vehicles, agricultural vehicles, or off-highway vehicle applications this may refer to the movement of the system from a present location to a destination. [062] In the case of stationary applications, such as but not limited to a stationary power generating station or network of power generating stations, a specified mission may refer to an amount of wattage (e.g., MW/hr) or other parameter or requirement to be satisfied by the diesel powered system. Likewise, operating conditions of the diesel-fueled power generating unit may include one or more of speed, load, fueling value, timing, and the like. Furthermore, though diesel powered systems are disclosed, those skilled in the art will readily recognize that embodiments of the invention may also be utilized with non-diesel powered systems, such as but not limited to natural gas powered systems, bio-diesel powered systems, etc. [063] Furthermore, as disclosed herein, such non-diesel powered systems, as well as diesel powered systems, may include multiple engines, other power sources, and/or additional power sources, such as, but not limited to, battery sources, voltage sources (such as but not limited to capacitors), chemical sources, pressure based sources (such as but not limited to spring and/or hydraulic expansion), electrical current sources (such as but not limited to inductors), inertial sources (such as but not limited to flywheel devices), gravitational-based power sources, and/or thermal-based power sources. Additionally, the power source may be external, such as but not limited to, an electrically powered system, such as a locomotive or train, where power is sourced externally from overhead catenary wire, third rail, and/or magnetic levitation coils. [064] In one example involving marine vessels, a plurality of tugs may be operating together where all are moving the same larger vessel, where each tug is linked in time to accomplish the mission of moving the larger vessel. In another example, a single marine vessel may have a plurality of engines. Off-highway vehicle (OHV) applications may involve a fleet of vehicles that have a same mission to move earth, from location "A" to location "B," where each OHV is linked in time to accomplish the mission. With respect to a stationary power generating station, a plurality of stations may be grouped together for collectively generating power for a specific location and/or purpose. In another exemplary embodiment, a single station is provided, but with a plurality of generators making up the single station. In one example involving locomotive vehicles, a plurality of diesel powered systems may be operated together, where all are moving the same, larger load, e.g., a plurality of rail cars, and where each system is linked in time to accomplish the mission of moving the larger load. In another exemplary embodiment a locomotive vehicle may have more than one diesel powered system. [065] Exemplary embodiments of the invention solves problems in the art by providing a system, method, and computer implemented method, such as a computer software code, for determining a mission plan for a powered system when a desired parameter of the mission plan is unobtainable and/or exceeds a predefined limit, so that optimized fuel efficiency, emissions output, vehicle performance, and/or infrastructure and environment mission performance of the diesel powered system is realized. With respect to locomotives, exemplary embodiments of the present invention are also operable when the locomotive consist is in distributed power operations. [066] Persons skilled in the art will recognize that an apparatus, such as a data processing system, including a CPU, memory, I/O, program storage, a connecting bus, and other appropriate components, could be programmed or otherwise designed to facilitate the practice of the method of the invention. Such a system would include appropriate program means for executing the method of the invention. [067] Also, an article of manufacture, such as a pre-recorded disk or other similar computer program product, for use with a data processing system, could include a storage medium and program means recorded thereon for directing the data processing system to facilitate the practice of the method of the invention. Such apparatus and articles of manufacture also fall within the spirit and scope of the invention. [068] Broadly speaking, a technical effect is to determine a mission plan for a powered system when a desired parameter of the mission plan is unobtainable and/or exceeds a predefined limit, so that optimized fuel efficiency, emissions output, vehicle performance, infrastructure and environment mission performance of the diesel powered system is realized. Though a mission plan is disclosed above, the term "mission plan" is not provided as a limitation. Specifically, the term "mission plan" encompasses an automatic or autonomous mission plan and/or planning, a manual mission plan and/or planning, as well as a combination of the two. [069] To facilitate an understanding of the exemplary embodiments of the invention, it is described hereinafter with reference to specific implementations thereof. Exemplary embodiments of the invention may be described in the general context of computer-executable instructions, such as program modules, being executed by any device, such as but not limited to a computer, designed to accept data, perform prescribed mathematical and/or logical operations usually at high speed, where results of such operations may or may not be displayed. Generally, program modules include routines, programs, objects, components, data structures, etc. that performs particular tasks or implement particular abstract data types. For example, the software programs that underlie exemplary embodiments of the invention can be coded in different programming languages, for use with different devices, or platforms. In the description that follows, examples of the invention may be described in the context of a web portal that employs a web browser. It will be appreciated, however, that the principles that underlie exemplary embodiments of the invention can be implemented with other types of computer software technologies as well. [070] Moreover, those skilled in the art will appreciate that exemplary embodiments of the invention may be practiced with other computer system configurations, including hand-held devices, multiprocessor systems, microprocessor- based or programmable consumer electronics, minicomputers, mainframe computers, and the like. Exemplary embodiments of the invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in 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 adjacent locomotives in consist, or off-board in wayside or central offices where wireless communication is used. [071] Throughout this document the term "locomotive consist" is used. As used herein, a locomotive consist may be described as having one or more locomotives in succession, connected together so as to provide motoring and/or braking capability. In many cases, the locomotives are connected together where no train cars are in between the locomotives. The train can have more than one locomotive consist in its composition. Specifically, there can be a lead consist and one or more remote consists, such as midway in the line of cars and another remote consist at the end of the train. Each locomotive consist may have a first locomotive and trail locomotive(s). Though a first locomotive is usually viewed as the lead locomotive, those skilled in the art will readily recognize that the first locomotive in a multi locomotive consist may be physically located in a physically trailing position. [072] Though a locomotive consist is usually viewed as involving successive locomotives, those skilled in the art will readily recognize that a group of locomotives may also be recognized as a consist even when one or more rail cars separate the locomotives, such as when the locomotive consist is configured for distributed power operation, wherein throttle and braking commands are relayed from the lead locomotive to the remote trains by a radio link or physical cable. Towards this end, the term locomotive consist should be not be considered a limiting factor when discussing multiple locomotives within the same train. [073] As disclosed herein, the idea of a consist may also be applicable when referring to other types of powered systems, including, but not limited to, marine vessels, off-highway vehicles, and/or stationary power plants, that operate together so as to provide motoring, power generation, and/or braking capability. Therefore, even though the term locomotive consist is used herein in regards to certain illustrative embodiments, this term may also apply to other powered systems. Similarly, sub- consists may exist. For example, the diesel powered system may have more than one diesel-fueled power generating unit. For example, a power plant may have more than one diesel electric power unit where optimization may be at the sub-consist level. Likewise, a locomotive may have more than one diesel power unit. [074] The term "notch" may be used herein. Though notch is generally interpreted as pre¬set throttle settings, in the context of this invention the term is defined to include pre-set throttle settings and/or a continuous resolution throttle application, where notch is any throttle value. [075] Referring now to the drawings, embodiments of the present invention will be described. Exemplary embodiments of the invention can be implemented in numerous ways, including as a system (including a computer processing system), a method (including a computerized method), an apparatus, a computer readable medium, a computer program product, a graphical user interface, including a web portal, or a data structure tangibly fixed in a computer readable memory. Several embodiments of the invention are discussed below. [076] Embodiments of the present invention relate to a method for controlling a train, other vehicle, or other powered system, and to a trip optimizer system 12 that implements the method for controlling a train, other vehicle, or other powered system. (The system 12 is generally applicable for controlling the mission of a powered system, and is not limited to controlling vehicles on trips.) [077] FIG. 1 is a flowchart illustrating a method for controlling a powered system through trip/mission optimization. FIGS. 3 and 7 show various elements of a powered system (e.g., train) that includes a trip or mission optimizer system 12 configured to carry out the method shown in FIG. 1. As illustrated, instructions are input specific to planning a trip either on board or from a remote location, such as a dispatch center 10. Such input information includes, but is not limited to, train position, consist description (such as locomotive models), locomotive power description, performance of locomotive traction transmission, consumption of engine fuel as a function of output power, cooling characteristics, the intended trip route (including information relating to effective track grade and curvature as function of milepost, and/or an "effective grade" component to reflect curvature following standard railroad practices), the train represented by car makeup and loading together with effective drag coefficients, trip desired parameters including, but not limited to, start time and location, end location, desired travel time, crew (user and/or operator) identification, crew shift expiration time, and route. [078] This data may be provided to the locomotive 42 (see FIG. 3) in a number of ways, such as, but not limited to, an operator manually entering this data into the locomotive 42 via an onboard display, inserting a memory device such as a hard card and/or USB flash drive containing the data into a receptacle aboard the locomotive, and transmitting the information via wireless communication from a central or wayside location 41, such as a track signaling device and/or a wayside device, to the locomotive 42. Locomotive 42 and train 31 load characteristics (e.g., drag) may also change over the route (e.g., with altitude, ambient temperature, and condition of the rails and rail-cars), and the plan may be updated to reflect such changes as needed by any of the methods discussed above and/or by real-time autonomous collection of locomotive/train conditions. This includes, for example, changes in locomotive or train characteristics detected by monitoring equipment on or off board the locomotive(s) 42. [079] The track signal system determines the allowable speed of the train. There are many types of track signal systems and operating rules associated with each of the signals. For example, some signals have a single light (on/off), some signals have a single lens with multiple colors, and some signals have multiple lights and colors. These signals can indicate that the track is clear and the train may proceed at a maximum allowable speed. They can also indicate that a reduced speed or stop is required. This reduced speed may need to be achieved immediately, or at a certain location (e.g., prior to the next signal or crossing). [080] The signal status is communicated to the train and/or operator through various means. Some systems have circuits in the track and inductive pick-up coils on the locomptives. Other systems have wireless communications systems. Signal systems can also require the operator to visually inspect the signal and take the appropriate actions. [081] The track signaling system may interface with the on-board signal system and adjust the locomotive speed according to the inputs and the appropriate operating rules. For signal systems that require the operator to visually inspect the signal status, the operator screen will present the appropriate signal options for the operator to enter based on the train's location. The type of signal systems and operating rules, as a function of location, may be stored in an onboard database 63. [082] Based on the specification data input into the trip optimizer system, an optimal plan which minimizes fuel use and/or emissions produced subject to speed limit constraints along the route with desired start and end times is computed to produce a trip profile 12a. The profile contains the optimal speed and power (notch) settings the train is to follow, expressed as a function of distance and/or time, and such train operating limits, including but not limited to, the maximum notch power and brake settings, and speed limits as a function of location, and the expected fuel used and emissions generated. (Thus, as should be appreciated, the trip profile is a set or list of control settlings of a train or other vehicle for implementing or following a trip plan.) In an exemplary embodiment, the value for the notch setting is selected to obtain throttle change decisions about once every 10 to 30 seconds. Those skilled in the art will readily recognize that the throttle change decisions may occur at a longer or shorter duration, if needed and/or desired to follow an optimal speed profile. In a broader sense, it should be evident to ones skilled in the art that the profiles provide power settings for the train, either at the train level, consist level, and/or individual train level. Power comprises braking power, motoring power, and airbrake power. In another embodiment, instead of operating at the traditional discrete notch power settings, a continuous power setting, determined as optimal for the profile selected, may be selected. Thus, for example, if an optimal profile specifies a notch setting of 6.8, instead of operating at notch setting 7 (assuming discreet notch setting of, e.g., 6, 7, 8, and so on), the locomotive 42 can operate at 6.8. Allowing such intermediate power settings may bring additional efficiency benefits as described below. [083] The procedure used to compute the optimal profile can be any number of methods for computing a power sequence that drives the train 31 to minimize fuel and/or emissions subject to locomotive operating and schedule constraints, as summarized below. In some cases the required optimal profile may be close enough to one previously determined, owing to the similarity of the train configuration, route and environmental conditions. In these cases it may be sufficient to look up the driving trajectory within a database 63 and attempt to follow it. When no previously computed plan is suitable, methods to compute a new one include, but are not limited to, direct calculation of the optimal profile using differential equation models which approximate the train physics of motion. The setup involves selection of a quantitative objective function, commonly a weighted sum (integral) of model variables that correspond to rate of fuel consumption and emissions generation plus a term to penalize excessive throttle variation. [084] An optimal control formulation is set up to minimize the quantitative objective function subject to constraints including but not limited to, speed limits and minimum and maximum power (throttle) settings and maximum cumulative and instantaneous emissions. Depending on planning objectives at any time, the problem may be implemented flexibly to minimize fuel subject to constraints on emissions and speed limits, or to minimize emissions, subject to constraints on fuel use and arrival time. It is also possible to establish, for example, a goal to minimize the total travel time without constraints on total emissions or fuel use where such relaxation of constraints would be permitted or required for the mission. [085] Throughout the document exemplary equations and objective functions are presented for minimizing locomotive fuel consumption. These equations and functions are for illustration only as other equations and objective functions can be employed to optimize fuel consumption or to optimize other locomotive/train operating parameters. [086] Mathematically, the problem to be solved may be stated more precisely. The basic physics are expressed by: = Te(u,v) - Ga(x) - R(v);v(0) = 0.0;v(Tf) = 0.0 where x is the position of the train, v its velocity and t is time (in miles, miles per hour, and minutes or hours, as appropriate) and u is the notch (throttle) command input. Further, D denotes the distance to be traveled, Tf the desired arrival time at distance D along the track, Te is the tractive effort produced by the locomotive consist, Ga is the gravitational drag which depends on the train length, train makeup, and terrain on which the train is located, and R is the net speed dependent drag of the locomotive consist and train combination. The initial and final speeds can also be specified, but without loss of generality are taken to be zero here (e.g., train stopped at beginning and end). Finally, the model is readily modified to include other important dynamics such the lag between a change in throttle, u, and the resulting tractive effort or braking. Using this model, an optimal control formulation is set up to minimize the quantitative objective function subject to constraints including but not limited to, speed limits and minimum and maximum power (throttle) settings. Depending on planning objectives at any time, the problem may be set up flexibly to minimize fuel subject to constraints on emissions and speed limits, or to minimize emissions, subject to constraints on fuel use and arrival time. [087] It is also possible to implement, for example, a goal to minimize the total travel time without constraints on total emissions or fuel use where such relaxation of constraints would be permitted or required for the mission. All these performance measures can be expressed as a linear combination of any of the following: xf min \ F(u(t))dt - Minimize total fuel consumption (1) „(0o min Tf - Minimize Travel Time u(t) J min V (Ul - ulA )2 - Minimize notch jockeying (piecewise constant input) min [ (du I dt)2 dt - Minimize notch jockeying (continuous input) „(0 J It is possible toreplace the fuel term F in (1) with a term corresponding to emissions production. For example, for emissions min \ E(u(t))dt - Minimize total emissions „(0 J production. In this equation E is the quantity of emissions in gm/hphr for each of the notches (or power settings). In addition, a minimization could be done based on a weighted total of fuel and emissions. [088] A commonly used and representative objective function is thus: tf min CLx J F(u(t))dt + a3Tf + a2 j (du I dt)2 dt (OP) u(t) o o The coefficients of the linear combination depend on the importance (weight) given to each of the terms. Note that in equation (OP), u(t) is the optimizing variable that is the continuous notch position. If discrete notch is required, e.g. for older locomotives, the solution to equation (OP) is discretized, which may result in lower fuel savings. Finding a minimum time solution ((XI set to zero and a2 set to zero or a relatively small value) is used to find a lower bound for the achievable travel time (Tf = Tfmin). In this case, both u(t) and Tf are optimizing variables. In one embodiment, equation (OP) is solved for various values of Tf with Tf > Tfmin with (X3 set to zero. In this latter case, Tf is treated as a constraint. [089] For those familiar with solutions to such optimal problems, it may be necessary to adjoin constraints, e.g., the speed limits along the path: or when using minimum time as the objective, that an end point constraint must hold, e.g., total fuel consumed must be less than what is in the tank, e.g. via: 0 < ^F(u(t))dt < WF o Here, Wp is the fuel remaining in the tank at Tf. Those skilled in the art will readily recognize that equation (OP) can be in other forms as well and that what is presented above is an exemplary equation for use in the exemplary embodiment of the present invention. For example, those skilled in the art will readily recognize that a variation of equation (OP) is required where multiple power systems, diesel and/or non-diesel, are used to provide multiple thrusters, such as, but not limited to, those that may be used when operating a marine vessel. [090] Reference to emissions in the context of the exemplary embodiment of the present invention is actually directed towards cumulative emissions produced in the form of oxides of nitrogen (NOx), carbon oxides (COx), unburned hydrocarbons (HC), particulate matter (PM), etc. However, other emissions may include, but not be limited to a maximum value of electromagnetic emission, such as a limit on radio frequency (RF) power output, measured in watts, for respective frequencies emitted by the locomotive. Yet another form of emission is the noise produced by the locomotive, typically measured in decibels (dB). An emission requirement may be variable based on a time of day, a time of year, and/or atmospheric conditions such as weather or pollutant level in the atmosphere. Emission regulations may vary geographically across a railroad system. For example, an operating area such as a city or state may have specified emission objectives, and an adjacent area may have different emission objectives, for example a lower amount of allowed emissions or a higher fee charged for a given level of emissions. [091] Accordingly, an emission profile for a certain geographic area may be tailored to include maximum emission values for each of the regulated emissions included in the profile to meet a predetermined emission objective required for that area. Typically, for a locomotive, these emission parameters are determined by, but not limited to, the power (notch) setting, ambient conditions, and engine control method. By design, every locomotive must be compliant with EPA emission standards, and thus in an embodiment of the present invention that optimizes emissions this may refer to mission-total emissions, for which there is no current EPA specification. Operation of the locomotive according to the optimized trip plan is at all times compliant with EPA emission standards. Those skilled in the art will readily recognize that because diesel engines are used in other applications, other regulations may also be applicable. For example, C02 emissions are considered in certain international treaties. [092] If an objective during a trip mission is to reduce emissions, the optimal control formulation, equation (OP), would be amended to consider this trip objective. A key flexibility in the optimization setup is that any or all of the trip objectives can vary by geographic region or mission. For example, for a high priority train, minimum time may be the only objective on one route because it is high priority traffic. In another example, emission output could vary from state to state along the planned train route. [093] To solve the resulting optimization problem, in an exemplary embodiment, a dynamic optimal control problem in the time domain is transcribed to an equivalent static mathematical programming problem with N decision variables, where the number 'N' depends on the frequency at which throttle and braking adjustments are made and the duration of the trip. For typical problems, this N can be in the thousands. For example, suppose a train is traveling a 172-mile (276.8 kilometers) stretch of track in the southwest United States. Utilizing the trip optimizer system, an exemplary 7.6% saving in fuel used may be realized when comparing a trip determined and followed using the trip optimizer system versus an actual driver throttle/speed history where the trip was determined by an operator. The improved savings is realized because the trip optimizer system produces a driving strategy with both less drag loss and little or no braking loss compared to the trip plan of the operator. [094] To make the optimization described above computationally tractable, a simplified mathematical model of the train may be employed, such as illustrated in FIG. 2 and the equations discussed above. As illustrated, certain set specifications, such as but not limited to information about the consist, route information, train information, and/or trip information, are considered to determine a profile, such as an optimized profile. Such factors incorporated in the profile include, but are not limited to, speed, distance remaining in the mission, and/or fuel used. As disclosed herein, other factors that may be included in the profile are notch setting and time. One possible refinement to the optimal profile is produced by driving a more detailed model with the optimal power sequence generated, to test if other thermal, electrical, and mechanical constraints are violated. This leads to a modified profile with speed versus distance that is closest to a run that can be achieved without harming locomotive or train equipment, i.e., satisfying additional implied constraints such as thermal and electrical limits on the locomotive and inter-car forces in the train. Those skilled in the art will readily recognize how the equations discussed herein are utilized with FIG. 2. [095] Referring back to FIG. 1, once the trip is started at 12a, power commands are generated 14 to put the mission plan in motion. Depending on the operational set-up of the trip optimizer system, one command is for the locomotive to follow the optimized power command 16 so as to achieve the optimal speed. The trip optimizer system obtains actual speed and power information 18 from the locomotive consist of the train. Owing to the inevitable approximations in the models used for the optimization, a closed-loop calculation of corrections to optimized power is obtained to track the desired optimal speed. Such corrections of train operating limits can be made automatically or by the operator, who always has ultimate control of the train. [096] In some cases, the model used in the optimization may differ significantly from the actual train. This can occur for many reasons, including, but not limited to, extra cargo pickups or setouts, locomotives that may become inoperable in route, and errors in the initial database 63 or data entry by the operator. For these reasons a monitoring system is in place that uses real-time train data to estimate locomotive and/or train parameters in real time 20. The estimated parameters are then compared to the assumed parameters used when the trip was initially created 22. Based on any differences in the assumed and estimated values, the trip may be re -planned 24, should large enough savings accrue from a new plan. [097] Other reasons a trip may be re-planned include directives from a remote location, such as dispatch, and/or the operator requesting a change in objectives to be consistent with more global movement planning objectives. Additional global movement planning objectives may include, but are not limited to, other train schedules, allowing exhaust to dissipate from a tunnel, maintenance operations, etc. Another reason may be due to an onboard degradation of a component. Strategies for re-planning may be grouped into incremental and major adjustments depending on the severity of the disruption, as discussed in more detail below. In general, a "new" plan must be derived from a solution to the optimization problem equation (OP) described above, but frequently faster approximate solutions can be found, as described herein. [098] In operation, the locomotive 42 will continuously monitor system efficiency and continuously update the trip plan based on the actual efficiency measured, whenever such an update would improve trip performance. Re-planning computations may be carried out entirely within the locomotive(s) or fully or partially moved to a remote location, such as dispatch or wayside processing facilities where wireless technology is used to communicate the plans to the locomotive 42. In one embodiment, the trip optimizer system may also generate efficiency trends that can be used to develop locomotive fleet data regarding efficiency transfer functions. The fleet-wide data may be used when determining the initial trip plan, and may be used for network- wide optimization tradeoff when considering locations of a plurality of trains. For example, the travel-time fuel use tradeoff curve as illustrated in FIG. 8 as discussed in detail below, reflects a capability of a train on a particular route at a current time, updated from ensemble averages collected for many similar trains on the same route. Thus, a central dispatch facility collecting curves like FIG. 8 from many locomotives could use that information to better coordinate overall train movements to achieve a system-wide advantage in fuel use or throughput. As disclosed above, those skilled in the art will recognize that various fuel types, such as but not limited to diesel fuel, heavy marine fuels, palm oil, bio-diesel, etc. may be used. [099] Furthermore, as disclosed above, those skilled in the art will recognize that various energy storage devices may be used. For example, the amount of power withdrawn from a particular source, such as a diesel engine and batteries, could be optimized so that the maximum fuel efficiency/emission, which may be an objective function, is obtained. As further illustration, suppose the total power demand is 2000 horse power (HP), where the batteries can supply 1500 HP and the engine can supply 4400 HP. The optimum point could be when batteries are supplying 1200 HP and engine is supplying 200 HP. [0100] Similarly, the amount of power may also be based on the amount of energy stored and the need for the energy in the future. For example, if there is a long high demand coming for power, the battery could be discharged at a slower rate. For example, if 1000 horsepower hour (HPhr) is stored in the battery and the demand is 4400 HP for the next 2 hours, it may be optimum to discharge the battery at 800 HP for the next 1.25 hours and take 3600 HP from the engine for that duration. [0101] Many events in daily operations can lead to a need to generate or modify a currently executing plan, where it desired to keep the same trip objectives, for example when a train is not on schedule for a planned meet or pass with another train and it needs to make up time. Using the actual speed, power, and location of the locomotive, a comparison is made between a planned arrival time and the currently estimated (predicted) arrival time 25. Based on a difference in the times, as well as the difference in parameters (detected or changed by dispatch or the operator), the plan is adjusted 26. This adjustment may be made automatically according to a railroad company's desire for how such departures from plan should be handled, or alternatives may be manually proposed for the on-board operator and dispatcher to jointly decide the best way to get back on plan. Whenever a plan is updated, in the case where the original objectives (such as, but not limited to, arrival time) remain the same, additional changes may be factored in concurrently, e.g., new future speed limit changes, which could affect the feasibility of ever recovering the original plan. In such instances, if the original trip plan cannot be maintained, or in other words the train is unable to meet the original trip plan objectives, as discussed herein other trip plan(s) may be presented to the operator and/or remote facility, or dispatch. [0102] A re -plan 24, or an adjustment to a plan 26, as illustrated in FIG. 1 may also be made when it is desired to change the original objectives. Such re-planning can be done at either fixed preplanned times, manually at the discretion of the operator or dispatcher, or autonomously when predefined limits, such as train operating limits, are exceeded. For example, if the current plan execution is running late by more than a specified threshold, such as thirty minutes, the exemplary embodiment of the present invention can re -plan the trip to accommodate the delay at the expense of increased fuel use, as described above, or to alert the operator and dispatcher how much of the time can be made up at all (e.g., what minimum time to go or the maximum fuel that can be saved within a time constraint). Other triggers for re-plan can also be envisioned based on fuel consumed or the health of the power consist, including but not limited time of arrival, loss of horsepower due to equipment degradation (such as operating too hot or too cold), and/or detection of gross setup errors, such as in the assumed train load. That is, if the change reflects impairment in the locomotive performance for the current trip, these may be factored into the models and/or equations used in the optimization. [0103] Changes in plan objectives can also arise from a need to coordinate events where the plan for one train compromises the ability of another train to meet objectives and arbitration at a different level, e.g., the dispatch office, is required. For example, the coordination of meets and passes may be further optimized through train-to-train communications. Thus, as an example, if a train knows that it is behind schedule in reaching a location for a meet and/or pass, communications from the other train can notify the late train (and/or dispatch). The operator can then enter information pertaining to being late into the trip optimizer system, wherein the system will recalculate the train's trip plan. [0104] The trip optimizer system can also be used at a high level, or network level, to allow a dispatch to determine which train should slow down or speed up should it be the case that a scheduled meet and/or pass time constraint may not be met. As discussed herein, this is accomplished by trains transmitting data to the dispatch to prioritize how each train should change its planning objective. A choice could be based on either schedule, fuel saving benefits and/or emission output, depending on the situation. [0105] Therefore, as explained herein, a re -plan 24 or adjustment to a plan 26, as illustrated in FIG. 1, may be carried out either independent of dispatch or in coordination with dispatch. Furthermore, as disclosed herein, a re-plan may be initiated, in whole or in part, based on information received at the powered system from dispatch or on information that originates from other sources, such as, but not limited to another powered system passing nearby and/or a wayside device or equipment. [0106] With respect to a train 31, one example relates to a situation where dispatch 60 determines that a train operator has entered incorrect information for optimizing a mission plan. In this example, when information is entered by the operator, such as, but not limited to, through a control counsel and/or display 68, for generating an optimized trip plan, the information is transmitted to dispatch 60, which is remote from the train. A wired and/or wireless communication system 47 is used for communicating with dispatch 60. Dispatch verifies the information. Dispatch may be an individual at a remote location or a remote system having a processor that is able to determine if the information provided is correct for the intended mission. If the information is incorrect, the trip/mission plan originally generated using the incorrect information may be adjusted, re -planned, or otherwise revised using new, correct, and/or corrected information (collectively, updated information). The source of this second information may come from the dispatch and/or any other system that may provide information updates to the train. Verification and, if required, re-plan may occur prior to commencing the mission, and/or while the mission is progressing. [0107] Changes to the optimized mission plan may also be made when updated information has a bearing on the currently implemented mission. One example of when such updated information may be used includes, but is not limited to, when the train is performing other than as contemplated with a current mission plan, e.g., the train's performance degrades at some point while an original mission plan is being followed. The change in performance may also be attributed to degraded operation capability of a rail infrastructure (or route infrastructure), crew change, time-out, if the operator decides to manually operate the train and then returns control for autonomous operation, etc. In another example, updated information is received from at least one of another train, such as through inter-train communication, a wayside device, and/or another localized source. When information is being transferred train-to-train, when the transmitting train has needed information. This information can include, but is not limited to, information learned based on track that the transmitting train has recently traversed and/or information relayed to the transmitting train when it was in communication with dispatch for transmitting to other trains that are unable to communicate with dispatch due to a communication interruption. In yet another example, such updated information may include a change in the mission objective, e.g., the train is reclassified from a high priority level to a low priority level. Where the train is operating with other trains (such as, but not limited to, on multi-section tracks in an intersecting railroad network), the updated information may provide for further optimizing the particular train's mission to insure that all trains using the same network of railways are operated safely and where no prolonged delays to any trains are realized, such as having to wait too long at a meet and pass location. [0108] Re -planning may be performed on board the train, even when dispatch is unaware of the information that causes the re-planning to take place. In such a situation, dispatch is subsequently informed of the re -plan. [0109] For any of the manually or automatically initiated re-plans, exemplary embodiments of the present invention may present more than one trip/mission plan to the operator. In an exemplary embodiment, the trip optimizer system presents different profiles to the operator, allowing the operator to select the arrival time and understand the corresponding fuel and/or emission impact. Such information can also be provided to the dispatch for similar consideration, either as a simple list of alternatives or as a plurality of tradeoff curves such as illustrated in FIG. 4. [0110] The trip optimizer system has the ability to learn and adapted to key changes in the train and power consist, which can be incorporated either in the current plan and/or in future plans. For example, one of the triggers discussed above is loss of horsepower. When building up horsepower over time, either after a loss of horsepower or when beginning a trip, transition logic is utilized to determine when desired horsepower is achieved. This information can be saved in the locomotive database 61 for use in optimizing either future trips or the current trip should loss of horsepower occur again. [0111] Likewise, in a similar fashion where multiple thrusters are available, each may need to be independently controlled. For example, a marine vessel may have many force producing elements, or thrusters, such as but not limited to propellers. Each propeller may need to be independently controlled to produce the optimum output. Therefore, utilizing transition logic, the trip optimizer system may determine which propeller to operate based on what has been learned previously and by adapting to key changes in the marine vessel's operation. [0112] As noted above, FIG. 3 depicts various elements that may part of an exemplary trip optimizer system, according to an embodiment of the invention. A locator element 30 to determine a location of the train 31 is provided. The locator element 30 can be a GPS sensor, or a system of sensors, that determines a location of the train 31. Examples of such other systems include, but are not limited to, wayside devices, such as radio frequency automatic equipment identification (RF AEI) tags, dispatch, and/or video determination. Another system may include the tachometer(s) aboard a locomotive and distance calculations from a reference point. As discussed previously, a wireless communication system 47 may also be provided to allow for communications between trains and/or with a remote location, such as dispatch 60. Information about travel locations may also be transferred from other trains. [0113] A track characterization element 33, which provides information about a track, principally grade and elevation and curvature information, is also provided. The track characterization element 33 may include an on-board track integrity database 36. Sensors 38 are used to measure a tractive effort 40 being hauled by the locomotive 42, throttle setting of the locomotive consist 42, locomotive consist 42 configuration information, speed of the locomotive consist 42, individual locomotive configuration, individual locomotive capability, etc. In an exemplary embodiment, the locomotive consist 42 configuration information may be loaded without the use of a sensor 38, but is input in other manners as discussed above. Furthermore, the health of the locomotives in the consist may also be considered. For example, if one locomotive in the consist is unable to operate above power notch level 5, this information is used when optimizing the trip plan. [0114] Information from the locator element may also be used to determine an appropriate arrival time of the train 31. For example, if there is a train 31 moving along a track 34 towards a destination and no train is following behind it, and the train has no fixed arrival deadline to adhere to, the locator element, including, but not limited to, RF AEI tags, dispatch, and/or video determination, may be used to gage the exact location of the train 31. Furthermore, inputs from these signaling systems may be used to adjust the train speed. Using the on-board track database, discussed below, and the locator element, such as GPS, the trip optimizer system can adjust the operator interface to reflect the signaling system state at the given locomotive location. In a situation where signal states would indicate restrictive speeds ahead, the planner may elect to slow the train to conserve fuel consumption. [0115] Information from the locator element 30 may also be used to change planning objectives as a function of distance to destination. For example, owing to inevitable uncertainties about congestion along the route, "faster" time objectives on the early part of a route may be employed as a hedge against delays that statistically occur later. If it happens on a particular trip that delays do not occur, the objectives on a latter part of the journey can be modified to exploit the built-in slack time that was banked earlier, and thereby recover some fuel efficiency. A similar strategy could be invoked with respect to emissions restrictive objectives, e.g., approaching an urban area. [0116] As an example of the hedging strategy, if a trip is planned from New York to Chicago, the system may have an option to operate the train slower at either the beginning of the trip or at the middle of the trip or at the end of the trip. In one embodiment, the trip optimizer system would optimize the trip plan to allow for slower operation at the end of the trip since unknown constraints, such as, but not limited to, weather conditions and track maintenance, may develop and become known during the trip. As another consideration, if traditionally congested areas are known, the plan is developed with an option to have more flexibility around these traditionally congested regions. Therefore, the trip optimizer system may also consider weighting/penalty as a function of time/distance into the future and/or based on known/past experience. At any time during the trip, planning and re-planning may also take into consideration weather conditions, track conditions, other trains on the track, etc., wherein the trip plan is adjusted accordingly. [0117] FIG. 3 further discloses other elements that may be part of the trip optimizer system 12. The trip optimizer system is configured to compute an optimized trip plan for the train 31 based on parameters involving the locomotive 42, train 31, track 34, and objectives of the mission as described above. The trip optimizer system comprises a processor 44 that is operable to receive information from the locator element 30, track characterization element 33, and sensors 38. (The processor 44 may be a general purpose control unit in the train, or specific to the trip optimizer system 12.) An algorithm 46 (computer program) operates within the processor 44 for implementing certain functional elements of the trip optimizer system. In an exemplary embodiment, the trip plan is established based on models for train behavior as the train 31 moves along the track 34 as a solution of non-linear differential equations derived from physics with simplifying assumptions that are provided in the algorithm. The trip optimizer system 12 has access to the information from the locator element 30, track characterizing element 33, and/or sensors 38 to create a trip plan minimizing (or at least reducing) fuel consumption of a locomotive consist 42, minimizing (or at least reducing) emissions of a locomotive consist 42, establishing a desired trip time, ensuring proper crew operating time aboard the locomotive consist 42, and/or otherwise optimizing an operating parameter of the train or other vehicle. In an exemplary embodiment, a controller element 51 (and/or driver or operator) is also provided. As discussed herein, the controller element 51 is used for controlling the train as it follows the trip plan. In an exemplary embodiment discussed further herein, the controller element 51 makes train operation decisions autonomously. In another exemplary embodiment, the operator may be involved with directing the train to follow the trip plan. [0118] A feature of an exemplary embodiment of the trip optimizer system is the ability to initially create and quickly modify "on the fly" any plan that is being executed. This includes creating the initial plan when a long distance is involved, owing to the complexity of the plan optimization algorithm. When a total length of a trip profile exceeds a given distance, an algorithm 46 may be used to segment the mission, wherein the mission may be divided by waypoints. Though only a single algorithm 46 is discussed, those skilled in the art will readily recognize that more than one algorithm may be used (and/or that the same algorithm may be executed a plurality of times) where the algorithms may be connected together. The waypoints may include natural locations where the train 31 stops, such as, but not limited to, sidings where a meet with opposing traffic (or pass with a train behind the current train) is scheduled to occur on a single-track rail, or at yard sidings or industry where cars are to be picked up and set out, and locations of planned work. At such waypoints, the train 31 may be required to be at the location at a scheduled time and be stopped or moving with speed in a specified range. The time duration from arrival to departure at waypoints is called "dwell time." [0119] In an exemplary embodiment, the trip optimizer system is able to break down a longer trip into smaller segments in a special systematic way. Each segment can be somewhat arbitrary in length, but is typically picked at a natural location such as a stop or significant speed restriction, or at key mileposts that define junctions with other routes. Given a partition, or segment, selected in this way, a driving profile is created for each segment of track as a function of travel time taken as an independent variable, such as shown in FIG. 4. The fuel used/travel-time tradeoff associated with each segment can be computed prior to the train 31 reaching that segment of track. A total trip plan can be created from the driving profiles created for each segment. The exemplary embodiment of the invention distributes travel time amongst all the segments of the trip in an optimal way so that the total trip time required is satisfied and total fuel consumed over all the segments is as small as possible. An exemplary three-segment trip is disclosed in FIG. 6 and discussed below. Those skilled in the art will recognize, however, that although segments are discussed, the trip plan may comprise a single segment representing the complete trip. [0120] FIG. 4 depicts an exemplary embodiment of a fuel-use/travel time curve 50. As mentioned previously, such a curve 50 is created when calculating an optimal trip profile for various travel times for each segment. That is, for a given travel time 49, fuel used 53 is the result of a detailed driving profile computed as described above. Once travel times for each segment are allocated, a power/speed plan is determined for each segment from the previously computed solutions. If there are any waypoint constraints on speed between the segments, such as, but not limited to, a change in a speed limit, they are matched up during creation of the optimal trip profile. If speed restrictions change in only a single segment, the fuel use/travel-time curve 50 has to be re-computed for only the segment changed. This reduces time for having to re-calculate more parts, or segments, of the trip. If the locomotive consist or train changes significantly along the route, e.g., from loss of a locomotive or pickup or set-out of cars, then driving profiles for all subsequent segments must be recomputed, thereby creating new instances of the curve 50. These new curves 50 would then be used along with new schedule objectives to plan the remaining trip. [0121] Once a trip plan is created as discussed above, a trajectory of speed and power versus distance is used to reach a destination with minimum fuel use and/or emissions at the required trip time. There are several ways in which to execute the trip plan. As provided below in more detail, in an exemplary embodiment, when in an operator "coaching" mode, information is displayed to the operator for the operator to follow to achieve the required power and speed determined according to the optimal trip plan. In this mode, the operating information includes suggested operating conditions that the operator should use. In another exemplary embodiment, acceleration and maintaining a constant speed are autonomously performed. However, when the train 31 must be slowed, the operator is responsible for applying a braking system 52. In another exemplary embodiment, commands for powering and braking are provided as required to follow the desired speed-distance path. [0122] Feedback control strategies are used to provide corrections to the power control sequence in the profile to correct for events such as, but not limited to, train load variations caused by fluctuating head winds and/or tail winds. Another such error may be caused by an error in train parameters, such as, but not limited to, train mass and/or drag, when compared to assumptions in the optimized trip plan. A third type of error may occur with information contained in the track database 36. Another possible error may involve un-modeled performance differences due to the locomotive engine, traction motor thermal deration, and/or other factors. Feedback control strategies compare the actual speed as a function of position to the speed in the desired optimal profile. Based on this difference, a correction to the optimal power profile is added to drive the actual velocity toward the optimal profile. To assure stable regulation, a compensation algorithm may be provided which filters the feedback speeds into power corrections so that closed-performance stability is assured. Compensation may include standard dynamic compensation as used by those skilled in the art of control system design to meet performance objectives. [0123] The trip optimizer system provides the simplest and therefore fastest means to accommodate changes in trip objectives, which is the rule, rather than the exception in railroad operations. In an exemplary embodiment, to determine the fuel- optimal trip from point "A" to point "B" where there are stops along the way, and for updating the trip for the remainder of the trip once the trip has begun, a sub-optimal decomposition method is usable for finding an optimal trip profile. Using modeling methods, the computation method can find the trip plan with specified travel time and initial and final speeds, so as to satisfy all the speed limits and locomotive capability constraints when there are stops. Though the following discussion is directed towards optimizing fuel use, it can also be applied to optimize other factors, such as, but not limited to, emissions, schedule, crew comfort, and load impact. The method may be used at the outset in developing a trip plan, and more importantly to adapting to changes in objectives after initiating a trip. [0124] As discussed herein, exemplary embodiments of the present invention may employ a setup as illustrated in the exemplary flowchart depicted in FIG. 5, and as an exemplary three-segment example depicted in detail in FIG. 6. As illustrated, the trip may be broken into two or more segments, Tl, T2, and T3. (As noted above, it is possible to consider the trip as a single segment.) As discussed herein, the segment boundaries may not result in equal segments. Instead, the segments may use natural or mission specific boundaries. Optimal trip plans are pre-computed for each segment. If fuel use versus trip time is the trip object to be met, fuel versus trip time curves are built for each segment. As discussed herein, the curves may be based on other factors, wherein the factors are objectives to be met with a trip plan. When trip time is the parameter being determined, trip time for each segment is computed while satisfying the overall trip time constraints. FIG. 6 illustrates speed limits 97 for an exemplary three-segment, 200-mile (321.9 kilometers) trip. Further illustrated are grade changes 98 over the 200-mile (321.9 kilometers) trip. A combined chart 99 illustrating curves for each segment of the trip of fuel used over the travel time is also shown. [0125] Using the optimal control setup described previously and the computation methods described herein, the trip optimizer system can generate the trip plan with specified travel time and initial and final speeds, so as to satisfy all the speed limits and locomotive capability constraints when there are stops. Though the following detailed discussion is directed towards optimizing fuel use, it can also be applied to optimize other factors as discussed herein, such as, but not limited to, emissions. A key flexibility is to accommodate desired dwell time at stops and to consider constraints on earliest arrival and departure at a location as may be required, for example, in single-track operations where the time to be in or get by a siding is critical. [0126] Exemplary embodiments of the present invention find a fuel-optimal trip from distance Do to DM, traveled in time T, with M-I intermediate stops at D1,...,DM I, and with the arrival and departure times at these stops constrained by: tmm(i) < ^(D1) < ^x(I)-Atl tarr(Dl) + Ml <^(A)<^x(0 i=l,...,M-l where tarr (Dl), tdep (Dl), and Atl are the arrival, departure, and minimum stop time at the iA stop, respectively. Assuming that fuel-optimality implies minimizing stop time, therefore tdep (Dl ) = tarr (Dl ) + Atl which eliminates the second inequality above. Suppose for each i=l,...,M, the fuel-optimal trip from DL! to Dl for travel time t, ^mn (0 -t - ^max (0 J is known. Let Fl (t) be the fuel-use corresponding to this trip. If the travel time from D,_i to Dj is denoted T„ then the arrival time at Dl is given by: (Equation Removed) where AtO is defined to be zero. The fuel-optimal trip from Do to DM for travel time T is then obtained by finding Tl, i= 1,... ,M, which minimize (Equation Removed) [0127] Once a trip is underway, the issue is re-determining the fuel-optimal solution for the remainder of a trip (originally from DO to DM in time T) as the trip is traveled, but where disturbances preclude following the fuel-optimal solution. Let the current distance and speed be x and v, respectively, where D1A v:j-i>vv) J=I subject to v • mm ( Vi' J i))< — v vij < —v Kmax (ViJ'J i)/ J / = 11VJ N Jv : - 1 -1 V10 = V = 0 By choosing Dy (e.g., at speed restrictions or meeting points), Vn^x (i,j) - vmm (i,j) can be minimized, thus minimizing the domain over which fy() needs to be known. [0130] Based on the partitioning above, a simpler suboptimal re -planning approach than that described above is to restrict re-planning to times when the train is at distance points D , 1 < i < M, 1 J